TA 7733-PHI - Support for Social Protection Reform: Final Report

Technical Assistance Consultant’s Report

This consultant’s report does not necessarily reflect the views of ADB or the Government concerned, and ADB and the Government cannot be held liable for its contents.

Project Number: 43263-012 January 2016 Philippines: Support for Social Protection Reform (Financed by the Japan Fund for Poverty Reduction)

Prepared by Vicente Paqueo

Quezon City, Philippines

For Department of Social Welfare and Development

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Consultant’s Final Report

ADB TA 7733-PHI: Support for Social Protection Reforms

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Table of Contents Page Introduction 3 Purpose of TA 7733-PHI 3 Context 4 An Overview of TA 7733 Supported Activities 5

Consulting Services 6 TA Activities and Intermediate Outputs 8 Conclusion 12 Table 1. Summary of DSWD List and Classification of TA 7733-Supported Activities by Output Type

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Table 2. TA 7733-Supported Consultants’ and Resource Persons’ Inputs 7 Appendix 1. Design and Monitoring Framework Update 13 Appendix 2. TA 7733: Support for Social Protection Reform Cumulative Activities 15 Appendix 3. Bibliography of the publications/reports supported by TA 7733 28 Appendix 4. Conference on Sustaining the Gains of the Conditional Cash Transfer Program in the Philippines: Program Outline

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Appendix 5. Consultants’ Reports Analysis of the Near-Poor Challenge and Strategy Development Ideas 32 Pantawid Extension to High School: Pathway for Accelerating Improvements in 104 Human Capital among the Poor Final Report on the Social Welfare and Development Indicator 157 Disaster Response Strategic Policy Framework for the New Normal 180

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Consultant’s Final Report ADB TA7733-PHI: Support for Social Protection Reforms1

I. Introduction

1. In 2010, the administration of newly elected President Benigno Aquino III decided to scale up the Pantawid Pamilyang Pilipino Program, a conditional cash transfer (CCT) program patterned after Mexico’s Oportunidades, Colombia’s Familias en Accion and Brazil’s Bolsa Familia. Pantawid Pamilya provides cash benefits directly to participating households. These beneficiaries are chosen from a registry of poor households (now called Listahanan) and in accordance with objective Pantawid eligibility criteria. 2. To help accelerate the implementation of the Pantawid Pamilya, ADB approved the Social Protection Support Project (SPSP), Loan 2662-PH. In December 2010 ADB approved a $1.4 million policy and advisory technical assistance (PATA) grant (TA 7733-PH) financed by the Japan Fund for Poverty Reduction. The Department of Social Welfare and Development (DSWD) was the executing agency. The TA closed after one extension on March 31, 2016. 3. This report presents the accomplishments of TA 7733-PH and discusses the significance of their contributions to the objectives of the technical assistance. It includes a list of TA 7733-PH activities and a narrative about its contributions.

II. Purpose of TA7733-PH

4. The TA was intended to give flexible and timely support to the government in its effort to rationalize the country’s social protection (SP) system and enhance its efficiency, equity and sustainability, particularly in serving the needs of poor and vulnerable groups. Appendix 1 describes in detail the TA’s design and monitoring framework.2

5. The three original TA outputs were: (1) national policy reforms for social protection developed; (2) capacity of national and local institutions to support the SP reform agenda developed; and (3) referral system and graduation policy for the Pantawid Pamilyang Pilipino Program beneficiaries established. During implementation, output 3 was re-conceptualized to cover the policy question of a potential extension of some form of benefits (conditional cash transfer or other) beyond Pantawid’s original 5-year limit, as well as the development of a “transition-promotion” strategy. This strategy was meant to assist poor beneficiary households to sustainably transition out of poverty, supported by referral to other programs.

6. The expected outcome and impact of the SPSP to which the TA was intended to contribute were (i) enhanced efficiency and sustainability of the social protection system and (ii) improved coverage of social protection and social services for the poor by 2018 (Appendix 1).

III. Context

7. To appreciate the contributions of the TA 7733-supported activities to its expected outputs and outcome, it is important to understand the political and social context of Pantawid Pamilya. To begin with, President Aquino’s administration envisioned a country where “no Filipino is left behind” in its pursuit of economic growth. To fulfill this political promise, the

1 This report is written by Vicente B. Paqueo, Ph.D, Lead Social Protection Consultant for TA7733-PH.

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administration has to address the inadequacies of the current social protection (SP) system, including both social assistance and social insurance. It was unacceptable that huge segments of the poor were left out from government social assistance programs. They failed to benefit the poor and vulnerable population due to low budget allocation, lack of poverty targeting, corruption, wastage, and high cost of social assistance delivery. Moreover, the contributory social insurance systems had limited coverage. They excluded huge segments of the population, particularly poor workers in the informal sectors.

8. In the past 5 years, the Philippines has achieved significant strides in the development of its social protection system. Financing of PhilHealth has increased significantly due to the increase in sin taxes, a considerable proportion of which are earmarked for funding the PhilHealth and public health services. This additional funding has enabled more progress towards universal health insurance coverage. At present, all poor households included in the Pantawid program are automatically provided PhilHealth insurance coverage without having to pay a premium for membership.

9. The scaling up of Pantawid Pamilya is another milestone in the country’s progress towards improved social protection. The CCT idea was introduced in the Philippines in 2008. By 2010, there were close to one million beneficiary households (or at least 5 million beneficiaries, at an average family size of 5). In 2015, the number stood at about 4.4 million households. As a result of the increased Pantawid budget allocation and the earmarking of sin taxes to PhilHealth, SP spending as a percentage of GDP rose from 2.3 % in 2009 to 4.1% in 2012.

10. Despite this progress, the poor continue to incur substantial out-of-pocket health expenses and suffer untreated illnesses. The poor have been slow in taking advantage of their PhilHealth insurance benefits. Health insurance utilization rate remains low among low income households, especially in rural areas. Moreover, households remain unprotected against the cost of natural disasters, whose impact has become more severe due to climate change. Furthermore, lack of social assistance for those above the poverty line but at high risk of falling into poverty has become a more salient issue that needs to be addressed.

11. Pantawid provides an important platform for the reform of the social assistance component of the SP system. But the platform’s utility depends on its sustainability. This has been challenged by various forces, although the challenge is less concerning than in the past, as a result of DSWD’s efforts, some of which have benefitted from TA 7733 support (see below).

12. Because the philosophy and design of Pantawid depart radically from traditional approaches to social assistance, there have been negative opinions and opposition to the program. Influential and vocal segments of the population have criticized the program and expressed concerns about its impact. The reasons for these are rooted in misinformation about the program and conflicting attitudes towards its concept, given governance problems in the Philippines. First, there has been an attitude common among the elite that the poor cannot be trusted with money. They have speculated in this regard that the beneficiaries would simply abuse their cash grants, spending the money on vices instead of spending wisely on children’s health and education. Second, critics have expressed concern about the effects of CCT on work ethics and the unintended promotion of a culture of dependency. Third, there has been resentment among poor people’s traditional sources of patronage that their influence would be undermined by Pantawid Pamilya, precisely because it provides support without their intervention and patronage. Fearing the program will foster greater loyalty to the state, militant activists and their political allies have waged disinformation campaigns and mounted persistent resistance to the program in the hopes of getting it cancelled.

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IV. An overview of TA7733 supported activities

13. The approval of TA 7733 in December 2010 came at an opportune time. Technical assistance was urgently needed to support activities that would provide the public evidence-based information about Pantawid Pamilya, strengthen its political support, and build its capacity and credibility to provide effective, efficient and equitable delivery of social assistance. These activities are important for the continued evolution of the SP system and its capability to protect the poor and vulnerable against the worst effects of poverty, economic shocks, catastrophic illnesses, and natural disasters. It is against this backdrop that the activities supported by TA 7733 should be viewed.

14. TA 7733 supported a range of activities over 5 years. Appendix 2 presents in detail DSWD’s list of those activities. These are summarized by output in Table 1 below. Additional items are included in the table. These are items that the DSWD list missed to include. These are TA 7733-supported and consists activities were carried out as part of the terms of reference of the Social Protection Specialist/Team Leader for TA 7733. The missed activities are added as a memorandum section to Table 1.

15. Consulting services. The TA financed the inputs of specialized consultants directly hired by ADB. They are listed below in Table 2, including some consultants who were engaged through a lumpsum contract. Given that the two lump sum consultants budgeted a total of 44 days to complete their assignments, the total inputs of all ADB hired consultants engaged under the TA would be nearly 800 days. The consultants’ reports are compiled in Appendix 5. In addition, ADB hired resource persons for short-term assignments (up to 10 days each) under the TA to support several activities which are listed in Appendix 2. ADB engaged sixty-three (63) resource persons (some repeated) for a total input of 546 days.

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Table 1. Summary of DSWD List and Classification of TA 7733-Supported Activities by Output and Thrust Type

Output and Thrust Number of

Activities

1. National policy reforms for social protection (SP) developed 35

• Thrust 1A: Evolution of the CCT and Social Protection Agenda 21

• Thrust 1B: Strengthening Social Protection Disaster Response Capacity

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• Others 3

2. Capacity of national and local institutions to support SP reform agenda developed

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• Thrust 2A: Continued support on DSWD - CSO partnership in FDS/FDS Plus

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• Thrust 2B: Support to DSWD for consolidation and use of supply-side and other data

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• Others 3

3. Strengthened operational mechanisms for convergence and promoting Pantawid Pamilya beneficiary households’ sustainable transition out of poverty

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• Thrust 3A: Review and enhancement of DSWD’s Social Welfare Indicators (SWI) tool

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• Thrust 3B: Promoting effective municipality transition planning (MTP)

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• Others 6 Total 61

Note:

The following activities are TA-7733-supported activities missed in the DSWD’s list.

Output type

(1) Analysis of CCT’s impact on work behavior Output 1 (2) Financial and economic analyses for additional financing of SPSP Outputs 1, 2, 3 (3) Ideas on next generation CCT presented at NEDA/AIM/UNDP Zero Poverty

Workshop Output 3

(4) Membership in the Pantawid Impact Evaluation Technical Working Group (TWG) Outputs 1,2, 3 (5) Development of strategic framework for more timely and efficient rapid disaster

response under the new normal Outputs 1, 2, 3

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Table 2. TA 7733-PHI Consultants’ Inputs

Name Position Title Contract

No. Contract Amount

Start Date Completion

Date Inputs

Remarks

Vicente Paqueo Social Protection Specialist/Team Leader

S71520 491,250.00 09-May-11 31-Jul-15 550 Days up to Dec 2015 only

Jose Ramon G. Albert

Social Assistance Programs and Finance Specialist

S82195 19,734.00 21-Apr-14 31-Dec-14

lumpsum contract

Elvie Orbeta Specialist on Analysis of Poverty and Social Service Data

S81482 12,228.00 03-Jan-14 30-Jun-14 64 Days

Romulo Virola Specialist on Microeconomics of Social Welfare

S81205 35,487.00 18-Nov-13 31-Jul-14 96 Days

Juan Blenn Huelgas

Specialist on Enhanced Disaster Response Capacity for Social Protection

S82120 41,300.00 08-Apr-14 31-Dec-14

contract terminated (no disbursements)

Minerva Dacanay

Specialist on Enhanced Disaster Response Capacity for Social Protection

S83670 9,700.00 12-Nov-14 31-Jan-15

lumpsum contract

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V. TA activities and intermediate outputs

16. It is apparent that TA 7733 resources have been deployed to support activities that would help the Government of the Philippines (GOP) meet the SP challenges discussed above. In so doing, the TA facilitated the strengthening of Pantawid’s sustainability and the development of a stronger foundation on which to build a more effective, efficient and inclusive social protection system.

17. On the whole, the activities supported by TA 7733 have been well received and are seen as helpful. Many of them have been carried out and participated in by well-respected researchers, academics, and practitioners. The activities and their results were based on original research, technical inputs, and extensive consultations and discussions with stakeholders.

18. The practical question is: how do those activities relate to the key challenges facing the country’s social protection system. It is not possible to quantitatively measure the impact of TA 7733 on the outputs, not to mention the outcome. But by relating the TA activities to the above-mentioned challenges, it is possible to develop a coherent and sensible view of TA 7733’s potential contributions to the expected outputs and outcome. The discussion below uses selected activities to develop this report’s narrative, in the five areas of:

(i) listening to stakeholders and enlightening public opinion, (ii) updating and institutionalizing targeting and beneficiary selection, (iii) building partnerships with CSOs and the private sector for better social protection, (iv) establishing credibility and building capacity, and (v) supporting Pantawid extension, convergence, and transition promotion.3

(i) Listening to stakeholders and enlightening public opinion

19. As shown in Appendix 2, the TA supported a series of policy reviews, consultations, conferences and symposia for DSWD to get a better understanding of the social protection needs of the poor and vulnerable. In particular, these activities provided DSWD opportunities to hear what people think about Pantawid Pamilya. The activities also provided opportunities for the Department to listen to a wide variety of ideas from experts and the public on what the government can and should do about the inadequacies of Pantawid program and, in general, about the country’s social protection system. The above dialogues, it must be stressed, included participants from the poor and vulnerable, civil society organizations, academe, and think tanks. Those listening activities are necessary for the development of a responsive social protection reform agenda, of which Pantawid is envisioned to be a core element.

20. In the course of those conversations with the public, DSWD got to educate them about Pantawid and to present to them evidence-based information. Specifically, with help from TA 7733, the Department was able to explain Pantawid’s objectives, rationale, design, institutional arrangements, implementation challenges and expected outputs and outcomes. Lessons on CCT from international experience were also shared with the public. The discussions enlightened the public about Pantawid’s short-term objective and its importance in immediately preventing the damaging consequences of poverty on human development. At the same time, DSWD got to explain Pantawid’s long term goal of reducing the transmission of intergenerational poverty through better health and education. The above dialogues led to a better understanding by the public of how Pantawid fits in the government’s broader agenda of poverty reduction and inclusive development. 3 For more details, see Appendix 2.

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21. The outreach activities covered Luzon, Visayas and Mindanao. Arguably, they contributed to the establishment of a stronger foundation for the development of social protection reform ideas that are sensitive to people’s demands. The importance of the contributions of those activities cannot be overestimated. For, as mentioned, significant segments of the country’s elite and influential people have expressed skepticism, criticisms and opposition against the program.

22. With TA 7733 support, DSWD have succeeded in mobilizing the support of influential stakeholders for Pantawid’s continued expansion and improvement. The effect is the diminution of political opposition against Pantawid Pamilya. This diminution can be gleaned from the fact that none of the Presidential candidates have proposed elimination or reduction of Pantawid Pamilya. To be sure, the militant activists and their allies in Congress continue to snipe at the program.

(ii) Updating and institutionalizing targeting and beneficiary selection.

23. A key to an efficient and equitable social protection system is a credible system for determining the target population and selecting beneficiary households and individuals. The DSWD’s National Household Targeting System for Poverty Reduction (NHTS-PR) – now known as “Listahanan”, is the first operational registry and database in the Philippines used for identifying the poor and selecting eligible beneficiaries of programs intended for the poor. A few years ago, Pantawid Pamily was the only anti-poverty program that has an objective targeting system for beneficiary selection. Today, the PhilHealth is using the Listahanan to determine poor households entitled to subsidized health insurance coverage. Following DSWD, the Commission for Higher Education Development (CHED) are also using the Listahanan to select students eligible for grant-in-aid. Further along, the government has institutionalized the Listahanan, designating the Philippine Statistics Authority (PSA) as officially responsible for its maintenance, upgrading and updating. This development is a significant step towards ensuring coherence and horizontal equity in the delivery of social services intended for the poor and vulnerable.

24. Some support from the TA has contributed to the above accomplishments and, moving forward, to the development of a government agenda for the updating and upgrading of the Listahanan. In the reviews, conferences, fora and consultations conducted by DSWD with the support of TA 7733, failures to enumerate households in communities in adverse conditions surfaced as a major reason for the exclusion of many poor households from Pantawid. This reason is on top of the exclusion and inclusion errors that normally occur due to statistical noise arising from the nature of Proxy Means Testing. To address these issues, TA 7733 supported the development and adoption of new procedures like on-demand assessment of the poverty status of complainant households.

25. A further issue that surfaced from fora and consultations relates to the “near poor” phenomenon. Data reveal that a large proportion of households moves in and out of the poverty line. The implication is that some households with incomes above but near the poverty line in a certain year will probably find themselves poor in the following year. Who these near poor people are and what can be done to address their precarious situation are key issues.

26. In response to DSWD’s request, TA 7733 supported a study of the near-poor issue. The study was presented at a Philippine Statistics Authority conference and discussed at NEDA’s Technical Committee for Social Development and the Cabinet Cluster for Human Development and Poverty Reduction. Recently, the Cluster approved a resolution adopting a near poor poverty line in accordance with the recommendation of the study. Looking ahead, DSWD is thinking of using the study’s near poor approach for graduating Pantawid beneficiaries and of

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developing a social assistance program tailored to the needs and capabilities of the near poor to keep them above the poverty line. The study provides the government ideas on policy options and a framework for formulating a coherent strategy for dealing with the near poor challenges.

(iii) Building partnerships with CSOs and private sector for better social protection.

27. DSWD has adopted a policy of building partnerships with CSOs and other non-governmental stakeholders. TA 7733 supported development and testing of ideas that would contribute to improvements in the design and delivery of social assistance, involving CSOs and the private sector. In line with this policy, the TA supported pilot testing of alternative ways of engaging CSOs and using their strengths to improve social assistance policies and programs. Noteworthy activities in this regard include the development and piloting of ideas for the Family Development Sessions (FDS) and FDS Plus. The latter refers to training and other human development activities that Pantawid beneficiaries are encouraged to voluntarily participate in. Those activities are additional to the original list of FDS topics that Pantawid beneficiaries must attend as part of the CCT conditions. TA 7733, incidentally, also supported experimentation involving CSOs to strengthen the grievance redress system and Pantawid’s accountability. Appendix 2 provides a detailed list of FDS, FDS Plus and other partnership building activities.

(iv) Establishing credibility and building capacity.

28. There were three challenges here that were addressed with the help of TA 7733. The first challenge was to show that (i) Pantawid Pamilya has been effective and efficient in assisting the poor in raising school enrolment and key health indicators; (ii) that the cash grants have been used well by beneficiaries; and (iii) that they have not encourage complacency, work reduction, welfare dependency and vices. In this regard, two major household surveys were undertaken. Various studies analyzed the data collected found that Pantawid was effective in improving children’s enrolment rate and selected health indicators. They also reveal that beneficiary households did not abuse the cash grants given to them.

29. Moreover, it has been shown that there was no significant effect on work ethics. These findings were made public and discussed in various fora with TA 7733 support. The TA, incidentally, supported the Orbeta and Paqueo analysis of the impact of Pantawid on work ethics and dependency. This analysis was presented at a conference organized by the Philippine Statistics Authority and was well received. Its finding provided evidence against overblown claims of the adverse consequence of CCT on work ethics and dependency.

30. The second challenge mentioned above relates to the need to establish systems that are efficiently functioning and are understood by stakeholders. With some help from TA 7733, Pantawid Pamilya has successfully instituted systems that are efficient, transparent, and accountable – with a well-functioning grievance redress system. These systems are competently run by trained and well-motivated personnel, whose capacity had to be patiently and systematically bought or built. On this score, it is noteworthy that beneficiaries have received their grants on time and in the right amount due to the establishment of those systems. Pantawid Pamilya is now a model that other government programs can learn from. It is well governed and managed with an emerging culture of good governance practices.

31. Looking forward, the program provides valuable lessons and ideas that should be documented for SP and other sectors to learn from on how to design and implement reforms. An example for which DSWD should be lauded is its success in developing a culture of impact evaluation. On this score, DSWD with some help from TA 7733 have built a functional capacity

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to manage, oversee and communicate impact evaluation results. It is not farfetched to say that the Department is way ahead of other agencies in this regard. This achievement provides good foundation for advancing social protection reforms in the future. This accomplishment will be sustained by further DSWD-ADB collaboration in the design and implementation of Pantawid Impact Evaluation Wave 3

(v) Supporting Pantawid extension, convergence and transition promotion.

32. TA 7733 supported a study that provided economic justification for the extension of Pantawid benefits from elementary to high school enrolment. The government did adopt such extension. Pari passu, the duration of the program was also extended from the original limit of five years. Further along, the TA supported strengthening operational mechanisms for convergence and the promotion of Pantawid Pamilya beneficiary households’ sustainable transition out of poverty. Activities here include: (i) review and enhancement of DSWD’s Social Welfare Indicators (SWI) tool ; (ii) municipal transition planning (MTP) plus supporting training, exercises, workshops and development of operational guidelines; and (iii) development of ideas, applying government’s convergence policy to identify available employment, training, livelihood, and other opportunities. These activities involve DSWD programs beyond Pantawid and partnerships with the private organizations and government agencies outside of DSWD.

33. In addition to supporting the development of referral schemes, TA 7733 also supported work on disaster response framework and guidelines. This work can be regarded as part of both “national policy reforms for social protection developed” and “convergence and transition promotion”. The near poor study can also be regarded similarly as contributing to both outputs.

34. Finally, a finding of the Pantawid evaluation studies indicates that there is a positive interaction between PhilHealth and Pantawid Pamilya. This interaction suggests that proportionately more Pantawid beneficiaries have taken advantage of PhilHealth than comparable groups. This result can be interpreted to mean that the orientation received by Pantawid beneficiaries from FDS has led to more Pantawid beneficiaries taking advantage of their PhilHealth rights and utilizing more of the benefits they are entitled to.

VI. Conclusion

35. TA 7733 has clearly supported activities that are contributing to current and, most probably, future reforms of the country’s social protection system. The TA facilitated the development of ideas for strengthening and reforming the Philippine social protection system. Some of the ideas developed are being implemented; others are still germinating and need follow up. The bottom line is that with TA 7733 support, the country’s social protection system is marking more progress towards (i) enhanced efficiency and sustainability of the social protection system and (ii) improved coverage of social protection and social services for the poor. The TA culminated with the Conference on Sustaining the Gains of the CCT Program in the Philippines held on 12-13 January 2016. At this conference, implementers, economists and social protection experts both national and international took stock of the Pantawid Program and discussed ideas on ways forward to sustain its gains (see conference agenda outline in Appendix 3).

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Appendix 1. Design and Monitoring Framework Update

Project Number: 43263-01/TA 7733

Design Summary

Performance Targets and Indicators

Update as of February 2016

Impact Improved coverage of social protection and social services for the poor

By 2018: MDG 1: Proportion of population below national poverty threshold less than 25% (2006 baseline: 33%) Share of households vulnerable to falling into poverty below 30% (2005 baseline: 45%) Share of poor households covered by 4Ps of conditional cash transfers reaches 50% (baseline = 20% at end of 2010), of whom at least half are effectively linked to community-driven development and/or employment programs

2012: 25.3% (FIES 2015 not yet released) 2015: 93% (using 2014 APIS estimate of poor households)

Outcome Enhanced efficiency and sustainability of the social protection system

By TA completion: The NHTS-PR is applied to at least three major national social protection programs. Social protection spending reaches 2.8% of gross domestic product (baseline: 2.3% in 2009)

The NHTS-PR, now called Listahanan, is now applied to more than three national programs, including Pantawid Pamilya, PhilHealth, CHED’s Expanded Student Grant-in-Aid Program, Department of Agriculture’s Targeted Actions to Reduce Poverty and Generate Economic Transformation (TARGET), and others.

Social protection spending in 2012: 4.1% of GDP

Outputs 1. National policy reforms for social protection developed

DSWD endorses core recommendations on (i) consolidation and rationalization; (ii) increased and efficient budget allocation; and (iii) enhanced targeting and delivery, including via gender mainstreaming Social protection reform panel established Action plan and milestones adopted and commenced by DSWD and the social protection and welfare cluster

DSWD endorsed social protection reform recommendations that were developed. These includes among others: the establishment of the near-poor poverty threshold and presentation of a strategy framework to the Cabinet Cluster on Poverty and Human Development, the institution of the Listahanan for poverty targeting and delivery, and free PhilHealth coverage of all Pantawid beneficiaries, and proposed guidelines for rapid disaster response An interagency group commenced by DSWD and the social protection and welfare cluster was organized to review and strengthen the social protection dimension of the Philippine Development Plan. Action plan, indicators and milestones were developed.

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2. Capacity of national and local institutions to support the social protection reform agenda developed 3. Referral system and graduation policy for 4Ps beneficiaries established

Capacity development plan formulated (ensuring gender- inclusiveness) and adopted by DSWD At least 80 central and local officials acquire new capacities through TAsupported training. Graduation policy adopted by DSWD Referral system piloted and evaluated, and plan adopted for its introduction within the 4Ps

. DSWD formulated capacity development plans, which were gender-inclusive. More than 80 central and local officials acquired new capacities through TA supported training

Transition plan was presented to the National Advisory TWG and the National Independent Advisory Monitoring Committee (NIAMC). The transition plan is undergoing revision based on the inputs provided by NAC TWG and NIAMC. The plan sets out a strategy for promoting sustainable transitioning of Pantawid beneficiaries from the cash transfers program, including but not limited to improved referral system.

Activities with Milestones 1.1. Rapid context assessment, including in view of dialogue leading up to the new Medium-Term Philippines Development Plan (Q1 2011) 1.2. Flesh out comprehensive framework and detailed work plan for the TA, and prepare a knowledge dissemination and communication plan, including reports, website posting, and other knowledge-sharing events under the TA (Q1–Q2 2011) 1.3. Combine desk study with extensive stakeholder dialogue to comprehensively review the social protection sector and policy framework, including gender analysis (Q2–Q3 2011). 1.4 Additional studies, working papers, and focused policy briefs (Q2 2011– Q1 2012) 1.5. Stakeholder consultations and workshops to discuss findings, ensure alignment with the forthcoming Medium-Term Philippines Development Plan, and build consensus behind recommendations (ongoing) 1.6. DSWD endorsement of review and recommendations (Q3 2011) 1.7. Develop action plan for rationalization (Q3–Q4 2011) 1.8. Stakeholder consultations and workshops on action plan (Q4 2011) 1.9. DSWD adoption (Q1 2012) and launch (Q2 2012) of the action plan 2.1. Develop capacity development plan (Q4 2011) 2.2. Flexible, needs-tailored capacity building program, including training and workshops, print and information and communication technology-based materials, mentoring, etc. (Q1–Q3 2012) 3.1. Develop referral system (Q1–Q2 2011) 3.2. Pilot test referral system in selected 4Ps areas (Q3 2011–Q3 2012) 3.3. Baseline and endline surveys for pilot test conducted in Q2 2011 and Q3 2012; evaluation report delivered in Q4 2012 3.4. Graduation policy developed and adopted by DSWD (Q1–Q4 2012)

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Appendix 2. TA 7733: Support for Social Protection Reform Cumulative Activities

Activity Title DSWD Proponent

Unit Participants Date Conducted Venue ADB TA Remarks

Output 1 - National policy reforms for social protection (SP) developed

1 Contracting of consultant (Dr. Vic Paqueo)

May 2011 - January 2016

2 Writeshop for the Youth Development Session Year 2 Curriculum Outline

Pantawid FDD DSWD FDS Supervisors, and FDS and YDS Implementers and Partner Agencies

18 - 22 Jan 2016 Richville Hotel, Mandaluyong City

Direct payment to Resource Persons; P765,000 for food and venue for 5 days

The writeshop produced draft of the (1) the YDS Year 2 program framework; and (2) Curriculum Outline.

3 Consolidation activity on the module development on FDS for IPs

Pantawid FDD DSWD FDS, IP & MCCT Focals

16 - 17 Dec 2015, 12 - 15 Jan 2016, 25 - 16 Jan 2016

Richville Hotel, Mandaluyong City

P775,200 for food and venue for 8 days

This is a follow through activity of the consultation workshops in 8 regions held in 2014 and January, 2015. This outputted FDS modules for IPs.

4 Policy Brief on Sustaining the Gains on CCT Implementation

Office of the Secretary

Dec 2015/Jan 2016 Direct Payment to Resource Person

Policy note will serve as DSWD's reference in enhancing the Pantawid implementation.

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5 Conference on CCT, Social Protection and Poverty

PDPB About 300 participants from DSWD Field Offices, NGAs, LCEs, Academe, CSOs, Media and Pantawid Beneficiaries

12 - 13 Jan 2016 ADB P510,000 ADB hosted the Conference; DFAT and WB co-shared the activity.

6 Workshops to Formulate a Policy Brief along the DSWD Vision and Mission and Its Link to the Challenges of the “New Normal”

RMEO 15-17 Oct 2014 Direct payment to Resource Persons

Working paper was presented in the National Management Development Conference held last 26-28 January 2015. CorPlan writeshop was held last 15-18 March 2015 at SWADCAP.

7 Capacity Building on Regression Discontinuity Design

18-20 August 2014 21-22 August 2014

Engaged Dr. Matias D. Cattaneo as Resource Person The mentoring sessions allowed thorough discussion and provision of assistance on the finalization 3rd wave IE design of the Pantawid Pamilya program.

8 IE TWG Meetings 05 Mar 2013 16 Jul 2013 06 Aug 2013

ADB With Dr. Paqueo's time and input

ADB hosted the seminar with academia and other TWG working meetings

9 Conference on the Philippine Social Protection Agenda

12 April 2013 La Breza Hotel, Quezon City

Covers Dr. Paqueo's time and input

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10 CSO Consultation and Planning Workshop on Family Development Sessions (FDS)

Pantawid Pamilya - Institutional Partnership Division (IPD)

156 CSO representatives from all over the country

17 - 20 April 2012 Rembrandt Hotel, Quezon City

Covers Dr. Paqueo's time and inputs, etc; workshop cost charged to TA 7586

11 Experience-sharing seminar on Philippine and Indonesian experiences with CDD and links with CCT programs.

November 2011- March 2012

ADB ADB-hosted meeting and video-conference; resource person (R. Gonzales), including provision of paper on "The Indonesian PNPM-Mandiri Program: Lessons for Philippine CDD". (Direct Payment)

12 CSO-DSWD National/Regional Forum on CCT (Mindanao)

Pantawid Pamilya 04 - 08 December 2011

Davao Insular Hotel, Davao City

Covers Dr. Paqueo's time and inputs, etc.; workshop cost charged to TA 7586.

13 Policy Review on CCT with Non-Beneficiaries (Mindanao Cluster) (Pantawid Pamilya Policy Review Forum Series)

Pantawid Pamilya 23 -25 November 2011

Phela Grande Hotel, General Santos

Covers Dr. Paqueo's time and inputs, etc.; workshop cost charged to TA 7586

14 National Media Forum (Pantawid Pamilya Policy Review Forum Series)

Pantawid Pamilya 22 - 24 November 2011

Sulu Riviera Hotel, Quezon City and La Breza Hotel, Quezon City


15 CSO-DSWD National/Regional Forum on CCT (Visayas)

Pantawid Pamilya 90 CSO representatives

13 - 17 November 2011

Sarabia Manor Hotel, Iloilo City


16 Forum on Conditional Cash Transfers

11-Nov-10 UP School of Economics

Covers Dr. Paqueo's time and inputs, etc.; PPTA 7468 funded workshop costs

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17 CSO-DSWD National/Regional Forum on CCT (Luzon)

Pantawid Pamilya 100 CSO representatives

04 - 07 September 2011

Holiday Inn, Clark, Pampanga

Covers Dr. Paqueo's time and inputs, etc.; Workshop cost charged to TA 7586

18 Updating and presentation for DSWD of the 2010 Point-Counterpoint informal note

Covers Dr. Paqueo's time and input to original paper funded under PPTA 7468. The Conditional Cash Transfers Program Debate: Point and Counterpoint (V. Paqueo and C. Spohr, October 2010)

19 Study on CCT extension Prepared by Dr. Vicente Paqueo, PIDS Senior Research Fellow Aniceto Orbeta and AusAid Consultant Tarcisio Castaneda, Dr. Chris Spohr Recommendation of the study for the extension of CCT coverage until 18 years old was announced by President Benigno S. Aquino III during his State of the Nation Address last 22 July

19

20 Strengthening DSWD-NCR to Improve Multi-Stakeholder Engagement and Delivery of Social Protection Services

OASOPG-Promotive Programs FO NCR Staff

Feb-15 FO NCR Direct payment to Resource Persons

The Consultants submitted their technical report last 14 April.

21 Rethinking Session: Revisiting the DSWD Convergence Strategy

OASOPG-Promotive Programs

CMO, Pantawid and Representatives from all Regions

Feb-15 DSWD Central Office

Direct payment to Resource Persons

Memorandum clarifying the new structure and functions was issued to all Field Offices.

Thrust 1A: Evolution of the CCT and Social Protection Agenda

22 Engagement of Resource Person to assess the performance of Pantawid Pamilyang Pilipino Program using Population Based Surveys

RMEO Oct-14 Engaged Dr. Stella Quimbo as resource person.

23 Engagement of Specialist on Social Assistance Programs and Finance

Pantawid NPMO – PMED

Completed Enaged Dr. Jose Albert as consultant; the consultant's most important findings include (i) 63 percent of covered barangays do not have HS facilities and (ii) 38 percent of students travel more than 5 km to reach the nearest HS which entails some tweaking on the amount of cash grant for HS beneficiaries

24 Simultaneous Regional and National Launching of Kaya Ko! Campaign*

Pantawid NPMO – SMU

28 September 2014 850,000

20

25 The Epal Effect: A Rapid Assessment of the Implementation and Effectiveness of the "Bawal ang Epal Dito" Campaign

Pantawid SMU Municipal Links nationwide, Pantawid beneficiaries in the NCR, Parent Leaders, Regional Information Officers COMELEC Representatives

15, 24, 30 April 2015 direct payment to consultacy services

Engaged Prof. Randy Solis; Conduct of focus group discussions was used as a methodology for the assessment; Administrative cost was charged to DFAT funds

26 Consultation Writeshop for the Development of the Regional FDS Module for Indigenous People (IP) Beneficiaries of Pantawid Pamilya

Pantawid NPMO- FDU

Pantawid FDD Regional Focals

30 Jul - 02 Aug, XII 03-06 Aug, CAR 05-08 Aug, XI 06-09 Aug, IVB 30 Jul-02 Aug, VII 03-06 Oct, VIII 9-12 December, X 2014 and 13-16 January 2015, CARAGA

2,079,947 Pantawid NPMO will use the results of the writeshops to come up with the FDS modules for the whole country.

27 National Communication Planning for the Expansion of Pantawid Pamilya

Pantawid NPMO – SMU

07-12 July 2014 1,630,592 National Communication Plan finalized and currently being implemented

28 Pantawid Pamilya National Family Day

Pantawid NPMO- SMU

28 September 2014 Direct Payment

29 Building Block Activities for the Development of FDS Module for High School Beneficiaries

Pantawid NPMO- FDU

01-03 April 769,954

30 FDS Module for High School Beneficiaries (FDS Adolescent) Training of Supervisors

Pantawid NPMO- FDU

All Regions Nationwide

16-21 June 2014 2,465,238 ADB covered: (a) board&lodging; (b) supplies; (c) transportation; (d) allowance

21

31 Pilot Testing of FDS Module for High School Beneficiaries (FDS Adolescent)

Pantawid NPMO- FDU

35 pax Regions II, VIII and X Pantawid beneficiaries, NPMO and RPMO staff

06 June 2014 10 June 2014

Region VIII Regions II and X

62,183 ADB covered: (a) food; (b) supplies; (c) transportation; (d) allowance for the miscellaneous incidental expenses of Pantawid Pamilya participants

32 Consultation Writeshop on the Development of FDS Modules for High School Beneficiaries (FDS Adolescent)

Pantawid NPMO- FDU

69 pax DepEd representatives, partner stakeholders, FDS focals and SWO III

26 - 30 May 2014 Gem Hotel and Conference Center, Antipolo City

769,954 ADB covered: Direct Payment - (1) board and lodging; (2) RP and facilitators fees APF2 – (1) Supplies; (2) transportation; (3) Fees for documenters

33 - Focus-Group Discussion in Set 1 Areas in Luzon, Visayas and Mindanao Clusters

105 Pax NCR, CARAGA, Region VII Pantawid beneficiaries, NPMO and RPMO staff

01 - 03 April NCR, CARAGA, Region VII

ADB covered (1) food; (2) supplies; (3) transportation; and (4) allowance for misc expenses of beneficiaries

Thrust 1B: Strengthening Social Protection Disaster Response Capacity

34 Engagement of the Specialist on Enhanced Disaster Response Capacity for Social Protection

DRRROO 10 person months; intermittent

The consultant, Mr. Blen Huelgas, withdrew from his engagement. Dr. Minerva Dacanay was engaged as replacement effective 12 November 2014. Dr. Dacanay will meet with ASec. Cabrera and Dir. Biolena on 17 and 18 November to jumpstart her engagement. As discussed during the meeting with the TAU

22

dated 13 November 2014, the TAU will provide Dr. Dacanay with relevant documents for her review in coordination with DRRROO and OASPG.

35 Training on Psychosocial Support Module for City and Municipal Links of Region VIII

Pantawid NPMO- FDU

346 pax CLs, MLs, SWO III, SWA

02 - 05 June 2014 Kuting Reef, Calbayog City Ciriano Hotel, Maasin City

778,300 ADB covered board and lodging and RP fees (through direct payment) and supplies and transportation costs (through APF 2)

Output 2 - Capacity of national and local institutions to support the SP reform agenda developed

36 Leadership for Covergence Training Program

National Convergence Technical Support Unit

DSWD Offices; CMAT November - December 2015

Mabuhay Manor, Pasay City

Direct Payment to Resource Persons

The activity outputted the conceptual framework for Leadership for Convergence and the C/MAT Scoreboard (based on the SWDI); and various tools and materials for convergence.

37 IE Demystification Briefing for DSWD Senior Officials - Batch 2

TAU 20 DSWD Officials (ManCom)

19 November 2011 DSWD Covered RP fee of Dr. Aniceto Orbeta (direct payment)

38 IE Demystification Briefing for DSWD Senior Officials - Batch 1

TAU 10 DSWD Officials (ExeCom)

13 November 2011 DSWD Covered RP fee of Dr. Aniceto Orbeta (direct payment)

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Thrust 2A: Continued support on DSWD - CSO partnership in FDS/FDS Plus

39 Development of Case Studies on Pantawid Pamilya CSO Engagement for FDS and FDS Plus

Pantawid Pamilya NPMO

Feb-15

Direct Payment to RPs

Case studies were consolidated into a booklet. Booklets were distributed to DSWD offices

40 CSO Workshops on institutionalizing CCT

Pantawid IPD CSOs

November - December 2015

Luzon, Visayas and Mindanao Direct Payment

to RPs

Workshops were done in 4 clusters: 1. Northern Luzon 2. Southern Luzon 3. Visayas 4. Mindanao

41 Organizational Review for Supply Side Assessment and Institutional Partnership Division of the Pantawid Pamilyang Pilipino Program

Pantawid IPD DSWD Field Offices

November - December 2015

Luzon, Visayas and Mindanao

Direct Payment to Resource Persons

Review was done in 5 clusters: 1. South Luzon cluster: Nov 29-Dec1 2. Visayas cluster: Dec 2-4 3. North Luzon cluster: Dec 9-11 4. North Mindanao cluster: Dec 14-16 5. South Mindanao cluster: Dec 16-18

42 FDS/FDS Plus Pilot Implementation Phase 2


9 CSOs

September - December 2012

Regions I, NCR and CARAGA

With Dr. Paqueo's time and input

43 Workshop on FDS/FDS Plus Pilot Implementation Phase 1 and lessons learned


9 CSOs, 6 FOs, 8 NPMO staff and 7 ADB representatives

October 2012 With Dr. Paqueo's time and input

44 FDS/FDS Plus Pilot Implementation Phase 1


9 CSOs July-August 2012 Regions I, NCR and CARAGA


24

45 Operational Guidelines and Manual for FDS/FDS Plus Pilot



46 Field Assessments of FDS/FDS Plus Pilot


Resource person (J. Dimaandal) - direct payment; not completed; With Dr. Paqueo's time and input

Thrust 2B: Support to DSWD for consolidation and use of supply-side and other data

47 Engagement of Specialist on Analysis of Poverty and Social Service Data

NHTO Oct-14 DSWD Resolution adopting the near poor policy is being circulated to NTAG members for signature/concurrence.

48 National Workshop on the Near-Poor Policy

NHTO 07 October 2014 70,313

49 Focus Group Discussion on the Near Poor

NHTO PSC, NEDA, NHTO, Pantawid NPMO, PDPB, PSB

12 March 2014 Covered venue rental and meals.

Output 3 - Strengthened operational mechanisms for convergence and promoting Pantawid Pamilya beneficiary households’ sustainable transition out of poverty

50 Workshop to Enhance Gender Mainstreaming in Pantawid Pamilya Operating Systems

Pantawid GAD Pantawid NPMO Staff 21 - 24 January 2016 Baguio City 140,000 The workshop output will serve as reference in enhancing plans for gender and development in Pantawid

51 Capacity Building Workshop for CSOs on Engagement with Government Agencies

Pantawid Pamilya – CBU

CSO and LGU representatives

07-11 January 2013 Rembrandt Hotel, Quezon City


25

52 Brainstorming Workshop to Develop the Transition Framework and Strategies for CCT Beneficiaries Brainstorming Workshop to Develop the Transition Framework and Strategies for CCT Beneficiaries

03 - 04 October 2012 With Dr. Paqueo's time and input

53 Brainstorming Workshop: Defining the Exit strategy for Pantawid Pamilya Beneficiaries

NCTSU DSWD Offices, CSOs, Academe and Private Sector

28 - 29 July 2015 DSWD and ADB

Direct Payment to Resource Person

The workshop output will serve as reference in defining Pantawid operations specifically for exiting Pantawid beneficiaries

54 Draft paper of transition promotion strategy for external convergence workshop


55 Brief on Pantawid Extension: After 5 Years of Pantawid, What’s Next?

Resource person (A. Orbeta) - direct payment; With Dr. Paqueo's time and input

Thrust 3A: Review and enhancement of DSWD’s Social Welfare Indicators (SWI) tool

56 Engagement of the Specialist on Microeconomics of Social Welfare

PDPB November 2013 – July 2014

Engaged Dr. Romulo Virola as consultant; the consultant's final report was endorsed to ADB on 07 August which included the draft SWDI toolkit

57 Enhancement of Social Welfare Indicators- Field Visit

PDPB DSWD CO and FO staff; Pantawid beneficiaries

04 March 2014 06 - 07 March 2014

Region III Region IVB

23,340 ADB covered (a) transportation, (b) meals, and (c) hotel accommodation

26

Thrust 3B: Promoting effective municipality transition planning (MTP)

58 Writeshop for the Enhancement of the Municipal Transition Plan Guidelines

CMO 10 RCCs 2 PDO IIIs 2 PLs 2 RPC-KC 2 PSU 17 MPDCs 5 MAT Leaders 5 CSOs 6 MSWDOs

28-31 July 2014 Richville Hotel, Mandaluyong

565,716 The activity was conducted to finalize the City/Municipal Transition Plan Manual by integrating effective strategies and initiatives of 2013 MTP experience

59 Accelerated Leadership Skills Enhancement Training

CMO 17 ARDOs 17 RCCs 17 PDO IIIs 12 RPCs of NCDDP 17 RPCs of PP

24-27 July 2014 507,270 The activity was aimed at improving the leadership skills of the field implementers thru advance sessions on Systems Thinking, Generative Dialogue, Stakeholder Analysis Next steps include Roll-Out Training for MAT Leaders & SWO IIs on the 1st Semester of 2015

60 Showcasing of the MTP best practices

CMO Reg'l Directors, Reg'l Convergence Coordinators, and selected C/MAT Leaders and local external partners

17-19 January 2014 A Knowledge Sharing Forum on the Operationalization of Convergence Strategy and Transition Initiatives was conducted on 17-19 January 2014. This was participated in by the Regional Directors

27

61 Review, documentation, and rapid evaluation of MTP experiences to date

CMO DSWD Convergence /MTP Team

December 2013 Under the SPSP Consultant Dr. Paqueo; the findings of the rapid evaluation of the MTP experience formed part of the report, “Reviewing the Pantawid Municipal Transition Plans. The findings of the review served as inputs to the Convergence Procedural Mechanics and Draft Operations Manual.

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Appendix 3. Bibliography of the publications/reports supported by TA 7733

Publication or Report Date published

Author Remarks (if not published)/ DSWD’s action

1. National Communication Plan

Pantawid NPMO-SMU

Processed Finalized and implemented (2015)

2. Study on CCT Extension

After Five Years of

Pantawid, What’s Next? A

Policy Brief

August 2013 Vicente Paqueo, Aniceto Orbeta Tarcisio Castaneda Chris Spohr

Processed/PIDS Discussion Paper Series, August 2013 Recommendation for the extension of coverage for 18 years old was announced by President Aquino in his SONA. The recommendation was adopted by DSWD Pantawid.

3. Does Pantawid Foster Dependence or Encourage Work? Evidence from a Randomized Experiment

September 2013

Aniceto Orbeta, Jr. and Vicente Paqueo

Processed/forthcoming in PIDS Philippine Journal of Development

4. Final Report on the Social Welfare and Development Indicator

July 2014 Romulo A. Virola Processed/adopted by DSWD

5. Analysis of the Near Poor Challenge and Strategy Development Ideas

November 2014

Vicente Paqueo Elvira Orbeta Franchesca Cortes Ana Cristina Cruz

Processed/forthcoming PIDS Philippine Journal of Development NEDA & DSWD Joint Res. 2015-001, Adopting DSWD Policy on Near Poor Income Threshold

6. Disaster Response Strategic Policy Framework for New Normal

2015 Minerva Dacanay Vicente Paqueo Susan Rachel Jose

Processed DSWD AO 3, s 2015 was issued entitled DSWD Disaster Operations Guidelines

7. Pantawid Extension to High School: Pathway for Accelerating Improvements in Human Capital Among the Poor

Jose Ramon G. Albert

Presented to DSWD in January 2015. The study has several recommendations for program enhancement which DSWD will follow through.

8. Working Paper : Result of Workshop to Formulate Policy Brief for the New Normal

January 2015 Processed Working paper was presented in the NMDC on 26-28 January 2015. CorPlan writeshop was held on 15-18 March 2015

9. Pintakasi: Civil Society Organizations and Pantawid Pamilyang Pilipino Program’s Family Development Sessions

December 2015

Ma. Cecilia Medel-Genzola et al.

Published by DSWD

10. Policy Brief on Sustaining the Gains on CCT Implementation

Geoann Hernandez-Yang

Submitted to the Secretary Being processed and discussed in the DSWD.

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Appendix 4. Conference on Sustaining the Gains of the Conditional Cash Transfer Program in the Philippines: Program Outline 12-13 January 2016, Asian Development Bank, Ortigas Center, Mandaluyong City

Day 1 AM Opening Remarks

Mr. Richard Bolt

Country Director, Asian Development Bank

Dr. David Dutton

Deputy Head of Mission, Australian Embassy, Manila

Welcome Message

Pantawid Pamilyang Pilipino Program Partner Beneficiaries (video)

Session 1: National Household Targeting System for Poverty

Dr. Dennis Mapa Dean, School of Economics, University of the Philippines

Open Forum

Coffee Break

Session 2: CCT Design and Delivery Mechanisms

Hon. Corazon Juliano-Soliman

Secretary, Department of Social Welfare and Development Open Forum

Day 1 PM Lunch

Keynote Speech Lessons from a Pioneer of CCT in Latin American (Mexico) Mr. Rogelio Gomez Hermosillo Former National Coordinstor of Opportunidades

Open Forum

Coffee Break

Session 3: CCT Impact Evaluatrion and Initial Outcomes

Dr. Aniceto Orbeta, Jr. Research Fellow II, Philippine Institute for Development Studies

Reactor: Dr. Pablo Acosta Senior Economist, World Bank-Manila

Networking Session (Cocktail Hour)

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Parallel Sessions

CCT Transition Strategy

Resource Person: Dr. Tarsicio Castanedan, International Consultant Faciliator: Dir. Ernestina Solloso, Deputy Program Manager, Pantawid Pamilyang Pilipino Program, DSWD

Civil Society and Social Accountability Facilitator: USec. Angelita Gregorio-Medel, Institutional Development Group, DSWD

Day 2 AM Day 1 Synthesis Ms. Ma. Carmen Mislang, Conference Moderator

Session 4: Voices from the Islands: Results of the DSWD Regional Multi-Stakeholder Workshops Ms. Ma. Carmen Mislang, Conference Moderator

Open Forum

Welcome Remarks Mr. Takehiko Nakao President, Asian Development Bank

Testimonial Speech Ms. Evangeline Ibanez Pregoner Pantawid Pamilya Beneficiary

Keynote Speech His Excellency Benigno S. Aquino III, President of the Republic of the Philippines

Session 5: CCT and its Various Impacts (Parallel Sessions)

Session A: Pioneering Social Protection System Reforms Resource Person: Dr. Fernando Aldaba, Dean, School of Social Sciences, Ateneo de Manila University Faciliator: USec. Florita Villar, Policy and Plans Groups, DSWD

Session B: CCT and the Local Economy Resource Person: Dr. Lourdes Adriano (Research Study Consultant) Facilitator: Dir. Leonardo Reynoso, National Program Manager, Pantawid Pamilya Program, DSWD

Session C: Family Well-Being Report Card of Pantawid Pamilya Beneficiaries Resource Person: Former DSWD Secretary Lina Laigo, Director, Philippine Women’s University, Institute of Family Life and Children Studies Facilitator: Usec Mateo Montano, General Administration and Support Services Group, DSWD

31

Day 2 PM Continuation of Session 5 (Parallel Sessions)

Session D: CCT and Peace Building Resource Person: Dr. Joseph Felter, Senior Research Scholar, Stanford University Facilitator: USec. Camilo Gudmain, Operations and Programs (Promotive) Group, DSWD

Session E: CCT and Disaster Risk Reduction Resource Person: Mr. Praveen Agrawal, Country Director, UN World Food Programme Facilitator: USec. Vilma Cabrera, Operations and Programs Group (Protective), DSWD

Session F: CCT and Civil Society Resource Person: Dr. Ruth Callanta, President and Founding Member, Center for Community Transformation Facilitator: Usec. Angelita Gregorio-Medel, Institutional Development Group, DSWD

Discussion of Session Outcomes

Session 6: Panel Discussion on Moving Forward Panelists: Mr. Rogelio Gomez Hermosillo, Former National Coordinator of Opportunidades Ms. Alison Chartres, Assistant Secretary, Australian Department of Foreign Affairs and Trade Ms. Aleksandra Posarac, Lead Economist and Program Leader, World Bank-Manila Mr. Randolf “Randy” David, Professor Emeritus of Sociology, University of the Philoippines Dr. Karin Schelzig, Senior Social Protection Specialist, Southeast Asia Regional Department, Asian Development Bank Moderator: Hon, Corazon Juliano-Soliman

Closing Message Ms. Angelita Castillo, Pantawid Pamilya Beneficiary

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Analysis of the Near-Poor Challenge and Strategy Development Ideas

By

Vicente B. Paqueo, Elvira M. Orbeta, Sol Francesca S. Cortes, and Ana Christina V. Cruz

1 September 2014

ADB supported this study under TA 7733. We are grateful to Dr. Aniceto C. Orbeta Jr. for his advice and help in statistical analysis. The study has benefitted from valuable comments from Dr. Gilbert LLanto, Dr. Denis Mapa, Vincent Leyson and his DSWD staff as well as from workshop discussions with ADB, World Bank and DFAT development partners. We would also like to acknowledge the help of Allan Christopher D. Dacanay. The authors are solely responsible for any errors in the paper and the views expressed herein.

Appendix 5. Consultants’ Reports

33

Executive Summary

The study presents a methodology for defining, identifying, and classifying near-poor households. Using this methodology, it describes their salient characteristics and the challenges facing them. Reviewing local and international literature, the study furthermore lays out ideas on ways to address those challenges. Methodology for operationalizing the near-poor concept. Conceptually, the near-poor are households with per capita income above the official total poverty threshold (TPT) at a given year, but at high risk of subsequently falling into poverty. Metaphorically, these are non-poor households that precariously live at a knife-edge with little or no buffer against the economic effects of idiosyncratic and covariate shocks. The present study operationalizes this metaphor by looking for a near-poor income threshold (NPT) below which there is a high probability (say, 50-50 chance) that a household observed to have an income above TPT at time t would subsequently become poor at least once within the next few years. Using the above-mentioned NPT, the study identifies the near-poor as those households with incomes falling between TPT and NPT. The ratio NPT/TPT, or RAT, provides a sense of the magnitude of NPT relative to the official total poverty threshold and is used to identify and classify near-poor households in non-panel databases like the NHTS-PR. To find the appropriate NPT, the study develops a statistical tool designed to help policy makers and their technical staff figure out the poverty risk associated with different choices of NPT. The purpose is to make explicit and transparent the implicit poverty risk associated with those choices. Evidenced-based awareness of this risk, and a systematic exchange of views about what poverty risk level is tolerable, is good practice. Consensus on the near-poor definition needs to be built among stakeholders, because they differ in their perception and tolerance of poverty risk. They also differ in their appreciation of the desirability of strengthening current buffers against income instability. Moreover, their sense of what will fly with taxpayers varies. Using APIS panel data 2004-2010, the study finds that the risk of subsequent poverty for near-poor households with RAT values on or below 1.28 is over 50 percent, while the corresponding risk for those households with RAT of 1.28 (or more) is less than 50 percent. Putting it differently, at the RAT level of 1.28, the APIS data reveals that a 2004 non-poor household has a 50 percent probability of subsequently falling into poverty at least once between 2007 and 2010. The RAT of 1.28 is, therefore, the value that is consistent with the idea of near-poverty as living at a knife edge. The study explores an alternative definition of the near-poor as households who cycle back and forth between poverty and non-poverty. Previous studies, using panel data, have labeled them cyclical or transient poor (as opposed to persistently poor or persistently non-poor). The use of this definition is explored to find another way to identify the near-poor households in a situation where only non-panel cross-section data are available. In this regard, the study measures NPT as the sum of the official total poverty threshold plus the mean per capita income of households. The RAT estimate in this regard is about 1.37, which is higher than the other estimates.

Choosing an NPT for official use. The table below shows international comparison of RAT values used or recommended. This figure of 1.28, it turns out, falls between the RAT of 1.33 recommended by Orshansky (1966) and the new RAT estimate of 1.25 for the US by Hokayem

34

and Heggeness (2014) of the US Bureau of Census. Vietnam has a RAT of 1.25. This finding suggests that for the long term the RAT value of 1.28 is a reasonable basis for setting the Philippine NPT.

Comparison of RATs Used or Recommended

NPT/TPT ratio

PhilHealth 1.1

World Bank 1.20

Vietnam 1.25 US Census Bureau (Hokayem and Heggeness, 2014)

1.25

US (Orshansky 1966) 1.33

Authors’ Estimate 1.28

1.37

The choice of the official RAT and NPT for purposes of resource allocation should take into account not only the risk of subsequent poverty but also the other risks arising from lack of absorptive capacity, financial constraints, and uncertainty about the effectiveness of interventions and their design. A lower NPT may be more realistic and prudent in the short term and medium term, especially when pro-poor social assistance programs are limited by binding budgetary constraint. On this score, RAT 1.10 would arguably be an appropriate parameter to determine the NPT for the near-term (say the next three years) for social assistance or protection involving subsidies. RAT 1.10 would be a prudent choice for the following reasons. First, starting modestly would ensure that the beneficiaries of near-poor interventions would be on average high-risk households. Second, a modest start would minimize the risk and cost of failures, which could arise from spreading thinly the limited managerial and financial resources of DSWD over a huge number of households. The use of untested assumptions in the design of interventions could also result in failures. Third, development experience indicates that, as a general rule, innovative interventions are likely to be more successful and sustainable, if they start small and are scaled up after they have been shown to work. Ideally, sufficient time should have elapsed for evaluating their impact, assessing its design and making evidence-based adjustments. The success of this strategic approach is illustrated by the experience of Pantawid Pamilya and other CCT programs around the world. Fourth, it is easier politically to expand and sustain funding of a modest but effective and well managed program. For the scaling up phase (say after the third year), raising the NPT to RAT 1.20 would be appropriate, consistent with the World Bank’s estimate of what would be a reasonable RAT. This expansion would allow the government to cover more high-risk near-poor households. For the long run, when the Philippines would have already become an upper middle income country, raising RAT to 1.28 would be a natural extension. Towards a near-poor strategy. The Government is concerned about the near poor and is interested in developing a strategy for dealing with the issue. This concern makes sense for a couple of reasons. First, the number of households above the poverty line at high risk of falling

35

into poverty is substantial. APIS Panel Data 2004-2010 reveal that 38.6 percent of total households are cyclical poor, compared to 8.9 percent of the persistently poor. Moreover, the risk of subsequent poverty for non-poor households with RAT of less than1.28 is high at 50 per cent or more probability. This near-poor group constitutes about 12 percent of total households in 2010, Second, it is probably easier to prevent the near-poor or, more generally, the cyclical non-poor from falling into poverty than getting the persistently poor from moving out of poverty permanently. This is not to say that the persistently poor should be ignored. Rather, the point is that prevention of the precarious non-poor could be a valuable part of cost-effective and comprehensive poverty reduction strategy. In view of the above observations, the study calls for the development of a near-poor strategy that would seek to prevent the near-poor or the more numerous cyclical poor from returning to poverty, while keeping persistent poverty down. How would that strategy look like and how could it be organized coherently? It is proposed that the strategy can be organized around three pillars, to wit:

I. reforming current government policies that have been shown to have counter-

productive impacts on low income households;

II. fixing market failures arising from pervasive under-provision of public goods and

services, especially those that hurt the low income population disproportionately; and

III. providing time-limited “pantawid” assistance to high risk near-poor households and

prevent a vicious downward spiral into the trap of persistence poverty.

The principle behind the above strategy is to help the near-poor without undermining the ability of government to provide assistance urgently needed by the poor. Putting it more positively, the strategy is about finding win-win and broad-based solutions to the problems of low-income households (both poor and near-poor). Given limited resources and the number of low-income households, it is critical to focus on policy choices and interventions that could either simultaneously help both the poor and non-poor alike, or assist the near-poor without reducing the ability of government to help the poor effectively. Concrete examples of measures under each pillar are elaborated in the last section of the report. For Pillar I, minimum wage and rice policy reforms are good examples of high priority reforms that could positively impact the poor and the near-poor. There is now preponderant evidence that minimum wages in the Philippines have detrimental effects on the employment and income of the “common tao” and the disadvantaged population. (Paqueo, Orbeta, Lanzona, and Dulay, 2014). Another example of a cross-cutting win-win measure that, on balance, could also benefit both the poor and the near-poor is the separation of income support of poor rice farmers from general price (production) support. The idea on this score is the liberalization of the importation of rice and coupling it with a “pantawid” income support program to help deserving rice farmers adapt to a new policy environment. The liberalization policy would reduce the price of rice to consumers, especially the low income families. In turn, this price reduction could help to raise the purchasing power of those families and reduce hunger and under-nutrition. Furthermore, there would be less pressure to raise minimum wages arising from price increases in basic commodities. A key example of Pillar II high priority action is the acceleration of public infrastructure funding and implementation. The program could include among others good farm to market roads and flood control measures in areas that are populated mostly by low income households. Another

36

example is better control of public health threats like dengue, malaria, and communicable diseases that disproportionately affect the poor and near-poor alike. Pillar II could also support the development and expansion of efficient and innovative risk pooling schemes to help LGUs and households deal with natural disasters. Expansion of secondary schools to barangays without them to complement the extended Pantawid Pamilya should be given priority consideration. In regard to Pillar III, the government could develop a near-poor social assistance program that would be largely self-financing, perhaps with a little time-limited subsidy. The general idea here is to capitalize on the fact that compared to the poor, the savings of the near-poor over the medium-term appear to be notably positive. The program for Pillar III could include a couple of components. One could be the development of an innovative public-private microfinance collaboration. This proposal, some details of which are elaborated at the last section of the report, involves (i) tweaking the SEA-K program and focusing it on the social preparation of the near-poor to establish their track record and credit worthiness and (ii) providing interested firms this information. This could help microfinance enterprises sort out at lower cost good creditors and promising low income entrepreneurs. Lower cost can stimulate expansion of microfinance enterprises and increased access of low income households to interest-bearing savings deposit services, business loans and emergency consumption loans. Another possible component of Pillar III could be to allow workers from poor or near-poor households to waive their right to work at prevailing daily legal minimum wage rates so they can earn additional incomes. This waiver program would probably require an amendment of the minimum wage law. While waiting for the amendment of the proposed waiver to be passed by Congress and signed by the President, the government could in the meantime develop an enterprise-based cash-for-work employment program. This would encourage small and medium scale enterprises to hire workers from poor and near-poor households for temporary jobs. The newly hired workers would be paid the current legal minimum wages; but a fraction of those wages would be financed by the proposed program. This wage subsidy would be time-limited and highly targeted. On this score, public financing of the gap between market-determined and legal minimum wages would be consistent with public finance principles. As pointed out by Paqueo, Orbeta, Lanzona and Dulay (2014), if the legal minimum wages are regarded by the country’s representatives as a “public good” for social cohesion and other reasons, then in principle general tax revenues should be used to close the gap between the legal minimum and the equilibrium market wages. Requiring individual enterprises instead of the general public to pay for the public good would be an inefficient public policy. On this point, the above-mentioned paper reveals that unlike large firms, the imposition of minimum wages have had a detrimental impact on the size of employment of small enterprises, which constitute about 80 percent of Philippine businesses. The above examples do not form an exhaustive list of measures that could be included as part of a broad-based near-poor strategy. Other policy options and interventions should also be considered and explored. These options are laid out in the main text of this report and have been drawn from a review of relevant local and international literature.

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Cost of near-poor program. If the government decides to invest in a program that would facilitate the development and implementation of policies and interventions for the near-poor, what could be the order of magnitude of the cost of such program? Two scenarios are presented at the last section of the report. These scenarios are based on an imaginary program in which near-poor households would be provided with financial assistance to fill their consumption deficit during times of temporary poverty. The deficit is defined as the difference between the poverty threshold TPT and their consumption expenditures during the lean months. Under an optimistic scenario, where a perfect targeting system is assumed to be in place (making it possible to include only eligible households), the near-poor program could cost about PHP 6 billion in 2014 prices. This includes a 10 percent overhead and administration (OA) cost. This amount could finance a well-targeted program aimed at protecting the near-poor against the crippling effects of economic, health and environmental shocks. The above estimate of PHP 6 billion is only 10 percent of proposed 2014 Pantawid Pamilya budget. The above cost estimate would be higher, depending on the choice of NPT. If the near-poor income threshold (NPT), for example, were set at RAT = 1.30, the program cost including OA cost would rise to about PHP 12 billion. This amount would be 19 percent of the 2014 Pantawid Pamilya budget. Incidentally, expressing the near-poor cost estimate as a ratio to the Pantawid Pamilya budget should not be taken to imply shifting the latter’s allocation to the near-poor. The assumption is that the finance of the near-poor assistance would be new money. Under the other scenario, cost estimates could further increase to even much higher levels. Without targeting, program cost could double or triple the amount under the optimistic scenario. In this pessimistic scenario, all of the near-poor households (both eligible and not eligible) are included, as data would probably not be readily available to identify their current actual situation. The differential results between the two scenarios indicate the value of developing a good targeting system. On this point, a methodology discussed in the main report is being explored to determine and rank the subsequent poverty risk of a near-poor household -- using variables that are in the NHTS-PR database. Given the importance of good targeting, it would be desirable to further test the accuracy of the aforementioned methodology and develop a richer model and up-to-date database needed for a more advanced targeting system.

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Main Report 1. Introduction

Most governments of the development world are focused on reducing poverty and alleviating its worst consequences on the poor. But what about the non-poor, whose incomes are above the official poverty line but live precariously? Many of them, it is said, live at a knife-edge. That is, their risk of falling back into poverty is so high, it is claimed, that they have had to lead miserable lives to survive without much social assistance. Being above the poverty line, this so-called near-poor are often not officially entitled to most of the social assistance that government provides to those it classifies as poor. Questions, therefore, have been raised on what the government can and should do for the near-poor. This issue has recently become topical among policy circles in the Philippines. On this score, the Department of Social Welfare and Development (DSWD) and other government agencies have sought to clarify the near-poor challenges and the nature of the policy issue. 4 This study seeks to define the near-poor families: Who they are, how large is their population, where do they live, what is their livelihood, how much are they benefitting from government social assistance and protection subsidies, and what are the socioeconomic challenges they are facing. On policy, what should be the stance of the Government, given its budget constraints and the more urgent needs of the poor? What (if any) can the Government do to meet the challenges of the near-poor without undermining its ability to help get them out of poverty? What can the near-poor do on their part? These are the questions this study is investigating. The structure of the study is as follows. The next section reviews the international discussion of the near-poor issue. Section 3 briefly describes poverty in the Philippines to put the near-poor issue in context. Section 4 proposes a methodology for defining a Near-Poor Threshold (NPT) relative to the Total Poverty Threshold (TPT) to classify and identify the near-poor. Included here is a proposal for a scoring scheme that would identify and prioritize high risk near-poor households and profile them. The final section includes reflections and suggestions on what could be the key elements of a coherent near-poor strategy. At the heart of these suggestions is the need to address the concerns of the near-poor that enhances rather than undermine efforts to help the current poor.

2. Review of the International Discussions of the Near-Poor

Mollie Orshansky (1966), architect of the modern day poverty measure, defines the “near-poor” as those individuals living between 100 and 133 percent of official poverty thresholds. She describes them as a “highly vulnerable population”, a “sizable group in the population living always in the margin – wavering between dire poverty and a level only slightly higher but never really free from the threat of deprivation” based on the reciprocal trend in the number of poor and near-poor between 1959 and 1964. They include low-income households that are “vulnerable to the stress of economic instability caused by jobs loss, ill heath, and fluctuations in housing, food and transportation costs” (Heggeness and Hokayem, 2013). Popular media provides a more graphic description of the near-poor. The New York Times for instance describes the near-poor in the US as “they drive cars, but seldom new ones. They earn paychecks, but not big ones. Many own homes. Most pay taxes. Half are married, and nearly half live in the suburbs. None are poor, but many describe themselves as barely scraping by” (DeParle, Gebeloff and Travernise, 2011).

4 The Department of Social Welfare and Development (DSWD) and the ADB support this study partly in response to a request by

PhilHealth, who needed to define an analytically sensible basis for identifying the near-poor and for dealing with an ongoing policy debate about near-poor poverty.

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The near-poor concept is primarily based on a household’s vulnerability to poverty, defined as “the propensity to suffer a significant welfare shock, bringing the household below a socially defined minimum level”5 (Haughton & Khandker, 2008). In risk and vulnerability (R & V) analysis, “propensity to suffer a significant shock” is measured as the probability of being poor next period or at some point over the next few years6; “welfare shock” is commonly measured as a change in consumption per capita, although income is also used; while “socially defined minimum level of welfare” is represented by the absolute poverty line. Transience and types of poverty. Studies have shown that people indeed move into and out of poverty. Therefore, there’s a need to distinguish between chronic and transient poverty to guide policy makers in the design and implementation of policies and programs. Households whose average consumption per capita over time is at or below the poverty line are classified as chronically poor while those who are poor from time to time but, on average are not poor, are classified as transient poor (Table 1). Chronic or transient poverty may result from a household’s inability to accumulate sufficient physical or human capital or its inability to smooth consumption, respectively (Kirimi and Sindi, 2006). Thus, for chronically poor households, the policy concern is with increasing their average consumption above the poverty line; and for those among them who remained poor, with providing more education, skills, and physical assets. For the transient poor, the likely concern is for short-term relief, through insurance or income stabilization schemes.

Table 1. Policy Concern by Type of Poverty

Type of Poverty Description Policy Concern

Chronically poor Households (HHs) whose average

consumption per capita over time is at or

below the poverty line

Raise average consumption levels above

the poverty line

Persistently poor HHs, among the chronically poor, who

never emerge from poverty, not even for a

year or two

More education, skills and assets, and to

become less isolated from the rest of the

economy

Transient poor HHs who are poor from time to time, but

who are not poor on average

Short-term relief, through insurance or

income stabilization schemes

Never poor

(Persistently non-poor)

HHs who do not even drop into poverty

occasionally

Source: Haughton & Khandker (2008)

Vulnerability-to-poverty framework. A framework for analyzing vulnerability to poverty has been developed by various analysts and is laid out in Table 2. The basic idea is that households have assets (such as land and labor and physical, social and human capital) which they deploy to generate income, which in turn, are used to generate well-being through consumption. At each process, poor households including those living just above the poverty line are exposed to risks which may degrade assets (through illness, uncertain land tenure, war, natural disaster), reduce income (if there is drought or when output prices fall), and reduce the ability to consume (if the cost of food rises or if food is rationed). Policies geared at reducing household vulnerability, thus, will need to focus on raising consumption and on providing social protection (Haughton and Khandker, 2008).

5 The definition was adopted by Haughton and Khandker (2008) from Kühl 2003, 4, citing Alwang, Siegel, and Jorgensen (2001). 6 To generate probabilities of being poor usually require the use of econometric models unless the household is persistently poor, in

which case, the probability of being poor is certain. Households with a 50% probability of being poor are referred to as “highly vulnerable”.

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Table 2. A Framework for Analyzing Vulnerability to Poverty

Assets Income Well-being/Capabilities

• Human capital, labor

Physical/financial capital

• Common and public goods

• Social capital

• Returns to activities and assets

• Returns from asset disposal

• Savings, credit, investment

• Transfers and remittances

Ability to obtain

• Consumption

• Nutrition

• Health

• Education

Examples of risk (a)

Examples of risk (b)

Examples of risk (c)

• Loss of skills due to ill

health or unemployment

• Land tenure insecurity

• Asset damage due to

climate, war, disaster

• Uncertain access to

common and public goods

• Loss of value of financial

assets

• Output falls due to climatic

shocks, disease, conflict

• Input prices rise

• Reduced returns on financial

assets

• Uncertain cash flow during

production

• Weak contract enforcement,

wages not paid

• Imperfect information about

opportunities

• Price risk in food markets

• Food availability/ rationing

• Uncertain quality of public

provision in health and

education

• Imperfect information on

how to achieve good health,

nutrition

Source: Based on Dercon (2001, 17); lifted from Haughton and Khandker, 2008 Tab. 12.4

On this score, Table 3 presents a menu of formal and informal mechanisms intended to help households reduce, mitigate or cope with the various risks facing them. Households and communities usually respond by diversifying assets and sources of income and through various types of social insurance and networks. Government can help in three ways: 1) reduce risks through sound macroeconomic, public health, education, infrastructure, and -labor market policies, 2) mitigate such risks by providing or regulating insurance and setting up safety nets, and 3) helping them cope with shocks through social assistance, subsidies, cash transfers. Group and market-based mechanisms are also available. (Haughton and Khandker, 2008)

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Table 3. Mechanisms for Managing Risk Informal Mechanisms Formal Mechanisms

Individual and household Group-based Market-based Publicly provided

Reducing risk

• preventive health

practices

• migration

• more secure income sources

• collective action

for infrastructure,

dikes, terraces

• common property

• resource

• management

• sound

macroeconomic

policies

• environmental

policy

• education and

training policy

• public health

policy

• infrastructure

• labor market

policies

Mitigating risk

Diversification

• crops and plots

• income source

• investment in physical and

human capital

• marriage and extended family

• sharecropping

• buffer stocks

Insurance

• occupational

associations

• rotating credit

associations

• investment in

social capital

• savings

accounts in

financial

institutions

• microfinance

• old age

annuities

• accident,

disability and

other insurance

• microfinance

• agricultural

extension

• liberalized trade

• protection of

property rights

• pension

systems

• mandatory

insurance for

unemployment,

illness, disability

Coping with Shocks

• sale of assets

• borrowing from moneylenders

• child labor

• seasonal/temporary

migration

• reduced food

consumption

• transfers from

mutual support

networks

• sale of financial

assets

• loans from

financial

institutions

• social

assistance

• workfare

• subsidies

• social fund

• cash transfers

Source: World Bank, 2000, 141(slightly modified); lifted from Haughton and Khandker, 2008 Table 12.5.

Table 4 further provides a comprehensive menu of responses for various types of risks/vulnerabilities crafted by the Department of Social Welfare and Development and the NEDA-SDC-Subcommittee on Social Protection (2012) for the Philippines. The risks/vulnerabilities are classified into four, namely, individual lifecycle, economic, environmental and natural, and social/governance.

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Table 4. Types of Risks/Vulnerability and Responses Assessment Responses

Types of

Risks/Vulnerability Household or Informal

Mechanism Government

Private and Civil Society Sector

Individual Lifecycle

Hunger and malnutrition Support from relatives, subsistence farming

Health and nutrition policy, programs and projects

Provision of nutrition services, soup kitchens, etc.

Illness, Injury, Disease (incl. HIV-AIDS

Extended family, community support

Social security, health insurance and micro-insurance

Private insurance schemes

Disability Hygiene, preventive health Social security, social assistance, employees compensation

Private insurance and micro-insurance

Old Age Asset/Savings reduction Pension Plan Old age annuities, private pension

Death Debt Social Security Private life insurance

Economic

End of source of livelihood Diversified sources of livelihood

Sound macro and sector policies for job generation; emergency and guaranteed employment

Private sector investments that are job-generating

Unemployment Private transfers, child labor Regional and rural development policies, Emergency and guaranteed employment

Private job search institutions

Low and irregular income Depletion of assets/savings Labor market policies, social assistance, conditional cash transfers

Banking services to the poor, microfinance

Price instability of basic commodities

Reduced consumption of basic goods

Price control inflation management

Sales discounts

Economic crisis Migration Social funds, subsidies, emergency employment

Environmental and Natural

Drought

Migration Community Action Private transfers Extended family support Asset/Savings Depletion

Environmental policy, programs and projects Infrastructure investments Relief and rehabilitation Relocation-temporary and permanent Disaster prevention and

mitigation measures Geo-hazard mapping Insurance against disasters

Environmental advocacy and prevention of man-made disasters Disaster mitigation and

prevention measures

Relief and Rehabilitation programs

Rains and floods

Earthquakes

Volcano eruption and landslides

Social/Governance

Social exclusion Community networks Inclusive Growth, Good governance, transparency and accountability

Good corporate governance, corporate social responsibility

Corruption Community pressure Public information, transparency and accountability campaign; bottoms up budgeting

Strengthening participation of NGOs and CBOs

Crime and domestic violence

Women’s groups and watchdogs

Providing security and equal access to justice

Peace and order promotion (e.g. anti-drug campaigns)

Political instability and armed conflict

Migration Participation of citizens and civil society groups; peace negotiations

Advocacy for democracy and democratic transitions

Source: Department of Social Welfare and Development and NEDA-SDC-Subcommittee on Social Protection, 2012.

Analytic methods used to identify near-poor. There are five common analytic methods for measuring vulnerability and identifying those most at risk of falling into poverty, namely, 1) proportions to poverty line, 2) vulnerability-to-poverty indicators, 3) lifecycle risks, 4) heuristic approaches, and 5) qualitative assessment. These methods have been used in the World Bank’s risk and vulnerability analytic work between FY2000-FY2007 (Kozel, Fallavier & Badiani, 2008). Table 5 provides a description of these methods/approaches and the type of data used.

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Table 5. Methods for Measuring Vulnerability and Identifying Those Most at Risk of Falling into Poverty

Method and Data Used Description

Proportions of the Poverty Line (PPL) (usually cross-section data)

Provide an estimate of households not classified as currently poor but whose incomes lie near the poverty line, and thus are at risk of poverty

Vulnerability-to-Poverty Indicators (VPI) (cross-section or panel data)

Identify vulnerable households and estimate using econometric models the probability of being poor next period given current consumption level; Classifies vulnerable HH into different categories (e.g., transient - or chronic) and by extent of vulnerability (e.g., high, moderate, low)

Lifecycle Risks (LR) (usually cross-section data)

Identify vulnerable groups at particular points in their life cycles or given particular characteristics such as age, gender, and other personal or household characteristics

Heuristic Approaches (HA) (cross-section data augmented by risk modules and by administrative information)

Draws on empirical information about individuals and households that experienced shocks, those who are poor or are badly off; Measures the incidence of shocks and identifies key risks faced by vulnerable HH

Qualitative Assessment (QA) (qualified field work, surveys)

Often combined with quantitative assessments to identify vulnerable HHs and the set of pivotal factors that perpetuate or exacerbate poverty

Source: Kozel et al., 2008 (modified)

Proportions of the poverty line. Using cross-section data, this approach identify individuals and households not classified as currently poor but are at risk of poverty because their incomes lie near the poverty line. In terms of some proportion of household consumption or income to the poverty line, existing studies define near-poor to include individuals whose household incomes or consumption are between 100 to 220 percent of the poverty line, depending on the threshold used (Table 6). In the U.S., Orshansky (1966) in her review of the relative economic position of different types of households in the US between 1959 and 1964 defined near-poor to include individuals and families with family incomes at 100 to 133 percent of the official poverty thresholds. The poverty and near poverty thresholds are based on the amounts needed by families to purchase nutritionally adequate diets at minimum cost when one third of the family income is used for food. The near poor level was derived from the low-cost food plan suggested by the U.S. Department of Agriculture; about one-third higher in dollar cost than the economy food plan which is used as basis for the poverty threshold. The latter is three times the cost of minimum food diet in 1963; varies by family size, composition, and age of householder; and are updated annually for inflation using the Consumer Price Index (CPI-U) (Annex 1). Gross before-tax income, the same family income used to determine those who are in poverty, was used as a resource measure. Data were derived from special tabulations from the Current Population Survey (CPS) for March 1960-1965 by the U.S. Census Bureau for the Social Security Administration. Heggeness and Hokayem (2013) noted that studies in the U.S. between 2003 and 2012 have not consistently defined near-poor. Depending on the poverty measure used, the proportions ranged from 100 to 150 percent of the poverty line using the National Academy of Sciences (NAS) measure (Ben-Shalom, Moffitt and Scholz, 2011) and 100 to 200 percent using the Supplemental Poverty Measure (SPM) (Short and Smeeding, 2012). These poverty measures differed according to five dimensions: the resource unit and measure, and the measure,

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adjustment and updating of the poverty threshold. For example, with respect to the resource measure used, the official poverty measure uses gross before-tax income while the NAS and SPM consider a wider range of resources including cash income, in-kind benefits, tax credits, work expenses, and out-of-pocket medical expenses. With respect to the calculation of the poverty threshold, the official measure uses the minimum food diet in 1963 while the NAS and SPM uses expenditures on food, clothing, shelter, utilities, plus ‘a little more’ for additional expenses. Annex 1 provides a comparison of these three poverty measures along these five dimensions. Heggeness and Hokayem (2013) using Orshansky’s definition and over 45 years (1966–2011) of micro data generated by the U.S. Census Bureau’s CPS Annual Social and Economic supplements (ASEC), compared the proportion of individuals living near poverty by demographic and socio-economic characteristics and examined how these proportions change under the two alternative poverty measures. Hokayem and Heggeness (2014), on the other hand, define individuals in near poverty to include those with family income between 100 and 125 percent of the poverty thresholds for consistency with what the U.S. Census Bureau refer to in their Current Population Reports as near poor since 19717. The study also utilized data from the CPS ASEC over 45 years (1967-2013). The International Labor Organization (ILO, 2013), in its classification of the world’s labor force, refers to near-poor workers as those with per-capita household consumption between US$2.0 to US$4.0 a day (about 160 to 220 percent above the US$1.25 a day poverty line) 8 . This classification was established as a measure of those who are not poor but are highly vulnerable to fall into poverty. In less developed countries, World Bank (WB) studies define near-poor or vulnerable households to include those with incomes or consumption within 20% of the poverty line. For instance, in the Philippines, the WB Philippine Development Report for 2013 refers to those with incomes within 20% of the US$2.0 a day 2009 official poverty line as vulnerable non-poor (Chua 2013). In Indonesia, near-poor is defined as those with consumption of approximately 1.2x the poverty line with a US$1.2 a day poverty threshold (Jellema and Noura, 2012). The near-poor is also used to refer to households belonging to the lowest three deciles based on consumption as covered by an Indonesian health insurance program intended for the poor and near-poor (Harimurti, Eko, Pigazzini & Ajay, 2013). It was noted that proportions of the poverty line will not serve as a good guide in identifying those who have a significant probability of being poor in the next period unless the individual/household is persistently poor.

7The Current Population Reports of the Census Bureau include tables on the number and proportion of the population with family

income between 100 and 125 percent of the poverty thresholds starting in 1971 in response to a Memorandum issued by the Bureau of the Budget in 1969 which provides, among others, for the publication of statistics on the population below 125 of the poverty threshold, noting that this is essentially the same level as Orshansky’s near poor level.

8 Measured at purchasing power parity (PPP) from the 2005 International Comparison Program

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Table 6. Definition of Near-Poor (Income-Based except ILO and Indonesia)

Definition of Near-Poor Poverty Threshold Measure Used

Reference

Individuals with family income between 100 and 133 percent of the official poverty threshold

three times the cost of minimum food diet in 1963

Orshansky (1966); Heggeness and Hokayem (2013)

Individuals with family income between 100 and 125 percent of the poverty thresholds

three times the cost of minimum food diet in 1963

Hokayem and Heggeness (2014)

Those living between 100 and 150 percent of poverty

National Academy of Sciences (NAS) measure

9

Ben-Shalom, Moffitt and Scholz (2011)

Those with modest incomes - living between 100 to 200 percent of poverty

Supplemental Poverty Measure (SPM)

10

Short and Smeeding (2012)

Workers with per-capita household consumption of between US$2.0 to US$4.0 a day ( i.e., between 160 to 220 percent of poverty)

US$1.25 a day (@2005 PPP) absolute poverty line

ILO (2013)

Vulnerable non-poor – those whose income is within 20% above the poverty line

US$2.0 a day – 2009 official poverty line

Chua (2013)

Those with consumption of approximately 1.2x the poverty line

US$1.20 a day 2011 national poverty line in Indonesia

Jellema and Noura (2012)

Lowest three deciles based on household consumption as covered by the Indonesian health insurance program intended for the poor and near-poor

lowest three deciles Harimurti et al. (2013)

Vulnerability-to-Poverty Indicators. This method uses econometric models and panel or cross-section data to identify the vulnerable HHs and estimate their probability of being poor. It also allows the classification of HHs into transient or chronic poor. For a simple probability of being poor model, three pieces of information are required: 1) household’s expected level of consumption per capita in the next period; 2) the variance of the household’s expected level of consumption per capita in the next period and some assumption about the distribution of the variance; and 3) poverty line (Haughton and Khandker, 2008). Vulnerability-to-poverty indicators may be categorized into income-related, non-income related, and multi-dimensional. For income-related vulnerability, NSCB (2005) considers the ratio of total expenditure to total income as a significant indicator of household vulnerability as it indicates the proportion of income going to saving. Families with higher ratios are said to have higher vulnerability incidence. For a ratio ≥2, vulnerability incidence is estimated at 82.4%. For non-income poverty and vulnerability, broader measures including basic living conditions and human capital with household assets and education, respectively, as proxies are used in assessments. Indicators for multi-dimensional poverty and vulnerability, on the other hand, include pre-existing conditions of poverty such as living in houses with light materials, water supply and sanitation, gender dimension, and human rights dimension.

9 The National Academy of Sciences Measure (NAS) poverty threshold measure is 80% of the median of expenditures on food,

clothing, shelter, and utilities for a 2 adult, 2-child family multiplied by 1.2. 10 For the Supplemental Policy Measure (SPM), the threshold measure used is the 33rd percentile of expenditures on food, clothing,

shelter, and utilities for a family with exactly two children multiplied by 1.2.

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The choice of the vulnerability line is arbitrary (Haughton and Khandker, 2008). One of two thresholds is typically used 11 : a 50% probability or use of headcount poverty rate. The probability of being poor is said to rise as the time horizon is increased. For risk and vulnerability (R & V) analysis, the absolute poverty line is used as threshold. The vulnerability-to-poverty indicators approach has been used by the World Bank in Burkina Faso, Indonesia, Thailand and the Philippines (Kozel et al., 2008). Lifecycle risks. This approach identifies those who are vulnerable at particular points in their life cycle or given particular characteristics. The approach has been applied by World Bank’s R & V analysis in Argentina, Mexico, Columbia and Benin (Kozel et al., 2008). The results indicate that single, young women, for example are found to be more vulnerable to poverty. Heuristic Approaches. This type of approaches measures the incidence of shocks and identifies those risks that are significant using empirical information from households that experienced shocks. This approach has also been applied in the World Bank’s R & V analysis in Guatemala, Afghanistan, Colombia and Ethiopia (Kozel et al., 2008). Qualitative Assessments. This method which is based on field work identifies those who are vulnerable and determine key factors that cause their situation to continue or worsen. Qualitative assessments are often combined with quantitative assessments such as those undertaken in Burkina Faso and Zambia (Kozel et al., 2008). Emerging method for identifying the near-poor. The Listahanan or the National Household Targeting System for Poverty Reduction (NHTS-PR) of the Department of Social Welfare and Development (DSWD) is an information management system that can be used in identifying the near-poor. The NHTS-PR contains a comprehensive socio-economic database of poor households nationwide which government agencies can use as basis in identifying beneficiaries for social protection programs as per E.O. 867 s. 2010 (DSWD-NHTS-PR Webpage). The NHTS-PR follows a multi-step process which includes geographic targeting, assessment of households, and validation of identified households (Chaudhury, 2012). To determine the household’s economic condition, the NHTS-PR combines geographic targeting with proxy means test (PMT)-based targeting. Official poverty incidence according to the latest FIES and the Small Area Estimates of the NSCB are used for regional targeting at the provincial and at the municipal levels, respectively. At the household level, targeting is based on a computerized ranking and PMT. PMT is a statistical model that estimates the income of families based on observable and verifiable variables. These variables include the marital status, level of education, and primary occupation of household heads; household composition; housing conditions and tenure status; access to basic services such as water, electricity and sanitation facilities; assets and appliances owned; frequency of OFW remittance, if any; type of disability and cause of displacement, if any; access to social protection programs/services; whether the household belongs to an indigenous people group; and regional variables (NHTS-PR Code Book – Household Family Roster). A household is classified as poor if the estimated income is below the provincial poverty threshold.

11 Using 50% probability – a HH with a 50% probability of being poor is considered “highly vulnerable”; Using Headcount poverty

rate P0, a probability higher than P0 – vulnerable HH; a probability higher than P0 but lower than 50% - low vulnerability; a probability lower than P0 are referred to as “not vulnerable”.

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A nationwide household assessment survey is conducted by the DSWD every four years starting in 2008 to generate the data needed. Validation of the list of potential household beneficiaries is done at the community level. The NHTS-PR was used to identify beneficiaries, initially for the 4Ps in 2008 and starting January 2011 for the other poverty and social-assistance programs of the government (Fernandez and Olfindol, 2011). The database was shared with PhilHealth, the Department of Agriculture, the Department of Health, and the International Labor Organization. PMT, following the country’s experience is also used by Malaysia, Indonesia, Mongolia, and by Latin American countries except Brazil. Stylized facts about near poverty. The following discussion summarizes significant findings about the near-poor or vulnerable non-poor population as to who they are, their share in the total population, their characteristic, and participation in government social protection programs based mainly on application of the various methods for risk and vulnerability analysis by the World Bank in different countries. The near-poor or vulnerable non-poor includes households with incomes or consumption between 100 to 220 percent of the poverty line based on existing studies as shown in Table 6. With respect to the share of the near-poor or vulnerable non-poor to the total population, studies indicate that they represent a sizeable group of the population (Table 7). In the U.S., Orshansky (1966), analyzing poverty trends for 1959-1964, concluded that the near-poor, which includes individuals with incomes between 100 and 133 percent of official poverty thresholds, is a sizeable group representing 9.0% in 1959 and 8.3% in 1964 of the non-institutional population. Using Orshansky’s definition, Heggeness and Hokayem (2013), estimated near-poor rates in the U.S. at 8.3% in 1966 and 6.6% in 2011. Hokayem & Heggeness (2014) estimated lower near-poverty rates at 6.3% in 1966 and 4.7% in 2012 based on the U.S. Census Bureau statistics of those in near poverty (i.e., those living within 100 to 125 percent of the poverty thresholds). The ILO (2013) estimates that near poor workers (those living between US$2 and US$4 a day) represent about 25% (661 million) of the developing world’s workforce in 2011. Using vulnerability to poverty indicators, those identified most at risk of poverty ranges from about 9 to 37 percent of the population. WB studies (Kozel et al., 2008) found that the vulnerable population was about 33% for Serbia and 37% for Montenegro, if the vulnerability line is set at 50% above the poverty line compared with 10.6% and 9.4%, respectively, if poverty line is set such that headcount poverty rate is 20 percent. For Indonesia, the vulnerable population was estimated at 10 to 30 percent using headcount poverty as a threshold. Some studies distinguish between chronic and transient poor among the identified vulnerable households. For Burkina Faso, transient poor accounted for 37% of the vulnerable households. For the Philippines, 53% of HHs classified as poor were transient poor in 2009 while of those classified as transient poor based on three surveys (2003, 2006, and 2009 FIES), 53% in 2003 and 63% in 2006 were classified as non-poor with income equal to or 20% of the poverty line (Reyes, Tabuga, Mina & Datu 2011).

48

Table 7. Share of Vulnerable Households to Total Population of Households

Country/Method/Data Used Vulnerable Population/Households

Burkina Faso1 (VPI)

-Used HH level survey data Of the vulnerable HHs: Chronic poor - 63% Transient poor- 37%

Indonesia1 (VPI)

-used two panel data sets to estimate the probability of being poor next period given current consumption levels

An additional 10-30% of the population were found at substantial risk of poverty if poverty line is set such that headcount poverty rate is 20%

Philippines2 (VPI; transition matrix)

-used panel data (2003, 2006 & 2009 FIES)

Of HHs classified as poor in 2009: Transient – 53% Of HHs classified as Transient poor based on the 3 surveys: Non-poor with income ≥ 20% of poverty line – 83% in 2003 and 63% in 2006

Serbia and Montenegro1 (PPL)

(cross-section data)

Vulnerability line is set at 50% above the poverty line: Serbia - 33%; Montenegro – 37% If poverty line is set such that headcount poverty rate is 20%: Serbia - 10.6%; Montenegro - 9.4%

U.S.3 (PPL) Near poor rates (using Orshansky’s definition – 100 to133% of the

poverty line): 1959 - 9.0%; 1964 - 8.3%

U. S.4 (PPL)

- U.S. Census Bureau’s CPS ASEC micro data from 1967-2012

Near poor rates (using Orshansky’s definition): 1966 – 8.3%; 2011 – 6.6%

U. S.5 (PPL)

- U.S. Census Bureau’s CPS ASEC micro data from 1967-2013

Near poor rates (using U.S. Census Bureau’s definition – 100 to 125% of the poverty line): 1966 – 6.3%; 2012 – 4.7%

Source: 1/ Kozel et al,. 2008; 2/ Reyes et al., 2011; 3/ Orshansky, 1966; 4/ Heggeness and Hokayem, 2013; 5/ Hokayem & Heggeness (2014)

As to the characteristics of households identified as near-poor or vulnerable non-poor, Table 8 highlights the significant findings based on studies in selected countries. The Philippine study indicated that, in terms of location characteristics, vulnerable households are mostly located in rural areas (Reyes et al., 2011). Rural households, based on a study in Afghanistan, are vulnerable to drought, farming shocks, natural disasters, epidemics, and increase in food price (Kozel et al., 2008). In terms of dwelling characteristics, transient poor12 in the Philippines, has a relatively lower proportion of HHs who lives as informal settlers compared to chronic poor. In terms of household/family characteristics, transient poor in the Philippines have smaller family size (same with Burkina Faso), mostly male-headed, single-headed; heads of HHs are more educated; have a lower dependency ratio, more are unemployed, a lower proportion of HH engaged in agriculture, more are in non-agriculture sector. In the U.S., near poverty rates are higher for single, separated, divorced, or widowed than those who are married; those with less education and those not in the labor force (Heggeness and Hokayem, 2013). In terms of ownership of durable goods, in the Philippines, transient poor have a higher proportion of assets owned and a higher proportion receiving remittances. Based on lifecycle, younger people, particularly young women are more vulnerable because their productivity may be reduced by childbearing (Kozel et al., 2008).

12 Transient poor is defined as “those who are classified as poor during a given point in time but were previously non-poor for at

least one year during the period under study” (Reyes et al., 2011)

49

Table 8. Characteristics of Vulnerable Households

Country/Method Characteristics of Vulnerable Households

Burkina Faso1 (VPI) Smaller HH, with limited access to land and transportation

Philippines2 (VPI) Vulnerable HHs (both chronic and transient poor) are located in rural areas and

are mostly engaged in agriculture; Transient poor (relative to chronic poor):

- Relatively lower proportion live as informal settlers - smaller family size - Mostly male-headed HH - Single-headed HHs; - Heads of HHs are more educated; - Lower dependency ratio - More are unemployed - Lower % of HH engaged in agriculture (59% vs. 71%) - Slightly higher % in non-agriculture sector (29% vs. 27%) - Higher proportion receiving remittances - Higher proportion of assets owned

Indonesia (VTP)3 HHs whose heads are engaged in agriculture (urban and rural areas)

Rural HHs whose heads are unemployed

U. S.4 (PPL) Those individuals who are single, separated, divorced, or widowed have higher

near poverty rates than those who are married; Those individuals with less education and those not in the labor force have both higher poverty and near poverty rates

Benin1 (LR) Younger people were more likely to be counted among the poorer, particularly

young women whose productivity is greatly reduced by childbearing

Columbia1 (HA) Individuals displaced due to conflict were found extremely vulnerable to shocks

Afghanistan1 (HA) Key risks identified among rural HH: drought, farming shocks resulting in a loss

of crops or animals, natural disasters, epidemics, and increases in food prices

Source: 1/ Kozel et al., 2008; 2/ Reyes et al., 2011; 3/Akita and Dariwardani, 2013; 4/ Heggeness and Hokayem, 2013

With respect to the participation of vulnerable households in government Social Protection Programs, Heggeness and Hokayem (2013) reported that in the U.S., more individuals living near poverty are participating in public assistance programs such as food stamps (currently known as SNAP), free or reduced school lunch, and Earned Income Tax Credit (EITC) in 2011 than in 1981. It was estimated that of individuals living near poverty, about 11.7% in 1981 and 5.0% in 2011 lived in households receiving public assistance. In developing countries such as the Philippines, leakages to targeting in social protection programs ranged from 44 to 71 percent indicating that, although the near-poor are not covered, they are actually receiving benefits from these programs (Manasan, 2010). Prevailing hypotheses about near poverty and economic mobility. The following summarizes some prevailing hypotheses about near poverty and economic mobility. The summary could be useful in thinking about near-poor targeting and policy modeling. Hypothesis 1: Economic mobility is sensitive to the choice of income or consumption as welfare indicator. Haughton and Khandker (2008) noted that the use of consumption as a measure of welfare implicitly allows for household’s coping mechanism to operate. Income, on the other hand, tends to overstate household’s well-being in good years and understate it in drought

50

years. The ratio of food expenditure to total expenditure or the ratio of total expenditure to total income were considered as significant indicators of the vulnerability of HHs by the NSCB (2005). Hypothesis 2: A household’s geographic location and geographic profile (which also includes natural resources, density of economic activity, industrial structure, public goods, government policies and programs, and a functioning credit and insurance market) influence their probability of falling into poverty. Vulnerability differs between urban and rural areas. Households located in rural areas were found to be more vulnerable to poverty than those in urban areas (Reyes et al., 2011; Kirimi and Sindi, 2006; Akita and Dariwardani, 2013). Hypothesis 3: Household’s assets, particularly, more wealth and financial resources can prevent vulnerable households from falling into poverty (Kirimi and Sindi, 2006). Hypothesis 4: Investments in human capital (proxied by education) are less important than financial resources and wealth in preventing households from falling into poverty (Kirimi and Sindi, 2006). Hypothesis 5: A household’s physical asset, in particular, the number of electrical devises owned (which has a direct relationship with a household’s electricity consumption) influence HHs probability of becoming poor the next period. NSCB (2005) showed that there is an inverse relationship between the number of electrical devices owned and vulnerability incidence. Hypothesis 6: Family characteristics such as family size and the proportion of HH member less than 7 years old and those 7 to 14 years old influence a household’s vulnerability to poverty (NSCB, 2005). Vulnerability incidence increases as these variables increase. Hypothesis 7: The extent of near poverty, particularly in rural areas, is sensitive to the change in poverty line. Akita and Dariwardani (2013) showed that a 10% increase in the poverty line will raise poverty incidence by 3.8% in urban areas and 6.8% in rural areas and by 8.2% and 13.7%, respectively with a 20% increase in poverty line. Solution approaches. Annex 2 shows policy recommendations to address the different types of risks/vulnerabilities faced by the near-poor based on studies in selected countries. The specific policy recommendations are classified further into three major types of intervention, namely: consumption smoothing, income stabilization, and poverty prevention. Other types of intervention include transition promotion, provision of education and health services, and labor market interventions. For individual lifecycle risks, the recommendations include the provision of quality health services and facilities in Mozambique; provision of increased health coverage in Indonesia; protection of incomes of older people in Mexico; and improved female education to address the problem of hunger and nutrition. For economic risks, the interventions include poverty prevention and income stabilization in Kenya; income stabilization in Mexico; and transition promotion for Mozambique and Rwanda. For environmental and natural risks/vulnerabilities faced by HHs such as flooding in the U.S., the specific interventions involve relocation and national flood forecasting. The Overseas Development Institute recommends the setting up of annual calamity funds especially in countries affected by disasters annually and exploration of financial risk transfer instruments (insurance, weather derivatives and catastrophe bonds), continued scientific understanding of natural hazards, dissemination of information on hazards and related risk in a user-friendly manner. For Bangladesh, income diversification to spread environmental risk across multiple

51

economic activities and artificial elevation of flood and drought prone villages, are among the policy recommendations. For social/governance related risks, implementation of social safety net policies and programs were recommended in Indonesia and Rwanda to smooth consumption of vulnerable households. In Rwanda, strengthening of peasant rights and lobbying for the rural poor were also recommended to address the problem of social exclusion. 3. Poverty, Inequality and Economic Mobility in the Philippines

To rationally deal with the near-poor issue, an understanding of the Philippine economic situation is required. This section, therefore, elaborates on certain economic and social issues that are pertinent to the objectives of the study. Poverty incidence rate and inequality remain high in the Philippines. These can be seen in Figures 1 and 2. Although there has been some reduction in the poverty rate in the past decades, the decline is not fast enough to reduce the total number of poor households, given rapid population growth. The conventional view, therefore, is that poverty has not changed much since the beginning of this century. In general, there is widespread impression that the poor remains poor (or even poorer).

Figure 1. Poverty Incidence Over Time (1985-2012)

Source: NSCB Poverty Statistics Report, lifted from Paqueo, Orbeta, Lanzona and Dulay (2014)

0

10

20

30

40

50

0.00

5.00

10.00

15.00

20.00

25.00

30.00

1985 1988 1991 1994 1997 2000 2003 2006 2009 2012%

Mil

lio

ns

Year

Poor Population Poverty Incidence (%)

52

Figure 2: Inequality Trends (Gini Coefficient)

Source: Lifted from NSCB, lifted from Paqueo, Orbeta, Lanzona and Dulay (2014)

A closer look, however, at the economic mobility data reveals a need for a more nuanced story. The reality is more complex, as pointed out by Reyes et al. (2011). Using FIES panel data, they find that there is in fact a lot of economic mobility.13 Paqueo, Orbeta, Lanzona and Dulay (2014) confirm the need for a more nuanced view of the economic mobility of Filipino households, including the poor. This can be seen in Figures 3a, 3b, and 3c, which show the distribution of households by economic status in 2004 in comparison with the distribution of the same in 2010. As can be seen from the graphs, a good proportion (34%) of the moderate poor in 2004 became non-poor by 2010. A smaller but significant proportion, however, of the non-poor in 2004 became poor in 2010.

13 Reyes et al. (2011)

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

1970 1971 1985 1988 1991 1994 1997 2000 2003 2006 2009 2012

53

Figure 3a. Where were the Moderate Poor of the 2004 APIS in 2010?

Note: Total number of moderate poor households in 2004: 459,639

Ultrapoor

2 (%) Moderate Poor (%) Non Poor (%)

2007 43.0 27.4 29.7

2008 32.8 29.3 37.9

2010 40.6 25.6 33.8

Figure 3b. Where were the Non-Poor of the 2004 APIS in 2010?

Note: Total number of non poor households in 2004: 1,104,621

Ultrapoor2 (%) Moderate Poor (%) Non Poor (%)

2007 12.7 15.7 71.6

2008 8.9 12.8 78.3

2010 13.2 16.3 70.4

0

10

20

30

40

50

Ultrapoor Moderate Poor Non Poor

TRANSITIONS OF THE 2004MODERATE POOR (%)

2007 2008 2010

0

20

40

60

80

100


TRANSITIONS OF THE 2004NON POOR (%)

2007 2008 2010

54

Figure 3c. Where were the Ultrapoor of the 2004 APIS in 2010?

Note: Total number of ultrapoor households in 2004: 1,009,699

Ultrapoor2 (%) Moderate Poor (%) Non Poor (%)

2007 74.6 15.8 71.6

2008 64.6 21.0 78.3

2010 70.6 17.4 70.4

Notes (for Firgures 3a-c) 1/ Numbers in the figures represent percentage of households 2/Ultrapoor, also known as subsistence poor are those who fall below the food poverty line Source: Paqueo, Orbeta, Lanzona and Dulay (2014)

It is interesting to also note that the persistently poor are only 8.9 percent of total households (Table 9). A household is classified as persistently poor (persistently non-poor), if in all the survey years they were found poor (non-poor). Otherwise, if the households were found poor at least once during any of the survey years, they were classified as transient households. Table 9. Distribution of Households by Economic Status: APIS Panel Data 2004-2010 Persistently Poor Transients Persistently Non-Poor

Percent of households 8.9 38.6 52.5

Source: Authors’ estimates based on APIS panel data 2004-2010

Surprisingly, 52.5 percent of total households can be classified as persistently non-poor and a substantial percentage (38.6) as transients. In later sections, it will be argued and shown that the transients can in fact be considered as near-poor. Many of these households have been said to cycle back and forth between being poor and non-poor. As expected, they are also highly vulnerable to idiosyncratic and covariant shocks. On this score, the concern is that many of them may be at a tipping point of becoming poor, compared to the hard core or persistently poor households. 4. Identifying and Analyzing the Philippine Near-Poor

Many Filipino households have incomes above the poverty threshold. Officially, therefore, they are considered non-poor. Yet, their lives remain miserable and precarious, with little (if any) margins for errors. Highly vulnerable to economic, health, environment and other shocks, their lives have been poetically described as being at a knife-edge and in constant struggle to keep

0

20

40

60

80


Pe

rce

nta

ge

Levels of Well-Being

TRANSITIONS OF THE 2004 ULTRA POOR (%)

2007

2008

2010

55

their body and soul afloat. This is the picture one get from the review of the literature. This is the reality to which our conception of the near-poor and its measurement are anchored. Based on this reality, three definitions of near-poverty are examined below (Table 10).

Table 10. Three Definitions of Near-Poor Label Definition

“Balik-balik Poor” or Cyclical Poor Those households who move in and out of poverty within a given time frame; so-called transient HHs.

“Static RAT Poor” Those households with per capita income between the official poverty threshold (TPT) and the near-poor threshold (NPT) at a given year; NPT= RAT x TPT where RAT is a fixed NPT/TPT ratio

“Balik Kahirapan Poor” or BK Poor Those non-poor households at year t with a high probability or risk that they would fall into poverty in the near future (say, t+3); classified based on three near poverty risk indicators (RSKe, RSKd, and RSK50)

The first definition identifies the near-poor as those households who move in and out of poverty within a given time frame. These are the so-called transient households, as opposed to the persistent poor and persistent non-poor. This definition of the near-poor captures cyclical poverty; hence, we can call the transients the “balik-balik poor”. The second definition regards the near-poor as those households with income per capita between the official poverty threshold (TPT) and the near-poor threshold (NPT). The latter threshold is measured as one plus a certain percentage of TPT. This approach is equivalent to using a fixed NPT/TPT ratio to determine the near-poor threshold. With a fixed ratio and given the official TPT, it is a matter of simple arithmetic to estimate NPT. This way of defining the near-poor will be referred to as the RAT definition. Implicit in this definition is the recognition that households need to have some buffer against the threats of covariate and idiosyncratic shocks. The RAT approach is “static”; that is, it is based on household income at a given survey year. At present, there is little basis for choosing the NPT/TPT ratio. The use of RAT is currently not grounded on data relating NPT/TPT to subsequent poverty risk or to estimates of the minimum income buffer needed by households. The static RAT model can be improved (as later shown in this study) by providing the users information relating quantitatively different RAT values at a given year to subsequent poverty risk. That is, the probability that a household observed as non-poor at a given year would become poor a couple of years later. With this kind of information, the RAT approach can be a more reliable tool for benchmarking and identifying the near-poor, when needed panel data are not available. In the third definition, the near-poor is identified as those non-poor households at year t with a high probability or risk that they would fall into poverty in the near future (say, t+3). We refer to this risk-based method of defining the near-poor as the “Balik Kahirapan” or BK definition. Measuring BK risks. Table 11 presents poverty risk indicators (columns 5a, 5b and 5c) and the distribution of the near-poor households by income, expressed as a ratio to the poverty threshold (RAT) based on 2004-2010 APIS panel data. Three indicators are used to analyze the probability of near-poor households falling back into poverty, denoted as RSKj. One of these indicators (RSKe) is the number of poverty episodes in 2007-2010 relative to the number of survey years (3) among households found to be non-poor in 2004. The second indicator (RSKd) is defined as the probability (percent) of non-poor households in 2004 becoming poor at least once in 2007-2010. The third indicator (RSK50) is similar to RSKd except that it refers to becoming poor twice instead of only once in 2007-2010.

56

It is clear from Table 11 that there is a strong correlation between mean income and the RSK indicators. Households who were initially non-poor in 2004 and whose RATs were between 1.000 -1.099 had a 66 percent chance of becoming poor at least once during the subsequent APIS survey years of 2007, 2009, and 2010. In comparison, for those households with per capita income equal to 2.0 times TPT or more in 2004, their probability of experiencing poverty at least once subsequently in 2007-2010 is only 9 percent. As expected, “long-term” consumption, indicated by the 4-year average consumption (3-year in the case of food), rises as households move from being persistently poor to persistently non-poor households or as their level of income moves farther away from the total poverty threshold (Table 12a). These observations are true of food expenditure and savings. As expected, the savings of an average persistently poor household is negative Interestingly, for the transients, savings are in contrast significantly positive. Another observation is that, as noted by a previous study NSCB (2005), the share of food expenditures in total income is a good distinguishing characteristic of poverty. In Table 12b, one finds that in 2007 the food share in income among the persistently poor is around 78 percent, while the corresponding figure for the persistently non-poor is only 42 percent. For the near-poor, it is around 65 percent. Moreover, it seems from the APIS panel data (Table 12b) that, in contrast to the non-poor, the persistently poor and near-poor experienced a substantial decline in their food share in income from 2007 to 2010.

Table 11. Poverty Risk (RSK) and Distribution of Near-Poor Households (in Percent): 2004-2010

Notes: a/ Near-Poor in 2004 = households in 2004 with per capita income between TPT and NPT. The latter is assumed to be equal to Php 13,279.87, the mean per capita income of the transient poor from 2004-2010 in 2000 prices. The TPT is total poverty income per capita in 2004 expressed in 2000 prices. b/ RSKe - Mean number of poverty episodes in 2007-2010 experienced by the non-poor households of 2004, as percent of the number of survey years c/ RSKd - Percent of non- poor households in 2004 becoming poor at least once in 2007-2010 d/ RSK50 - Percent of non-poor households in 2004 falling into poverty at least twice in 2007-2010 Source: Authors’ estimates, based on APIS data

NPT/TPT ratio interval

(1)

Percent distribution

of 2004 Near-Poor

householdsa

(2)

Percent Distribution

of 2004 Non-Poor

Households

(3)

Cumulative Distribution of the 2004 Non-Poor

(4)

Near-Poor Poverty Risk Indicators RSKe

b

(5a)

RSKdc

(5b)

RSK50d

(5c) 1.000-1.099 30 7 7 38 66 36 1.100-1.199 30 7 13 30 54 26 1.200-1.299 27 5 18 28 53 26 1.300-1.399 13 5 23 28 52 24 1.400-1.499 0 4 27 19 42 11 1.500-1.599 0 4 31 20 41 13 1.600-1.699 0 4 35 14 30 9 1.700-1.799 0 4 39 17 34 14 1.800-1.899 0 3 42 12 26 9 1.900.1.999 0 3 45 12 23 10

2.000 and over 0 55 100 4 9 3 Total 100 100

57

Table 12a. Non-Poor Profile: 2004-2010

Household

classification

according to NPT/TPT

ratio interval

Mean Characteristics of Households Classified as Non Poor in 2004

(in constant 2000 prices)

Household

income per

capita a

Household

expenditures

per capita a

Savings per

capita a

Food

expenditure

per capita b

Food

expenditure

as percent of

income b

1.000-1.099 10,162 10,259 -97 6,385 62

1.100-1.199 11,143 10,993 150 6,741 60

1.200-1.299 12,101 11,597 504 7,091 59

1.300-1.399 13,068 12,773 295 7,556 58

1.400-1.499 14,050 13,346 704 7,723 55

1.500-1.599 14,050 14,063 -13 8,209 54

1.600-1.699 16,021 15,498 523 8,495 53

1.700-1.799 16,960 16,019 941 8,875 52

1.800-1.899 17,952 16,490 1,462 8,920 50

1.900.1.999 18,913 17,364 1,549 9,568 50

2.000 and over 44,386 37,295 7,091 14,207 38

Mean for all incomes 25,194 22,095 3,099 9,857 52

Notes: a/ Annual per capita values were derived by getting the average for the years 2004, 2007, 2008, and 2010. b/ Food expenditure values were derived by getting the average for the years 2007, 2008 and 2010. APIS 2004 does not have a “food expenditure” variable. Source: Authors’ estimates, based on APIS panel data 2004-2010

Table 12b. Trends in Household Income, Consumption, Savings and Food Expenditures:

2004-2010 (in constant 2000 prices)1 Year 2004

3 2007 2008 2010

Household income per capita

Persistently poor 5,802 5,518 6,084 6,363

Transient-Poor2 11,541 11,210 12,032 13,280

Persistently non-poor 37,884 37,366 36,837 38,878

All 25,079 24,652 24,731 26,314

Household expenditures per

capita

Persistently poor 6,451 6,046 6,543 6,604

Transient-Poor2 11,354 10,859 11,726 12,444


All 21,915 21,223 22,102 23,143

Savings per capita

Persistently poor -649 -528 -459 -241

Transient-Poor2 187 351 306 836


58

All 3,164 3,429 2,629 3,171

Food expenditure per capita

Persistently poor 4,084 4,566 4,483

Transient-Poor2 6,316 7,067 7,259

Persistently non-poor 12,207 13,238 13,203

All 9,258 10,134 10,181

Food expenditure relative to

income

Persistently poor 0.78 0.78 0.73

Transient-Poor2 0.65 0.65 0.61

Persistently non-poor 0.42 0.45 0.43

All 0.54 0.56 0.52

Notes 1/ Based on APIS Panel Data 2004-2010; incomes and expenditures are annual. 2/ Transient-poor is defined as HHs who fell into poverty at least once between 2004 and 2010. 3/ APIS 2004 does not have a “food expenditure” variable. Source: Authors’ estimates

59

Identifying the near-poor in NHTS-PR. The NHTS-PR provides a good database for targeting social assistance to millions of poor households. Unlike APIS, however, the NHTS-PR database at present has no panel data component. This type of data is necessary for computing the BK risk. A challenge for this study is how to figure out a way of using the NHTS-PR data to identify the near-poor for targeting special interventions to them, should the government decide to do so. The following discussion explores this challenge and presents a practical model that could prove useful in measuring and thinking about the near-poor issue. To fix ideas, consider the following simple model (referred to as the BK model): Eq. 1. RSKj = a + b (1/PCY) for j = e, d, or 50 Eq. 2. RAT = PCY/TPT Eq. 3. CON = c + d PCY

Where: RSKj = the probability or risk of a non-poor household falling into poverty in the near future PCY = household income per capita CON = consumption expenditures RAT = the ratio of income to the official poverty threshold RSKe = mean number of poverty episodes in 2007-2010 experienced by the non-poor

households of 2004, as a percent of number of survey years RSKd = percent of non-poor households in 2004 becoming poor at least once in 2007-2010 RSK50 = percent of non-poor households in 2004 falling into poverty at least twice

The following steps illustrate how the BK model can be used to generate information and facilitate the process of decision-making:

• Calculate the RSK corresponding to a given income per capita (PCY). Do this step for

several PCYs to estimate corresponding RSKs;

• Present those estimates to a policy committee or advisory group as options. The

purpose is for them to pass judgment on the tolerability of the various RSKs associated

with given PCYs and to choose that PCY level (PCY*) they want to adopt as near-poor

threshold (NPT);

• Calculate the resulting RAT for each of the PCY being considered. As mentioned RAT is

the ratio of NPT to the official poverty threshold (TPT). Compare the RAT against

international practices (discussed above). Examples of RAT norms used or suggested

include 1.10 (PhilHealth), 1.20 (World Bank), 1.33 (Orshanksy,1966) or greater (Short

and Smeeding, 2013);

• Do a sensitivity test for political correctness, using Eq.3. The objective of the test is to

inform decision makers against egregiously high NPTs. As a rule, no NPT should be set

so high that the mean consumption level of the near-poor targeted for social assistance

programs exceeds that of the average household or voter. Such a rule will minimize

strong pushback from taxpayers that could be damaging to program sustainability.

Figure 4 illustrates how the BK model can be visualized to facilitate analysis and discussion, using existing data to estimate the RSK-income and consumption-income functions (Equations 1 and 3) presented in Table 12c.14

14

The equations were estimated, using ordinary least squares (OLS) and the mean RSKj, income and consumption of each of the ten income groups shown in Tables 11 and 12. These income groups were used as units of observations to estimate Eqs. 1 and 3.

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Figure 4: Choosing the Near-Poor Threshold (NPT)

In the diagram, non-poor households with per capita incomes between the poverty threshold and Php 12,400 appear to be living at a knife-edge. That is, they have a more than 50-50 chance of falling into poverty at least once in the near future. In contrast, those households with income of over Php 21,000 per capita seem unlikely to become poor any time soon and, therefore, should perhaps be given low priority in any social assistance program for the near-poor. It would further appear that at the RAT of 1.10, 1.20, and 1.30 the average consumption of the near-poor at these income levels remains below that of the average household. Incidentally, for a household with a per capita income that is 1.30 times the total poverty threshold (TPT), the estimated RSKd is close to 50 percent. In comparison, the RSKd for households with incomes 1.20 times TPT appears higher than 50 percent.15

15 Incidentally, the figure 1.37 is the ratio of the mean per capita household income of transient households to the official total poverty threshold (TPT). The ratio 1.20 is the near-poor income threshold relative to TPT (advocated by the World Bank).

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Table 12c. Regression Equation Estimates Relating Poverty Risk of Non-Poor Households and their Consumption to Income

RSKd RSKe RSK50 Consumption

Constant 1.090317 .6256392 .5805259 5473.049

(19.42) (12.53) (7.40) (5.22)

Per Capita Income -0.0000463 -0.0000282 -0.0000278 0.7518739

(-12.14) (-8.31) (-5.21) (10.55)

Adjusted R-squared 0.9421 0.8833 0.7439 0.9246

Constant -0.2326382 -0.189562 -.2329088

(-4.43) (-5.27) (-3.86)

1/Per Capita income 9083.147 5663.6 5728.426

(12.69) (11.56) (6.97)

Adjusted R-squared 0.9468 0.9365 0.8410

Number of Observations 10

Note: For definition of RSKd, RSKe and RSK50 refer to Table 11. APIS households were grouped into ten income intervals. Their mean values for RSKj, PCY, and Consumption were used to estimate the above regression equations. Source: Authors’ estimates based on APIS Panel Data 2004-2010.

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The above conclusions should be treated with caution. The parameters used to operationalize the model need validation. Moreover, the reliability and predictive ability of the model has yet to be tested and established. Nevertheless, the findings illustrate the potential usefulness of the model and point to ideas that can be further developed to get a better sense of the incremental RSK associated with higher or lower RAT.

Table 13. Predicted RSKj and Consumption Expenditures, Using NHTS-PR Proxy Means Test Income Estimates

NPT =Mean income per

capitaa

NPT/TPTb Percent

frequency distribution

of non-poor

c

Cumulative percent

distribution of non-poor

c

Predictedd

RSKd Predicted

d

RSKe Predicted

d

RSK50 Mean

predicted consumption

per capitae

10,163.16 1.05 14 14 66 37 33 13,114

11,129.40 1.15 12 26 58 32 28 13,840

12,095.88 1.25 11 36 52 28 24 14,567

13,072.29 1.35 9 45 46 24 21 15,301

14,039.35 1.45 8 53 41 21 18 16,028

15,004.49 1.55 6 59 37 19 15 16,754

15,968.30 1.65 5 65 34 17 13 17,479

16,921.13 1.75 5 69 30 15 11 18,195

17,904.98 1.85 4 73 27 13 9 18,935

18,872.01 1.95 3 77 25 11 7 19,662

27,310.20 2.82 23 100 10 2 -2 26,006

Notes: a/ NHTS-PR predicted income per capita in 2000 prices b/ Offical total poverty threshold = Php 9,686.31 c/ NHTS-PR data d/ RSKd, RSKe, and RSK50 = predicted values of RSK equations based on APIS data; see equations in Table 12c. For definition of RSKd, RSKe and RSK50 refer to Table 11 e/ Predicted consumption per capita from consumption function estimated from APIS data (Table 12c) Source: Authors’ estimates, based on APIS panel data and NHTS-PR data.

Analysis of balik-balik poverty. We now spotlight the near-poor issue from the perspective of cyclical poverty. Further analysis of the balik-balik concept and the idea that transients (households in cyclical poverty) can be regarded as near-poor can yield important hints for poverty reduction strategy. The balik-balik phenomenon is interesting because it invites the conjecture that transients on average might be at a tipping point. With a small push, they might be able to reach escape velocity out of cyclical poverty. In contrast, a big and expensive long slog might be needed to move the persistently poor out of their poverty trap. If true, this conjecture would imply that neglecting the near-poor would make the achievement of poverty reduction more difficult. Government policymakers would miss an opportunity to make its poverty reduction strategy more effective. Using the balik-balik definition of the near-poor, one finds from Table 9 that the near-poor constitute about 38.6 percent of the population. The rest are considered persistently poor (8.9 percent) and persistently non-poor (52.5), as noted previously. The profile of the balik-balik near-poor can also be gleaned from Table 14a and compared with the other categories of poverty. The differences in mean characteristics between the balik-balik near-poor and the rest of the households are very telling. As expected, there are huge differences in regard to total income and expenditures. These huge gaps are also reflected in specific expenditures like

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education and health spending. Not surprisingly, the characteristics of the balik-balik near-poor are between those of the persistently poor and non-poor. Remarkably, however, the average

Table 14a. Characteristics of Households by Type of Poverty: APIS 2004-20101 Profiles All HHs Persistently

Poor2

Transient Poor

3

Persistently Non Poor

4

Distribution 100.00 8.90 38.65 52.45

Income and Expenditure-related Poverty & Vulnerability Indicators

Total Income 88,352 46,038 78,285 180,501

Wages and Salaries 35,628 17,466 29,354 78,672

Entrepreneurial Income 24,319 17,425 24,720 35,680

Other Income 28,406 11,148 24,210 66,149

Total Expenditures 78,274 45,314 69,912 150,984

Savings 10078 724 8373 29517 Education Expenditures 3,916 1,392 3,069 9,851

Medical Expenditures 2,542 655 2,128 6,587

Loans from other Families 2,728 1,477 2,363 5,571

Amount deposited in banks and investments 2,754 128 1,362 9,847

% Employed 83.16 92.33 79.47 73.72

% Class of Worker:

Worked for private HH 2.33 2.49 2.59 1.48 Worked for private establishments 33.42 38.02 32.08 25.93 Worked for government 8.08 3.84 6.63 20.19 Self-employed w/o any employee 47.38 50.46 48.75 37.96 Employed in own family operated farm or business 7.59 4.47 8.50 12.69 Worked with pay on own family operated business 0.16 0.17 0.10 0.28 Worked without pay on own family operated business

1.03 0.55 1.34 1.48

% Wages of Total Income 35.58 34.44 34.10 40.25

% Entrepreneurial Activity of Total Income 32.16 38.30 32.10 21.46

% Other Income of Total Income 32.26 27.23 33.81 38.29

Non-income-related Poverty & Vulnerability Indicators

% Did not graduate high school 47.87 66.23 45.57 19.80

% Own Lot 72.71 63.88 75.47 83.35

% with Own Electricity 77.73 57.38 86.21 98.48

% with Own Water 28.37 11.99 29.48 55.38

% Houses made of Strong/Predominantly Strong

Materials

73.25 55.31 78.53 95.51

% Urban Household 38.82 19.36 43.13 65.19

Notes 1/ All variables except household mean income and expenditures are in percentages. Household means are in Pesos @2000 prices. 2/ Persistently Poor households are households that are poor in all 4 survey periods. 3/ Transient Poor defined as either those households that were not poor in 2004 and became poor in at least one of the three subsequent survey periods or were poor in 2004 and achieved Non Poor status at least once in the subsequent survey periods. 4/ Persistently Non Poor households are households that are not poor in all 4 survey periods. Source: Slightly modified table from Paqueo, Orbeta, Lanzona, and Dulay (2014) slightly modified.

characteristics of the transient households are closer to those of the persistently poor. It appears, therefore, that the labeling of the transients as near-poor has empirical basis. The persistently non-poor are much better educated and predominantly live in urban areas. While only 19 percent of the persistently poor live in urban locations, 65 percent of the persistently non-poor live in them. In regard to education, moreover, only about 20 percent of the heads of the latter type of households did not graduate from high school. The corresponding figure for the persistently poor is 66 percent. Education is clearly a key factor in poverty and economic mobility, reflecting the importance of human capital investments in poverty reduction.

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Interestingly, the amount of savings is way much larger for the transient poor than the persistently poor.

Table 14b: Profile of Near-Poor Households as Defined by 1.28 Near-Poor Threshold (NPT)

2004 2010

Profiles All HHs Poor Near-Poor Non Poor All HHs Poor Near-Poor

Non Poor

Distribution (%) 100.00 28.38 12.27 59.35 100.00 22.93 12.15 64.93

Income & Expenditure-related Poverty & Vulnerability Indicators

Total Income1 108,522 40,456 55,682 151,994 106,385 41,090 57,593 138,567

Wages and Salaries 1 45,865 13,470 22,825 66,119 42,900 14,435 22,842 56,703

Entrepreneurial Income1 29,974 17,341 20,336 38,008 29,282 15,583 20,566 35,749

Other Income1 407 138 63 607 273 220 139 317

Total Expenditures1 95,566 45,085 56,488 127,784 94,250 43,751 56,352 119,170

Education Expenditures1 4,540 1,085 1,490 6,823 4,715 971 1,639 6,613

Medical Expenditures1 2,544 658 760 3,814 3,060 462 948 4,373

Loans from other Families1 4,042 2,206 1,819 5,379 3,285 1,885 1,744 4,067

Savings2 12,956 -4,629 -806 24,210 12,135 -2,661 1,240 19,397

Amount deposited in banks and investments1 3,377 218 187 5,547 3,316 48 34 5,084

% Employed 86.76 93.27 89.58 83.05 83.16 91.54 87.75 79.35

% Class of Worker:

Worked for private HH 1.62 1.21 2.37 1.68 2.33 2.51 1.83 2.36

Worked for private establishments 33.77 30.48 36.54 34.94 33.42 38.11 39.07 30.35

Worked for government 7.55 2.47 2.23 11.48 8.08 3.58 3.24 10.91

Self-employed w/o any employee 46.40 56.93 49.79 39.95 47.38 50.57 50.78 45.37

Employed in own family operated farm or business

8.91 7.42 6.97 10.14 7.59 4.37 4.37 9.57

Worked with pay on own family operated business

0.97 1.15 0.98 0.87 0.16 0.21 0.00 0.18

Worked without pay on own family operated business

0.78 0.35 1.12 0.93 1.03 0.64 0.71 1.25

% Wages of Total Income 42.26 33.30 40.99 43.50 40.32 35.13 39.66 40.92

% Entrepreneurial Activity of Total Income 27.62 42.86 36.52 25.01 27.52 37.92 35.71 25.80

% Other Income of Total Income 0.38 0.34 0.11 0.40 0.26 0.53 0.24 0.23


% Did not graduate high school 61.91 83.05 75.74 48.94 59.40 83.28 75.50 47.95

% Own Lot 72.78 63.56 70.34 77.68 74.40 66.16 70.05 78.12

% with Own Electricity 77.80 50.90 71.20 92.02 86.12 65.31 78.84 94.84

% with Own Water 28.53 10.54 12.99 40.35 38.76 14.10 20.42 50.89

% Houses made of Strong/Predominantly Strong Materials

73.33 50.90 64.83 85.82 77.03 54.23 65.47 87.24

% Urban Household 38.82 14.25 27.08 52.99 38.82 17.77 24.50 48.92

Notes 1/ The household mean income and expenditure values are in pesos expressed in 2000 prices. 2/ Savings = Total Income – Total Expenditure

Does it matter whether a transient household is poor or non-poor at the beginning of an intervention? To address this question, we examine the mean characteristics of the upwardly mobile poor, defined as those households classified as poor in 2004 who managed to subsequently become non-poor at least once during the APIS survey years of 2007-2010. These characteristics are then compared to those of the downwardly mobile non-poor – those households deemed non-poor in 2004 that fell into poverty subsequently at least once in 2007-2010. It appears that in majority of the variables analyzed, the difference between the average characteristics of the upwardly mobile poor versus the downwardly mobile non-poor is not

65

significant statistically. Jointly testing the differences in means between the two samples16 further indicates that the null hypothesis of equality of means in all characteristics should be rejected. This finding can be interpreted as indicating that the two groups of transient

Table 15. Test of Differences in Means between the Upwardly and Downward Mobile Transient Households: APIS Panel Data 2004-2010

Variable Transient Households P-Value

Upwardly Mobile Poor

Downwardly Mobile Poor


Total Income 79682.62 76687.88 0.1990 Wages and Salaries* 30724.17 27789.68 0.0572 Education Spending 3186.656 2935.394 0.4151 Medical Care Spending 2366.759 1855.666 0.3197 Taxes Spending 809.3593 770.0581 0.7585 % Household Head Unemployed***

1.178955 1.235487 0.0003

Per Capita Expenditure 16716.7 16551.77 0.7010 Amount deposited in banks 1634.841 1049.886 0.1054 Total Disbursements 75621.84 75438 0.9360 Recreation Spending 161.6156 156.1071 0.8174 Food Spending 34939.42 35488.47 0.4890 % Female Household Head* 0.20544 0.233851 0.0793 Alcoholic Beverage Spending*** 788.3751 644.9403 0.0092 Total Non-Food Spending 34644.13 34799.13 0.9101

Non-Income-related Poverty & Vulnerability Indicators

Family size 4.392269 4.511856 0.1412 % Urban*** 0.631353 0.497138 0.0000 Age of Household Head 53.72584 54.18888 0.3894 1/ * the equality of means hypothesis is rejected at 10 percent level of significance, ** at the 5 percent level, and *** at the 1 percent level. 2/ Three out of 18 variables are statistically significant at the 5 percent level, at least. 3/ Upwardly Mobile Poor defined as transient households that were poor in 2004 but were Non Poor in at least 1of the 3 subsequent survey periods. 4/ Downwardly Mobile Poor defined as transient households that were Non Poor in 2004 but were poor in at least 1 of the subsequent survey periods. 5/ Values are in constant 2000 prices Source: Paqueo, Orbeta, Lanzona and Dulay (2014)

households have common ground. They are substantially similar in their family size and level of income and expenditures. Yet, they are significantly different in some respects. For example, the upwardly mobile poor spend a bit more on alcoholic beverages. On the other hand, relatively more of the initially non-poor transients that have fallen into poverty are located in urban areas; their heads have higher unemployment rate; wages and salaries as sources of income are lower; and a larger proportion of them are headed by females. These findings suggest that the strategy for dealing with the near-poor as transients would have to include both promotive and preventive measures. The findings also suggest that a near-poor study can yield more information, if in addition to looking at the transients as a whole, a separate analysis is also done on those transients who are non-poor at the beginning of the period. The balik-balik near-poor definition can be used to identify the near-poor in a database (like the NHTS-PR) without panel information to measure economic mobility. In light of the foregoing

16 Hotelling’s T-Squared test

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discussion, one idea is to use the mean per capita income of the transient households (who were non-poor in 2004) as an estimator of the near-poor threshold. In the Philippines, that would mean that the NPT would then be about Php 13,269 per capita per year or about 37 percent higher than TPT. To put this estimate in perspective, the NPT advocated by the World Bank is 20 percent higher than the TPT. At the NPT/TPT ratio of about 1.37, the estimated probability (RSKd) that households deemed non-poor (say in 2004) would become poor subsequently at least once within a few years would be between 45-50 percent. On the other hand, a ratio of 1.20 would imply a RSK of over 50 percent. If the RSK associated with an NPT/TPT ratio of 1.37 is acceptable, then the near-poor would consist of households with income per capita between the TPT and 1.37xTPT. Using this income interval, the near-poor in the NHTS-PR data can be identified as those households with per capita incomes between the official poverty threshold of Php 9,686 and the near-poor income threshold of Php 13,269. This amount is higher than the NPT of Php 12,400 estimated using the BK Model (Figure 4). On this point, it is important to remember that the interval and, hence, the identification of the NHTS-PR near-poor households will depend on the policymakers’ choice of RSK they are willing to accept. Prioritizing high risk households. Given tight budget constraints, there is a necessity to prioritize social assistance for the near-poor. Consequently, a scoring scheme would have to be developed to identify high risk near-poor households and prioritize their inclusion into social programs being envisioned to maximize their impact. Such a scoring scheme can be built by identifying the significant correlates of poverty risk. To illustrate, we present in Table 16 the correlates of RSKe, the number of poverty episodes experienced by a non-poor household of 2004 relative to the number of APIS survey years (3) in 2004-2010. At the level of individual households, the near-poor are heterogeneous; they vary in their individual characteristics. Within the near-poor category, these variations in traits generate differences in RSKe.

Table 16. Correlates of Poverty Risk: OLS Regression on the Non-Poor of 2004

Variables Coefficients Elasticity Variables Coefficients Elasticity

Constant 0.4765859***

(8.82)

Income per capita -0.0000006*** -0.30621

High School Graduate -0.0698544*** -0.8185

(-4.27) (-8.01)

Household size 0.0169491*** 1.16699

Sex (Male) -0.0096480

(98.35) (-0.58) Home built from Strong Materials

-0.0151651 Age

-0.0084159*** -5.90034 (-1.51) (-4.25)

Own Electricity -0.0892894*** -1.31351

Age-squared 0.0000618*** 2.043439

(-6.65) (3.09)

Own Water -0.0271347*** -0.22265

Urban -0.0349733*** -0.4031

(-3.13) (-4.15)

Number of consumer durables

-0.0193140*** -1.65286 Self-Employed

0.0173827** 0.117202 (-10.5) (2.22)

Average Wage -0.0000010* -0.06054

Single -0.0183866

(-1.67) (-0.78)

Regional Unemployment Rate

0.0018366 Divorced/Separated

-0.0567049* 0.01778 (1.3) (-1.8)

Regional Underemployment Rate

0.0041283*** 1.182034 Widowed

-0.0346207* -0.01659 (6.44) (-1.91)

R-squared 0.2395

Adjusted R-Squared 0.236

Sample Size 3904

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Notes 1/ * significant at the 10 percent level, ** at the 5 percent level, and *** at the 1 percent level. Dependent Variable is RSKe . 2/ Figures in parentheses are t-values. 3/ See below for definition of variables Authors’ estimates using APIS 2004-2010

Definition of

Variables used in Table 16

RSKe The number of poverty episodes experienced by a non-poor household of 2004

during the succeeding years of 2007, 2008, and 2010 divided by 3

Income and Expenditure-related Poverty & Vulnerability Indicators Income per capita Per capita income, average of 2004-2010 in constant 2000 prices

Average Wage Average Wage per region in 2004

Regional Unemployment Rate Regional Unemployment rate in 2004

Regional Underemployment Rate Regional Underemployment rate in 2004

Self-Employed Number of Self-Employed HH heads

Non-Income-related Poverty & Vulnerability Indicators Household size Number of member of HH

Home built from Strong Materials HH with outer wall and roof made of strong or predominantly strong materials

Own Electricity Number of HH with own electricity

Own Water Number of HH with own water

Number of consumer durables Number of the following consumer durables a HH has:

TV,Video,Stereo,Refrigerator,Washing machine,Aircon,Phone,

Cell phone,Computer, Cars,Motorcycles

High School Graduate Education level of HH head is at least high school level

Sex (Male) Gender of HH head

Age Age of HH head

Age-squared Square of Age of HH head

Urban Number of urban HH

Divorced/Separated Number of Divorced/Separated HH heads

Widowed Number of Widowed HH head

As shown in Table 16, the following characteristics appear to be significantly related to RSKe: education of household head, urban location, employment, regional labor characteristics like wage rate and underemployment rate. Table 16 also shows that the elasticity estimates of RSK with respect to selected variables appear substantially high for some variables. These are: household size, home with strong materials, own electricity connection, number of consumer durables, regional underemployment, age and high school education. In looking at Table 16, it should be emphasized that the equation is not based on a causal model. It is presented here mainly to illustrate a possible way of developing a scoring scheme for ranking the near-poor households in terms of predicted risk (RSK) and for identifying high risk and low households. The specification in Table 16 was re-estimated, dropping the household income variable to obtain an equation that can be used to get predicted RSK for each individual households in the NHTS data base. The NHTS does not have actual household income data. What it has is predicted household income variables calculated from household assets, characteristics of household heads, and other variables similar to those listed in the right hand side of the RSK equation in Table 16. The regression equation with income, as presented in Table 16, is basically similar to the equation estimated without the income variable. For purposes, however, of obtaining predicted RSK for NHTS households, the latter estimated equation is recommended to avoid statistical bias.17

17

The authors are grateful to Dr. Denis Mapa for this recommendation.

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5. Share of the Near-Poor in the Distribution of Public Subsidy Benefits.

One of the motives articulated in the literature is the idea that the near-poor are not getting social assistance or, generally, social protection. The following section examines this issue for the Philippines, recognizing that because of inadequate targeting of supposedly pro-poor programs and the “unintended consequences” of existing policies and programs, those near-poor households might have actually captured a substantial portion of government subsidies. In this regard, it is desirable to measure how much of this assistance go to the near-poor (versus other economic groups) and discuss whether and what kind of social assistance the near-poor actually (deserved or undeserved) get from the government. Benefit-incidence analysis was used for the purpose. This methodology is used to determine the relative share of the near-poor in the distribution of public subsidy benefits based on the APIS July 2011 data on the number of households who received payments in cash or in-kind from social protection programs in the last six months. There are two main messages from Table 17. First, it shows that, in general, relatively few households receive social protection benefits. Second, it further reveals that near-poor households, as well as non-poor households actually benefitted from the different social protection programs of the government which are primarily designed for the poor. These programs may be grouped into social insurance, social welfare and assistance, and labor market interventions/programs. Social insurance programs seek to mitigate income risks while social welfare and assistance programs seek to support the minimum basic requirements of the poor. Labor market interventions/programs, on the other hand, aim to enhance employment opportunities and protect the rights and welfare of workers. Annex 3 provides a list of the types of programs for each of these categories while Annexes 4 to 7 provide a comprehensive list and description of the country’s social protection programs under the different categories. For the social insurance programs included in the APIS (i.e., pension, survivor’s benefit, disability benefit, sickness/injury compensation, maternity benefit, PhilHealth and private medical insurance) the near-poor households, in general, have higher benefit-incidence rates than the poor households but lower than the non-poor households, with rates ranging from 0.07 to 4.93 percent. In particular, of the near-poor households, about 2.42 percent received pension from government and double the share from private pension (4.93%); 1.23 percent received survivor’s benefits; at least 0.1 percent received other benefits such as disability and maternity benefits and compensation for sickness or injury; 1.10 percent benefited from either the National Health Insurance Program or PhilHealth-Sponsored Program; an additional 0.07 percent received private medical insurance. Of the poor households, about 0.03 to 1.71 percent received benefits from any of these social insurance programs, mostly from government and private pension and from health insurance from PhilHealth. Of the non-poor households, which indicated the highest benefit incidence in almost all social insurance programs (except for sickness/injury compensation), the rates ranged from 0.13 to 7.37 percent with pension from the government and private sector as the major source. Among the different economic groups, the non-poor, benefited most from each of the social insurance programs comprising 37.0 to 73.8 percent of the respective total number of program beneficiaries, except from PhilHealth, survivor’s benefit, and sickness/injury compensation where the poor led. Poor beneficiaries accounted for about 15.4 to 51.0 percent of the total number of beneficiaries. The near-poor beneficiaries represented 10.8 to 18.2 percent of the total. For social insurance programs which distinguish between the government and private sectors, the benefit-incidence for each economic group is relatively higher for the private, in the case of pension and lower, in the case of health insurance. For pension, the incidence rates by

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economic group range from 1.71 to 7.37 percent for private and from 0.92 to 6.60 percent for government. For health insurance, the rates range from 0.92 to 1.72 percent for PhilHealth compared with 0.03 to 0.13 percent for private medical insurance. The distribution of benefits by economic group also differed between government and private social insurance. Non-poor program beneficiaries constitute the largest share in both sectors (48.7% to 73.8% of their respective total number of program beneficiaries), with a higher share receiving government pension (73.8%) than private pension (62.0%) and the reverse for health insurance (65.2% vs. 48.7%). Of the near-poor beneficiaries, a slightly larger percentage received private pension (16.5% vs.10.8%); the same is true with health insurance programs (13.6% vs. 12.4%). Poor beneficiaries, similarly, received a slightly larger share from private than from government pension (21.5% vs. 15.4%) but a larger share from PhilHealth than from private medical insurance (38.9% vs.21.2%).

Table 17. Incidence and Relative Distribution of Social Protection and Other Benefits: Near-poor vs. Other Economic Groups (2011)1

Program

Benefit Incidence Rate2

Percentage Share of

Beneficiaries3

Total

Household

Beneficiaries

Percentage

Share to Total

Households4 Poor

Near-

Poor

Non-

Poor Poor

Near-

Poor

Non-

Poor

Social Insurance Programs

Pension from

government 0.92 2.42 6.60 15.4 10.8 73.8 591,263 3.1

Pension from private 1.71 4.93 7.37 21.5 16.5 62.0 785,501 4.1

Survivor’s benefit 0.90 1.23 2.54 30.6 11.2 58.1 289,063 1.5

Disability benefit 0.05 0.13 0.21 23.6 14.7 61.8 22,434 0.1

Sickness/injury

compensation 0.13 0.11 0.14 51.0 12.0 37.0 24,372 0.1

Maternity benefit 0.04 0.11 0.14 24.3 18.2 57.5 15,876 0.1

PhilHealth 0.92 1.10 1.72 38.9 12.4 48.7 233,474 1.2

Private medical

insurance 0.03 0.07 0.13 21.2 13.6 65.2 13,283 0.1

Social Welfare and Assistance Programs

4P’s 11.8 1.31 0.32 95.5 2.8 1.7 1,221,630 6.4

Agrarian Reform

Community

Development Program

0.01 0.00 0.00 100.0 0.0 0.0 743 0.0

Scholarship Benefits –

Gov’t 1.11 1.77 1.14 47.3 20.1 32.6 231,482 1.2

Scholarship Benefits -

Private 0.94 1.00 0.78 54.6 15.4 30.0 170,796 0.9

Supplemental Feeding

program 2.51 0.78 0.40 84.1 6.9 9.0 295,730 1.5

Disaster relief (typhoon,

volcanic eruption, etc.) 3.07 1.78 1.01 72.7 11.2 16.0 416,482 2.2

Labor Market Interventions/Programs

Training for Work

Scholarship Program 0.02 0.02 0.04 42.3 8.9 48.8 5,166 0.0

Community-Based

Employment Program 0.10 0.05 0.01 83.9 12.1 4.0 11,630 0.1

Food for Work program 0.68 0.23 0.04 88.1 8.0 3.8 76,320 0.4

Note: 1/ Author’s estimates based on APIS 2011 data and the total number of HH estimated at 19,127,866. 2/The economic groups are defined as follows: Non-Poor = household income above knife-edge income threshold (KNT);

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Near-Poor = household income above total poverty threshold (TPT) but below KNT; Poor = household income below TPT. 3/ Benefit incidence rate = number of HH beneficiaries by category/total number of HH for the same category 4/ % share of beneficiaries = number of HH beneficiaries by category/total no. of HH beneficiaries 5/ % share to total HH = total number of HH beneficiaries/total number of HH Source: Author’s estimates, APIS 2011 For social welfare and assistance, almost all the programs included in the APIS 2011 benefited primarily poor households which accounted for 47.3 to 100 percent of program beneficiaries, at a benefit incidence rate ranging from 0.01 to 11.8 percent (Table 17). Among these programs, the 4Ps, which is the first conditional cash transfer program of the government, intended among others, to provide short-term cash assistance to poor households reflected the highest benefit incidence among poor households which also accounted for the largest share of program beneficiaries. Of the poor households, 11.8 percent received payments from 4Ps and accounted for about 95.5 percent of program beneficiaries. Near-poor and non-poor households also benefited from 4Ps. The benefit incidence is 1.31 percent for near-poor households and about 0.32 percent for non-poor households. The near-poor and non-poor beneficiaries of 4Ps account for about 2.8 and 1.7 percent of the total program beneficiaries, respectively or a total of about 4.5 percent of program beneficiaries in 2011. This is an improvement to the estimated leakage of 29 percent program benefits that went to the non-poor in 2009 due to poor targeting (Fernandez and Velarde, 2012). For the scholarship programs, the near-poor received the largest share among the three economic groups. For the supplemental feeding and disaster relief programs, the shares of the near-poor beneficiaries are generally higher than those received by the non-poor households but lower than those of poor households. For the Agrarian Reform Community Development Program, the beneficiaries all belong to poor households. For the labor market interventions/programs included in the APIS, the benefit-incidence rates are low ranging from 0.04 to 0.68 percent for the food for work program and 0.02 to 0.04 percent for the training for work scholarship. The poor benefited most from the food for work program with an incidence rate of 0.68 percent and beneficiaries accounting for 88.1 percent of the total. The non-poor, on the other hand, benefited most from the training for work scholarship with an incidence rate of 0.04 percent and beneficiaries representing almost half of the total program beneficiaries (48.8%). As with the poor, the near-poor also benefited more from the food for work program than from the training for work scholarship with an incidence rate of 0.23 vs. 0.02 percent, however, the poor beneficiaries accounted for almost the same share of the total for each program (i.e., 8.0 to 8.9%). The different social protection programs benefited from a negligible share to as much as 6.4 percent of the total number of households in 2011. Of these programs, the largest incidence of benefits was generated from pensions for social insurance, 4Ps for social assistance, and food for work program for labor market interventions.

6. Findings from the Focus Group Discussion (FGD).

In order to deepen its understanding of the near-poor issue and explore policy ideas, the Near-poor Study Team in coordination with the National Household Targeting Office (NHTO) conducted an FGD on the near-poor challenge on March 12, 2014 from 9:00 am to 3:00 pm at the Greenhills Elan Hotel, in San Juan, Manila. The FGD wanted to know what the government’s Social Protection and Poverty Reduction Policies and the Philippine Development Plan say about the near-poor and what the government officials and agencies think about specific issues relevant to the analysis of the near-poor challenge. The participants included representatives from the National Economic and Development Authority (NEDA), the Philippine

71

Statistics Authority (PSA) - Makati, and from different offices and bureaus of the Department of Social Welfare and Development (DSWD) which include the OUSPPG, CMO, TAU, PDPB, PSB, and 4Ps. Representatives from the PhilHealth were also invited but were unable to attend. Highlights of the discussion are presented below.

a. What do the Government's Social Protection and Poverty Reduction Policies and the Philippine Development Plan say about the Near-poor?

According to the DSWD, the near-poor are captured by the Social Protection Framework as its target beneficiaries are not limited to the poor but extend to the marginalized and vulnerable. DSWD cited existing programs like social safety nets and social insurance that extend assistance to the near-poor. The Self-Employment Assistance-Kaunlaran Program (SEA-K) likewise was cited as it targets the economically active poor.

The National Economic Development Authority (NEDA) also suggested that TESDA

training for work may be considered as assistance to the near-poor as it bridges the gap between the job seekers and employers.

b. What do Government officials and agencies think about the following issues?

The definition and measurement of the near-poor

On the definition of the near-poor, the NEDA noted that there is no official definition

of the near-poor yet. Participating agencies highlighted the need for a national standard definition of near-poor to enable government to provide targeted interventions aimed at preventing them from sliding down into poverty. DSWD also noted that coming up with a standard definition of near-poor will also support the professional assessment/judgment of social workers. Based on the participants’ knowledge, the near-poor includes those assessed as non-poor at a specific point in time with income approximately 100 to 133% of poverty threshold (according to the U.S. Census Bureau definition of near-poor) but are considered to be vulnerable or highly at risk of falling below the poverty line when exposed to various shocks such as illness, unemployment, and natural disasters, among others.

As to the methods for identifying the near-poor or those who are vulnerable or at risk

of falling below the poverty line, the DSWD noted that the same variables used in identifying the poor, which include those that determine the level of consumption and quality of life may be applied. In addition, DSWD and the other participating agencies recommended that the household’s vulnerability to various shocks such as illness, unemployment and natural disasters also be taken into account. PSA cited household characteristics and income as determinants of a household’s vulnerability to poverty based on an NSCB study which assessed the vulnerability to poverty in the Philippines. Utilization of per capita income instead of family income in the proposed income model was recommended to address possible discrepancies related to the relationship of income and family size. DSWD also highlighted the need to determine the acceptable/tolerable level of risk.

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The vulnerabilities and social protection needs of the near-poor Based on the discussion, the near-poor are vulnerable to or exposed to risks which

degrade assets, income and capabilities/well-being such as economic and climatic shocks, loss of job, illness, and natural disasters, aging, and physical or mental disability. The geographic profile of the location of households (upland/coastal) is said to affect their vulnerability to natural disasters. The nature of the income source is said to also contribute to household vulnerability. Examples cited were households with income sources sensitive to weather (e.g., agriculture) and households that are dependent on transfers and remittances as these are sensitive to foreign exchange fluctuations.

To reduce the risks and vulnerabilities that the near-poor face, the recommendations

fall under the existing social protection programs but with extended coverage or under modified schemes. For social insurance, coverage of the near-poor with limited government subsidy for premium payments and that which would require a counterpart from beneficiaries (e.g., for health insurance), was recommended. The idea of establishing insurance for disaster was considered. DSWD suggested that it be financed also through contribution/counterpart from the beneficiaries and limited government assistance. For social safety net and social assistance, programs that are time-bounded and preventive, in nature, are proposed. Labor market interventions (skills training, work fair schemes, food for work, income support) that are temporary in nature, limited in scale, and well-targeted are proposed.

The priority of the near-poor for social assistance and their inclusion in the government's social protection and development agenda

NEDA pointed out that the existing social protection policy of the government [which

“seeks to reduce poverty and vulnerability to risks and enhance the social status and rights of the marginalized”] and development plan include the vulnerable groups. The policy implication is that the near-poor can be accommodated if social protection coverage is expanded. The Philippine Development Plan [which includes strategies for improving the delivery of social services and empowering the vulnerable groups] also addresses the vulnerabilities of the near-poor through, for example, the expansion of coverage of the PhilHealth to include the unemployed and the expansion of housing coverage to include in-city resettlement and vertical development. DSWD stressed the importance of prioritizing the poor, given limited resources but also acknowledged the need to develop a separate policy to address the needs of the near-poor. PSA, on the other hand, stated that although those considered ultra-poor are the ones who are most in need of assistance, assisting the near-poor would have a greater impact on poverty incidence.

Guiding principles in addressing the near-poor challenge, given widespread poverty

The agencies stressed the importance of clearly defining the near-poor in order

to craft policies appropriate for their characteristics and capabilities. In relation to the Pantawid Pamilya, definition of the near-poor which now account for the program leakages will enable the program to become more tolerant to the leakages and able to cater to their needs. As with the post Yolanda interventions, DSWD noted that the underlying principle for these interventions should be inclusion, equitable distribution of resources, and ROI as a measure of success. NEDA asserted that for the near-poor, the

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approach to interventions should be preventive (e.g., insurance coverage to caution the shocks) as opposed to developmental (e.g., literacy and health-related programs) which is suited for the poor; time-bounded; and less frequent compared to assistance provided to the poor. DSWD also suggested that assistance to the near-poor be intended to maintain consumption/quality of life. The PSA added that such assistance should be geared at improving their resilience to shocks. The type and timing of assistance is said to be a crucial factor in the development of programs for the near-poor.

Specific tools for helping the near-poor reduce their risk of falling into poverty and increase their chances of moving out of near poverty

Three specific tools were recommended, namely: a) establishment of

partnerships with the private sector to address the issue of limited government resources (NEDA and DSWD); b) educate people on their rights and the government services available to them; and c) re-evaluate existing legislation with respect to their effects on the near-poor.

7. Towards a near-poor strategy: reflections and conclusions

The review of the international literature and the empirical analysis of the near-poor

issue, discussed above, lay out a range of options for dealing with the near-poor

concern. Many of those options are relevant to the Philippines and are worth trying. The

decision, however, regarding the choice of objectives, instruments and interventions

should be part of a coherent strategy that is suitable to Filipino values and the organizing

principles on which the country’s economy and political system have been established.

This integrative approach would not only maximize the overall efficiency of resource use,

it would also ensure fair balancing of the legitimate claims of the poor, near-poor and the

rest of society to social protection. This section provides ideas on the development of

such strategy.

Framing the issue. It was noted above that the near-poor move in and out of poverty

and non-poverty, suggesting that perhaps a good number of them might be at a tipping

point or a situation where with direct or indirect nudges from government and civil

societies, they could achieve escape velocity out of the vicious cycle of poverty. What

could these nudges be that can be utilized to move people out of poverty? More

broadly: Why, in what form and to what extent can and should the government help the

near-poor? Given scarce resources, how can the government assist the near-poor

without undermining its ability to help the real poor? The discussion below provides

ideas for building a framework or scaffolding for thinking about these questions.

In addressing those questions, it would be wise to anchor the discussion on the basic

organizing principles that govern the Philippines. To begin with, the country is organized

as a “mixed economy”, a free enterprise system with a crucial but limited role. This role

is primarily to protect and promote the common good that a competitive economy is

unable to bring about without some form of government intervention. Under the system,

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workers’ earnings as a rule are supposed to depend on the value of their productivity.

This arrangement in turn is supposed to drive the incomes of households and, in large

part, their economic status. The principle is that a competitive market empowers and

motivates individuals and enterprises to be productive and efficient. This vision should

inform the development of the country’s near-poor strategy.

Concretely, the vision is about households and their members harnessing and

developing their skills, talents, drive, and potential, including both current and future

generations. From the social standpoint, the idea is to develop a cohesive society of self-

reliant productive citizens.

Translating this vision into reality in a world buffeted by shocks and uncertainty requires

individual households and their members not only to work hard but also to be prudent

about their future. They are also expected to have foresight and grit. This means saving

for the rainy days, building their capacity to adapt to changing conditions, anticipating

and preparing for economic disruptions lurking around the corner, and taking advantage

of the economic opportunities brought about by the process of creative destruction of

industries accompanying technological and market changes.

The public policy perspective. The promise of the free enterprise system depends on

certain conditions. In the developing economies, these are often seriously violated,

leading to market failures that limit the economic opportunities of individuals. But even in

an economy without market failures, the optimality of the outcomes of a perfectly

competitive system depends on the social acceptability of the initial and resulting income

distribution. Traditionally, many mainstream economists have tended to regard income

distribution a matter of individual preferences or values about which economics as a

discipline has nothing to say about. Recent economic studies, however, such as Ostry,

Berg & Tsangarides (2014 ), points out that high and increasing income inequality leads

to lower sustainable economic growth for a variety of reasons. The implication of this

finding is that the promise of a perfectly competitive market is not only vitiated by market

failures but also by intolerably high income inequality.

Under these circumstances, the chances of the poor extricating themselves out of the

poverty trap without some government interventions are low and the expansion and

development of the near-poor into a vigorous middle class are severely limited. In the

Philippines, many households are so constrained by their initial endowments and

economic history that they are unable to take advantage of whatever economic

opportunities exist.

Despite such difficulty, history is not destiny. Data on economy mobility cited above

indicate that households and individuals can exit poverty and can rise to middle class

status and beyond. Additionally, as indicated by the aforementioned studies on the

causal relationship between growth and inequality, government interventions to improve

equity can have positive effects on economic efficiency and growth. In recognizing this

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possibility, however, we do not imply that all government interventions intended to

improve equity do actually help the poor (more below). Their actual impact depends on

specific design and implementation issues.

Moving on, market failures in developing economies are so pervasive that, as noted,

they severely limit opportunities for productive activities and curtail gainful jobs

opportunities for households with little capital and financial assets to begin with. These

opportunities are likely to remain scarce without effective government actions (Justin Lin

2011).

The point of the above discussion is that, while it is true that despite initial adversities,

disadvantaged workers have climbed up the economic ladder under a free market

economy, many of them are unlikely to make it without the helping hand of government

and in an environment where economic opportunities are stifled by unsupportive public

policies. On this score, government reforms and social assistance can have an important

role in enabling deserving low income households to get out of their poverty trap. Those

reforms couple with social assistance can nudge transient households toward joining the

persistently non-poor. On this point, however, it is important the government is highly

selective and well informed in their choice of interventions.

The near-poor strategy: objective and strategic pillars. The Government is

concerned about the near poor18 and is interested in addressing the issue. This concern

makes sense for a couple of reasons mentioned above. First, the number of households

above the poverty line at high risk of falling into poverty is substantial. APIS Panel Data

2004-2010 reveal that 38.6 percent of total households are cyclical poor, compared to

8.9 percent of the persistently poor. Moreover, the risk for non-poor households with

RAT of less than 1.28 to fall into poverty, which constitute about 12 percent of total

households in 2010, is high at 50 per cent or more probability. Second, it is probably

easier to prevent the near-poor or, more generally, the cyclical non-poor from falling into

poverty than getting the persistently poor from moving out of poverty permanently. This

is not to say that the persistently poor should be ignored. Rather, the point is that

prevention of the precarious non-poor could be a valuable part of cost-effective and

comprehensive poverty reduction strategy.

In view of the above observations, the study calls for the development of a near-poor

strategy that would seek to prevent the near-poor or the more numerous cyclical poor

from returning to poverty, while keeping persistent poverty down. How would that

strategy look like and how could it be organized coherently?

The objective of the near-poor strategy should be the prevention of the near-poor from

falling back into poverty and helping the transients to reach escape velocity out of

poverty. Sustainable preventive action is necessary to avoid adding to the currently huge

18

Government concern about the near-poor was expressed by Secretary Arsenio Balisacan, Director-General of the NEDA, in a recent ANC Forum on the 2014 State of the Nation Address (SONA).

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number of poor households. Without this preventive action, poverty reduction would

become more difficult than it already is.

In seeking to advance the welfare of the near-poor, it should be emphasized again that

care should be taken not to undermine the goal of poverty reduction. On this score, it

would be wise for the government to focus on the development of win-win solutions that

would benefit the near-poor and the rest of society, particularly the poor. Moreover, the

solutions should be aligned to the country’s fundamental vision of developing a cohesive

society of self-reliant and progressive citizens.

Given the above premises and the need to be highly selective in the use of public funds,

the near-poor strategy can be organized around the following three pillars:

Pillar I – Reform of the regulatory environment. This part of the strategy is directed

against public policy failures, whose impact cuts across the poor, near-poor and other

economic groups. The objective here is to change those government policies, laws and

regulations that have been seriously damaging to economic development and the

welfare of the common man. The premise is that such reform would benefit not only the

near-poor but the other disadvantaged groups as well. Examples of those policies, laws

and regulations include: constitutional restrictions on FDIs, protection against rice

importation, and some labor regulations like mandatory minimum wages and

regularization law. Our policy conjecture is that revamping them will most likely be

beneficial predominantly to low income households (both poor and near-poor).

To illustrate, we highlight below two examples of policy failures that have hurt the

common man and low income households. One example is on labor policy; the other on

food policy.

Reforming the mandatory minimum wages. The rapid expansion of gainful jobs should arguably be at the center of an inclusive, rapid and sustainable development. The government, therefore, is right to focus its development plan on the jobs issue. As can be seen in Figure 5, a huge and growing number of households are not earning enough for the sustenance because of low productivity, high underemployment and, to some extent, open unemployment.

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Figure 5 Underproductive Labor as % of the Labor Force

BSP – Below Subsistence Productivity ASP – Above Subsistence Productivity

Source: Paqueo, Orbeta, Lanzona and Dulay (2014) The usual solution that labor unions and their supports keep advocating year in and year out is increased minimum wages. Raising mandatory minimum wages is not an effective policy. A recent study by Paqueo, Orbeta, Lanzona and Dulay (2014) clearly reveals that empirically the minimum wages have been detrimental to the average Filipino households and the disadvantaged population. Using difference-in-difference impact evaluation method, the study shows that the income of the average household has been significantly reduced by minimum wages. Moreover, contrary to expectations, faster rates of wage increases have led to a higher rate of poverty than would have otherwise prevailed if the rate of increase in minimum wages were lower (see Table 18a). The decrease in household incomes relative to the counterfactual averages about 20 percent, while the rise in the prevalence rate of poverty is about 1.7- 3.0 percentage points.

Table 18a. Impact of Minimum Wages on Household Income and Poverty Incidence:

Difference-in-Difference Impact Evaluation Method

• 20% reduction in average household income relative to counterfactual • Significant increase in poverty incidence rate by 1.7 to 3.0 percentage points

Source: Paqueo, Orbeta, Lanzona and Dulay (2014)

The aforementioned study further shows the impact of minimum wages on the employment of enterprises. The findings shown in Tables 18b indicate that overall the employment of enterprises is reduced with higher minimum wages. This effect is driven mostly by small enterprises reducing their work force as a result of higher minimum wages.

0.00%

10.00%

20.00%

30.00%

40.00%

20

01

20

02

20

03

20

04

20

05

20

06

20

07

20

08

20

09

20

10

Unemployed

Fully Employed BSP

Underemployed ASP

Underemployed BSP

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Table 18b. Minimum Wage Elasticities on Labor Employment by Type of Enterprise and Worker

Note: ** indicates significance at 1 percent level, and * indicates significance at 5 percent. Source: Paqueo, Orbeta, Lanzona and Dulay (2014)

Finally, analysis of labor force participation surveys (LFS) indicates additionally that the

overall impact of minimum wages on individual employment is significantly negative. This impact is due to the damaging effects of minimum wages on the employment of women, the young, the inexperienced, and the less educated – that is, the low productivity workers with little human capital. On this point, it is estimated that on the whole, a 10 percent increase in minimum wages is associated with over 6.3 or more percent decrease on an average person’s probability of being employed (see Table 18c).

Table 18c. Minimum Wage Elasticities on Labor Market Participation (Employment Probability)

All workers

No Schooling

Primary School

Teenage (15-19 y.o)

Young (20-34 y.o)

Middle Age (35-49 y.o)

Male

Panel Logit

Fixed effects -0.636** -0.236** 0.022 -0.597** -0.364** -0.459** 1.983** Random Effects -0.689** -0.295** -0.446** -0.298** -0.091 -0.306** 0.283

Note: Probabilities are relative to college education for schooling variables, and relative old working age (50 and above) for age variables. For specific workers, these probabilities are based on interactions of minimum wages and specific worker qualities. Source: Paqueo, Orbeta, Lanzona, and Dulay (2014)

Reforming the rice policy. This is another example of a cross-cutting win-win measure that, on balance, could also benefit both the poor and the near-poor. The liberalization of the importation of rice coupled with a “pantawid” income support program to help deserving rice farmers adapt to a new policy environment could be beneficial to both the near-poor and the poor. The liberalization policy would reduce the price of rice to consumers, especially the low income families. In turn, this price reduction could help to raise the purchasing power of those families and reduce hunger and under-nutrition. Furthermore, there would be less pressure to raise minimum wages arising from price increases in basic commodities. The income support program for targeted farmers could be designed like the Pantawid Pamilya, but with a different conditionality. This assistance could be linked to palay production and its sale to the government at some pre-determined price. Other conditions could be considered. The general idea is to separate income support due to poverty from rice production support. Clarete (2014), an expert on the rice policy issue, has pointed out that the government’s rice policies had made the public pay relatively high rice prices and that farmers receive less than the trade protection implied by current policies. The total loss from the inefficiencies of rice trade

Data- Indicator of Minimum

Wage

Methodology All Enterprises Small Enterprise Large Enterprises

Production Non-

Production Production

Non-Production

Production Non-

Production

Industry Level With Regional Controls- Kaitz index

Difference-in-Differences -0.513** -0.386** -0.702** -0.385** 1.113** 0.102

Fixed Effects -0.295** -0.607** -0.284* -0.600** -0.031 -0.821** Firm Level (Panel Data) -Minimum Wage

Fixed Effects -0.927** -0.782** -1.107** -0.915** 0.991* -0.859

Random Effects -0.926** -0.783** -1.131** -0.858** 0.980* -0.936

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protection amounted to Php 31.24 billion a year. He further points out that the benefits of the protection accrue more to the richer rice producers than the poorer ones. The top quintile rice producers gain an extra Php 94,478 while the bottom quintiles receive PhP 36,039 to PhP 9,067 annually. To put the total rice trade protection losses in perspective, he estimates that, if the target output were imported instead of produced domestically, the equivalent import bill (assuming Php40:$1 plus 10 % shipping/insurance cost) would be about Php 91.38 billion. This would be Php 50.6 billion cheaper than the expected cost of the self-sufficiency program. This finding suggests that if a free market policy in rice trade were adopted, the consumers would be paying only about half of what they would pay under the government self-sufficiency program. The intention of the Philippine Food Self-Sufficiency Program is laudable. It aims at making the country fully self-sufficient in rice by the year 201619 and keeping the country secure as to rice availability. To achieve the rice self-sufficiency output, the program plans to increase rice yields by investing on improved irrigation, research, improved management, and protection of the domestic market. Given the estimates cited above, Clarete expresses the view held by many professional economists that trying to attain the aforementioned objective may be too costly for society. He further argues that the security concern is overblown, citing estimates showing that the likelihood that rice-producing countries may run out of exportable surplus is very low. In contrast, achieving program success is unlikely, considering the finding of another study indicating that the probability of achieving the self-sufficiency target is as low as 10 percent. This means that that, despite the high cost of the program, the country will likely continue to import rice (albeit, inefficiently under current institutional arrangements). Bad governance and expected typhoon damages and adverse weather conditions make the self-sufficiency goal unrealistic. In this regard, it does not bode well that 15 years after the WTO and Congress passed a law in 1995 aiming to modernize Philippine agriculture and fishery, the sector productivity growth remains low. The country may be better off if it adjusts its target for self-sufficiency and allow the private sector with the NFA to freely import the remaining gap. In response to the rising rice prices, Economic Planning Secretary Arsenio M. Balisacan, in a public interview expressed his sentiment on rice trade policy: “We need to get our trade policy right to address rising rise prices.” He mentioned that a proposal to adopt a free market and allow private traders to import unlimited amounts of rice with tariffs is being considered in July (“NEDA favors easing of rice-import curbs,” 2014). Pillar II – Investing in public goods. Like other developing countries, the Philippines, suffers from market failures due to pervasive problems of spillover effects and under-provision of public goods. These problems, which usually cut across income groups, relate to: (i) lack of infrastructure, such as good networks of national and local highways, ports, and other public works; and (ii) inadequacies in human capital accumulation.20 These inadequacies (i and ii), which have been damaging to the education and training of the near-poor as well as the poor, can be attributed to the country’s chronic under-investments in infrastructure, education and training over past decades.

19

The target year was previously set for 2013. 20

Education and health insurance are considered part of the universal rights of Filipino citizens. They are recognized as essential for the development and maintenance of a sustainable, inclusive and well-ordered society.

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To address the above inadequacies, the government has recently, allocated hefty increases in the budget of those sectors. Moreover, it has committed to allocate more resources for infrastructure and education in the coming years. Its intention is to allocate up to 5 percent of GDP to infrastructure and about 4-5 percent to education. Spending more on infrastructure, good basic education and on-the-job training will arguably promote the welfare of the near-poor along with rest of the country. Consistent with the win-win approach advocated in this paper, we suggest support for the development of a near-poor strategy that is focused on the following ideas: (i) Sustained implementation of good quality K-12 education for all and the Extended Pantawid Pamilya along with increased investment in (among others)

- building secondary schools in all barangays, a large proportion of which do not yet have secondary schools - focus children’s development on cognitive learning in school as well as on character formation, promoting resilience, grit, persistence, curiosity and other virtues that have been found by scientific research to account for most of the success of children when they become adults. 21 - promote apprenticeships and on-the-job training, which is considered the most effective form of training, but accounts for only a small part of Philippine graduates (Paqueo, Orbeta, Lanzona and Dulay 2014).

(ii) Implementation of PhilHealth’s universal coverage program and an increase in its support value, which amounts to only about 10 percent of medical expenditures on average (iii) Faster implementation of infrastructure projects, increased absorptive capacity of the sector, and development of cash for work or workfare program, which can be designed as a vehicle to provide temporary employment for the poor and the near-poor and to build social and physical capital at the same time (iv) Investing more resources to develop and establish richer panel data databases, building on current statistical surveys, maintaining and upgrading existing panel surveys, and linking them to other sources of information. These efforts should include improving the SWI and exploring its use to track the mobility and vulnerability of the poor and near-poor households. Pillar III. Individually targeted “pantawid” social assistance for the near-poor. The efforts discussed above will take time to bear fruit. In the meantime, there will be near-poor households who will be pushed into poverty due to health and economic shocks as well as natural disasters. These households will be in dire need of social assistance. It is likely that some of them could spiral into poverty from which they might not be able to escape without the helping hand of government. On this score, it would make sense to explore the feasibility and wisdom of developing a program that would provide time-limited help to these highly vulnerable near-poor households. Such program could include the following options:

21

Tough, 2012 and Heckman et al., 2006

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(i) The government could develop a near-poor social assistance program that would

be largely self-financing.. The general idea here is to capitalize on the fact that as noted

above the savings of the near-poor over the medium-term appear to be notably positive

(see also Table 19 below). A concrete example could be the development of public-

private microfinance collaboration, tweaking the SEA-K program and focusing it on the

social preparation of the near-poor. This activity will help participants establish a track

record showing their reliability, trustworthiness and business potential (e.g. two years or

less). The SEA-K could then provide to public and private financial institutions like CARD

information about SEA-K’s proven participants. These institutions are interested in

expanding their clientele and membership to low income households – delivering

services that include savings deposits, investment loans and emergency consumption

loans. They are constrained, however, by the high cost of sorting out reliable from risky

borrowers. This constraint can be relaxed by the SEA-K social preparation program by

reducing the sorting cost.

(ii) Empowerment of workers from poor or near-poor households to waive their right

to work at prevailing daily legal minimum wage rates so they can earn additional

incomes. This waiver program would probably require an amendment of the minimum

wage law.

(iii) Development of enterprise-based cash-for-work employment program. This

initiative could be established, while waiting for the above-mentioned proposed waiver to

be passed by Congress and signed by the President. Essentially, the program would

provide strictly time-limited and highly targeted wage subsidy for the employment of

jobless and underemployed workers from poor and near-poor households. The newly

hired workers would be paid the current legal minimum wages, but a fraction of those

wages would be financed by the proposed program. Such program is akin to a

conditional cash transfers with the condition being work in a business enterprise.

Public financing of the gap between market-determined and legal minimum wages would

be consistent with public finance principles. As pointed out by Paqueo, Orbeta, Lanzona

and Dulay (2014), if the legal minimum wages are regarded by the country’s

representatives as a “public good” for social cohesion and other reasons, then in

principle general tax revenues should be used to close the gap between the legal

minimum and the equilibrium market wages. Requiring individual enterprises instead of

the general public to pay for the public good would be an inefficient public policy.

The condition of the above cash-for-work program could be specified as employment in

small scale (maybe, medium) enterprises. The justification for this condition is that unlike

the case of large firms, the imposition of minimum wages has had a detrimental impact

on the size of employment of small scale enterprises, which constitute about 80 percent

of Philippine businesses.

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(iv) Yet, another possibility might be the development of temporary public works

employment program mentioned in Pillar II above.

Cost of near-poor program. If the government decides to invest in a program that would facilitate the development and implementation of policies and interventions for the near-poor, what could be the cost of such program? This is a difficult question to answer without knowing the specifics of the near-poor program government is contemplating. One, however, can imagine some scenarios to get a feel of the orders of magnitude of what a near-poor program could cost. Two scenarios are presented below. Imagine a program in which near-poor households would be provided with financial assistance to fill the consumption deficit during times when they become poor temporarily. The deficit is defined as the difference between the poverty threshold TPT and their consumption expenditures during the months of poverty (assume a uniform average amount). Table 19 presents cost estimates for different RAT levels. The assumption here is that there is a perfect targeting system in place so that only eligible households are provided the financial assistance. Due to this assumption, the costs given in Table 19 can be labeled as estimates under an optimistic scenario. Under this scenario, a near-poor program could cost about PHP 5.5 billion pesos a year in current prices, or PHP 6 billion if a 10 percent overhead and administration cost is added. This amount could finance a well-targeted program aimed at protecting the near-poor against the crippling effects of economic, health and environmental shocks. The above cost estimate would be higher, depending on the choice of NPT. Table 19 shows the formula and the data used to estimate the potential cost of investing in near-poor assistance. The above figure of PHP 5.5 billion or PHP 6.0 billion with 10 percent overhead and administration (OA) cost would cover only those households with per capita incomes between RAT 1.0 and 1.10. If the near-poor income threshold (NPT) were set at RAT = 1.20 or at 1.30, the program cost without allowance for OA cost would rise to about PHP 9 billion or to almost PHP 11 billion, respectively. As a percentage of the proposed 2014 Pantawid Pamilya budget, these estimates would be about 9 percent for RAT= 1.10; 14 percent for RAT=1.20; and 17 percent for RAT=1.30. It must be emphasized that expressing the near-poor cost estimate as a ratio to the Pantawid Pamilya budget does not imply shifting the latter’s allocation to the near-poor. Our assumption is that the finance of the near-poor assistance is new money.

83

Table 19. Distribution and Mean Characteristics of Households by RAT Interval

Near-Poor Non-Poor

RATj Interval 1.00-1.10

(1)

1.00-1.20

(2)

1.00 – 1.30

(3)

Over 1.30

(4)

A. Percent of HH in RATj 5 10 14 64

B. Total Near-poor HHs in RATj (C=AxB) 1,045,735 2,039,079 2,908,779 13,468,819

C. Ave income per capita of near-poor HHs in 2007 10,146 10,631 11,111 37,003

Near-poor averages for 2007-2010

D1. Savings when poor 1,267 1,636 1,570 8,336

D2. Savings when not poor 1,033 1,134 1,239 19,789

D3. Saving when poor or not poor 1,225 1,293 1,367 19,778

D4. Consumption deficit when poor -6254 -6024 -5850 -4547

D5. Consumption deficit when non poor -5813 -5621 -5454 -4932

D6. Consumption deficit when poor or not poor -6013 -5770 -5588 -4854

D7. Consumption surplus when poor 6,179 7,266 8,459 24,477

D8. Consumption surplus when not poor 6,066 7,576 8,885 74,867

D9. Consumption surplus when poor or not poor 6,045 7,529 8,837 74,823

D10. Consumption gap when poor or not poor 742 3,130 5,102 75,670

D11. Percent of HH with deficit when poor 44.33 35.45 29.39 5.8

D12. Percent of HH with surplus when poor 55.67 64.55 70.61 94.2

D13. Percent of HH with deficit when not poor 43.63 32.32 25.2 1.05

D14. Percent of HH with surplus when not poor 56.37 67.68 74.8 98.95

E. Average number of poverty episodes experienced

per year in 2009-2010 by 2007 near-poor HHs 0.41 0.35 0.31 0.03

F. Expected annual amount needed to finance

consumption gap of near-poor for a year in poverty

(F=D4 x E) per HH; in 2000 Pesos 2,581 2,104 1,790 152

G. Expected annual amount needed to finance

consumption gap of all near-poor for a year in poverty

(G = F x B); in 2000 billion Pesos 2.7 4.3 5.21 2.04

H. Expected annual amount needed to finance

consumption gap of all near-poor for a year in poverty;

(G) in 2014 billion Pesos

5.46 8.70

10.55

4.13

I. Percent of proposed 4P's 2014 Budget 9 14 17 7

Notes

A: Total HHs in 2015 = 20,956,619.63; used latest official household projection: year 2015 B: Using 2007 APIS data D1-3: Savings = Total Income – Total Expenditures D1: “When poor” indicate that only those values for years when HH is in poverty are included while ‘When not poor”, otherwise D3-5: Consumption deficit = consumption gap if total expenditure < total poverty threshold D6-9 Consumption surplus = consumption gap if total expenditure > total poverty threshold D10: Consumption gap means total consumption expenditure minus (TPT x Household size) E: Number of poverty episodes experienced by near-poor of 2007 divided by two years F-H: Presented in absolute value H: Overhead and administration costs (10 percent or more of above cost estimate) are not included. CPI 2014 First Quarter. (Source:http://www.census.gov.ph/sites/default/files/attachments/itsd/specialrelease/B30_14Q101.pdf) I: Proposed 2014 4P's Budget = P62,614,247,297 (Source: Official Gazette: Official Journal of the Philippine Government)

Table 20 presents a pessimistic scenario in which all of the near-poor households (both eligible and not eligible) are included because no targeting system is available to identify the actual situation of the near-poor households. This scenario shows much higher cost estimates. No targeting could mean doubling to tripling the cost under the optimistic scenario. The differential

84

results indicate the value of developing a good targeting system. In general, the cost of a near-poor program would depend not only on the adequacy of its targeting system but also on the kinds of measures included in the program.

Table 20. Summary of Cost of Near-Poor Program

RAT Percent of HH in RATj

Total Near-poor HHs in RATj

Cost in 2014 billion pesos

% of Pantawid Pamilya Budget

OPTIMISTIC 1.0-1.1 5 1,045,735 5.46 9 1.0-1.20 10 2,039,079 8.70 14 1.0-1.30 14 2,908,779 10.55 17

PESSIMISTIC 1.0-1.1 5 1,045,735 13.24 21 1.0-1.20 10 2,039,079 24.92 40 1.0-1.30 14 2,908,779 34.45 55

Source: authors’ calculation. Note: Overhead and administrative costs are not included.

85

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88

ANNEXES Annex 1. Comparison of Official, National Academy of Sciences, and Supplemental

Poverty Measures Used by the U.S. Census Bureau Dimension Official Poverty Measure National Academy of

Sciences Measure

Supplemental Poverty

Measure

Resource Unit All individuals who are

related by birth, marriage,

or adoption; excludes

unrelated individuals over

15

All individuals who are

related by birth, marriage,

or adoption; excludes

unrelated individuals over

15

All related individuals who

live at the same address,

including any coresident

unrelated children who are

cared for by the family

(such as foster children)

and any cohabitors and

their relatives

Resource Measure Gross before-tax income Sum of cash income plus

in-kind benefits that

families can use to meet

their food, clothing, shelter,

and utilities needs, minus

taxes (or plus tax credits),

minus work expenses,

minus out-of pocket

medical expenses

Sum of cash income plus

in-kind benefits that

families can use to meet

their food, clothing, shelter,

and utilities needs, minus

taxes (or plus tax credits),

minus work expenses,

minus out-of pocket

medical expenses, minus

child support paid

Threshold Measure Three times the cost of

minimum food diet in 1963

80 percent of the median

of expenditures on food,

clothing, clothing, shelter,

and utilities for a 2 adult, 2

child family multiplied by

1.2

The 33rd

percentile of

expenditures on food,

clothing, clothing, shelter,

and utilities for a family

with exactly two children

multiplied by 1.2

Threshold Adjustment Vary by family size,

composition, and age of

householder

Geographic adjustments

for differences in housing

costs and a three

parameter equivalence

scale for family size and

composition

Geographic adjustments

for differences in housing

costs and a three

parameter equivalence

scale for family size and

composition; Thresholds

vary by housing tenure

Threshold Updating Consumer Price Index: All

items

Three year moving

average of expenditures

on food, clothing, shelter

and utilities

Five year moving average

of expenditures on food,

clothing, shelter and

utilities

Source: Heggeness and Hokayem, 2013; Table 3, p. 19

89

Annex 2. Policy Recommendations for Risks/Vulnerabilities of the Near-Poor: Selected Countries

Types of Risks/Vulnerability

Policy Recommendation Type of

Intervention Country References

Individual Lifecycle Health: Jamkesmas Program - intended to reduce coverage gaps

Health Services Indonesia World Bank 2012

Hunger and malnutrition Improve female education given their close relationship

Education Coudel, Hentschel & Wodon (nd)

Illness, Injury, Disease (incl. HIV-AIDS

Provision of quality health services and facilities

Health Services Mozambique Groover 2011

Disability

Old Age Protecting incomes of older people

Income Stabilization

Mexico Garza-Rodriguez 2010

Death Provision of quality health services and facilities

Health Services Mozambique Groover 2011

Economic (End of source of livelihood, Unemployment, Low and irregular income, Price instability of basic commodities, economic crisis)

Promotion of diversification of incomes, Provision of jobs/employment opportunities

Poverty Prevention, Income Stabilization

Kenya Krishna, Janson, Radeny & Nindo 2004

Unemployment Insurance, Income Support programs


Mexico Garza-Rodriguez 2010

Input fairs, Food-for-Work (FFW) programs

Transition Promotion

Mozambique Groover 2011

Revision of international policies for greater emphasis on aid to poor agricultural countries


Rwanda Muller 2000

Provision of off farm employment: reduction of business licenses to establish an environment conducive for business development; encouragement of investment; job creation


Kenya Suri, Tschirley, Irungu, gitua & Kariuki 2008

Improve access to productive capital to encourage income generating activities


Kenya Suri, Tschirley, Irungu, gitua & Kariuki 2008

Improve access to and adoption of improved agricultural technologies; fertilizer market liberalization


Kenya Suri, Tschirley, Irungu, Gitua & Kariuki 2008

Environmental and Natural

Relocation as primary fiscal response to disaster


Washington, USA

Benson & Clay 2004

National flood forecasting Poverty Prevention Washington, USA

Benson & Clay 2004

Establishment of annual calamity funds especially in countries affected by disasters annually

Overseas Development Institute 2005

Exploration of Financial risk transfer instruments (insurance, weather



90

Types of Risks/Vulnerability

Policy Recommendation Type of

Intervention Country References

derivatives and catastrophe bonds

Continued scientific understanding of natural hazards, dissemination of information on hazards and related risk in a user-friendly manner

Education Overseas Development Institute 2005

Ex-ante risk reduction > ex-post mitigation

Skoufias, E. 2003

Trade liberalization + well-functioning private markets, public and NGO interventions (Bangladesh flood cited)

Labor Market Intervention

Skoufias 2003

Person-specific transfer programs run the risk of having a lower effect on the intended individuals due to reallocation of resources within families over which policy makers have no direct control'

Skoufias 2003

Drought

Rains and floods

Bangladesh: flood and drought prone villages are artificially elevated on unprotected Ganges-Brahmanputra floodplains


Spreading of environmental risk across multiple economic activities - Income Diversification


Bangladesh Aftab, Brouwer, Brander & Hague 2000

Earthquakes

Volcano eruption and landslides

Social/Governance

Social Safety net programs that could keep transiently poor above poverty line

Consumption Smoothing

Indonesia Akita and Dariwardina 2013

Social safety net policies at crucial periods

Consumption Smoothing

Rwanda Muller 2000

Provision of Secondary education


Kenya Suri, Tschirley, Irungu, Gitua & Kariuki 2008

Social exclusion Strengthening of peasant rights; lobbying for rural poor

Rwanda

Muller 2000

Note: Please refer to column 5 of the Table for References used.

91

Annex 3. Types of Social Protection Programs by Category Social Protection Category Type of Program

Social Insurance Programs Pensions

Unemployment Benefits

Health Insurance - but not universal health insurance

Other social insurance (maternity, disability benefits)

Social Assistance Assistance for the elderly (e.g., non-contributory basic allowances for the elderly, old-age allowances)

Health assistance (e.g., reduced medical fees for vulnerable groups)

Child protection (school feeding, scholarships, fee waivers, allowances for orphans, street children initiatives)

Family allowances (e.g., in-kind or cash transfers to assist families with young children to meet part of their basic needs) – excluding any transfers through the tax system

Welfare and social services targeted at the sick, the poor, the disabled, and other vulnerable groups

Disaster relief and assistance

Cash/in-kind transfer (e.g., food stamps, food aid)

Temporary subsidies for utilities and staple foods - only if imposed in times of crisis and if targeted at particular vulnerable groups. General subsidies are excluded even if their rationale is to assist the poor

Land tax exemptions

Labor Market Programs Direct employment generation through public works programs – including food for work programs

Direct employment generation through loan-based programs – included if loans are subsidized and/or job creation is an explicit objective of the program

Labor exchanges and other employment services – if distinct from social insurance and including retrenchment programs

Unemployment benefits – if distinct from social insurance and including retrenchment programs

Skills development and training – included if targeted at particular groups (e.g., the unemployed or disadvantaged children. General vocational training is excluded).

Source: ADB, 2011.

92

Annex 4. Social Insurance Programs: Philippines

Program Implement-ing Agency

Description Eligible Beneficiaries

Social insurance for workers and employees in government service

GSIS All workers & employees in government service

Pensions Old-age pension with monthly payments until death is directly related to the level of earnings and length of employment. The pension level is based on the applicable presidential decree or republic act relative to pension payments, and terms and annuities during the year of retirement.

Unemployment Benefits A disability benefit; not available or a right given to employees after losing a job, during voluntary or forced resignation, retrenchment or removal from a job for any specific reason

Health Insurance - but not universal health insurance

Health insurance All Filipino citizens

Other social insurance Maternity, disability benefits Deserving members

Social Insurance for Workers and Employees in the Private Sector

SSS

- Social security program Maternity, disability, retirement, death, and funeral services

- Employees’ compensation Includes medical services, rehabilitation services and income cash benefit during the first day of disability or sickness, permanent totaldisability, including medical services and appliances

Government health insurance program - National Health Insurance

Program (RA7875)

PhilHealth

Health insurance for SSS and GSIS members and their dependents; overseas Filipino workers; and indigent, privately sponsored members, or a retired pension member Each member is assigned a permanent and unique PIN or PhilHealth Identification Number

All Filipino citizens;

93

Program Implement-ing Agency


- PhilHealth Sponsored Program

One year health insurance coverage

- Retirement program for veterans (RA2664)

Assistance to ex-servicemen including placement and training, assistance to widows, dependents and retired personnel; Benefits, pensions and other privileges granted to veterans, heirs and beneficiaries; Medical treatment to veterans

Veterans, widows, and their dependents

Source: ADB (2012)

94

Annex 5. Social Assistance Programs: Philippines

Program Implementing Agency


Medical Assistance Program

- Funding assistance to government and private hospitals for indigent patients

- PCSO-PhilHealth Greater Medicare Access Program

PCSO PhilHealth & LGUs

Provide a maximum amount of P50,000 per year for medicines, special drugs (e.g., chemo, dialysis, facts 8, and 9 IGIV); consumables (e.g., reagents, supplies, dye); diagnostic procedures (e.g., MRI, 2D Echo); metallic shunts; implants; equipment rental (e.g., life-saving ventilator, respirator); hearing aid; prosthetic devices; brachy therapy; and radiotherapy; additional assistance is granted on a case-to-case basis as justified by a social worker Assist the enrolment of 539,670 indigent families in PhilHealth’s Medicare para sa Masa program by providing counterpart funds for the LGU share

Poor (PCSO-authorized indigent patients)

Social Amelioration Program (SAP) in the Sugar Industry (RA6982)

SAP provides Cash Bonus; also includes a minimal contributory insurance scheme and a program that supports rural labor market

Poor (Workers in sugar plantations (mill and field workers))

Supplementary Feeding Program sponsored by SSS (MOU with representatives from public elementary schools in selected areas)

SSS Public Affairs and Special Events Division

Provision of healthy lunches for 6 days every week in a span of 120 days

Poor (Mostly undernourished school children)

Food for School and Other Feeding Programs

DSWD, DepEd A form of food subsidy for young learners belonging to poor families to address hunger among families through their children; consists of a daily ration of 1 kilo of rice to a child for a specific period of time; Also include deworming, orientation of stakeholders, and nutrition education.

Poor & Non-poor (All Grade 1-3 pupils from government schools, DepEd supervised preschools, and day care children in identified target areas)

Calamity Assistance SSS Distribution of relief bags in areas affected by calamities such as typhoon and floods; Imposition of less stringent loan requirements during and after the calamity period

Poor & Non-Poor (Affected families)

Shelter Assistance Program DSWD A rehabilitation program intended to provide structurally strong shelter units that can withstand approximately 180-220 kph wind velocity, earthquake of moderate intensity, and other similar hazards.

Poor (Families with houses completely destroyed by natural and man-made calamities, without capacity to build or construct their own typhoon-resistant low cost

95



housing and shelter units)

Pantawid Pamilyang Pilipino Progam or Subsidy to the Filipino Family Program

DSWD Provides cash grants to extremely poor households to improve health, nutrition and education, particularly of children aged 0-14; Cash grants amounting P6,000 a year or P500 per month per household for health and nutrition expenses; P3,000 for 1 school year or P300 per month for 10 months per child for educational expenses. A maximum of 3 children per household is allowed. A household with 3 qualified children that meet the conditions of the program receives a subsidy of P1,400 per month during the school year or P15,000 annually. Cash grants are given to the head of household, usually the mother, through the government’s Land Bank cash card. Program conditionalities: Pregnant women shall avail pre-and post-natal care and have a trained health professional in attendance during childbirth. Parents have to attend family development sessions. Children aged 0-5 years need to receive regular preventive health check-ups and vaccines; Children aged 3-5 years attended day care or pre-school classes at least 85% of the time; and Children aged 6-14 years received deworming pills twice a year and enrolled in elementary or high school, with at least 85% attendance.

Poor

-HHs with an economic status within or below the provincial poverty threshold, households with children 0-14 years old, pregnant woman during the time of assessment, and households that meet the conditions specified in the program Municipalities covered: 1st phase (March-Dec 2008) –poorest municipalities selected based on the poverty incidence of Small Area Estimates of the NSCB within the 20 poorest provinces selected based on official poverty incidence and the poorest provinces in other regions; 2nd phase – (March-July 2009) – in poorest municipalities where poverty incidence was above 60% 3rd phase – (Oct. 2009-Dec 2010) – nationwide; poverty incidence no longer considered

Katas ng VAT: Tulong Para Kay Lolo at Lola (Value-Added-Tax Assisted Cash Subsidy to Grandparents) Project (RA9498)

DSWD in coordination with LGUs and OSCAs

A cash subsidy of P500 to alleviate economic difficulties affecting senior citizens; funded from the expanded VAT collections

Poor & Non-Poor

(70 years old and above; dependent or belonging to a family with an income within or below the poverty threshold per area; and, not covered

96



by retirement benefits from GSIS, SSS, or any private or government agency)

Katas ng VAT: Pantawid Kuryente (Value-Added-Tax-Assisted Electric Bill Subsidy)

MERALCO Subsidy to the poorest sector of society to cushion the impact of high cost of electricity; a one-time cash subsidy amounting P500 to be deducted from a households total electricity bill for a designated period; funded from oil VAT collections

Poor (households with monthly electricity consumption of 100 kwh or less during the designated billing period)

Assistance to individuals needing special protection: -Information Technology Literacy Program for Out-of –School Youth and Youth with Disability or SCALA Program -Group Home for Older Street Children -Special Drug Education Program

DSWD

Center and community-based assistance to individuals including children who are victims of crimes and difficult circumstances - a community-based basic computer literacy program aimed to enhance the employment opportunities of disadvantaged youth; -a residential facility within a community that provides alternative home arrangement for rehabilitated male street children ages 16-21 years old. It has 8 to 10 persons living together under the supervision of a social worker from the LGU or NGO - a community-based facility that serves as a venue to equip out-of-school youth and street children with knowledge and life-coping skills to prevent drug and substance abuse

Poor

Victims or witnesses of crimes OSY in pilot sites Rehabilitated street children 16-21 y.o. OSY and street children

CHED Programs CHED Provides educational opportunities through scholarships and student financial assistance, support for alternative modes of learning, and acquiring qualifications for future employment, viz:

- One Town and One Scholar (full or

half merit);

- scholarship programs for persons

with disability (PWD), and

indigenous and ethnic people;

- Grant-in-aids;

- student loan programs;

- study grant programs for single

parents and their dependents,

senior citizens and elderly persons;

- study-now-pay-later plans;

- expanded tertiary education

equivalency and accreditation

programs (ETEEAP);

- ladderized education program

(LEP);

Poor and Non-Poor

97



- DND-CHED PASUC Scholarship

Program;

- OPAPP-CHED study grant

program for rebel returnees; and

- Tulong-Dunong or Assistance-

Intellect program

Educational Benefit for Veteran Dependents

PVAO College scholarships for dependents of veterans

Poor or Non-poor

(dependents of veterans)

Scholarship Grant from Other Agencies

TESDA, DOST and the CFO; DepEd

Student financial assistance and scholarships from other agencies and literacy and anti-poverty programs

Poor (deserving poor students)

Source: ADB (2012).

98

Annex 6. Labor Market Programs: Philippines


Description Type of Beneficiaries

KALAHI-CIDSS (Kapit-Bisig Laban sa Kahirapan – Comprehensive and Integrated Delivery of Social Services) (2003-__)

-Empowers the poorest barangays to plan, implement, and manage their own community projects like roads, water systems, electrification and other small-scale infrastructure; - Employs other interventions intended to provide security and protection for the poor and identified vulnerable groups, including victims of armed conflicts and individuals and communities that lack access to basic social services

Poor (Poorest 25% of municipalities in the country’s 42 poorest provinces)

Forestry and Coastal Livelihood Component (Comprehensive Livelihood and Emergency Employment Program (CLEEP))

DENR-CAR

Job generation and training for the most vulnerable sectors of the population such as the poor, returning overseas Filipino workers, workers in the export industry, and OSY through the Bantay Gubat (Forest Watch) project workers are given relevant training and serves as forest guards, tree seed gatherers, and conducts IEC in the community on preservation of the forest; Technical assistance for reforestation and production of seedlings through the Upland Development program for upland people and communitiesdependent on forest and forest resources

Poor & Non-Poor (poor, returning overseas Filipino workers, workers in the export industry, and OSY) Poor & Non-poor (individual farmers, upland farmer households, able-bodied senior citizens, and OSY)

One Town, One Product (OTOP) Program

DTI in coordination with LGUs and other agencies

-Provides a broad assistance package through a union of services from the local government units, national government agencies, and the private sector; - The package includes skills and entrepreneurial training, business counseling, advice on appropriate technology, marketing, product design and development. -Local chief executives in each city and municipality leads the process of identification, development, and promotion of a specific product or service, with a viable and competitive advantage

Non-poor

Skills Development and Training for Work Program

TESDA in coordination with LGUs, NGOs, POs and other agencies

The country’s technical-vocational education and training (TVET) system consists of three programs:

1. Institution-based programs -

training programs

Poor & Non-poor

99



implemented by the TVET

schools, delivered by

agricultural, fishery and trade

schools and TESDA‘s 15

regional and 45 provincial

training centers throughout

the country

2. Enterprise-based programs

- implemented by companies

and firms, which accept

apprenticeship, learning

programs and other training

systems

Community-based training program –provide skills training for poor and marginal groups, catalyze the creation of livelihood enterprises, and assist partner agencies to involve the poor in productive activities

Source: ADB (2011).

100

Annex 7. Micro Programs: Philippines



Self-Employment Assistance – Kaunlaran Project (SEA-K)

DSWD in partnership with LGUs

Provide the poor capability and entrepreneurial skills training and seed capital to start their own business - Entrepreneurial skills are developed by organizing community-based associations (with 20-30 members) to save and borrow for their businesses; - Maximum loanable amount to finance small businesses is PHP 125,000 per member, payable in monthly instalments for 1-2 years at zero interest

Poor

Microfinance**

- People’s Credit & Finance Corporation (PCFC) (AO148)

LBP Provide affordable credit to the marginalized sector of the country through conduits or providers like rural banks, NGOs and cooperative banks

Poor

- National Livelihood Support Fund

LBP Intended to promote, generate and develop sustainable community-based micro enterprises for farmer households in agrarian reform zones, fisherfolks, the unemployed and other marginalized sectors; -Credit programs utilizes program partners/conduits to retail the funds to target beneficiaries

Poor and Non-Poor (farmers in agrarian reform communities, fisherfolks, the unemployed and other marginalized sectors

- Microfinance Institutions (MFIs)

LBP Credit assistance to Barangay Micro Business Enterprises (BMBEs) and the poor sector; -Provides funds to MFI retailers which in turn on-lend to microfinance sub-borrowers

Non-Poor (MFI retailers including cooperatives, countryside financial institutions, and NGOs)

- Loans for small farmers and fisherfolk (with ADB funding assistance)

LBP Credit assistance to small farmers through partner cooperatives and countryside financial institutions (rural banks, cooperative banks, and development banks) and Quedancor

Poor and Non-Poor (small farmers and fisherfolks)

- Micro-insurance Micro-insurance Mutual Benefit Associations

-Provides financial protection to the poor for certain risks in a way that reflects their cash constraints and coverage requirements; -A micro-insurance product is an insurance policy where: 1) daily premium is <10% of current daily minimum wage rate for non-agricultural workers in Metro Manila, and 2) maximum amount of life insurance coverage <500x daily minimum wage rate for non-agricultural workers in Metro Manila -C ARD (Center for Agriculture and Rural Development) MBA, the largest micro-insurance MBA, provides life insurance to its low-income members and provident and loan redemption cover to members of CARD Inc. and CARD Bank (Please refer to Box _ for features of CARD’s micro-insurance scheme).

Poor and Non-Poor (Low-income individuals)

- Agricultural insurance PCIC -Provides insurance protection to agricultural producers against crop losses arising from calamities, plant diseases and pest infestations and non-crop agricultural losses due to perils for which the asset has been insured against; For rice and corn crops: - Insurance cover the cost of production inputs (based on a Farm Plan Budget) plus an amount of cover at the option of the farmer of up to a maximum of 20% to cover part of the value of

Poor and Non-Poor -Farmers who obtained production loans from any lending institutions participating in the government-supervised rice production programs, government-owned

101



the expected yield. - Premium rate varies by region, by season, and by risk classification which will be shared by the farmer, the lending institution and the government; -Risks covered include natural disasters including typhoons, floods, droughts, earthquake, and volcanic eruptions and plant diseases For livestock: -Types of insurance covered include: non-commercial mortality, commercial mortality, livestock dispersal, and game fowls and animals - Period covered: maximum of 1 year -Premium rate is determined as a percentage of sum insured - Farmer pays the premium For non-agricultural assets: -Types of insurance covered include: fire and lightning, agricultural equipment and machinery and commercial vehicles used for agricultural purposes - Farmer pays the premium

corporations and financial institutions, NGOs, DILG-sponsored credit programs) - self-financed farmer/organization, POs or group of farmers

Source: Weber (2012).

102

Annex 8A. Profile of Transient Poor Households as Defined by 1.37 Transient Poor Threshold

2004 2010

Profiles All HHs Pers. Poor

Transient Poor

Pers. Non Poor

All HHs Pers. Poor

Transient Poor

Pers. Non Poor

Distribution (%) 100 28.38 15.51 56.1 100 22.93 15.69 61.38


Total Income1 108,522 40,456 57,144 157,164 106,385 41,090 58,354 143,053

Wages and Salaries1 45,865 13,470 23,604 68,410 42,900 14,435 22,434 58,764

Entrepreneurial Income1 29,974 17,341 20,464 38,995 29,282 15,583 21,117 36,486

Other Income1 407 138 56 641 273 220 214 308

Total Expenditures1 95,566 45,085 57,214 131,709 94,250 43,751 57,373 122,540

Education Expenditures1 4,540 1,085 1,494 7,130 4,715 971 1,700 6,884

Medical Expenditures1 2,544 658 732 3,999 3,060 462 1,022 4,552

Loans from other Families1 4,042 2,206 1,754 5,603 3,285 1,885 1,844 4,176

Savings1 12,956 -4,629 -70 25,454 12,135 -2,661 981 20,513

Amount deposited in banks and investments

1

3,377 218 224 5,847 3,316 48 44 5,374

% Employed 86.76 93.27 89.92 82.58 83.16 91.54 86.78 79.11

% Class of Worker

Worked for private HH 1.62 1.21 2.21 1.69 2.33 2.51 1.66 2.45

Worked for private establishments 33.77 30.48 36.91 34.73 33.42 38.11 37.64 30.22

Worked for government 7.55 2.47 2.32 12.03 8.08 3.58 3.20 11.39

Self-employed w/o any employee 46.40 56.93 48.95 39.59 47.38 50.57 52.32 44.61

Employed in own family operated farm or business

8.91 7.42 7.62 10.15 7.59 4.37 4.42 9.88

Worked with pay on own family operated business

0.97 1.15 0.99 0.86 0.16 0.21 0.00 0.19

Worked without pay on own family operated business

0.78 0.35 0.99 0.96 1.03 0.64 0.77 1.27

% Wages of Total Income 42.26 33.30 41.31 43.53 40.32 35.13 38.44 41.08

% Entrepreneurial Activity of Total Income

27.62 42.86 35.81 24.81 27.52 37.92 36.19 25.51

% Other Income of Total Income 0.38 0.34 0.10 0.41 0.26 0.53 0.37 0.22


% Did not graduate high school 61.91 83.05 75.10 47.56 59.40 83.28 74.81 46.53

% Own Lot 72.78 63.56 70.45 78.08 74.40 66.16 70.11 78.57


% with Own Water 28.53 10.54 13.37 41.83 38.76 14.10 21.36 52.41

% Houses made of Strong/Predominantly Strong Materials

73.33 50.90 64.63 87.08 77.03 54.23 66.19 88.32

% Urban Household 38.82 14.25 27.23 54.45 38.82 17.77 24.04 50.45

Notes 1/ These are household mean values are expressed in 2000 prices. 2/ Savings = Total Income – Total Expenditure 3/ 2006 Per capita total poverty threshold in 2000 prices= Php 9,686.31

103

Annex 8B. Difference in Profiles of Near- and Transient Poor Households in 2004 and 2010

DIFFERENCE

NPT 1.28 1.37

Profiles All

HHs Poor

Near-Poor

Non Poor

All HHs

Poor Near-Poor

Non Poor

Distribution (%) 0 -5.45 -0.12 5.58 0 -5.45 0.18 5.28


Total Income1 -2138 634 1910 -13426 -2138 634 1210 -14111

Wages and Salaries1 -2966 965 17 -9417 -2966 965 -1170 -9646

Entrepreneurial Income1 -693 -1758 230 -2259 -693 -1758 654 -2509

Other Income1 -134 82 76 -290 -134 82 158 -332

Total Expenditures1 -1316 -1333 -136 -8613 -1316 -1333 160 -9169

Education Expenditures1 175 -115 149 -210 175 -115 206 -246

Medical Expenditures1 517 -196 188 559 517 -196 291 553

Loans from other Families1 -757 -321 -75 -1312 -757 -321 90 -1427

Savings1 -822 1967 2046 -4813 -822 1967 1050 -4941

Amount deposited in banks and investments

1 -61 -169 -153 -463 -61 -169 -180 -474

% Employed -3.59 -1.73 -1.84 -3.71 -3.59 -1.73 -3.14 -3.47

% Class of Worker:

Worked for private HH 0.71 1.30 -0.54 0.68 0.71 1.30 -0.55 0.76

Worked for private establishments -0.35 7.63 2.53 -4.59 -0.35 7.63 0.73 -4.52

Worked for government 0.53 1.11 1.01 -0.57 0.53 1.11 0.88 -0.64

Self-employed w/o any employee 0.98 -6.36 0.98 5.42 0.98 -6.36 3.37 5.02

Employed in own family operated farm or business -1.31 -3.05 -2.60 -0.57 -1.31 -3.05 -3.21 -0.27

Worked with pay on own family operated business -0.81 -0.94 -0.98 -0.70 -0.81 -0.94 -0.99 -0.67

Worked without pay on own family operated business 0.25 0.30 -0.41 0.32 0.25 0.30 -0.22 0.31

% Wages of Total Income -1.94 1.83 -1.33 -2.58 -1.94 1.83 -2.86 -2.45

% Entrepreneurial Activity of Total Income -0.10 -4.94 -0.81 0.79 -0.10 -4.94 0.38 0.69

% Other Income of Total Income -0.12 0.19 0.13 -0.17 -0.12 0.19 0.27 -0.19


% Did not graduate high school -2.51 0.23 -0.24 -0.99 -2.51 0.23 -0.29 -1.03

% Own Lot 1.62 2.60 -0.29 0.44 1.62 2.60 -0.33 0.49


% with Own Water 10.22 3.56 7.43 10.54 10.22 3.56 7.99 10.59

% Houses made of Strong/Predominantly Strong Materials 3.70 3.33 0.64 1.43 3.70 3.33 1.56 1.23

% Urban Household 0.00 3.52 -2.58 -4.07 0.00 3.52 -3.19 -3.99 Notes 1/ These are household mean values are expressed in 2000 prices. 2/ Savings = Total Income – Total Expenditure 3/ 2006 Per capita total poverty threshold in 2000 prices= Php 9,686.31

104

Final Report (5 Jan 2015)

Pantawid Extension to High School: Pathway for Accelerating Improvements in

Human Capital among the Poor22 by

Jose Ramon G. Albert, Ph.D.

Report Prepared for the Department of Social Welfare and Development (DSWD)

and the Asian Development Bank (ADB)

22

Support for this report provided by ADB Technical Assistance 7733: Support for Social Protection Reform

105

A. Background

1. As part of its overall strategy to improve social services, to assist those in most need of

social protection, and to promote inclusive growth, the government, through the

Department of Social Welfare and Development (DSWD), has been implementing a

conditional cash transfer (CCT) called the Pantawid Pamilyang Pilipino Program.

Piloted in 2007 among 30 thousand household-beneficiaries23

, and launched nationwide

in 2008 to assist 300 thousand poor households24

, under its former name Ahon

Pamilyang Pilipino, the flagship CCT program is also provided support by the Asian

Development Bank (ADB), the World Bank, and the Australian Agency for International

Development (AusAID). Primarily a social protection25

program, the CCT was originally

aimed at providing social assistance for poor households on condition that these

households invest in their education and health, particularly those of their children 0 to

14 years old, and that they improve their availment of maternal health services. Social

protection systems actually cover a wide ranging set of tools including labor market

programs/interventions, social insurance, social welfare and social safety nets (Villar,

2013 ; Orbeta, 2011; Manasan, 2009).

2. As of December 2013, Pantawid has covered over 3.9 million households (including

94 thousand households who are covered under a Modified CCT, such as households

in need of social protection, homeless and street families). According to World Bank

staff26

, Pantawid has also become the third largest CCT program globally, next only to

Brazil (8.8 million households) and Mexico (6.5 million households). The CCT has also

disbursed 41.7 billion pesos for the entire period of 2013 (DSWD, 2013), thus making

the program the largest social welfare intervention that the government has ever

implemented.

23

The pilot of the CCT was implemented in municipalities of Sibagat and Esperanza in Agusan del Sur, in the municipalities of Lopez Jaena and Bonifacio in Misamis Occidental, and in the cities of Pasay and Caloocan with a 50 million peso- budget.

24

These households were selected from the 20 poorest provinces (with the exception of three ARMM provinces) and the poorest province in each of the 5 regions which were not represented by the 20 poorest provinces. In each of the poorest provinces, the poorest municipalities are selected based on the small area estimate (SAE) of poverty incidence released by the now defunct NSCB, and peace and order situation there at. A household enumeration of these areas was then administered in the selected municipalities. Subsequently, households were then selected on the basis of a proxy means test for identifying poor households in the enumerated areas.

25

According to National Economic and Development Authority -Social Development Committee (NEDA-SDC) Resolution No. 1, series of 2007, social protection is defined as “policies and programs that seek to reduce poverty and vulnerability to risks and enhance the social status and rights of the marginalized, by promoting and protecting livelihood an employment, protecting against hazards and sudden loss of income and improving people’s capacity to manage risks.”

26

Powerpoint presentation at DSWD forum on Pantawid Pamilya 2nd Wave Impact Evaluation, Nov 14, 2014, Oracle Hotel .

106

3. Designed based on successful CCTs in Latin America (Fiszbein and Schady, 2009),

Pantawid involves using a statistical model called a proxy means test (PMT) 27

to

obtain a list of poor households, from which, eligible households are then identified,

and subsequently provided cash grants provided that the household beneficiaries

comply with a set of conditions. In its original design, eligible households are those

tagged as poor by the PMT, with children 0-14 years of age and/or a pregnant woman

among its members. The cash grants were also designed to be provided to the

households for a maximum of five years. Grants for education amounted to P3,000 per

child per year (for a maximum of three children per household), while for health and

nutrition, grants for each household aggregated to P6,000 per year. The conditions for

the health grant were that: (i) pregnant household members should visit their local

health center every month to avail of pre- and post-natal care based on the Department

of Health (DOH) protocol; (ii) children 0-5 years old should visit their local health center

every month to avail of health services based on the DOH protocol; (iii) children in

primary school should be dewormed twice a year; and (iv) parent beneficiaries should

be attending monthly Family Development Sessions (FDS). On the other hand, the

condition for the education grant was enrolment and at least 85 percent attendance at

school for children. These co-responsibilities for the cash grant are meant to encourage

the poor households to invest in human capital that will eventually enable them to

break away from the clutches of intergenerational cycle of poverty, while at the same

time, providing them some immediate financial relief, and fostering social inclusion.

4. During the 2013 State of the Nation Address28

(SONA), the President of the Philippines

announced the extension of support of Pantawid to include children aged up to 18

years old starting 2014 in order to allow children-beneficiaries to finish high school.

This decision was based on policy research conducted by Reyes et al., (2011b) of the

Philippine Institute for Development Studies (PIDS), the government’s think tank. The

PIDS study suggested that it is crucial to deepen the impact of the CCT by expanding

coverage to high-school-aged children, since wages received by high school graduates

are 40 percent higher compared to those who only graduated from primary school. In

27

The PMT is a statistical model involving regression analysis used to predict the income of a household based on observable characteristics that correlate with, but are easier to measure, than income itself. The predicted income per capita from the PMT model is then compare with official poverty thresholds, computed by the now defunct National Statistical Coordination Board (NSCB). The household is then classified as poor when the per capita income proxy is below the official poverty threshold, otherwise, the household is classified as non-poor (Fernandez, 2012). The use of the PMT for identifying poor households ensures credibility in beneficiary selection since a scientific approach is used for targeting, and reduces risks associated with political patronage in selection of beneficiaries for a program meant to help the poor.

28

http://www.gov.ph/sona-2013/

107

addition to the PIDS study, the results of the first wave of IE studies of the program as

reported in Chaudhuri et al. (2013), as well as other studies examining the 2011 Annual

Poverty Indicator Survey (APIS) such as Paqueo, Orbeta, Castaneda, & Spohr (2013)

were additional bases in the conceptualization of the Extended CCT (ECCT) Program that

extends age coverage to allow children beneficiaries to finish high school. Exit in the

ECCT program under is no longer after five years, but rather, after the three children

beneficiaries in a household beneficiary graduate from high school, or reach 18 years

old, whichever comes first.

5. In this report, we examine the Pantawid Results Framework as per the original

program design and various data in relation to opportunities and challenges in

yielding expected outcomes for the program and the design changes in the wake of

the extension of support for children to finish high school and plans to shift

beneficiaries from households to families. We suggest changes in the framework and

its articulation. We also provide suggestions on some extra revisions in program design

to address other disparities, i.e. between boys and girls, and between urban and rural

areas, that can further improve the impact of Pantawid. This report is in fulfilment of

the Terms of Reference of the Assignment (that is supported by ADB Technical

Assistance 7733: Support for Social Protection Reform) which provides for: i) a review of

existing or emerging DSWD policies, plans, and procedures for proposed evolutions in

Pantawid and the National Household Targeting System for Poverty Reduction (NHTS-

PR), including the extension of CCT education benefits through age 18 and the transition

of NHTS-PR and Pantawid benefit eligibility from a household-based to a family-based

classification; (ii) an assessment of the operational implications of the proposed ECCT

policies and procedures, including regarding likely efficacy, as well as financial and

implementation-related dimensions, including those related to complexity, human

resource requirements, various MIS systems, and implications of the ECCT in the current

results framework (particularly on the committed program objectives, outputs, and

outcomes, which are based mainly on the existing CCT design); (iii) a quantitative

assessment of the implications of the expected transition from the household-based to

family-based classification, including the potential impact on the outcomes committed

in the Pantawid results framework (e.g., targets on increased household/family

consumption, percentage reduction in school dropouts, etc.); (iv) assist the Pantawid

Pamilya National Project Management Office (NPMO) in updating the results framework

in view of ECCT and (if adopted) the shift to family-based targeting; (v) provide

additional analytical inputs to support implementation of options identified as being

most viable, and incorporate these in the final report.

108

B. High Expectations of Pantawid

6. The CCT Program has been extensively scrutinized, in the wake of huge resources

provided for Pantawid. Rightfully, every program involving public funds should undergo

careful examination: everyone should ask about the value of each peso spent in

government programs and projects. However, criticisms must also be fair, and those

that are not, should be answered by DSWD and its stakeholders. Some point out that (a)

Pantawid is an expensive dole-out for the poor, (b) the program encourages

mendicancy, (c) the program has errors in identifying the poor, and (d) the CCT is

ineffective since official poverty rates released by the defunct National Statistical

Coordination Board (NSCB) have remain unchanged29

from 2006 to 2012 despite the

huge cost of Pantawid. From being provided a budget of 50 million pesos in 2007 to

support 6 thousand households, Pantawid has been provided increasing resources,

particularly a budget of 62.6 billion pesos in 2014 to assist 4.3 million households,

including the extension of support of education grants for children to complete high

school.

7. While the program budget may seem huge, what goes to Pantawid beneficiaries is not

a lot, the grants are not enough for these households to cross the poverty line. Based

on an analysis of the APIS 2013, the World Bank reports30

that in 2013, Pantawid

beneficiary families received an average of P1,407 of monthly cash grants, if they sent

their 3 beneficiary children to school, and received health services for their household

members. Without the cash grants, these families had an average per capita income of

P13,293, whereas the poverty line per person was P19,262. Thus, the cash grants in

Pantawid will not really help the poor cross the poverty line, but these were never

meant as such. The defunct NSCB, now a part of the Philippine Statistics Authority

(PSA), estimated that in 2012, the aggregate poverty gap, i.e. the total cost of

eliminating poverty if all poor households were given what they need to reach the

poverty threshold, is practically 124 Billion pesos in 2012 (exclusive of targeting costs)31

,

which is more than three times the DWSD budget for Pantawid during that year. Poor

households have an average size of six household members, and such households

would, on average, need 29,760 pesos for the entire year of 2012 to reach the poverty

line, while at most, beneficiary families in 2012 were given 15,000 pesos if they have

three beneficiary children and a pregnant member. While the cash grants are of clearly

29

NSCB December 2013 press release. 30


31

http://www.nscb.gov.ph/pressreleases/2013/NSCB-PR-20131213_povertypress.asp

109

help to the household, the maximum amount given to a household beneficiary is merely

half of the average amount required by the poor to reach the poverty threshold.

8. Since the cash grant has not changed since program inception, the amount received in

real terms has eroded and needs reexamination. By program design, the maximum

cash grant of P13,000 per month was 23 percent of household income of pilot

beneficiaries in 2006, but this amount has decreased to 16 percent of household

income as of 2009, and to 7 percent as of 2013.

9. Although the cash grants per household are small, they are of help to the households

and have aggregate effects of keeping poverty from worsening. Despite population

growth of 1.9 percent for the entire population for the past two decades, the official

estimate of the magnitude of extremely poor families has remained steady at around

1.60 million from 1991 to 2012 (see Figure 1). When the NSCB released official poverty

statistics in December 2013 examining trends from 1991 to 2012, it also indicated that

this steady magnitude of extremely poor families might be construed as partial

evidence that Pantawid helps extremely poor families get out of subsistence.

Figure 1. Number of Poor Families and Extremely Poor (or Subsistence) Families, 1991-2012.

Source: PSA

10. While the latest official estimate of poverty rate for the first semester of 2013 is 24.9

percent, poverty stakeholders, including the DSWD, should be aware that this figure,

while lower than the estimate for the first semester of 2012 (based on the FIES), does

not suggest declining poverty, and therefore no recent reduction in poverty rate can

be established and attributed to Pantawid. The estimate (of 24.9 percent) using the

1.5

22.5

33.5

4m

illio

ns

1990 1995 2000 2005 2010year

number of poor families

number of extremely poor families

110

2013 APIS is incomparable to the estimate (27.9 percent) for the first semester for 2012

using the FIES. While the 2013 APIS made use of more detailed questions on income by

adopting the income module of the FIES, but the instrument was a “modification” of the

FIES module, so that in consequence the estimates of poverty are not comparable.

While the survey instruments are similar, they are not exactly the same, thus it is not

clear whether poverty reduced at all between the first half of 2012 to 2013. Trends in

income poverty rates from 2006 to 2012 have been practically unchanged, but not to

the fault of Pantawid.

11. Pantawid has increased income of beneficiaries so that they have moved closer to the

poverty line. The World Bank suggests32

that per peso cash grant, the poverty gap,

another summary measure of poverty representing the average amount of income

shortfall of the poor from the poverty line in relation to the poverty line, has been

reduced by 61 centavos. As was pointed out earlier, in 2012, the aggregate ‘income

gap’ of the poor, i.e. the total amount required for all poor persons to cross the poverty

line (assuming we could identify them and give them just what they needed, without

even considering the costs of identifying them) was P136.6B pesos, whereas the total

CCT budget amounted to P39.4B. So while the CCT budget is large, the amounts given to

beneficiaries would not be enough to help them get out of poverty, and should not be

expected to change poverty incidence considerably. The amounts given to the

households have also even been eroded by inflation: in the pilot implementation of

Pantawid in 2006, the maximum cash grants were a fourth (23%) of household income,

but by 2013, this has gone down to less than a tenth (7%) on account of inflation.

12. Poverty rates would have further worsened without Pantawid. The World Bank33

estimates that the official national poverty rate (of 25% estimated in the first semester

of 2013) could have been as much 26.4% without Pantawid. Even the extreme poverty

rate (of 11.1% estimated in the first half of 2013 from the APIS 2013), the proportion of

Filipinos whose (per capita) income is less than their needs for food, would have been

1.4 percentage points higher without Pantawid (12.5%) in place.

32


33


111

Table 1. Estimates of Poverty Incidence (using Total Poverty Line and Food Poverty Line) with and without Pantawid.

National Among Pantawid beneficiaries

Without Pantawid

With Pantawid

Without Pantawid

With Pantawid

Poverty rate 26.4% 25.0% 64.5% 58.1% Extreme poverty rate

12.5% 11.1% 35.3% 28.7%

Note: Estimates generated by World Bank Staff using data from national household surveys conducted by PSA, as presented in DSWD forum on Pantawid Pamilya 2nd Wave Impact Evaluation, Nov 14, 2014.

13. Among CCT beneficiaries, the increase in poverty rate without Pantawid in place is

even higher. The World Bank suggests that poverty among Pantawid beneficiaries

(estimated at 58.1% in the first semester of 2013) would have been 6.4 percentage

points higher (64.5%) without the CCT in place.

14. While this suggests that some CCT households are not (income) “poor”, but these non-

poor beneficiaries are not rich, and the DSWD proxy means targeting system is fairly

accurate. Independent evaluation by the Social Weather Stations, (see Chaudhuri et al.,

2013), shows that while there are household beneficiaries that are not income poor,

these households are not rich. Government officially defines poor according to (per

capita) income data and poverty thresholds: the PSA collects income data through a

meticulous process of asking detailed information on household income through

nationally representative sample surveys, and determines households to be poor if the

per capita income is less than the poverty threshold. The latter is obtained by the PSA as

the minimum cost of basic food and non-food requirements. On the other hand, the

DSWD does not collect income data, but rather proxies of income, through the NHTS-PR

(also called Listahanan), an administrative reporting system of households. In the

NHTS-PR, the DSWD collects information from households on their facilities (such as

electricity, toilets, walls, roofs) and assets (such as refrigerators, television sets, and the

like), and on the basis of a statistical model (called a proxy means targeting model)

estimates household income, which, together with official poverty lines, provide the

DSWD a mechanism to identify poor households. Such a process involves

misclassification34

of households, but the DSWD has also a process for delisting the non-

poor, and also for having those who consider themselves as poor and who are not in its

list to be enlisted, subject to verification of information. The World Bank35

estimates

34

when a non-poor household is thought to be poor, or a poor household is tagged as non-poor 35


112

that in 2013, more than four fifths (82%) of Pantawid beneficiaries were from the

bottom 40 percent of income distribution, and more than half (53%) were from the

bottom 20 percent. The World Bank also suggests that when Pantawid is compared in

targeting accuracy with other CCTs across the world (see Figure 2), the DSWD targeting

system performs better than all CCTs with a large coverage in the population (of more

than 15%), except for that of Brazil.

Figure 2. Targeting accuracy to the poorest 20 percent of CCTs with more than fifteen

percent coverage of the population.

Note: Estimates generated by World Bank Staff, as presented in DSWD forum on Pantawid Pamilya 2nd

Wave Impact Evaluation, Nov 14, 2014.

15. It must be emphasized that Pantawid is not a dole out as it does not follow the

traditional approach of providing goods and services unconditionally to those in need,

but rather attaches conditions to the availment of cash grants. By having conditions or

co-responsibilities to receiving the cash grants, CCTs aim to incentivize long term

investments in human capital accumulation, since poor households often make short-

term coping decisions not to send their children to school. Poverty reduction should not

necessarily result in the short-term but rather, in the long term, when the child-

beneficiaries join the labor market with better educational attainments that will provide

them better income prospects, and thus substantially better chances to escape from

poverty. The latest 2014 World Development Report (WDR) of the World Bank (2014)

describes various sources of risks to household welfare, and the need to manage these

risks. The WDR explains that some of these risks to welfare are idiosyncratic and specific

57.0

52.850.4

40.6 39.537.0

02

04

06

0%

ben

eficia

ries f

rom

th

e p

oore

st 2

0%

Brazil (2009)

Philippines (2

013)

Mexico (2010)

Jamaica (2010)

Colombia (2012)

Ecuador (2010)

113

to individuals and households, such as illness, injury, disability and death, while other

sources of risks are systemic, and cover groups of households, communities, regions,

countries, such as epidemics and natural disasters. If designed and implemented well,

social protection programs such as Pantawid can be an effective means to manage

these risks, by assisting households (and communities) to build their assets, protect

these assets when shocks occur, and use these assets more efficiently.

16. The DSWD developed a results framework for Pantawid, and an operations manual as

per original program design, but these were not widely disseminated and maybe

contributing to too many expectations of the program. Much of the criticisms levelled

against Pantawid appear to be a misunderstanding of what the program is meant for.

The results framework (see Appendix Figure 1) illustrates how a sequence of inputs

(financial, human and material resources at the disposal of the program), activities (task

and actions performed to transform input into outputs), and outputs (the tangible

goods and services produced by the program ) for which Pantawid is directly responsible

interacts with behavior of beneficiaries to establish mechanisms through which

intermediate results (or outcomes) and impacts (or final goal or outcomes of Pantawid)

are achieved. Gertler et al., (2011) point out that a results framework is a simple way to

outline the “theory of change”, which describes how a program is supposed to deliver

the desired outcomes and impact, and that a results framework also allows program

managers to communicate program goals explicit, thus helping everyone, especially

stakeholders, understand the causal logic and the sequence of events behind the

program. The Pantawid results framework as well as the program’s operations

manual36

, however, were not widely disseminated and communicated to stakeholders,

in particular, and the public, in general, to dispel unfair remarks of program critics. It will

be important to improve communication strategies about the program by clarifying

what the program is expected to deliver (and what it is not meant for).

C. Examining the Original Pantawid Results Framework, Operations Manual and other

Program Documents

17. With the implementation of the ECCT, it is important to reexamine all components of

Pantawid’s original results framework. Pantawid is not a strategy for immediate

36

The Operations Manual (OM) of Pantawid, as of 2013, was approved in principle by DSWD management and the World Bank, with a previous drafts written for the pilot. As of the moment of this writing, another draft of the OM that incorporates the high extension, the convergence efforts, and other current activities is being finalized. Once it has been copy edited, it will need to be presented to Pantawid stakeholders by DSWD to achieve a clear and common understanding of Pantawid operations. Feedback and comments of stakeholders can subsequently be incorporated in the draft. Official approval of government and development partners on the OM will be necessary.

114

poverty reduction, but a social protection mechanism aimed at contributing to the

improvement of attendance of children in school, maternal and child health, nutrition,

and efforts in preventing child labor. These manifold objectives37

and sub-objectives38

under the first objective of Pantawid that have been listed in the original Operations

Manual prior to the high school extension are too elaborate. Cash grants are supposed

to be triggers for behavioural changes, and they assume supply side requirements, e.g.,

schools are accessible to households, schools deliver quality learning for children.

Effects of natural disasters and other factors that can further put households into

further risk of worsened welfare will certainly run counter to stimulating demand for

school and health services among poor households.

18. Some of the program objectives articulated in the original Operations Manual are not

actually within the control of the program. The Operations Manual listed many noble

program objectives based on the DSWD’s wide agenda, but it is likely that some of these

objectives will not be met on account of the program. For instance, as regards child

labor, if children are engaged in labor, the cash grants to encourage them to go to

school do not carry conditions about the children getting disengaged from work

activities. Thus, it would be too much to expect reductions in child labor because of

Pantawid. The results of Orbeta and Paqueo (2013) confirm that Pantawid has no

impact on keeping children from joining the labor force, although the hours at work is

less (by 4hours) for children of primary school age for Pantawid households (as

compared to a “control group” that are not Pantawid beneficiaries). Thus, while

government and the DSWD, in particular, will need to work on minimizing child labor

activities in the country because the engagement of children in work activity when they

are currently in school can make the children more prone to dropping out, Pantawid can

only contribute to this effort, and thus the DSWD’s objective to minimize children’s

involvement in work, while laudable, cannot be a program objective of Pantawid. The

focus of Pantawid is on building human capital of poorest households (in terms of their

children’s education, as well as the health and nutrition of members) since the poor do

not have the enough opportunities to improve their education and health conditions,

37

The original program objectives include : (1) to improve the health of young children and mothers by promoting preventive health care; (2) to increase the enrolment and attendance rate of children in Day Care, Kindergarten, Elementary and Secondary school; (3) to contribute to the reduction of incidence of child labor; (4) to raise the average consumption rate in food expenditure of poor households; (5) to encourage parents to invest in their children’s health, nutrition and education; and, (6) to enhance the performance of parenting roles of beneficiaries and their participation in community development activities.

38

Sub-objectives of the first original program objective on health include: (a) to increase growth and nutrition monitoring visits of infants and children under five years old; (b) to promote complete immunization of infants and children under three years old; (c) to ensure regular visit to health centers of pregnant women and young children; (d) to increase child growth and lower stunting among children 5 years old below; and, (e) to lower the incidence of complications in pregnancy and maternal deaths.

115

and cash grants, though limited, provide some immediate relief to the living conditions

of poor households who suffer from various deprivations in income and expenditure.

While the cash grants, for health and education, may be used to increase consumption

for food, they may also be used for non-food consumption, so the Program objective to

“raise the average consumption rate in food expenditure of poor households” is also not

realistic. Results of impact evaluations of Pantawid (see, e.g., Chaudhuri et al., 2013 )

validate this observation.

19. Criticisms on Pantawid may partly be resulting from the lack of a coherent

communication strategy to inform the public about what the program can and cannot

do, and how long it will take for certain final outcomes to result. It appears that there

are too many expectations from Pantawid, in part because the program is being used as

a vehicle for many of the noble objectives of the DSWD. Poverty reduction and

reduction of income inequality are long term outcomes that can only be realistically

expected when the children-beneficiaries join the labor force with better education

attainments. The DSWD may need to work on simplifying, explaining and improving its

articulation of what are the program’s ultimate goals, medium-term outcomes, and

what can be expected in the short-term from the program inception.

20. Outcomes and final outcomes articulated in the original Results Framework and

Operations Manual that are desired of Pantawid need reexamination by DSWD.

Desired impacts can be influenced by several factors that are not necessarily within the

control of the program, and these impacts are typically achieved over a longer period of

time compared to outcomes that may be achieved in the short or medium-term. It has

been noted that the Program Management Office (PMO) has developed as of this

writing a better articulation of the program’s Results Framework, which has been

discussed within DSWD, but will need to be communicated to stakeholders.

21. While assumptions and risks identified in the Original Pantawid Results Framework

were quite exhaustive, the Framework did not consider how having a uniform level of

cash grant may pose considerable risks on maximizing the effects of the program. Any

Results Framework lists the assumptions about the context in which the program

resides, and the risks that may affect the intended results, so that mitigation strategies

may be put in place to manage those risks. The assumptions and risks for Pantawid

were identified in its original Results Framework, both in terms of how outcomes are

converted to impacts (Table 2a), as well as how outputs are converted to outcomes

(Table 2b). But the Results Framework did not consider how a uniform level of

education grant (300 pesos per month per child) would be able to match varying

116

opportunity costs of sending children to school. Historical data on school participation

would show that this indicator is considerably different for sub-groups of the

population, e.g., male children and female children, younger children and older children,

children from rural households and those from urban households, children from special

marginalized groups and those from the rest of the household beneficiaries. These

disparities suggest that opportunity costs for going to school are actually varied, and

consequently, incentives should also be varied. More will be discussed about these

disparities in education participation in the next section of this paper.

Table 2a. Assumptions and Risks for Outcomes-Impact

Impact: Empowered,

self-sufficient and

productive Pantawid

Pamilya households by

2023.

Outcome-Impact Assumptions and Risks

• A: Empowered? FDS and other community assemblies continue

with beneficiaries; able to mobilize resources and identify

topic-specific discussion to address particular issues

• A: Productive: Internal (SLP, KC) and external convergence

(Coco Levy Fund development); access to market; stable

income source. (R: Food consumption may be a risk to

economic productivity if inadequate).)

• A: Self-sufficient? 2023, institutionalization of service delivery

so that safety nets are available when financial/political

instability and disasters occur.

• R: Supply side, i.e. infrastructure requirements are not met

(because if not met, productivity/self-sufficiency will be

disrupted)

• R: Force majeure may erode prior health/education

investments in supply-side and human capital

• R: IP sensitivity requirements are not addressed in all sectors at

different levels of intervention and implementation.

• A: Household members continue to voluntarily avail health and

education services after program exposure (behavioural

change)

• A: LGUs sustain spending in education through the Special

Education Fund.

Outcome 1: Sustained access of program beneficiaries to preventive health care services by 2018. Outcome 2: Sustained gross enrolment and attendance rates of children beneficiaries by 2018. Outcome 3: Food

consumption per

nutrition is meeting

requirements of

pregnant women and

children beneficiaries

by 2018.

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Table 2b. Assumptions and Risks for Outputs-Outcomes.

Outcome 1: Sustained access of program beneficiaries to preventive health care services by 2018.

Outputs-Outcomes Assumptions and Risks

• A: Cash grants are delivered on time to the beneficiaries

• A: External factors such as supply side requirements are

fulfilled

• A: Households comply with program conditions.

• A: External factors are controlled or taken into consideration

(force majeure)

• R: Grievances are not redressed; lower entitlement complaints

are not resolved within acceptable timeframe.

• R: Updates on facilities are inadequate or absent.

• R: Systems-related errors (updates issues, encoded/forwarded

but does not take effect)

• A: Operations manual is enforced

• A: Systems/field manual operationalized

• A: Conduit reports are verified against actual receipt of cash

Outcome 2: Sustained gross enrolment and attendance rates of children beneficiaries by 2018. Outcome 3: Food

consumption per


requirements of

pregnant women and

children beneficiaries by

2018.

Output 1. Poor

Households have

received cash grants for

a minimum of five years

Output 2. Program areas-- barangays, municipalities, cities, provinces and regions --- have updated and relevant profiles for development planning Output 3. Local

stakeholders benefit

from improved

implementation

mechanisms in a

responsive environment

22. The list of statistical indicators in the original Results Framework requires

modifications. For each of the identified outputs and outcomes of Pantawid, a specific

set of indicators, including baselines and targets for 2018, were also identified in the

original Results Framework (see Table A-1a and Table A-1b of Annex A), but

• statistical indicators identified may not necessarily be objective nor verifiable

(for lack of baseline data as well regular data source),

118

• some indicators unnecessarily state directional changes expected from the

project, including targets and baselines (rather than have these as remarks to

the indicators), and

• some targets and baseline data do not relate directly to the indicators.

• for some numerical targets on the indicators, it is also worth asking whether to

what extent these targets are merely aspirational.

In practice, targets for statistical indicators need to balance ambition with reality by

examining historical trends on indicators. Statistical indicators for the program also

need to be sufficiently specific. It is thus important to modify the list of program

indicators in the original Results Framework, especially as the program and the DSWD

may be pursuing goals that, while lofty, may be difficult to achieve even with extra

resources currently at the disposal in the program, as compared to the program’s onset.

23. Whatever targets specified in the final version of the Results Framework of Pantawid

should reflect a consensus and understanding of program objectives among DSWD

program implementors and stakeholders. While indicators can take various forms

(such as rates, ratios, percentages, numbers), the indicators should be measurable over

time and linked to targets. They should also not identify the targets. Ultimately,

statistical indicators should be helpful in communicating information to stakeholders on

whether or not progress is being achieved.

24. Activities of the program for achieving outputs need to be specified in the Pantawid

Results Framework. Clearly, the major activities of the program as per the Operations

Manual include: (a) (one-time) identification of beneficiaries and generation / updating

of information on beneficiaries, (b) distribution of cash grants, (c) conduct of FDS and

Youth Development Sessions (YDS); (d) verification of compliance by household-

beneficiaries to grant conditions/co-responsibilities; (e) capturing information on

complaints about the program and resolving these grievances, (f) coordination within

DSWD and with institutional partners for convergence, were not explicitly spelled out in

the Results Framework. Figure 3 illustrates a proposed revised Results Framework. It

explicitly states these activities, as well as incorporates updates on the original Pantawid

results framework based on the expansion to high school, and efforts for convergence

from DSWD, and other government agencies to assist beneficiaries. For a one-time

identification of Pantawid beneficiaries, the program makes use of results obtained by

the National Household Targeting System for Poverty Reduction (NHTS-PR), to identify

poor households (Fernandez, 2007; Fernandez, 2012) using a proxy-means model. In the

original program design, eligibility checks are undertaken to determine poor households

identified from the PMT that have pregnant women and children 0-14 years old. With

119

the expansion for high school beneficiaries, the upper limit of children’s ages has been

increased to 18 years old. Households that graduated from the program due to the

original five year limit for grants may be eligible for re-entry if they have children up to

18 years old. The generated list of eligible households is then sent to the field offices

for public posting for at least a week. A registration is then conducted through a

Community Assembly, where households fill out Land Bank39

Enrolment Forms as well

as “Validation Forms” to update household information.

25. The DSWD has developed various technical and administrative systems to manage

effectively Pantawid and the implementation of ECCT should not pose major

challenges to system updates. The systems for Pantawid are chiefly the Beneficiary

Update System (BUS), Compliance Verification System (CVS), Payment System (PS) and

Grievance Redress System (GRS) that aim to organize the program implementation,

address issues systematically, and to effectively ensure that the program objectives are

being met. The BUS gathers, validates, reports and records information on beneficiaries

that has bearing on cash payments and continued eligibility of household beneficiaries.

The CVS provides for a regular monitoring of the compliance to the grant conditions,

based on information obtained from school teachers or principals (for the education

conditions), health personnel and Municipal Links (for the health conditions on visits to

health facilities and participation in the FDS), with the outputs of the compliance

verification linked to the distribution of cash grants via the PS on a bimonthly basis

through different modes of payment. The GRS provides a mechanism for capturing

grievances, facilitating due process in resolving these complaints of household

beneficiaries and the community regarding Pantawid. The DSWD also regularly

conducts a simple assessment of supply side requirements to determine the readiness

of schools and health center facilities as a pre-requisite to implementing Pantawid in a

locality. This process involves encoding, editing and viewing of health and education

data of assessed school and health facilities of a given area vis-à-vis the benchmark

ratios on health and education. System updates appear to have been effectively carried

out by DSWD staff toward making changes in the entire program for implementing the

ECCT, i.e., from registration, to monitoring, to payments (with the additional conditions

such as attendance in FDS/YDS). System updates did not appear to require major

challenges.

39

Cash grants from Pantawid are typically coursed through the Land Bank of the Philippines (LBP). Beneficiaries are issued identification cards and bank cards, with payment of the cash grants made to the most responsible adult in the household, often the mother of beneficiary-children, through automated teller machines of the LBP. Others avail of the transfer either through rural banks, telcos, cooperatives, or the post office.

120

Figure 3. (Revised) Pantawid Results Framework.

Inputs

• Structures

• Systems

• Policies

• Processes (informal)

• Logistics

Activities

•Identification of Program Beneficiaries

•Distribution of Cash Grants

•Conduct of FDS and YDS

•Monitoring of Grant Conditions / Co-responsibilities

•Collection of Information on Complaints, and Addressing of these Grievances

•Coordination within DSWD and with NGAs, LGUs, other partners to ensure supplies in the program areas

Outputs

•Poor Households have received cash grants up to time when their 3 children beneficiaries graduate from high school or reaches 18 years old, whichever comes first

•Households fulfilling their co-responsibilities

•Local stakeholders benefit from improved implementation mechanisms in a responsive environment

Outcomes

•Sustained access of program beneficiaries to preventive health care services by 2018.

•Sustained gross enrolment and attendance rates of children beneficiaries by 2018.

•Improved attitudes on education and health and practices on parenting and active citizenship among beneficiaries by 2018.

Impact

•Empowered, self-sufficient and productive Pantawid Pamilyahouseholds by

2023.

121

26. What Pantawid will need to improve on is the methodology for “spot checks”

particularly as regards the payment system, to assure stakeholders that beneficiaries

are getting the correct cash grants, and in a timely fashion. There is currently in place

a mechanism for the conduct of “spot checks”, supported by ADB and the World Bank,

in the respective areas of assistance by these development partners. However, the spot

checks are independent and not designed to have national representation. While 1,200

household beneficiaries are checked twice a year by both ADB and the World Bank, the

selection of provinces and areas within the provinces will not even make the households

representative at the particular province. The methodology for selection of spot checks

needs considerable improvement to identify system problems. Specific payment

systems that have varied from the usual process will also need extra checking, perhaps

by developing a separate “stratum” for sampling of these beneficiaries, and doing some

over-sampling of this stratum. The DSWD may want to explore a cooperation

arrangement with the PSA. The PSA regularly conducts quarterly surveys of the labor

force survey (LFS) with four “replicates” from its master sample of households. Even if

one replicate comprising about 12,000 households is used for this purpose of spot

checking, this replicate is likely to have a fifth of this sample (about 2,400 households) to

be Pantawid beneficiary households. The benefit of having PSA conduct this spot

checking is to enable a rich analysis of information on spot checks with other

information merged from results of the LFS, including the APIS and FIES, which are

themselves riders of the LFS.

27. Beyond improving spot checks, the DSWD should plan to measure how many of the

current Pantawid beneficiaries may still be currently poor and how many have exited

from poverty, if new information is obtained about the assets of beneficiaries during

the conduct of the next Listahanan. The Listahanan was conducted in 2008, while the

PMT was carried out in 2009. It may be possible that some of the households may no

longer be poor, whether as a result of the cash grants, or other means. There may also

be new households eligible for entry into Pantawid, as a result of income volatility in the

country (Albert, et al., 2013). When the DSWD conducts a new Listahanan it will be

important to have parallel runs of the old proxy means testing model and the new

model it will be making use of, in order to ensure that improvements to households are

not due to a change in the PMT model used.

28. As Pantawid moves on to ECCT to assist children beneficiaries in completing high

school education, it is important not only to revisit the goals, objectives, outcomes,

outputs and statistical indicators, but also to re-express the entire results framework

122

into a logical-frame approach, and work toward developing improved monitoring and

evaluation based on identified objectively verifiable indicators (OVIs). The OVIs need

to be very specific, but these do not require directions of improvements or reductions in

the values of the OVIs, as was done in the Results Framework for the original program

design (see Tables A-1a-b of Annex A). Targets and baselines need also not part of the

indicator. Rather these should be remarks to the indicators. A regular examination of

these indicators should be conducted to identify bottlenecks for yielding desired

outputs and outcomes, and to help identify strategies to address or mitigate these

bottlenecks.. Table 2 presents a suggested logical frame (see, e.g., Bakewell and

Garbutt, 2005) for Pantawid that takes into account of the theory of change in the

program (see Figure 2 and Figure B-1 of Annex B) pertaining to nutritional and welfare

status of household beneficiaries. Welfare changes are assumed to result from

improved education of the children-beneficiaries. Figure 2 is adapted from the theory of

change in a CCT described in Leroy, Ruel, and Verhofstadt (2009) while Figure B-1 of

Annex B was, as of this writing, recently developed by Pantawid PMO staff to articulate

the program’s theory of change. The changes in attitudinal behavior suggested here

among parents and youth arising from the FDS and YDS should, however, be measured.

29. The Pantawid cash grants are expected to increase the use of schools and preventive

health services among the poor who are currently under-utilizing these social services,

likely on account of demand side issues. These include the lack of household income,

and the time involved to avail of these services (which competes with the time women

devote to either caring for children, doing household chores, or finding extra sources of

income). An increase in utilization of health services is expected to improve health

status of household members, while increased years of schooling for children from poor

households would equip them with better prospects of quality employment that will

minimize their risks of staying poor. The cash grant would also, in the short term,

improve consumption of food and other basic items required by the household.

Participation in family development sessions (FDS) would improve parental knowledge

on health and nutrition of household members, and assist parent beneficiaries on their

provision of requisite guidance to their children, which is important for children to stay

in school especially in the early years of child schooling (see David and Albert, 2012).

The transfer of information to parent beneficiaries during the FDS is expected to induce

behaviour changes. Similarly, participation in youth development sessions (YDS) would

be expected to yield behavioural changes in the youth beneficiaries. Imposing

conditions to the grants, including the participation in the FDS and YDS, and monitoring

the compliance of households would ensure increase utilization of health and education

services to desired levels.

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Table 2. “Suggested” Logical Framework for Pantawid A. PROJECT

DESCRIPTION B. INTERVENTION

LOGIC

OBJECTIVELY VERIFIABLE INDICATORS

(OVIs)

SOURCES OF VERIFICATION

(SOV)

ASSUMPTIONS AND PRE CONDITIONS

1 GOAL (or IMPACT) • Empowered, self-sufficient

and productive Pantawid

Pamilya households by 2020

• Average income gap of Pantawid households BASELINE: 34.1% in 2009 TARGET: 28.7 % in 2020 • Number of households participating in local decision-making structures/processes such as community assemblies and barangay councils , disaggregated by marginalized sectors such as women, indigenous peoples (IPS), and Persons with Disability (PWD) • Proportion of unpaid family workers and own-account workers as a percentage of total employment. BASELINE: 43.5% in 2008 TARGET: 32.1% in 2020

• generated PMT scores (2014-2009 and 2018-2014) in NHTS database

• NHTS-PR or IE Study • Labor Force Survey (LFS), PSA

2 Specific objectives (SO)

1. Contribute to Government's Efforts to Break Intergenerational Poverty

•Subsistence poverty rate BASELINE: 10.9% in 2009 TARGET: 8.2% in 2018

• Family Income and Expenditure Survey (FIES), PSA

A: Cash grants are able to help some extremely poor break away from extreme (or subsistence) poverty A : Health cash grants and FDS sessions improve awareness of parent-beneficiaries on maternal and reproductive health A: FDS and other community assemblies continue with beneficiaries; able to mobilize resources and identify topic-specific discussion to address particular issues A: Household members continue to voluntarily avail health and education services after program exposure (behavioural change) A: LGUs assist national government by increased spending in education through the Special Education Fund A: Internal (SLP, KC) and external convergence

• Poverty gap ratio BASELINE : 5.4% in 2009 TARGET: 3.6% in 2018

• FIES, PSA

• Infant mortality rate BASELINE: 25 deaths per 1,000 live births (2008) TARGET: 20 deaths per 1,000 live births (2018)

• National Demographic and Health Survey (NDHS), PSA

124

• Proportion of unplanned pregnancies BASELINE: 37% in 2008 TARGET: 27% in 2018

• NDHS, PSA

(Coco Levy Fund development); access to market; stable income source. (R: Food consumption may be a risk to economic productivity if inadequate).) A: By 2023, institutionalization of service delivery so that safety nets are available when financial/political instability and disasters occur. R: Supply side issues counter demand side investments R: Supply side, i.e. infrastructure requirements are not met (because if not met, productivity/self-sufficiency will be disrupted) R: Force majeure may erode prior health/education investments in supply-side and human capital

2. Accumulate Human Capital

• Average number of school years completed among 15-24 years old in bottom 20 percent of wealth/income distribution BASELINE : 6.2 years in 2008 TARGET: 8.6 years in 2020

• NDHS, PSA

• Functional literacy rate among bottom 30 percent of wealth distribution BASELINE: 75.1% in 2008 TARGET : 87.7% in 2018

• Functional Literacy, Education, Mass Media Survey (FLEMMS), PSA

3 II.

III. INTERMEDIATE RESULTS

(OR OUTCOMES)

1. Increased use of preventive health care services in accordance with DOH protocols by program beneficiaries in 2016

1.1. Percentage of children availing preventive health care such as deworming (see Policy Output for special cases), vitamin A, and immunization. Alternative Indicator: Percentage of 0-5 yrs old children undergoing growth monitoring and check-ups BASELINE: 63% in 2009 TARGET: 90% by 2016

1.1. DOH Reports/ Facilities Report (NNC); Health Center Records; MHO records

A: Health component of PDP Social Development Agenda, including health goals in MDGS, has contributed to improved living conditions of poor households. A: Poverty profiles of local communities are used to address gaps in health services that impact poverty incidence and magnitude. R: Supply side requirements are not met. A: NNC periodic reports serve as basis for process and target enhancements. R: Force majeure may erode prior health investments in supply-side and human capital. A: Number of pregnant women availing pre & post natal check-ups & live births in health facilities attended and monitored by health professionals. A: DOH provides the information for measuring compliance with DOH protocols

Education component of PDP Social

125

1.2. Percentage of pregnant women availing pre- and post-natal check-ups BASELINE : 52% in Q1 2010 TARGET : 80% in 2016

1.2. DOH Reports/ Facilities Report (NNC); Health Center Records; MHO records

Development Agenda, including education goals in MDGs, has contributed to improved living conditions of poor households. A: Poverty profiles of local communities are used to address gaps in education services that impact poverty incidence and magnitude. R: Force majeure may erode prior education investments in supply-side and human capital. A: Households continue to send their children to school even after program exposure.

126

2. Increased enrolment and attendance rates of children beneficiaries by 2016.

2.1. a. School attendance rates of children aged 3-14 from bottom 20 percent of income distribution (and children aged 3-18) BASELINES: 74.0% in 2008 (and 69.3% for 3-18 years old) TARGETS: 83.8% in 2020 (and 77.3% for 3-18 years old) 2.1. b. Adjusted Net Attendance Rates (for Pre-primary, Primary and Secondary age Children) of Children from Bottom 20 percent of income distribution BASELINES: 22.1% (for Pre-primary); 86.5% (for Primary) and 43.9% (for Secondary) , and Overall 57.9% (for 3-18 years old), in 2008 TARGETS: 36.5% (for Pre-primary), 92.8% (for Primary), and 63.7% (for Secondary) and Overall 70.5% (for 3-18 years old) in 2020 2.2.Proportion of Pantawid children beneficiaries attending school at least 85% of the time BASELINE: 76 % in 2009 TARGET: 95% in 2018

2.1. APIS, PSA

2.2. Pantawid Monitoring

3.2..NNS,FNRI-DOST

R: Lack of daycare centers and high schools. A: Distance to schools is not a factor to low attendance. A: LGUs sustain spending in education through the Special Education Fund. A: Household beneficiaries meet the requirements of national dietary standards(Recommended Energy and Nutrient Intakes). R: High Inflation rate fluctuates and affect food prices in the market, or erode purchasing power of households. A: Households have other sources or income for food expenditure; or other sources of food.

127

3. Improved attitudes on education and health and practices on parenting and active citizenship among beneficiaries by 2018.

3.1Proportion of beneficiaries (among YDS/FDS participants) with adequate attitudes on education and health, and practices on parenting and active citizenship BASELINE: Should be obtained ASAP TARGET: Can be aspirational

Pantawid Monitoring and or IE Studies on FDS/YDS participants

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4 IV. OUTPUTS

1. Poor households have received cash grants for a minimum of five years

1.1. Number of beneficiaries receiving cash grants (disaggregated by sex and by area, and by IP status, by PWD status, and by other segments of vulnerability, such as solo parents, farming/fishing households) 1.2. Number of child-beneficiaries 1.3. Number of grantees, by sex. 1.4. Number of grants-related grievances.

• Implementation Status

Report

A: Cash grants are delivered on time to the beneficiaries. A: External factors such as supply side requirements are fulfilled. A: Households comply with program conditions. A: External factors are controlled or taken into consideration (force majeure) R: Grievances are not redressed; lower entitlement complaints are not resolved within acceptable timeframe. R: Updates on facilities are inadequate or absent. R: Systems-related errors (updates issues, encoded/forwarded but does not take effect) A: Operations Manual is enforced. A: Systems/Field manuals operationalized A: Conduit reports are verified against actual receipt of cash.

129

2. Households fulfilling co-responsibilities

2.1 Compliance Rates Baseline: (in 2008) Education 3-5: 91.65% Education 6-14: 94.12% Health 0-5: 93.97% Pregnant: 78.95% FDS: 95.24% Target: 95% Compliance Based households (2018)

• Grievance Reports

• System Spot Checks

• Feedback mechanisms for

conduits

• NAPA

A: Program contributes to an increased demand for health and education services; profiles will identify local gaps and challenges. A: Database will be used by LGUs or other development agencies for locally-significant social development planning. A: Random checking is in place to ensure updates are reflected. A: Data sharing protocol is in place. A: Frequency of updates is as scheduled. R: Database is not regularly updated due to several factors outside program systems (technology, human error, other logistical challenges) A: Public have access to information. A: Partner agencies (DepED, DOH, DILG, etc) maximize use of data and information, such as harmonization with learner’s ID, PhilHealth ID. R: No integrated QA mechanism available to ensure data integrity.

130

3. Local stakeholders benefit from improved implementation mechanisms in a responsive policy environment

Number of partners ensuring supply in program areas

• Program monitoring

A: Proposed policies are documented and implemented A: Policy recommendations are evidence-based. A: Commitments by participating NGS and LGUs are ensued. A: Assessment of stakeholders commitment is undertaken (i.e. SSA, LGU, etc) A: Policy review process is consultative. A: Policies are culturally sensitive in response to special cases at the community level (i.e. cultural practice affects compliance; hence a policy intervention should be considered) R: Some policies are not evidence-based and misinformed about required policy issues and gaps. A: agencies roll out implementing guidelines of approved policies A: NAC convenes regular meetings according to agreed frequency per year A: NAC TWG reviews policy recommendations.

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5 V. ACTIVITIES

1. Identification of Beneficiaries and Updating of Beneficiary Information 2. Distribution of Cash grants 3. Monitoring of Conditions 4. Obtaining and Addressing Grievances against Program 5. Implementing of Partnerships /Organizational Arrangements

Means • Beneficiary Update

System ; Program Monitoring System

• Logistics

• Compliance Verification System (CVS)

• Grievance Redress System (GRS)

Costs (for 2013) A. TOTAL OPERATING

BUDGET PHP 3839 M

• Training 507 M • Cost of Service

2375 M (BREAK DOWN)

• Advocacy 94 M

• Bank Service Fees 426 M

• Monitoring & Evaluation 67 M

• Admin Cost 370 M

B. EDUCATION GRANTS PHP

20595 M

C. HEALTH GRANTS

PHP 21117 M

GRAND TOTAL: PHP 45551 M

VI.

VII. PRE CONDITIONS

NHTS-PR conducted; PMT conducted Institutional arrangements with partner agencies formulated Sufficient financial resources available for cash grants and logistics Sufficient human resources at DSWD for program implementation

132

Figure 2. Mechanisms by which Pantawid might affect nutritional and welfare status of household-beneficiaries

OU

TC

OM

E

S

UN

DE

RL

YIN

G C

AU

SE

S

PR

OG

RA

MM

E

Pre- and post-natal care for pregnant women (condition)

Health Cash Grant (often to women)

Health visits by children 0-5 yrs old (condition)

Pre-primary and primary participation

Education Cash Grant (often given to women)

attendance in pre-primary or primary school for 3-14 yrs old children (condition)

Household income and women’s control over resources

Household food security: diet quantity and quality

Child Nutrition Household Welfare

Women’s Education (knowledge and awareness)

Feeding and Care practices

Use of Health & Nutrition Services

Participation of parents in FDS and youth in YDS (condition)

attendance in high school for 12-18 yrs old children (condition)

Women’s time

IMM

ED

IAT

E C

AU

SE

S

Secondary participation

Food Nutrient/Intake

Income

Educated Boys and Girls

Education Supply

Health Supply

Employment Health

133

30. Some requirements and processes for the education grants for children-beneficiaries

in high school children will need clarification. High school beneficiaries are supposed to

pass the General Weighted Average (GWA) prescribed by DepED, and/or get promoted

to the next year level (as per Implementing Rules of the NAC Resolutions 12 and 18).

This may need clarification whether this is meant to provide higher expectations (for the

higher incentives for high school), since child-beneficiaries are allowed to repeat a grade

at the primary level.

31. Monitoring of participation in the DepED Alternative Learning System (ALS), or

alternative delivery modes (ADMs) will need clarification. For high school beneficiaries

who opt out of formal schooling and participate in the ALS or ADMs of DepED, the

DSWD will need to define clearly systems for compliance monitoring given that the ALS

and ADMs are less structured than formal schooling.

32. The DSWD will also have to recognize that there are risks that the supply of education

(or health) services are minimal, or that the cash transfers would not be sufficient to

ensure optimal changes in outcomes. There are likely differences in how cash transfers

would affect different types of households, i.e., those with large family sizes, say larger

than five or more children, against those with smaller sizes, or those in rural areas

versus those in urban areas (as there is a higher cost of living in urban areas). In

addition, there has been a lot of empirical research about disparities in education

opportunities and learning outcomes between boys and girls, or between older against

younger children, that have not been taken into account with uniform education grants

of 500 pesos per month for those going to high school, and 300 pesos per month for

those in primary or pre-primary schools. This issue may be far more important to

consider addressing than changing the beneficiary of support in Pantawid from the

household to the family.

D. Further Analytical Results

33. Trends in education (and health) statistics from data sources outside of DSWD need to

be examined. Although this paper is not aimed at conducting a rigorous impact

evaluation of Pantawid (see Chaudhury and Okamura, 2012), it is important to look into

broad trends on various statistics not only to contextualize why government needs to

invest in Pantawid and identify evidence-based targets to make for the program’s

indicators, but also to identify what the program should be watching out for as it

embarks on its expansion (see, e.g., Paqueo, et al., 2013). Various empirical research

examining panel data in the Philippines (e.g., Reyes, et al. 2011b, Albert et al., 2013)

have indicated that the poor consist of transient and persistent poor. Albert et al.

(2013) estimates (using 6,701 panel households surveyed in FIES 2003, APIS 2004, FIES

134

2006, APIS 2007, and APIS 2008) that between 2003 and 2006, around a third of the

poor (7.9%) in 2003 moved out of poverty in 2006, but 8.3 percent of the population in

2003 who were non-poor moved into poverty, thus having poverty rates practically

unchanged at around 25 percent of the population between 2003 and 2006. The

estimated number (13.3 million) of persons that either moved into or out of poverty,

which may be viewed as the relatively vulnerable population, are slightly fewer than the

estimated number (14 million) of persons that were poor in both 2003 and 2006. The

chronic and transient poor will need different interventions, with the chronic poor,

requiring long-term investments in education. The minimal poverty reduction in the

country in the past results not only from vulnerability of households to income poverty,

i.e. the volatility in household income, but also from the lack of adequate targeting

mechanisms to assist the poor and the vulnerable. The latter issue has been addressed

in Pantawid, with the use of the PMT for identifying poor households systematically and

scientifically that will provide a means of helping those who need help the most. In

addition, the program is originally aimed at identifying the persistent poor, the poorest

of the poor, to lessen their chances of remaining poor with household members. The

suggestions to define the “near poor” (Orbeta, etc. ) which subsequently led DSWD to

define a near poor threshold (of 10 percent more than the income poverty threshold) is

a step in the right direction. Albert et al. (2013) observed that non-poor in 2003 with

incomes that dropped in the period 2003 to 2008 did not send their children to school.

It may be important for DSWD to start working on defining specific interventions to help

the near poor.

34. From 2008 to 2011, net school attendance rates for three-to-five year old children, for

primary age children (six to eleven years old), and secondary age children have

increased. Whether we examine net attendance rates, or adjusted net attendance

rates40

using the APIS 2008 and the APIS 2011, we find evidence that Pantawid has

contributed to improved education outcomes (see Table 3). Participation of three to

five year old children at pre-primary schools has increase by 13 percentage points from

around 35% in 2008 to 48%. In 2008, among six-to-eleven years old children, 95.3%

were in school, but only 90.4% were at the primary level (or higher). By 2011, school

participation among primary aged children (six to eleven years old) has gone up to

97.1%, with 93.4% of six to eleven year old children at the primary level or higher.

Among children aged twelve to fifteen, about 9 in 10 (89.6%) of children were in school,

seven of whom (66.2%) are at the secondary level (or higher) in 2008. By 2011, 91.6

percent of children aged 12 to 15 were in school, with 81.1 percent at the secondary

40

Adjusted net attendance rate is the ratio of the number of children in an age range that attends the proper education tier (or higher) relative to the number of children of the school-age range.

135

level or higher. Defining out of school children (OOSC) as five year old children not in

school, and children between six to fifteen not in the primary level (or higher), a report

on Out of School Children (OOSC) 41

prepared by PIDS (2012) for UNICEF and DepED that

examined APIS data suggests that in school year 2008-2009, there were an estimated

number of 2.9 million OOSC. This number has gone down to 1.4 million OOSC for

schoolyear 2011-2012.

Table 3. Net School Attendance Rates in 2007, 2008 and 2011 by Age Group Age Group 2007 2008 2011

Pre-primary Age (3- 5 Years Old) 35.5 34.8 47.8

Primary Age (6 to 11 years old)

94.4 (89.8

a)

95.2 (90.8

a)

97.1 (93.4

a)

Secondary Age (12 to 15 years old)

88.5 (65.8

a)

89.6 (66.3

a)

91.6 (66.3

a)

Source: APIS 2007, 2008, 2011 Notes:

a adjusted net attendance rates (ANAR) is the ratio of the number of children in an age range that attends the proper education tier

(or higher) relative to the number of children of the school-age range

35. The cash grants in Pantawid need re-examination. Uniform education cash grants of

300 pesos per child beneficiary (currently for ECCT beneficiaries in pre-primary and

primary school, and 500 pesos per ECCT high school beneficiary) does not address the

disparities in school participation, especially between older secondary age children (and

younger ones), and between boys and girls. In addition, the generosity of the cash

grants in Pantawid has already been eroded by inflation, and thus needs adjustment.

36. Disaggregated data between the bottom 40 percent and the upper 60 percent of per

capita income distribution shows that there have been disparities between the

education outcomes of poor and non-poor households. As Table 4 show, in 2008, the

proportion of children attending school is much higher among the non-poor (i.e. those

at the upper 60 percent of per capita income distribution) than among those at the

lowest 40 percent of income distribution. By 2011, while the disparity between net

attendance rates of the poor and non-poor continue, the disparity has narrowed,

especially among pre-primary and primary age children. Among primary-age children, in

particular, where school participation has been relatively high even in 2008,

participation in 2011 is nearing the Millennium Development Goals Target to have all

primary-aged children in school, even among the poor. In addition, it must be pointed

out that more and more children are going to school at the expected education tier, i.e.

there are fewer children in school in 2011 (than in 2008) who are over-age for their

41

Out of school children refer here to (a) five year old children who are not in preprimary or primary school; (b) children of primary-school age (6 to 11) who are not in primary school or secondary school; and (c) children of secondary-school age (12-15) who are not in primary school or secondary education.

136

education level, which seems to be an unintended benefit resulting from the

investments made in Pantawid.

Table 4. Net School Attendance Rates among Poor and Nonpoor Household in 2008 and 2011 by Age Group

2008 2011

Age Group Bottom 40

percent Upper 60 percent

Bottom 40 percent

Upper 60 percent

Pre-primary Age (3- 5 Years Old) 25.0 44.9 44.4 52.8

Primary Age (6 to 11 years old)

92.7 (88.4

a)

98.0 (93.4

a)

96.1 (92.0

a)

98.7 (95.5

a)

Secondary Age (12 to 15 years old)

84.3 (53.5

a)

94.6 (78.3

a)

88.0 (72.8

a)

96.2 (91.8

a)

Source: APIS 2008, 2011 Notes:

a adjusted net attendance rates (ANAR) is the ratio of the number of children in an age range that attends the proper education tier

(or higher) relative to the number of children of the school-age range

37. Reasons for non-attendance in school vary by age, with lack of interest being the

predominant reason for primary and secondary age children, and economic reasons

reported to be a major reason among older secondary age children. Table 5 list the

reasons for non-attendance in school in 2007, 2008 and 2011. Most pre-primary school

age children are not in school because they are thought of as being too young for

schooling, which suggests the need for greater advocacy campaigns for early childhood

education. Among primary-age children as well as among secondary age children who

are not in school, half are reported to lack interest, which Albert et al. (2014) suggests is

strongly related to low educational attainment of mothers. The FDS, if done well, can

address lack of parental capacity to support their children’s education. Among

secondary age children, a third are not in school for economic reasons such as the cost

of education and the need for employment (especially among older secondary age

children from poorer households). In consequence, the ECCT should help improve

school participation for secondary age children.

Table 5. Reason for Nonattendance in School, by Pre-Primary, Primary and Secondary School-Age: 2007, 2008, and 2011.

Reason for Nonattendance

Pre-primary Age (3 to 5 years old)

Primary Age (6 to11 years old)

Pre-primary Age (12 to 15 years old)

2007 2008 2011 2007 2008 2011 2007 2008 2011

Lack of personal interest or Cannot cope with schooling 2.17 2.54 7.78 27.61 34.66 54.91 46.83 48.95 53 High cost of education

1.82 1.38 1.59 13.09 11.72 10.42 25.15 24.88 23.77 Too young to go to school

92.88 93.07 86.26 33.65 28.7 2.24 0.19 0.73 0 Illness/disability

0.25 0.34 0.59 8.24 9.68 15.14 5.92 6.18 7 Lack of nearby schools

1.85 1.61 2.02 8.49 7.47 8.16 4.15 4 2.63 Employment

0.05 0.03 0.12 0.32 0.13 0.58 7.37 8.75 7.08 Other reasons (e.g., school records, marriage*, housekeeping) 0.98 1.03 1.64 8.6 7.64 8.55 10.39 6.51 6.52

Source: APIS 2007, 2008, 2011

137

38. The extension of Pantawid to cover children aged up to 18 years old is a promising

pathway to further bridge the gap in education outcomes between the poor and non-

poor, improve future social mobility for children from poor households, and thus

increase prospects for inclusive growth and prosperity. The literature shows that

returns to schooling are larger for completing high school. However, this heavily

assumes that supply-side requirements in the basic education sector are met. Figure 3,

generated from a DepED mapping exercise of elementary and high schools42

throughout

the country, shows that while there are many primary schools across the country, with

practically one in every barangay, this is not the case for secondary schools.

(a) (b)

Figure 3. Barangay Mapping of (a) Elementary Schools and (b) High Schools in the country

39. Among children aged 12 to 18 who are not in school, there appear to be supply side

challenges. Combining information on the availability (or lack thereof) of high schools in

each barangay sourced from data gathered by the PSA for Form 5 of the 2010 Census of

Population and Housing (CPH) on barangay facilities, as well as the DepED mapping

exercise, which was further completed with the addition of Philippine Standard

Geographic Codes (PSGC) of the barangays, as well as results of the APIS 2011, we

estimate that about 816 thousand children aged 12-18 years old belong to the bottom

40 percent of income distribution who were not in school in 2011, and who have

finished grade school but not high school. Table 6 shows that about 63% of these

42

As of June 13, 2014, the DepEd has managed to provide the geo-locations of 6856 public high schools out of the total 7913 high schools in the country (86.6%). These however only had geo-codes without the Philippine Standard Geographic Codes (PSGC) that are necessary enable merging of such information with microdata of surveys and other databases generated by the PSA.

138

children are residing in barangays without high schools. More than seven out of every

ten such children run into supply side issues is highest in Eastern Visayas (86.2%), Ilocos

(78.5%) ARMM (71.7%), Bicol (71.2%) and Western Visayas (70.6%).

Table 6. Distribution of 12-18 year old children from the bottom two income quintiles currently not attending school, who have finished at least grade school but not high school, by region, by urban/rural residence, and by presence or absence of high schools in barangay, 2011

Source: merged information from APIS 2011, CPH 2010 (conducted by PSA) and 2014 DepED school mapping

40. Rural areas have the most supply side challenges for availability of high schools. It can

be noticed from Table 4 that in practically all regions, except for Ilocos, the “likely” high

school aged child-beneficiaries of Pantawid have higher risks of not having a high school

in the barangay where they reside, if they are from the rural areas. In addition, merged

information from the 2010 CPH barangay facilities data and the 2011 APIS, suggests that

of an estimated 500 thousand children aged 12-18 from the bottom 20 percent of

income in distribution, who were not in school in 2011 & live in barangays without a HS,

about two fifth (38.4%) would need to travel more than 5 kms to the nearest high

school. A big bulk of these children are in rural areas (Figure 4).

Region With high schools in barangay Without high schools in barangay

Urban Rural Total Urban Rural Total

Region I - Ilocos Region 1299 5549 6848 5876 19128 25003

Region II - Cagayan Valley 3348 6691 10039 3353 14839 18193

Region III - Central Luzon 13646 15072 28717 24088 38921 63010

Region V- Bicol 8139 14369 22508 7230 48463 55693

Region VI - Western Visayas 4252 13612 17864 6329 36479 42807

Region VII - Central Visayas 14187 21051 35238 6427 24177 30604

Region VIII - Eastern Visayas 3125 5507 8633 6968 47055 54022

Region IX - Zamboanga Peninsula

3874 15629 19503 2246 22851 25097

Region X - Northern Mindanao

7356 13582 20939 3182 23249 26431

Region XI – Davao 5481 9321 14802 937 20704 21641

Region XII – SOCCSKSARGEN

10449 17408 27857 718 15093 15811

National Capital Region 18947 18947 15221 15221

Cordillera Administrative Region

2247 2563 4810 180 5742 5922

Autonomous Region in Muslim Mindanao

3404 10558 13962 5564 29887 35451

Region XIII – Caraga 4894 7444 12339 1358 13231 14590

Region IVA – CALABARZON 15547 10818 26364 8080 32536 40615

Region IVB – MIMAROPA 3096 9069 12165 5779 18402 24181

Total 123292 178243 301535 103534 410757 514290

139

Figure 4. Distribution of 500,000 children aged 12 to 18 years old from the bottom quintiles and who finished grade school but not high school, residing in barangays with no high schools, by distance to nearest high school, 2011

41. In consequence, there ought to be some extra measures that DSWD will have to

consider to further assist Pantawid child-beneficiaries in going to the nearest high

school, which may be quite a distance from his/her residence, especially in rural areas.

While there are current efforts to expand access to high schools in the country, but this

will clearly take time and is likely to involve a lot of costs as it also involves hiring of

teachers, which may be in short supply, among others. It may be important to allow

these child beneficiaries to enrol instead in the alternative learning systems (ALS), or

alternative delivery modes (ADMs) of DepED, there will be a need to examine the

corresponding compliance monitoring for such modes. It will be important to look into

providing extra incentives (whether a transportation allowance, or even a one-time non-

cash incentive like a bicycle) for child-beneficiaries of high school-age (i.e. at least 12

years old) who are eligible to go to high school in rural areas, especially where supply

side deficits are most challenging such as . See Muralidharan and Prakash (2013) for a

discussion of the bicycle program in the Indian state of Bihar for increasing school

attendance of girls in high school.

42. Provision for higher than usual Pantawid cash incentives should be similarly provided,

for boys to address gender disparities in school participation, as well as for older

children to address the disparities between older (and younger) children whose

opportunity costs for going to school and staying in school are higher. The disparity in

0 50,000 100000 150000 200000persons

Rural

Urban

don't know

5 kms or more

more than 2 kms but less than 5

2 kms or less

don't know

5 kms or more

more than 2 kms but less than 5

2 kms or less

140

adjusted net attendance rates across ages, and between boys and girls of the same age,

is shown in Figure 5. School attendance is in favor of girls across ages, with the disparity

very pronounced among secondary school age children. School attendance rates are

also considerably lower among 12 to 15 year old children than among 8 to 11 year old

kids. Although net attendance rates have improved from 2008 to 2011 per age, the

disparities between 12 to 15 year old children and 8 to 11 year old children as well as

between boys and girls, particularly among secondary-age children, persists and needs

to be addressed by providing for extra cash incentives. While the current cash incentive

for high school beneficiaries is substantially higher (500 pesos) than pre-primary and

primary school beneficiaries (300 pesos), there is currently no difference in cash

incentives for boys and girls.

Figure 5. Adjusted Net attendance rates among children aged 3 to 15 years old, by age and by sex, 2007, 2008 and 2011. [Note: Sourced from APIS data]

43. Extra cash incentives for boys, especially in the secondary level, are suggested to

address gender disparities. In Mexico’s CCT, additional cash provisions for females were

provided a decade ago, when girls were at a disadvantage in terms of educational

participation, and for children nearing the last stage of the education cycle, which led to

a considerable bridging of the gender divide in Mexico. Boys and older children who are

covered by Pantawid should be given additional cash incentives to encourage their

school participation and to put off their involvement in work activities. Pilot of such

02

04

06

08

01

00

0 5 10 15AGE

2011 Adjusted Net Attendance Rate (Boys vs Girls)



2011 Adjusted Net Attendance Rate (Both Sexes)

141

extra incentives may be undertaken soonest, and will further deepen the impact of

school participation, particularly promote more inclusive education. Table 7 provides

estimates of extra costs for education cash grants based on two scenarios involving the

provision of (a) 350 pesos per month for grade VI students and 600 pesos per month for

fourth year/grades 10-12 students; (b) 350 pesos per month for grade VI students, 550

pesos per month for boys 1st

-3rd

year/grades 7-9; 550 pesos per month for girls fourth

year/ grades 10-12; 600 pesos per month for girls fourth year/ grades 10-12. The first

scenario is meant to improve school completion and cohort survival rates, while the

second scenario builds on the first scenario but introduces also extra cash for boys in

the secondary level.

Table 7. Estimated Extra Costs for Additional Education Cash Grants Year Scenario A Scenario B

2015 312,642,450 601,702,300 2016 909,991,170 1,269,053,990 2017 1,275,305,205 1,596,470,970 2018 1,558,287,165 1,825,186,005 2019 1,697,197,065 1,916,588,025 2020 1,777,117,800 1,946,666,155 2021 1,702,344,690 1,838,869,695 2022 1,612,201,260 1,672,872,220 2023 1,557,228,000 2,058,699,140 2024 1,467,371,400 1,318,152,445 2025 1,249,656,300 1,076,608,190 2026 900,625,200 766,640,550 2027 525,398,400 447,242,600 2028 201,993,000 171,836,275 2029 37,446,000 31,800,725 2030 16,850,700 15,057,495

44. While the attempt of DSWD to shift beneficiaries from households to families may

have its use, the costs for this transition are serious in system updates. There certainly

is some value in shifting Pantawid beneficiaries from households to families 43

especially

as some poor households have more than one nuclear family, but there are operational

complexities in making this transition. Estimation of the number of families per

household is challenging. Table 8 shows that the distribution of persons in the APIS and

43

The UN Statistics Division (http://unstats.un.org/unsd/demographic/sconcerns/fam/fammethods.htm ) points out that a household is a group of persons living together who make common provision for food or other essentials for living; the persons in the household may pool their incomes and have a common budget to a greater or lesser extent; they may be related or unrelated persons or a combination of persons both related and unrelated. A family, on the other hand, is defined as those members of the household who are related, to a specified degree, through blood, adoption or marriage.

142

Pantawid databases, by relationship to the household head. If we count the number of

household heads together with everyone in the household who is neither a spouse of

the head, a child of the head, a parent or a grandchild of the head, in relation to the

household heads, we can get a proxy of the number of nuclear families per household.

The Pantawid database also includes information on the reported number of families

per Pantawid household, whose average is 1.18, with the NHTS-PR team providing an

initial estimate that was much higher. Counting nuclear families per household is

problematic. A shift from families to households can also lead to serious operational

challenges in system modification. In addition, this shift can be the subject of abuse.

The complexities in identifying households with more than one nuclear family,

performing verification and conducting system modification may have costs that far

outweigh the benefits of doing so.

Table 8. Distribution of Persons by Relationship to Household Head, by Data Source. APIS 2011 DSWD

Pantawid Databases

Relation to Household Head

Poorest Quintile

Lower Middle Quintile

Middle Quintile

Upper Middle Quintile

Richest Quintile

All Pantawid households

Head 17.17 20.12 22.42 24.1 28.69 17.03 Wife/Spouse 14.22 15.42 15.91 15.48 15.27 15.37 Son/Daughter 55.45 48.21 43.65 40.65 37.25 59.75 Brother/Sister 0.6 0.92 1.18 1.69 2.2 0.39 Son in law/Daughter in law 1.77 2.46 2.96 3.09 2.49 0.86 Grandchild 7.89 9.23 9.53 9.31 7.5 4.27 Father/Mother 0.56 0.67 0.71 0.77 0.88 0.55 Other Relative 2.34 2.98 3.64 4.9 5.72 0.91 Boarder 0.01 Domestic Helper 0.01 Non-relative 0.83 Guardian 0.01 Unknown (Missing Data) 0.02 Total 100.00 100.00 100.00 100.00 100.00 100.00

Memo Note:

Estimate of average number of nuclear families per household 1.27 1.32 1.35 1.40 1.36 1.18 Sources: APIS 2011 and DSWD Pantawid database

45. The extension of support to high school beneficiaries clearly deepens the impact of

the expected outcomes of human capital investment in Pantawid, and further

deepening would result from improved monitoring activities, and from increasing the

support for older children to encourage school completion, and for boys to address

143

gender disparities in school outcomes in favor of girls. In isolation, Pantawid will not be

enough to reduce poverty in the short term, but the attempt to incentivize the poor to

make investments in their human capital will need to be further improved since inflation

has eroded on the generosity of the cash grants. Improvements will need to be made in

communicating the expected outcomes of the program, in providing quality FDS and

YDS, in implementing spot checks especially for monitoring the cash grants, and in

providing differentiated incentives to address disparities between younger and older

children, and between boys and girls (especially in the secondary level). This way,

Pantawid can contribute to the government’s attempt to ensure that no one, whether

poor or nonpoor, male or female, is left behind as the country pursues a path of growth,

prosperity and development.

144

References Albert, J. R. G., Dumagan, J. and, Martinez, A., (2014). Inequalities in Income, Labor and Education: The Challenge of Inclusive Growth. PIDS Discussion Paper to be released in January 2015. Philippine Institute for Development Studies. Chaudhuri, N., Friedman, J. and Onishi, J. (2013). Philippines Conditional Cash Transfer Program Impact Evaluation 2012. Washington, DC, World Bank. . (Available in the Internet http://pantawid.dswd.gov.ph/images/philippines_conditional_cash_transfer_program_impact_evaluation_2012.pdf Last Accessed November 30, 2014) Chaudhury, N. and Okamura, Y. (2012). Conditional cash transfers and school enrolment: Impact of the conditional cash transfer program in the Philippines. Philippine Social Protection Note No. 6 (July). Washington, D.C.: The World Bank. Fiszbein, A., Schady, N. (2009). Conditional Cash Transfers, Reducing Present and Future Poverty, The World Bank, Washington, D.C. (Available in the Internet https://openknowledge.worldbank.org/bitstream/handle/10986/2597/476030PUB0Cond101Official0Use0Only1.pdf?sequence=1 Last Accessed July 30, 2014). Fernandez, L. (2007) “Technical Note on Estimation of a Proxy Means Test Model (PMT) for Conditional Cash Transfer (CCT) Pilot Program in the Philippines” prepared for the Department of Social Welfare and Development (DSWD), Philippines. Fernadez, L. (2012), “Technical Note on Estimations of Proxy Means Test Model (PMT) of the National Household Targeting System for Poverty Reduction (NHTS-PR) with latest household surveys: FIES-LFS 2009 in the Philippines” prepared for the World Bank, Manila and the DSWD, Philippines. David, C. and Albert, J. R. (2012). Primary Education: Barriers to Entry and Bottlenecks to Completion. Discussion Paper Series No. 2012-07. Philippine Institute for Development Studies. (available in the Internet at http://dirp3.pids.gov.ph/ris/dps/pidsdps1207.pdf Last Accessed August 30, 2014 ) Muralidharan, K. and Prakash, N. (2013). Cycling to School: Increasing Secondary School Enrolment for Girls in India. Working Paper 19305. National Bureau Of Economic Research. (available in the Internet at http://www.nber.org/papers/w19305.pdf Last Accessed August 30, 2014 ) Gertler, P. J., Martinez, S., Premand, P. , Rawlings, L. B., Vermeersch, C. M. J.. (2011). Impact Evaluation in Practice, World Bank. Manasan, R. (2009). Reforming Social Protection Policy: Responding to the Global Financial Crisis and Beyond. Discussion Paper Series No. 2009-20. Philippine Institute for Development Studies. (available in the Internet at http://dirp4.pids.gov.ph/ris/dps/pidsdps0922.pdf Last Accessed July 30, 2014 ) Orbeta, A. (2011). Social Protection in the Philippines: Current State and Challenges. Discussion Paper Series No. 2011-02. Philippine Institute for Development Studies. (available in the Internet at http://dirp4.pids.gov.ph/ris/dps/pidsdps1102.pdf Last Accessed July 30, 2014 ) Paqueo, V., Orbeta, A, Castaneda, T., and Spohr, C. (2013). After Five Years of Pantawid, What Next? Discussion Paper Series No. 2013-41. Philippine Institute for Development Studies. (available in the Internet at http://dirp3.pids.gov.ph/ris/dps/pidsdps1341.pdf Last Accessed July 30, 2014 ) Reyes, C., Tabuga, A., Mina, C., Asis, R. and Datu, M. B., (2011a). Dynamics of Poverty in the Philippines: Distinguishing the Chronic from the Transient Poor. Discussion Paper Series No. 2011-31. Philippine Institute for Development Studies. (available in the Internet at http://dirp4.pids.gov.ph/ris/dps/pidsdps1131.pdf Last Accessed August 30, 2014).

145

Reyes, C., Tabuga, A., Mina, C., Asis, R. and Datu, M. B., (2013). Pantawid Pamilyang Pilipino: Why “deepening” matters in achieving its human capital objectives PIDS Policy Notes No. 2013-02. (available in the Internet at http://dirp3.pids.gov.ph/ris/pn/pidspn1302.pdf Last Accessed August 30, 2014). Villar, F. R. (2012). The Philippine Social Protection Framework And Strategy: An Overview. Proceedings of the 12th National Convention on Statistics (NCS). (Available in the Internet http://www.nscb.gov.ph/ncs/12thncs/papers/INVITED/IPS-09%20Social%20Protection%20Statistics/IPS-09_3%20The%20Philippine%20Social%20Protection%20Framework%20and%20Strategy_An%20Overview.pdf Last Accessed July 30, 2014).

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ANNEX A

Figure A-1. Original Results Framework

147

Table A-1a. Original Output Indicators, Baseline and target.

Output Indicators Baseline Target

1. Poor Households have received cash grants for a minimum of five years

• Number of beneficiaries

receiving cash grants

• Percentage decrease in

grants-related grievances

• Percentage increase in

compliance

• Indicators on gender and IPs

(96% female grantees)

• Percentage increase in

number of IP beneficiaries to

indicate greater geographic

scope

0 households

(2008)

95%

compliance-

based

households

(2018)

2. Program areas--

barangays,

municipalities, cities,

provinces and regions

--- have updated and

relevant profiles for

development planning

• Trends in compliance per set

and area

• % increase in population of

household beneficiaries per

area

• Number of grantee

disaggregated by sex and area

• Number of children

beneficiaries disaggregated by

sex

• Number of IP beneficiaries

• Number of PWD beneficiaries

• Number of solo parent

beneficiaries

• Number of farming/fishing

beneficiaries

• Number of eligible versus

assessed poor per are

Pilot areas with

data on

indicators

(2008)

Latest set with

data on

indicators

(2018)

3. Local stakeholders

benefit from improved

implementation

mechanisms in a

responsive

environment

• Positive local perception

toward government

interventions against

corruption, illicit

electioneering and

misbehaviour of beneficiaries

• Number of evidenced-based

policy enhancements related

to evaluation/spotcheck

findings

• % of approved policies with

corresponding guidelines to

address grievances and other

NAC resolution

on

Implementation

Policies (2010)

Number of

implemented

policies for

program

enhancement

(2018)

148

issues related to program

implementation

• Number of action plans based

on approved policies

• Number of relevant

publications to highlight

program innovations and

accomplishments

149

Table A-1b. Original Outcome Indicators, Baseline and target.

Outcome Indicators Baseline Target

Outcome 1: Sustained access of program beneficiaries to preventive health care services by 2018.

• % increase of children availing

preventing health care such as

deworming (see Policy Output

for special cases), vitamin A,

and immunization

0-5 yrs old

undergoing

growth

monitoring and

check-ups – 63%

(2009)

87% (2018)

• % increase of pregnant

women availing pre-and post-

natal check-ups

Pregnant

women availing

pre-and post-

natal check-ups

52% (based on

compliance rate

Q1 2010)

77% (2018)

Outcome 2: Sustained gross enrolment and attendance rates of children beneficiaries by 2018.

• % increase

enrolment/participation rate

of children aged 3-5 and 6-14

• % attendance rate 3-5 and 6-

14

76% of children 6-14 yrs and number of children 3-5 years old attending school at least 85% of the time (2009)

254,000 Filipino working children, permissible and not considered child labor, are not attending school

2.993 million exposed to hazardous child labor (NSO 2011)

95% children 3-5 and 6-14 yrs old attending school at least 85% of the time (2018) Reduced number of reported cases of hazardous child labor by 2015 (relative to the target of 893,000 Filipino children as a convergence program of the PH government led by DOLE); we can set 15-25% as target based on Mexico

150

CCT. No available data since attendance was not required among day care children prior to Pantawid (2009)

Outcome 3: Food

consumption per


requirements of

pregnant women and

children beneficiaries

by 2018.

• % increase in production of

major food group

consumption (available data:

rice, fruits and vegetables) by

consumption

• % increase in the ratio of

household food expenditure

to total basic expenditure

versus national and regional

averages

Family

expenditure for

food is 42.6%

(2009)

Average

household

consumption

of major food

group items

between

municipal

average and

total dietary

energy

requirement

19% increase

in spending of

beneficiaries

on food

151

ANNEX B Figure B-1. Theory of Change for Pantawid

153

ANNEX C How to Set Targets for Project Indicators?

A. Introduction

1 Once project indicators are identified to help gauge progress in achieving project goals, the desired

value of the indicator, i.e., a target, by the end of the project will need to be defined. A target may be

viewed as a commitment to achieve specified results (as viewed from a statistical indicator) within a

predefined time period, typically by the end of project lifetime. Clear and explicit targets for indicators

of a project play a role in identifying priority actions on the direction or re-direction of resource

allocation. Targets also play a role in strengthening accountability, since they provide benchmarks

against which project performance can be assessed.

2 While target setting is an aspirational exercise based on an understanding of what would be

considered a success of the intervention at the end of the project, targets cannot be purely

aspirational, especially as they can lead to a lot more challenges explaining why a project might be

doing well even if the project is not meeting or falling behind targets. Thus, targets in a project need to

be also firmly grounded on reality. Toward this end, baseline data, historical trajectory of the indicator,

or other patterns in available data on the indicator or a proxy indicator, can be examined to set targets.

But more importantly, the setting of targets should also undergo a process of discussions and

agreements among the project team, and even with stakeholders.

3 Targets specify directional changes in indicators, either in absolute terms (e.g., household income

increases 10 thousand pesos by 2020 from baseline data of project beneficiaries’ household income),

or in relative terms (e.g., household income increases 10 percent by 2020 from levels for bottom 20

percent of income distribution in 2000). The targets can describe changes from benchmark figures,

expected levels, or the changes can even be tied to a threshold. The way a target is expressed can

depend on the nature of the data, the indicator, and the project’s objectives.

4 Note, however, that setting targets for project indicators is not a pure science, since the relationship

between project resources and end results is not quite straightforward. Targets are specific to an

indicator, and these targets can vary according to the level of certainty and predictability of the

phenomenon being measured. In this annex note, we describe the justification for the proposed

targets for the chosen indicators in Table 2.

B. Targets for Overall Goal/Impact

5 The three indicators for the overall goal/impact on empowered, self-sufficient and productive

Pantawid Pamilya households by 2020 pertain to income, employment and community participation.

6 For the first indicator (i.e., the average income gap of Pantawid households), the baseline for 2009, (as

indicated by Velarde and Fernandez, 2011) for Set 1 and Set 2 Pantawid Households was identified at

34.1%. Velarde and Fernandez, 2011, simulated that increase in income from the cash grants would

bring down income gap to 29.3% (from the previous cash grants).

7 The PSA reports that in the period 2006-2009, income gap throughout the country decreased from

27.5% in 2006 to 26.2% in 2009 or 0.43% per year. However, despite the CCT, income gap remain

unchanged from 26.2% in 2009 to 26.2% in 2012. The PSA also reports that for the first semester of

154

2006, income gap was measured at 30.1%, while for the first semester of 2009, 2012, and 201344

,

income gap was estimated at 29.0%, 29.2%, and 27.4%, respectively, or about 0.39 percentage point

decline per year from 2006 to 2013. Thus, if we were to use a 0.45 percentage point decline per year

from 2009 baseline figures (of 34.1%) for the income gap of Pantawid households, we would expect

that by 2020, these figures would go down to 28.7%. Note that the only way to verify this target would

be to use the original proxy means test model to predict incomes on the Pantawid Set 1 and Set 2

households (all of them, or even a random sample) in an end-of-project assessment exercise. Even for

the upcoming Listahanan, this may also be done to see whether incomes have improved but using the

original proxy means model, as otherwise changes in income and income gap may be on account of the

change in PMT methodology.

8 The second indicator suggested (i.e. the number of households participating in local decision-making

structures/processes such as community assemblies and barangay councils) is meant to measure the

empowerment goal, with the assumption that some benchmark figure may have been generated, even

in an Impact-Evaluation (IE) Study, and that a future IE study would be able to assess this behavioral

change. Here, because of the lack of information on “trends”, no target is specified. However, if a

benchmark figure of say, 10% is obtained, and an aspirational target of 20% may be set by the project

team.

9 As regards the third indicator (i.e., the proportion of unpaid family workers and own-account workers

as a percentage of total employment), the baseline figures from the Labor Force Survey are at 43.5%

in 2008, and this indicator has reached 39.8% in 2012, or a decline of 0.925 percentage points per year.

Assuming an overall decline of 0.95 percentage points per year from the baseline, we would expect

that by 2020, the indicator could fall to 32.1%.

C. Targets for SO1

10 The four indicators for Specific Objective 1 (SO1) to contribute to government's efforts to break

intergenerational poverty pertain to income and non-income poverty indicators.

11 The first indicator, on the subsistence poverty rate, has a baseline of 10.9% in 2009 (according to the

PSA estimate from the FIES). This slightly went down to 10.4% in 2012, a mere 0.17 percentage points

per year. For the first semester alone, subsistence poverty was estimated at 13.3% in 2009, while in

2013, it was estimated at 10.8%, yielding a decline of 0.625 percentage points per year. Assuming a

reduction of 0.3 percentage points per year, we would expect a reduction of 2.7 percentage points

from the 10.9% in 2009 by 2018 to 8.2%.

12 The second indicator, the poverty gap ratio, has a baseline of 5.4% in 2009 (as estimated by the PSA

from the FIES). This decreased (insignificantly) to 5.1% in 2012, or a 0.1 percentage point reduction per

year, while again for the corresponding first semester figures, we find a reduction of 0.35 percentage

points per year from 6.6% in the first half of 2009 to 5.2% in the first half of 2013. Assuming a 0.2

percentage point reduction per year from the baseline figures, we can target reduction of 1.8

percentage points from the 2009 levels by 2018 to 3.6%.

44

This estimate is based on APIS 2013, which used a modified income module based on the FIES. Technically, this is not fully comparable with estimates based on the FIES for 2006, 2009, and 2012.

155

13 As regards the third indicator, (i.e. the infant mortality rate), baseline figures in 2008, according to the

NDHS, are estimated at 25 deaths per 1,000 live births. In 2013, the figures have been estimated at 23

deaths per 1,000 live births, a reduction of 0.4 deaths per year. Assuming a reduction of 0.5 deaths per

year from 2008 to 2018, we would expect 20 deaths per 1,000 live births in 2018.

14 Regarding the fourth indicator, (i.e. the proportion of unplanned pregnancies), baseline figures are

estimated at 37% in 2008, a reduction of 7 percentage points from the 2003 levels of 44%. Assuming

that in ten years, there would be a less tempered reduction of 10 percentage points, since

improvements may be more challenging to achieve in time, we would expect the proportion of

unplanned pregnancies at 27%.

D. Targets for SO2

15 The two indicators for Specific Objective 2 (SO2) on accumulating human capital pertain to years of

schooling and functional literacy.

16 For the first indicator, i.e. the average number of school years completed among 15-24 years old in

bottom 20 percent of wealth/income distribution, the APIS 2008 identifies this indicator as 6.2 years,

whereas the corresponding 15-24 years old in the middle 20 percent have an average of 6.8 years of

schooling.

Per Capita Income Quintile

Average Years of Schooling of 15-24 years old

Poorest 6.2 Second 6.6

Third 6.8

Fourth 7.1 Richest 7.4

Total 6.7 Source: 2008 APIS, PSA.

17 By 2020, with the high school expansion of Pantawid, we would aspire to bring the bottom 20 percent

to the levels of the middle 20 percent, with extra years of schooling from K-12, to a target of 8.8 years

of average years of schooling.

18 According to the 2008 Functional Literacy, Education and Mass Media Survey (FLEMMS), the functional

literacy rate among bottom 30 percent of wealth distribution was 75.1% in 2008, while the next 30

percent of wealth distribution had a functional literacy rate of 87.7%. By 2018, we would expect the

poor (of 2008) to reach the functional literacy rate of the “average” of the wealth distribution in 2008.

E. Targets for Outcomes

19 Outcome 1 pertains to increased use of preventive health care services in accordance with DOH

protocols by program beneficiaries in 2016. Two indicators have been identified for monitoring this

outcome, viz., the percentage of children availing preventive health care such as deworming, vitamin

A, and immunization; as well as the percentage of pregnant women availing pre- and post-natal check-

ups. Baseline for these indicators were 63% in 2009, and 52% in the second quarter of 2010,

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respectively. Aspirational targets of 90% and 80% have been developed by 2016. Currently,

compliance rates are being monitored monthly, seem to be way over these targets, but strictly

speaking, comparability may be an issue, since the number of being monitored is not the same

throughout the year, and may involve additions (to the program), and deletions (from lack of

compliance).

20 Outcome 2 is increased enrolment and attendance rates of children beneficiaries by 2016. Enrolment

rates of the poor can be proxied by the proportion of children among the bottom 20 percent of income

distribution who are attending school, and by an adjusted net attendance ratio that only counts

attendance in the schooling system appropriate for the specific age of the child. Baseline data (in

2008) can be determined from the APIS 2008. It would be realistic to aim for having the poorest 20

percent achieve outcomes of the middle income quintile by 2020.

Education Indicator

Poorest 20 percent

Lower Middle 20 percent

Middle 20 percent

Upper Middle 20 percent

Richest 20 percent Total

Attendance rates of children aged 3 to 14 74.0 79.2 83.1 86.5 88.5 80.9 Attendance rates of children aged 3 to 18 69.3 73.8 77.3 82.2 88.0 76.7 Adjusted Net Attendance Rates

3-5 years old 22.1 28.8 36.5 44.4 56.5 34.8 6-11 years old 86.5 90.7 92.8 94.0 93.7 90.8 12-18 years old 43.9 55.4 63.7 72.8 84.4 62.0 Total (3-18 years old) 57.9 65.1 70.5 76.1 82.9 68.6 Source: APIS 2008, PSA

21 Another indicator for Outcome 2, that can be sourced from PMO, is the proportion of beneficiary

children (aged 6-14 yrs old or 6-18 yrs old) attending school at least 85% of the time. Baseline figures

in 2009 are 76%, and by 2018, an aspirational target of 95% may be do-able, especially with current

monitoring suggesting this is already more or less being achieved.

22 Outcome 3, i.e., Improved attitudes on education and health and practices on parenting and active

citizenship among beneficiaries, may be monitored and evaluated with the proportion of beneficiaries

(among YDS/FDS participants) with adequate attitudes on education and health, and practices on

parenting and active citizenship. There may be two specific indicators, one for YDS participants, and

another for FDS participants, that could be monitored. There ought to be a diagnostic for measuring

whether or not these participants have “adequate” attitudes, to serve as baseline, with aspirational

targets developed accordingly.

157

TA 7733-PHI: Support for Social Protection Reform

Final Report on the Social Welfare and Development

Indicator1

Romulo A. Virola, ADB Consultant

July 2014

1 The assistance of the officials and employees of the Department of Social Welfare and Development particularly Undersecretary

Florita R. Villar, Director Rhodora Alday and Ms. Millete Santos of the Policy Development & Planning Bureau, and Christopher S. Pohr of the ADB, including on technical matters is gratefully acknowledged. Also acknowledged is the assistance of the Consultant’s Team: Jessamyn O. Encarnacion, Bernadette B. Balamban, Mechelle M. Viernes, Anna Jean G. Casañas, Joseph Albert Nino M. Bulan, Andrea C. Baylon and the three Research Assistants: Andrea S. Morales, Noel S. Nepomuceno, and Albert A. Garcia.

158

TABLE OF CONTENTS

List of Acronyms 1. Introduction 2. Literature Review 3. The Existing Social Welfare Indicators (SWI) and the SWI Toolkit 3.1 The Indicators, Data Sources, and Operationalization of the Existing SWI/SWI

Toolkit 3.2 Some Issues and Concerns 4. Methodology 5. Assessment of the Existing SWI and the SWI Toolkit: Findings/Observations

5.1 Some Challenges Encountered 5.2 The Data Quality 5.3 Statistical Analysis: Findings 5.4 Gaps and Areas for Improvement: Critical Assessment of the SWI/SWI Toolkit

6. Final Recommendations/Decision Points for the DSWD References Appendices (available upon request) Appendix 1 - Terms of Reference of the Specialist on Microeconomics of Social

Welfare Appendix 2 – Interim Report Appendix 3 – Existing SWI Toolkit Appendix 4 – Report on the Site Visits Appendix 5 – List of discussions/consultations/meetings Appendix 6 – Copies of Power Point Presentations Appendix 7 – Report on the Pilot Test Appendix 8 – The Social Welfare and Development Indicators (SWDI) Matrix Appendix 9 – The SWDI Toolkit Appendix 10 – The SWDI Tabulator Tables (available upon request) Table 1 – Results of Correlation Analysis Table 2 – Weights of Components/Indicators under the Existing SWI and the new

SWDI Table 3 – Hypothetical Computations on Range of Scores Under the Existing SWI Table 4 – Hypothetical Computations on Range of Scores Under the new SWDI

159

List of Acronyms ADB Asian Development Bank CHED Commission on Higher Education CL City Link DepEp Department of Education DOH Department of Health DSWD Department of Social Welfare and Development FDS Family Development Sessions FIES Family Income and Expenditures Survey HDI Human Development Index HDN Human Development Network IPs Indigenous Peoples MDGs Millennium Development Goals ML Municipal Link NHTS-PR National Household Targeting System for Poverty Reduction NSCB National Statistical Coordination Board PCA Principal Component Analysis PDPB Policy Development & Planning Bureau (DSWD) PHIC Philippine Health Insurance Corporation PRC Professional Regulations Commission PSA Philippine Statistics Authority PSGC Philippine Standard Geographic Code PSOC Philippine Standard Occupational Classification PSS Philippine Statistical System PWDs Persons with Disability RCCs Regional Convergence Coordinators SP Social Protection SWDI Social Welfare and Development Indicators SWI Social Welfare Indicators SWOs Social Welfare Officers TA Technical Assistance TESDA Technical Education and Skills Development Authority TOR Terms of Reference

160

1. Introduction

1.1. The Asian Development Bank (ADB) is supporting the Department of Social Welfare and Development (DSWD) and the Government of the Philippines in advancing its social protection reform agenda, through among others, a loan-based support via Loan 2662-PHI: Social Protection Support Project as well as three technical assistance (TA) grants, which collectively support the Philippine Government’s social protection reform agenda and key programs, in particular the Pantawid Pamilyang Pilipino Program of conditional cash transfers and the National Household Targeting System for Poverty Reduction (NHTS-PR). Among these, TA 7733-PHI: Support for Social Protection Reform complements the loan project and targets the outcome of rationalized social protection system endorsed and has three outputs: (i) national policy reforms for social protection (SP) developed; (ii) capacity of national and local institutions to support the SP reform agenda developed; and (iii) strengthened operational mechanisms for convergence and promoting Pantawid Pamilya beneficiary households’ sustainable transition out of poverty. DSWD is the executing agency for the TA.

1.2. Under Output 3, the TA supports the review and enhancement of DSWD’s Social Welfare Indicators (SWI) Toolkit.

1.3. The SWI Toolkit is potentially a powerful tool for monitoring progress in poverty alleviation. It uses and promotes the use of hard data in assessing the social protection program of the DSWD. It recognizes that statistics are critical inputs to evidence-based decision-making towards the attainment of the Millennium Development Goals (MDGs). Since good statistics lead to better-informed decisions, better-informed policies, and better-informed programs, they lead to better development outcomes and the use of statistics by the SWI Toolkit should continue to be pushed.

1.4. The ADB Consultant was engaged by the ADB as a Specialist on Microeconomics of Social Welfare under Contract No. 111000-S81205 to assist the DSWD in reviewing, assessing, and proposing refinements to DSWD’s existing SWI instrument to enhance its efficacy as a tool for measuring poor households’ wellbeing and grassroots-level case management aimed at promoting these households’ transition out of poverty on a sustainable basis. This work will include careful consideration of gender, indigenous peoples (IP)-related, and other dimensions.

1.5. The Terms of Reference (TOR) of the ADB Consultant are attached as Appendix 1. 1.6. In accordance with the TOR, a proposed work plan was submitted to the ADB on 24

November 2013. This was discussed with the DSWD, revised, and resubmitted to the ADB on 5 December 2013.

1.7. Per consultation with the ADB, three research assistants were hired for the project: Andrea Morales, Noel S. Nepomuceno, and Albert A. Garcia.

1.8. An Interim Report was submitted to the ADB on 31 January 2014 (Appendix 2). 1.9. A Contract Variation No. 1 was approved on 6 March 2014 extending the contract end

date from 31 January 2014 to 30 June 2014 with additional inputs of 30 days and an increase in the provision for out of pocket expenses.

1.10. On 26 June 2014, a Contract Variation No. 2 was approved extending the contract end date from 30 June 2014 to 31 July 2014.

1.11. In the course of his work, the ADB Consultant had consultations/meetings with the DSWD, particularly Undersecretary Florita R. Villar and the Policy Development & Planning Bureau (PDPB) and the SP Specialist. He attended presentations/discussions on the ADB Near Poor Study and received critical inputs from Christopher S. Pohr of the ADB.

1.12. The Consultant is grateful for the assistance and full support provided by the DSWD and the ADB and their respective officials and staff, and the research assistants, towards the completion of the project.

161

2. Literature Review

In addition to the literature review covering the Decent Work Agenda2 and Chile’s Solidario and Ethical Family Income3 that was included in the Interim Report (Appendix 2), the Consultant looked at the Human Development Index.

The Human Development Index

The Human Development Index (HDI) is a summary measure of human development

developed by the United Nations Development Programme. It is a composite index that

measures the average achievement in a country in three equally-weighted basic dimensions of

human development: longevity or a long and healthy life, access to knowledge or education,

and a decent standard of living. These dimensions are measured by a set of indicators that are

aggregated into indices.

Since 1990, the HDI has been widely recognized as a universal measure of human

development. In 20104, refinements were introduced in the HDI framework, the three basic dimensions and four indicators of which have been adopted by the Philippines, through the Human Development Network (HDN) and the former National Statistical Coordination Board (NSCB):

Long and healthy life is measured using life expectancy at birth;

Access to knowledge or education is measured using mean years of schooling for those aged 25 years and above, and expected years of schooling for those aged 6 – 24

years. The old Philippine HDI used literacy rate and gross enrolment rate; and

Standard of living is measured using real per capita income.

Recognizing the huge challenges of geography in the Philippines particularly on service delivery and building human capabilities that affect human development, the HDN has been recognizing provinces with the highest and the most improved HDI.

This could very well be extended to cities and municipalities and even Pantawid Pamilya families.

3. The Existing Social Welfare Indicators (SWI) and the SWI Toolkit

The Social Welfare Indicators (SWI) Toolkit is a tool used by the Department of Social Welfare and Development (DSWD) to measure the quality of life of poor households, primarily the Pantawid Pamilya beneficiaries. It is one of the tools in social case management used by the social workers/case managers to assess, plan, monitor and evaluate the progress of poor households, as well as determine the effectiveness of the interventions/services provided. The Existing SWI Toolkit is in Appendix 3.

2 See http://www.bles.dole.gov.ph/dews/Default.aspx and the Report of the Tripartite Validation Workshop of the Philippines Decent Work Country Profile. International Labour Office (ILO). 2012.

3 See Cash Transfer Programmes, Poverty Reduction and Empowerment of Women: A comparative analysis of experiences from Brazil, Chile, India, Mexico and South Africa, International Labour Organization, International Policy Research Brief, Center for Inclusive Growth by Simeone Cecchini, Claudia Robles and Luis Hernan Vargas, and Powerpoint Presentation of the Ministry of Social Development, Chile

162

4 The Philippines thru Dr. Romulo A. Virola, Secretary General of the former NSCB was a member of the Statistical Advisory Panel on the 2012-2013 Human Development Report

163

3.1. Indicators, Data Sources, and the Operationalization of the Existing SWI/SWI Toolkit

In measuring the progress of households, the SWI toolkit looks into three levels of well-being, namely, survival (Level 1), subsistence (Level 2) and self-sufficiency (Level 3) based on two major components, economic sufficiency and social adequacy. These are measured through the SWI score, using a number of components and indicators. A summary is included in the Interim Report (Appendix 2)

3.2. Some Issues and Concerns

Towards enhancing, rationalizing, and simplifying the SWI and the SWI Toolkit, the following issues and concerns arose:

Major Issues and Concerns:

The weights have to be revisited to consider internationally recognized measures of

well-being and to the extent possible, align them with the mandate of the DSWD; The number of indicators should be reduced; It is very difficult for a family to gain Level 3 of well-being. The existing cut-off marks

are too stringent; Should working children (below 18 years old) be monitored under employment and

their income counted? Likewise, should the employable skills and employment of senior citizens and persons with disability (PWDs) be captured in the enhanced SWI? This is not done in the existing SWI but it can be useful in case management;

The Toolkit does not directly address various concerns such as IP-, gender sensitivity, working children, senior citizens, PWDs, and disaster risk reduction and management;

Results of each wave of the SWI have not been systematically generated and comprehensively analyzed;

The administration and reporting of the Toolkit by the MLs does not follow clear and uniform standards;

The SWI database only contains the scores and does not capture/reflect raw data/information that could be useful (e.g. income) in data validation, profiling and case management. The SWI data should be stored in an integrated database that could allow more in-depth analysis of the Pantawid Pamilya program; and

Municipal links are overloaded with work. On the average, they manage 820 beneficiary cases each, making it almost impossible to comply with the semestral frequency of monitoring required by the existing SWI Toolkit.

Other Issues and Concerns: It must be noted however, that the following does not complete the enumeration of the many issues and concerns regarding the SWI:

The unit of analysis should be the family rather than the household as the Pantawid

Pamilya deals with families, not households; Will the SWDI be used for performance monitoring? If so, will this not raise questions

on the integrity of the information collected? Getting a certification on employable skills is a problem and is biased towards those

who have attended skills training and against those who acquired their skills thru informal means such as farmers, fishermen, and carpenters.

The quality of the data on the income indicator suffers from the lack of rigor in the measurement of income

o Per capita income computations exclude the chronically ill and the

physically/mentally challenged family members which is inconsistent with the computation of per capita income for purposes of official poverty statistics

o The exclusion of grants from the Pantawid Pamilya Program as part of income is

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likewise inconsistent with the way family income is computed in the FIES which serves as basis for official poverty statistics.

o Realizing the need to simplify the SWI, the possibility of using the NHTS-PR proxy variables for income was considered. However, the NHTS-PR database is updated quite infrequently (once in five years), raising questions on the accuracy of the income estimated using the NHTS-PR proxy means test.

Some indicators are difficult/complex to measure

o Based on the experience with typhoon Yolanda, the housing indicator on

“Location is safe and secure” is difficult to score. o It is too much to expect that on the basis of the SWI Toolkit, the MLs will be able

to determine whether a family is eating well-balanced meals unless they are properly trained and acquire the necessary competency.

o How MLs determine whether family members practice self-care/personal hygiene based on its many dimensions and on whether “the individual generally looks clean and smells good” lends to much subjectivity and room for measurement error.

o It is not easy for an ML using just the Toolkit to capture the involvement of household members in incidence of neglect, abuse, exploitation, and violence at home which are areas generally shrouded in a culture of silence due to risks of stigmatization and rejection.

Some indicators are deemed to be no longer relevant

o Membership in the PHIC – there is already universal coverage of the Pantawid

Pamilya families o Attendance in FDS – already compulsory for the Pantawid Pamilya families

o Some indicators are scored using categories that are not mutually exclusive and

exhaustive o Under the first indicator for role performance of household members, the situation

when adult household members can define the problems, are aware of the causes/implications and are able to think of solutions but without the participation of family members does not fall under any of Level 1, Level 2 or Level 3.

o Under income, the situation when the per capita income is 25% more than the poverty threshold is neither Level 1 nor Level 2 nor Level 3. It falls between Level 1 and Level 2, but the Toolkit does not say how this is to be scored.

For practical purposes, it does not seem right to give greater weight to employment of the household head over employment of the other members of the household;

Family scores should be computed for some of the indicators without having to ask separate questions for each of the individual members; and

The number of years of schooling of family members aged 18 years or over which is captured by the HDI was considered as one of the indicators for the component on education. This would be in lieu of functional literacy which was already at 86.4% as of the 2008 FLEMMS5 from 84.1% in the 2003 FLEMMS. This indicator, together with an indicator on enrolment of school age children would have taken into consideration both current and future generations in assessing the human capital of the country. However, issues arose in setting the appropriate standards on this indicator for the three levels of well being with the implementation of the K-12 curriculum and the fact that the DSWD would have little powers in convincing a 24-year old family member who reached only fourth grade to go back to school.

4. Methodology

Objectives:

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Based on an integrated appreciation of the purpose of enhancing the Toolkit, and the surrounding issues and concerns, it was deemed appropriate that the enhanced Toolkit should serve the following objectives:

It should be useful in monitoring progress in the level of well-being of 4P families; and It should be useful as a DSWD Management Tool, particularly in Case

Management

Criteria on how to enhance the SWI:

With the above objectives, the criteria followed in reviewing and enhancing the SWI were the following:

Focus should be on social welfare and development – This means that as much as

possible, the enhanced SWI should include components and indicators over which the DSWD has some control in managing, improving, or moving from one level to a higher level of well-being;

Gender-, IP-related, and other concerns should be considered; Since poverty reduction is the overarching concern in the national development efforts,

the income indicator should receive much focus in the enhanced SWI even though raising family income is not the sole or primary mandate of the DSWD. It is to be noted that poverty incidence, the official measure of poverty used in development planning is based on income.

In recognition of the heavy workload of the MLs, the enhanced SWI should be simple and easy to implement.

Review of the Literature

A review of the literature was conducted, looking at the social welfare indicators and/or similar indicators in other countries. In addition, international frameworks such as those on the MDGs, the HDI, and the Decent Work Agenda were assessed. (see Section 2) Assessment of DSWD Internal and Other Documents

In addition to the SWI Toolkit itself, the following documents, among others, were reviewed: Internal Review of the Social Welfare Indicators (October 2013) NHTS-PR Documents List of Recommendations (to improve the Toolkit) from the MLs of Region III and Oriental

Mindoro Family and Community-Based Disaster Preparedness Manual Data on the workload of the MLs in all the provinces of all the regions as of 05 February 2014 Assessment of Data Quality

The SWI data for several waves of the SWI were requested from and provided by the DSWD. These were assessed for quality providing some indication on how strictly the Toolkit is being implemented Use of Standard Statistical Concepts and Definitions Also considered were standard statistical concepts and definitions and best practices adopted in 5 Functional Literacy, Education and Mass Media Survey

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the Philippine Statistical System (PSS) and which are generally consistent with international guidelines. Among these are the following: Philippine Standard Geographic Code Philippine Standard Occupational Code Household Survey Concepts and Definitions ( like those used in the Family Income and

Expenditures Survey, Annual Poverty Indicators Survey) Census of Population and Housing Concepts and Definitions ( on water and sanitation,

housing, relationship to head) Recommendations of the Washington Group6 on the compilation of disability statistics ILO’s International Classification by Status in Employment

Link with the NHTS-PR and other related frameworks

In enhancing the SWI, it is important to consider other related frameworks and initiatives in order to optimize its use and relevance.

Foremost among these is the NHTS-PR database. Thus, to the extent possible, the SWDI used concepts, definitions and coding systems that are consistent with the NHTS-PR. This will allow the SWDI and NHTS-PR databases to be merged for a richer analysis and monitoring system.

The project also tried to establish correspondence with the related Near Poor Study also funded by the ADB. While the Near Poor Study has not finalized its recommendations, it provided insights towards the initial recommendations on the scoring of the income indicator. Weights Analysis

Recognizing that the equal weighting used in the existing SWI may not be appropriate considering the objectives and criteria in the enhancement of the SWI, an analysis of its impact on the resulting SWI scores and consequently on the level of well-being of the 4P families was done. Basically, it was assessed what it meant to get a score corresponding to Levels 1 and 2, and what it would take to achieve Level 3. Site Visits

To be able to further assess the effectiveness of the SWI Toolkit and to be able to draw on the perspectives of the MLs, the Consultant conducted site visits to Pampanga (for the municipalities of Nueva Ecija, Pampanga, and Tarlac) and Mindoro Oriental to cover some municipalities with high, medium, and low poverty incidence and which have already undertaken at least two waves of the SWI. These were held on 4 March 2014 at the DSWD Regional Office in San Fernando, Pampanga, and on 6-7 March 2014 in Calapan City, Mindoro Oriental. Two activities were conducted:

1) A questionnaire was developed to be accomplished by the MLs on site. The objectives of

the first activity were as follows:

To determine if the assessment of the well-being of families by Municipal Links using the questionnaire is consistent with the resulting scores from the SWI toolkit;

To identify the problems being encountered, if any, by the municipal links/social worker in administering the SWI toolkit;

To gather suggestions on how to further improve the SWI toolkit; and

6 The Washington Group is a City Group created by the UN Statistical Commission tasked to improve the generation, dissemination, and use of internationally comparable disability statistics. The Philippines, thru the NSCB and the NSO, is an active member of the Group.

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To assess if the responses generated from the toolkit may be affected/influenced by some characteristics of the municipal link.

2) The existing Toolkit was administered to families comprising at least two from Level 1, at

least two from Level 2, and at least two from Level 3, for each province. The objectives of the second activity were to find out the following:

The appreciation of the respondents on the purpose of the SWI If the SWI is being administered in accordance with Toolkit Given the purpose of the SWI, what do they think of the current SWI in terms of its

usefulness/relevance, effectiveness? A copy of the Report on the Site Visits is in Appendix 4.

Assessment of the Workload of the MLs

From the very beginning, the Consultant was alerted on the difficulty faced by the MLs and the backlog in the administration of the SWI. Data were requested from the DSWD on the number of cases handled by the MLs in all the provinces of all the regions of the country as of 05 February 2014. Use of Statistical Tools for Data Analysis

A number of statistical tools were attempted/used to analyze the data: Principal Component Analysis, Cluster Analysis, Correlation Analysis; Ordered Logistic Regression Analysis and Paired Differences Analysis. These tools were used despite the data limitations just to get insights on the SWI dataset. The discussion on these tools except for the correlation analysis, formed part of the Interim Report (Appendix 2)

Series of Discussions/Consultations/Meetings

During the project implementation, the Consultant held discussions/consultations/ meetings with the DSWD, the ADB, and the Social Protection Specialist, specifically, on the Near Poor Study. In addition, various presentations were made including one during a meeting of the DSWD Executive Committee presided by Secretary Corazon Soliman. The list of discussions/consultations/meetings and copies of the power point presentations are in Appendix 5 and Appendix 6

In addition, the DSWD is planning to sponsor after July a consultative forum with key stakeholders outside of the DSWD where the Consultant may serve as a Resource Person. Pilot Test

After the SWI had undergone a series of discussions between the Consultant and the DSWD/ADB, the preliminary version of the SWI was pilot tested in Pampanga on 17 June 2014, covering the municipalities of Porac and Mabalacat and Angeles City.

Prior to the pilot test, a whole-day training of three MLs who will be administering the draft Toolkit was conducted at the DSWD Central Office

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A copy of the brief report on the pilot test is in Appendix 7.

Preparation of Metadata

To improve the documentation of the enhanced SWI, metadata were prepared, both for the existing SWI and the new SWDI. The metadata for the old SWI formed part of the Interim Report (Appendix 2) while the metadata for the new SWDI are incorporated in the SWDI Toolkit.

Decision Points for the DSWD

Towards the finalization of the recommendations on the enhanced SWI, decision points were presented to the DSWD Executive Committee for consideration.

5. Assessment of the Existing SWI and the SWI Toolki: Findings/Observations

5.1. Some Challenges Encountered

Prior to the engagement, the Consultant expressed concerns about the timeline of the project, noting particularly the Christmas holidays when workers in general are not at their most productive period. In a meeting with the DSWD, the DSWD suggested that in consideration of this concern, the deliverables could be adjusted. The devastation caused by typhoon Yolanda also significantly altered the working schedule of the DSWD, which held the PDPB staff on call, and limited the time available for the project consultation.

The planned site visits could not be done as initially scheduled because of administrative issues between the ADB and the DSWD and between the ADB and the Consultant. It was only during the third week of January when the Consultant found out that the administrative issues between the DSWD and the ADB had been settled which was too late to make arrangements for the site visits. Besides, it was discovered that the existing contract between the ADB and the Consultant did not provide for budgetary support for such visits even though the visits were included in the TOR. Per discussion with the DSWD, if project extension could be granted, the plan is to schedule the site visits after January 31. With close coordination among the ADB, the DSWD, and the Consultant, the project contract variation was approved and the site visits took place.

The pilot tests of the SWI instruments could also not be conducted as planned because of some difficulties in coming up with a schedule that is suitable to the DSWD and the Consultant. The approval of the second contract variation made it possible to do the pilot tests before finalizing the instruments.

Originally, the Consultant had expected that the consultation with stakeholders would include individuals and institutions outside of the DSWD. As the main user of the Toolkit would be the DSWD, it was agreed that the consultations be conducted internally within the DSWD. Towards the end of the project, the DSWD made plans to conduct a consultative forum with external stakeholders after July 2014.

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5.2. The Data Quality

Data provided by the DSWD to the Consultant turned out to be not as suitable for statistical analysis as had been envisioned. The following are its main features:

The data captures various dimensions of well-being such as: o

Employment; o Health; o Work/Life Balance; o Education and skills; o Social Connections; o Civic engagements; o Environmental quality, among others

The data are basically in ordinal scale. The SWI data are “dirty” which could be due to the loose implementation of the SWI

or because of the heavy SWI workload of the MLs.

Some questions on the data were raised with the DSWD which provided clarifications as tabulated in the Interim Report (Appendix 2)

5.3. Statistical Analysis: Findings

As mentioned earlier, the results of the statistical analyses using a number of tools were presented in the Interim Report (Appendix 2). However, it did not include the results of the correlation analysis.

5.3.1. Correlation Analysis

Correlation Analysis is the statistical technique used to test whether and how strongly the components are related. The components with at least some degree of correlation may be combined or some of the correlated components may be removed.

Table 1 shows the results of the correlation analysis made on the scores of the components.

The table shows that all the components are associated with each other at 5% level of significance. It is worth noting that among the components, the Hygiene Component is most highly correlated with Sanitation with correlation coefficient equal to 0.4902. Likewise, Role Performance is moderately correlated with Family activities with correlation coefficient equal to 0.4323.

In addition, role performance is relatively highly correlated with Nutrition, Sanitation and Hygiene.

These findings suggest that the SWI can be simplified by merging the following components, considering that these components are moderately associated with each other:

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a) Hygiene and Sanitation b) Role Performance and Family Activities

5.3.2. Weights Analysis

The equal weighting system under the existing SWI has the following implications:

Social adequacy, one of two major components of the SWI, and which can be

considered as an aspect of well-being that is more in line with the mandate of the DSWD has equal weight as the other major component of Economic Sufficiency, over which the DSWD does not have much direct control. (Table 2 )

The eight components of Social Adequacy have individually smaller weights than the four components of Economic Sufficiency. For example, education has a weight of 0.0625 compared to 0.1250 for employment.

The indicators of Social Adequacy have individually lower weights than the indicators of Economic Sufficiency. For example, access to safe drinking water has a weight of 0.021 compared to possession of occupational skills certified by appropriate authorities which has a weight of 0.125.

As a result, the achievement of Level 3 or self-sufficiency is biased against the indicators of social adequacy such as nutritional status of children below 6 years old, and enrolment of school age population

In addition, hypothetical computations were done to assess what it would take to be categorized as Level 1, Level 2, or Level 3. Under the existing SWI Toolkit: (Table 3 )

Level 1 in any one of the 12 components even if Level 3 in all other 11

components will already be Level 2 Level 2 in any one Economic Sufficiency component even if Level 3 in all other

11 components will already be Level 2 Level 2 in two Social Adequacy components even if Level 3 in all other 10

components will already be Level 2

Together with the results of the Cluster Analysis, the above suggests that the scores defining Level 3 (and Level 2) maybe too stringent. In refining the ranges of scores, it is deemed reasonable to consider the following:

A score of 3 in Social Adequacy and 2.5 in Economic Sufficiency should

already be Level 3 ( Level 2 in the existing) A score of 2 in Social Adequacy and 1.5 in Economic Sufficiency should still

be Level 2 ( Level 1 in the existing) Thinking that the three most important components should be Health,

Education, and Income, being Level 3 in these three components should be a necessary but not sufficient condition to achieve Level 3

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5.3.3. Site Visits

The report on the site visits is in Appendix 4. Its highlights include the following:

Eight out of 13 MLs confirmed that they are assigned at least 700 households

each. Administration of the Toolkit lasts at most 30 minutes for 11 of 13 MLs There is divergence (23%) between the scores generated from the SWI and the

scores directly obtained from the MLs for a number of selected families. Problems identified by the MLs included

o Too many cases to handle o Questionnaire is not in Filipino o Questionnaire is not IP-sensitive o Lack of appreciation from the households o On the administration of the SWI o Difficulty in assessing what a well-balanced meal is o No uniformity in concepts and procedures ( e.g. whether to interview grantee

or household head; use of different poverty thresholds within a province) o Tendency of households not to tell the truth for fear of being delisted from the

4P.

Of the 12 components of the SWI, 5 were identified to pose difficulty in data

collection o Employment/job o Income o Social insurance o Health, and o Nutrition

Nine of 13 MLs think the existing Toolkit is generally sufficient but needs to be

improved o Training provided to the MLs is generally adequate but can be improved o Some MLs think the standard to attain Level 3 is too high o Some indicators are redundant and could lead to different interpretations by

the MLs o The weights should be changed o Possibility of using advances in technology in data collection or outsourcing

of data encoding and processing o Use of group work method in data collection o Uniform template for profiling and preparation of reports

Some observations:

o The MLs are generally dedicated and hard working o Most of the households are not familiar with the SWI o Income could have been underreported due to lack of understanding of the

different sources of income that are covered and must be reported

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5.3.4. Pilot Test

The report on the pilot test is in Appendix 7. Its highlights are as follows: The MLs generally appreciated the proposed enhancements on the Toolkit,

noting that the indicators were “more measurable and easier to quantify” It took at least 40 minutes to administer the Toolkit The MLs did not appear to encounter problems in the operationalization of the

proposed Toolkit In spite of the fact that rights of children, gender-based violence and disaster

preparedness are covered in the FDS, respondents have difficulty enumerating the issues being asked.

The MLs suggested the following: o An orientation of the grantees be conducted prior to the administration of the

Toolkit; o A number of suggestions on the General Intake Sheet o The component on Income should follow the component on Employment for

ease of administration; o Training on the collection of the income component; o Need for formal coordination between the DSWD and DepED on the provision

of information on school attendance; and o Provision of summary score sheets in excel format to facilitate computations

by the MLs.

5.4. Gaps and Areas for Improvement: Critical Assessment of the SWI/SWI

Toolkit

Based on the methodology used to enhance the SWI, the following gaps and areas for improvement are identified:

1) Weights Analysis – There is a need to revisit the weighting system used in computing

the overall index for each family.

This involves not only the weights used In the formulas for the subindices and the overall index but also the structure of the different components of the index. For example, the weight of employment of household head is heavier than the weight allocated to employment of the other household members. While cultural norms and standards may have been the basis of this differentiation, in practical terms there seems to be no reason why employment of the household head would carry greater weight in assessing the well-being of the household.

A weight of ½ for Economic Sufficiency and ½ for Social Adequacy does not seem to be consistent with the mandate of the DSWD, considering that the enhanced SWI is to serve as a DSWD Management Tool.

The HDI, internationally accepted as a measure of human development, takes into consideration three dimensions: health, education, and income and gives a weight of 1/3 to each dimension. The importance of these three dimensions in assessing well-being is widely recognized. In fact, according to the World

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Bank President,7 24% of economic growth is explained by the health variable. On the other hand, education statistics show a systematic deterioration in the human capital of the country in recent decades, It must be noted that the Philippines used to enjoy a comparative advantage in education over other ASEAN countries. And given the overarching development goal of poverty reduction and given that official poverty statistics are based on income, the importance of the income indicator cannot be overemphasized, notwithstanding recent initiatives on the measurement of progress beyond economic development.

It is deemed desirable therefore that in refining the SWI, the greatest weights should be attached to health, education and income.

2) Range of scores defining the three levels of well-being – The ranges are too

stringent making it difficult for a family to achieve Level 3 and easy to fall to Level 1

A score of 3 for Social Adequacy and 2.5 for Economic Sufficiency means Level 2

A score of 2 for one component even if 3 in all other components means Level 2

A score of 2 for Social Adequacy and 1.5 for Economic Sufficiency means Level 1

A score of 1 for an Economic Sufficiency component even if 2 in all other components means Level 1

Of 386,683 Pantawid Pamilya families for which data have been provided by the DSWD to the Consultant, 48.75% were Level 1 and only 0.03 % were Level 3.

3) Duplication/ redundancy among the indicators/components - There appears to be

overlaps in the information contained in some of the indicators and some components have high correlation.

4) There is a need to revisit some items, which might be stringent and/or

unnecessarily complicating the SWI e.g. need for a certification from TESDA to be able to recognize that the skill is employable, or too subjective or difficult to assess like being “able to make appropriate decisions on his/her own” under the role performance indicator on participation of adult members in decision making

5) Link with the NHTS-PR database – Consistency in the coding and classification

systems used by the SWI and the NHTS-PR database is not optimized. Thus, the flexibility in merging the datasets for a richer analysis of the situation of the 4P beneficiaries is reduced..

7 CNN Interview with Christine Amanpour

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6) Use of Standard Statistical Concepts and Definitions - Adherence to local and international statistical standards is inadequate.

Standard classification systems are not adopted.

Official statistical concepts and definitions prescribed in the Philippine Statistical System are not adopted.

7) Lack of metadata – Metadata or data about the SWI data are not systematically

provided and certainly inadequate. This could have contributed to a number of the issues/flaws of the SWI, including the different interpretations by the MLs of how the Toolkit should be operationalized.

8) Workload of the MLs – The timeline for the administration of the SWI has not been

strictly adhered to. The primary reason is the heavy workload of the MLs. As of February 26, 2014, the 4,875 MLs/CLs were serving 3,996,967 4P family beneficiaries for an average load of 820 families per ML/CL.

9) The Uses of the SWI - Based on the interactions with the MLs, it is not clear that the

SWI has been used enough for case management. However, during the site visits, the MLs identified some uses of the SWI (Appendix 4)

The following are potential uses of the SWDI:

Design of different intervention schemes for families specific to their levels of

well being Budgeting for the interventions needed to help the Pantawid Pamilya families. Promoting faster progress in raising the level of well being of families by

recognizing communities and families in terms of achievements in increasing their SWI Index. This would be similar to the awards institutionalized by the HDN to the provinces with the highest and most improved HDI. It can also be used as a criterion for selecting the best ML but validation will of course be necessary.

Case management functions of MLs based on information collected thru the SWDI such as on working children and senior citizens over 65 years old, income earned by PWDs, lack of awareness of gender-based violence, malpractices in the component on water and sanitation, etc.

6. Final Recommendations/Decision Points for the DSWD

A number of recommendations were initially considered as discussed in the Interim Report (Appendix 2). They covered the following:

1) Use of the term ‘vulnerable/vulnerability” instead of subsistence; 2) Use of standard concepts and definitions for statistical purposes including the

preparation of metadata; 3) Computation of sub-indices by sex, IP, geographic disaggregation; 4) Standardizing the SWI Household ID system; 5) Promoting the Use of the SWI Toolkit; 6) Simplifying the Operationalization of the SWI Toolkit; and

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7) On specific steps/tasks needed to be further undertaken.

Before the recommendations were finalized, a number of options were presented to the DSWD such as:

On the scoring of the income indicator On the coverage of the Employable Skills/Employment components On the labels of the different levels of Well-being On the definition of the near poor, in case it will be relevant in decomposing the structure of

Level 3 families

The first two have been resolved and incorporated in the recommended SWDI and SWDI Toolkit. However, the third and fourth remain undecided upon.

The options for the labels are:

Survival, Vulnerable, and Self-sufficient for Level 1, Level 2, and Level 3, respectively. Vulnerable Survival; Vulnerable, Near Poor; and Self-sufficient for Level 1, Level 2, and

Level 3, respectively. Survival, Poor, Near Poor for Level 1, Level 2, and Level 3, respectively.

The appropriate labels should probably depend on the cutoff limits for the income indicator defining the score for the three levels. The reason subsistence is not recommended for Level 2 is that in the official poverty statistics methodology, survival and subsistence families essentially refer to the same group.

For the near poor, some possible options are: families with income above the poverty threshold by 10% or by 20%, or by 35%8.

In addition, the issue on whether the SWDI will be used for performance monitoring was presented to the DSWD Executive Committee. It was clarified that definitely the SWDI will not be used to assess the performance of the President. However, it can be a tool for performance monitoring of the DSWD, the MLs in particular, with the need to address the inevitable questions on the integrity of the SWDI if it is used for performance monitoring.

The final major recommendations are the following:

1) The title should be the Social Welfare and Development Indicators (SWDI) and the SWDI

Toolkit – this was approved by the DSWD Executive Committee;

2) The frequency of administration of the SWDI should be once a year - this was approved by

the DSWD Executive Committee;

3) The number of indicators should be reduced from 27 to 23 - this was approved by the

DSWD Executive Committee;

8 The ADB Near Poor study is considering 35% above the poverty threshold as the ultimate upper limit for near poor

families, starting with 10% in the beginning.

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4) The weights of the different components and indicators have been revised to give the greatest weights to Income, Health, and Education. The new set of weights is in Table 2. This results in a weight of 2/3 for Social Adequacy and 1/3 for Economic Sufficiency - this was approved in principle by the DSWD Executive Committee;

5) The range of overall scores defining the overall levels of well-being of the Pantawid

Pamilya families was recommended to be as follows and this was approved by the DSWD Executive Committee (hypothetical computations are shown in Table 4):

Level 1: From 1 up to, but not including 1.83

Level 2: From 1.83 up to, but not including 2.83

Level 3: From 2.83 up to 3

6) The recommended SWDI Matrix is in Appendix 8 - this was approved in principle by the


7) The recommended SWDI Toolkit is in Appendix 9 - this was approved in principle by the


8) The recommended Excel File for the use of the MLs in data processing of the SWDI is in

Appendix 10

9) Other recommendations:

a. The SWDI should not be administered during the rainy season and as much as

possible, during the same month of each year..

b. Intensive training of the MLs on the administration of the SWDI.

c. Benchmarking or collection of baseline data and the review of the DSWD target on its

three Strategic Goals d. The use of geometric means instead of arithmetic means in aggregating the scores

could be considered as is done in the HDI. This minimizes the substitution effect, when underperformance in one indicator can be compensated by overperformance in other indicators in a linear fashion. Of course, the geometric mean is not as easily understood and is not as easy to interpret/analyze as the arithmetic mean.

e. Towards enriching the analysis of the SWDI, computation of the SWDI Index for

specific groups ( PWDs, IPs) and appropriately disaggregated such as by sex and geographic disaggregation is recommended. Also recommended is the computation of other summary indicators aside from the number of families that moved between levels, such as the proportion of families with improved SWDI Index over time. Analyzing the data on working children will also give insights on the gravity of child labor. Likewise for senior citizens and PWDs.

f. Systematic and efficient sharing of information at the LGU level should be put in place.

Toward this end, memoranda of agreements should be agreed upon by the DSWD with the DepED, the DOH, and the LGUs.

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g. The DSWD should allocate greater investments on data capture technology to lessen the burden on the MLs and to facilitate the processing of the SWDI data. Alternatively, the encoding and processing of the SWDI data can be subcontracted. The DSWD Executive Committee has approved the use of its existing tablets for the first administration of the SWDI.

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National Statistics Office. Functional Literacy, Education and Mass Media Survey. Manila, Philippines. 2008. National Statistics Office. Labor Force Survey Enumerator’s Manual. Manila, Philippines. 2008.

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National Statistics Office. National Demographic and Health Survey. Manila, Philippines. 2008.

Philippine Statistics Authority. Philippine Standard Geographic Code. Makati, Philippines. 2014. Powerpoint Presentation of the Ministry of Social Development, Chile

Report of the Tripartite Validation Workshop of the Philippines Decent Work Country Profile.

International Labour Office (ILO). 2012. United Nations Children’s Fund. Convention on the Rights of Children. United Nations. New York, USA.

United Nations Population Fund. A Practical Approach to Gender-Based Violence. United Nations. New York, USA. 2001.

United Nations Principles and Recommendations for Population and Housing Censuses, Revision 2. United Nations. New York, USA. 2008.

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As of January 30, 2015

Department of Social Welfare and Development Disaster Response

Strategic Policy Framework for the New Normal

This report has been prepared for DSWD by a team composed of Dr. Vicente Paqueo (Advisor), Minerva Dacanay (Consultant), and Susan Rachel Jose (Resource Person) with the support of ADB under TA 7733, Support for Social Protection Reform in the Philippines. The preparation of this draft involved consultations with DSWD officials, review of related documents of DSWD, and a focus group discussion and writeshop with staff from the central and field offices of DSWD on 12-14 January 2015. The International Organization on Migration represented by Mark Maulit also provided inputs.

181

List of Acronyms

AFP Armed Forces of the Philippines COA Commission on Audit DBM Department of Budget and Management DepEd Department of Education DILG Department of Interior and Local Government DOH Department of Health DND Department of National Defense DPWH Department of Public Works and Highways IASCHC Inter-Agency Standing Committee’s Humanitarian Cluster LGU Local Government Unit MGB Mines and Geosciences Bureau NCDDP National Community- Driven Development Program NDRRMC National Disaster Risk Reduction and Management Council NEDA National Economic and Development Authority OCD Office of Civil Defense OP Office of the President 4P Pantawid Pamilyang Pilipino Program PAGASA Philippine Atmospheric, Geophysical and Astronomical Services

Administration PDRRMA Philippines Disaster Reduction and Management Act QRF Quick Response Fund SLP Sustainable Livelihood Program

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1. Introduction

It is the misfortune of the Philippines to be regularly hit by devastating natural disasters and violent conflicts. These environmental and man-made disasters inflict untold human suffering and economic losses resulting from injuries, illnesses, deaths, destruction of infrastructure and physical assets, displacement of people, and costly disruption of livelihood and other economic activities. As a consequence, affected local economies have been set back, making it even more difficult for the poor and near poor to move out of poverty.

As if the sufferings inflicted on the Filipino people were not enough, more natural disasters are expected to visit the Philippines. Remarkably, many of them would probably be as massively destructive as Ondoy and Yolanda. This new pattern of extreme weather events has been dubbed the “new normal”.

As a consequence of the emergence of the new normal phenomena, the challenges of typhoons, flooding, earthquake and other disasters are becoming more complex. On this point, the occurrence of sequential disasters clustered within a short interval and over multiple regions means widespread shortages and increased number of victims in bigger geographic areas. Simultaneous assistance to disasters would stretch thinly available trained manpower, equipment and financial resources.

Further complicating the challenge of responding to disasters under the new normal is rising public expectations and demand for higher service standards. Government is under intense pressure to provide timely and high quality assistance. Yet, budgets are limited relative to the needs of the affected poor; and timeliness is severely constrained by the need to comply with time-consuming processes and bureaucratic rules.

DSWD have taken steps to improve its capabilities and practices in disaster response management over time. Further improvements, however, are needed. A critical step on this score is the formulation of a written Strategic Policy Framework to guide the development of DSWD’s all-hazards guidelines for its disaster response operations. The framework speaks to the challenges of the new normal, and how they could be responded to more efficiently, equitably, and compassionately. The document is needed by DSWD and its partners to get clarity about the agency’s objectives, policies and strategies for the new normal to ensure coherence and better coordination.

The paper is structured as follows. The next section lays out the current challenges and institutional context. Section 3 presents the policy and strategy framework, while Section 4 identifies practical ways forward. The conclusion summarizes the principles and strategies articulated by the framework.

2. Disasters and Challenges

2.1 Profiling Disasters, Consequences and Victims

The Philippines ranks second out of 171 countries in the 2014 World Risk Index, and tops the 2014 global estimates of the Internal Displacement Monitoring Center with almost 6.6 million internally displaced persons due to disasters. 45 In 2013 alone, the Philippines experienced successive, hydro-meteorological, geological and human-induced disasters, straining disaster response systems and resources (see Table 1).

45

www.ehs.unu.edu/article/read/world-risk-report-2014 and http://www.internal-displacement.org

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Table 1. 2013 Disasters in the Philippines

Type of Disaster

Name of Disaster

Date of Occurrence

Affected Areas

No. of Affected and

Displaced Persons

Assistance (PhP M)

Hydro-Meteorolo-gical Hazards

Typhoon Maring

18 Aug 2013 NCR, CAR, I, III, IV-A, IV-B

4,,500,000 46.5

Typhoon Santi

09 Oct 2013 I, II, III, IV-A, V 1,692,308 19.3

Typhoon Yolanda

06 Nov 2013 IV-B, V, VI, VII, VIII, CARAGA

6,600,000 2,300

Geological Hazards

Bohol Earthquake

15 Oct 2013 VI, VII 3,665,146 71.82

Human-Induced Disasters

Lahad Datu Incident

04 Mar 2013 IV-B, IX, ARMM 21,186 11.9

Zamboanga Crisis

09 Sep 2013 Zamboanga City 118,819 276.2

Source: DSWD’s 2013 Post-Disaster Operations Review

Being in the typhoon belt, the country experiences an average of 20 typhoons a year. These typhoons are accompanied by strong winds, intense rainfall, storm surges, and flooding. In recent years, these events appear to have become more frequent and are more severe like Ondoy and Yolanda. This changed pattern, which is probably due to climate change, is now interestingly called the “new normal”.

Other risks of future environmental shocks are also worth noting and preparing for. The

Philippine Institute of Volcanology and Seismology has declared that the West Valley Fault is due to move anytime, and this earthquake can result in staggering destruction and loss of lives which could exceed 10,000.46

Economic losses due to disasters could run into billions of pesos due to displacement of

people, destruction of crops, and damages to infrastructure and other physical assets. Other effects of disasters include loss of lives, pain and suffering, and the dysfunctional effects of risk and uncertainty. It is difficult to estimate the total value of economic and non-monetary losses from disasters. Nevertheless, keeping this caveat in mind, Figure 1 provides some estimates of the cost of damage from seven (7) typhoons that visited the Philippines between 2008 and 2013.47 The table suggests that, not including indirect losses, the cost of damage from typhoons are huge. In 2013 alone, the amount of damage stood at 89.6 billion pesos. This figure is much greater than the cost of damage of only 13.5 billion pesos in 2008, a six-fold increase in the cost of damage.

It is remarkable that the amount budgeted for the Calamity Fund and Quick Response

Fund allocated to agencies like DSWD, and DPWH, pale in comparison with the estimated

46

PHIVOLCS updated estimates based on Metro Manila Earthquake Impact of Risk Study (MMEIRS).

47 What were considered here are only the typhoons with estimated cost of damage greater than 10

billion pesos, at current prices.

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value of the cost of damage from the typhoons. In 2013, for example, the Calamity Fund and Quick Respond Fund combined amounted to only 8.3 percent of the estimated cost of damage.

The interaction between natural disasters and economic indicators has been the subject of various studies. From the sectoral and micro perspective, they found that natural disaster had significant effects on sectoral outputs, household incomes and, therefore, poverty. A discussion paper recently published by the Philippine Institute of Development Studies (PIDS) found that “the occurrence and frequency of typhoons and/or floods in Pasay City, Metro Manila have significant and negative effects on household per capita income.” For other similarly situated urban areas in the country, the study also found similar results.48 Moreover, another study reports that although “typhoons, floods and droughts have an insignificant impact on agricultural production at the national level, typhoons have a significant negative impact on paddy rice production at the provincial level”. This impact, as exemplified by Ondoy and Pepeng in 2009, have a significant negative consequence on the food security of the households in the affected areas.49

48

Israel and Briones (2014) 49

Israel and Briones (2012)

Figure 1. Cost of Damage vs. Calamity Fund* (In billion pesos, at current prices)

Source: OCD, DBM

* For 2009, 2010 and 2011, the quick response fund (QRF) were sourced from the calamity fund. Starting 2012, QRF allocation were lodged against respective budgets of departments.

13.500

38.250

11.500

15.550

36.950

89.600

4.304 3.750

6.000 7.500

3.764

13.000

0.598 0.645 1.788 2.645

3.695 4.850

0.000

10.000

20.000

30.000

40.000

50.000

60.000

70.000

80.000

90.000

100.000

Frank (Fengshen) Ondoy (Ketsanan)

and Pepeng (Parma)

Juan (Megi) Pedring (Nesat) Pablo (Bopha) Yolanda (Haiyan)

2008 2009 2010 2011 2012 2013 2014

In B

illion P

eso

s, C

urr

ent Pri

ces

Cost of Damage Calamity Fund Quick Response Fund

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2.2 Institutional Arrangements for Disaster Management

2.2.1 General Set Up The Philippines Disaster Risk Reduction and Management Act (PDRRMA) of 201050

created the National Disaster Risk Reduction and Management Council (NDRRMC) which is chaired by the Department of National Defense. The PDRRMA instituted a comprehensive approach to managing disasters, including the impacts of climate change. It introduces fundamental paradigm shifts from reactive to proactive approaches: from disaster response and relief to disaster risk reduction; from top-down/centralized to a combined top-down and bottom up, decentralized and participatory approaches; and from an understanding that disasters are merely a function of physical hazards to one that recognizes that disasters reflect vulnerability of people and assets.

The activities of the NDRRMC are organized in thematic areas or pillars: (i) prevention and mitigation, (ii) preparedness, (iii) response, (iv) recovery and rehabilitation. A Vice-Chair is designated for each pillar. DSWD is Vice-Chair for Response.

As head of the response pillar, DSWD ensures that the response of government as a

whole is well coordinated, follows national standards, and is clearly communicated to the public. This involves coordination with key agencies such as DILG, DOH, DND, and OCD. An in the event of a large-scale disaster involving the international aid community, the UN Interagency Standing Committee’s (IASC) Humanitarian Clusters are activated with DSWD being the country lead for protection, camp-coordination management, and food and nonfood assistance.

50

Republic Act No. 10121, dated 27 July 2009, otherwise known as An Act Strengthening the Philippine Disaster Risk Reduction and Management System, Providing for the National Disaster Risk Reduction and Management Framework and Institutionalizing the National Disaster Risk Reduction and Management Plan, Appropriating Funds Therefore and for Other Purposes.

Figure 2. Organizational Structure of the Response Cluster

Chairperson, NDRRMC

Vice Chairperson for Response, DSWD

DepEd DOH DND thru

AFP OCD DILG

Food and Non-Food Items

Protection. Camp Coordination and

Management

Search, Rescue and Retrieval

Health: (WASH, Medical, Nutrition,

MHPSS) Education Logistics

Emergency Telecoms

Managemethe Dead and

Missing (MD

DSWD Cluster Leads

Clusters

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The Regional Disaster Risk Reduction and Management Councils have similar structures as the NDRRMS with the Field Offices (FOs) of DSWD serving as Vice-Chair. The FO takes the lead in response when disasters occur in two or more provinces in its region.

The PDRRMA provides the allocation of a calamity fund in the annual budget as source

for disaster risk management. Other funding sources for disaster risk reduction, mitigation, and preparedness are embedded in the regular programs of agencies. The calamity fund is intended for disaster risk reduction, mitigation, and preparedness, which may likewise be used for relief, recovery, and reconstruction for calamities that happened during or two years prior to the current budget year. Thirty percent of the calamity fund is allocated as quick response fund (QRF) or stand-by fund for relief and recovery programs. Access to the calamity fund is based on the recommendation of the Council and is subject to approval by the President.

Since 2012, several agencies, including the DSWD have QRFs built into their budgets

which are not part of the Calamity Fund. This is to ensure immediate action during calamities.

Unlike the Calamity Fund, the QRF does not require the recommendation of the NDRRMC or

the approval of Office of the President (OP) to trigger the use and release of funds. When the

agency QRF gets depleted, the agency may submit a request to DBM for replenishment for

approval by the OP.

In regard to the role of local government units (LGUs), PDRRMA assigns LGUs primary

responsibility for local disaster response. This assignment is consistent with the provisions of the 1991 Local Government Code devolving to local governments the responsibility to provide for the social welfare and protection of their constituents. The LGUs are supported technically and financially by national government agencies. DSWD, in particular, enables LGUs51 to implement social welfare and development programs including disaster management through technical assistance, resource generation and augmentation.

With respect to the budget of local governments, they are mandated by the PDRRMA to

allocate not less than five percent of their local revenues as Local Disaster Risk Reduction and Management Fund, of which 30 percent constitutes the local quick response fund. Unexpended balance of the fund accrues as trust fund for disaster risk reduction and management available for use within the next five years.

2.2.2 DSWD’s Response Performance

In times of disaster, DSWD is expected to (a) provide leadership and coordination; (b)

readily mobilize and deliver material resources for disaster response; (c) be in the frontline for the delivery of disaster response assistance.

In localized disasters or disasters that happen in one region, this would mean simple

augmentation of the local government’s relief goods by the Field Office based in the region, and mobilization of its stand-by resources, as may be necessary.

However, in the event of a large-scale disaster which causes displacements of large

numbers of families, DSWD central office supports its Field Offices and the local governments. For this purpose, DSWD uses its stand-by QRF and replenishments from the calamity fund.

51

Along with NGOs, other NGAs, POs, and members of civil society, per Executive Order 221 series of 2003.

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DSWD’s involvement could be in one region, e.g., Zamboanga siege, or multiple regions as in the case of Yolanda. In these instances, the agency provides relief and protection, evacuation and camp management assistance, temporary shelter, and early recovery assistance.

Over the years, DSWD delivered valuable assistance to millions of beneficiaries. The

harrowing experience with Yolanda, however, exposed weaknesses that compromised the credibility of the agency’s response system. DSWD improved its performance in subsequent disasters by mobilizing additional staff, volunteers and successfully tapping resources of other organizations. Still, more improvements are needed, as shown by Typhoon Seniang.

DSWD recognizes that it can and should do better, moving forward. Lessons learned

from past disasters and post disaster reviews point to the following areas for improvement: (a) need for better logistics and supply chain management (including procurement, warehousing, transportation and communication) to ensure goods are available even in hard to reach areas; (b) lack of continually trained staff as reserve manpower to meet surges in demand for assistance brought about by multiple disasters hitting several geographic areas at close intervals; (c) lack of clear delineation of responsibilities and robust communication lines; (d) weak coordination and harnessing of the strengths of partner agencies, local governments, interagency bodies; and (e) need for locally appropriate service standards for disaster response comparable to international benchmarks. These are the findings from post-disaster operations review and feedback from central and field offices.

The “problem tree” below (Figure 2) illustrates in greater detail the weaknesses of the

current disaster response system of DSWD. The tree was developed based on the findings of a focus group discussion participated by representatives from DSWD’s central and field offices involved in the planning, programming management, implementation and funding of the agency’s disaster response operations.

188

Figure 2: Problem Tree Analysis of DSWD’s Current Disaster Response

This problem tree was developed based on the discussions of a focus group from central and field offices of DSWD who are involved in the planning, programming, management, implementation and funding of the agency’s disaster response operations. The focus group discussions were held on 12-14 January 2015 in Quezon City.

Not all affected individuals, families and communites are provided with adequate assistance

based on acceptable standards during disasters

Disaster assistance are

not readily available to

the affected individuals,

communi es and

families

Insufficient

stockpiles Delay in delivery

Transport and

other logis cs

support insufficient

and infrastructures

are unserviceable

Lack or absence

of local

government

stockpiles

Insufficient

LGU budget

for disasters

Duplica on

Lack of

coordina on

Poor targe ng

and

priori za on

Unsustained disaster

staff

a

ssi stanc e

Lack of

trained back

up

emergency

staff

Lack of

volunteers

Insufficient

programs to

con nuously

mobilize

volunteers

from

communi es

Depleted

stocks in

the

market

Delayed resump on of

opera ons of affected

private businesses or

permanent closure

Lack /unclear policies, guidelines and processes

Overextended

duty of

emergency staff

Insufficient

knowledge on

number and

characteris cs

of poten ally

affected

persons

Disaster

assistance are

of different

standards

Mul ple

agencies

providing

assistance

Insufficient

budget to

meet

Sphere

standards

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3. Policy and Strategy Framework 3.1 Analytical Foundation

Figure 3 presents a simplified overview of the key actors and mechanisms of the Philippine disaster response system and how they hang together. The diagram highlights the idea that human welfare is affected by shocks generated by natural and man-made events. Their impact and significance depend on the responses of the (i) State represented by the National Government (NG) and the Local Governments (LGUs), (ii) communities and their network connections of families, individuals and civil societies, and (iii) the markets with their price mechanism. The responses of these actors and mechanisms are themselves conditioned by geography, resource availability, technological and informational constraints, social norms, institutions (rules of the game) and quality of governance.

The market is a resource allocation mechanism using price signals to match demand

and supply arising from voluntary decisions of individual economic agents. During times of shortages brought about by disasters, prices go up to signal and motivate profit-seeking suppliers to bring their goods to areas with unmet demand. Private enterprises are also encouraged by the prospect of earning extra profits when they correctly anticipate shortages and stockpile commodities to be sold during times and in areas of shortages. The price system also reward enterprising businesses for correctly pre-positioning their stockpiles for timely and least-cost delivery to areas hit by disasters.

Of course, enterprises could also lose money, if their anticipatory decisions turn out to be wrong. This is the risk that enterprises take in return for extra profits. Incidentally, price

Figure 3. The Impact of Hazards depends on the Political, Economic and Social (PES) System reactions and interactions

Markets Local

Governments

Na onal

Government

Individual, Families, Communi es

and Social Capital

Shocks

Natural

Manmade

Outcomes

People’s

Wellbeing

PES System

190

surges and excess profits are expected to be eventually tempered by entry of additional suppliers into disaster areas provided by competitors.

In general, competitive markets are efficient in matching supply and demand.

Progressive economies rely on them. Countries formerly run by command and control mechanisms now also use competitive markets and the price system.

There are, however, reasons for not relying exclusively on markets for maximizing social

welfare. One is that there are situations of market failures, which are often expected to arise from the existence of risk and uncertainty. For example, markets for disaster insurance to cover losses from all hazards may be absent or incomplete due to moral hazards and adverse selection. Another reason is that people find it painful to watch fellow human beings suffer and die when prices surges make basic commodities suddenly beyond their reach because of poverty. The situation is not only painful to watch; it is also seen by many as morally and politically unacceptable, given the unfair distribution of income.

For the above reasons, the State in the Philippines, as in most other countries, provide some forms of safety nets to Filipinos, including inter alia emergency and relief assistance for disaster affected communities and families. For the same reasons, expenditures for safety nets are considered a public good and, therefore, largely financed by tax revenues. Without public funding, safety nets would be under-provided, making Philippine society worse off on the whole.

The State represented by NG and LGUs provides the mechanism to get individual

economic agents to reallocate resources to under-provided goods by using appropriate subsidies and/or legal enforcement mechanism. The role of the State in this regard is divided by two agencies, as previously discussed. LGUs have been assigned by law the primary responsibility for disaster response. They have the autonomy to carry out social assistance activities suitable to the needs of their constituents. This arrangement makes sense, conforming as it does to the principle of subsidarity. There is, though, the financial allocation issue between NG and LGUs that needs to be fixed. Moreover, there is the issue of high manpower turnovers and frequent re-training of LGU staff due to the short local political cycle of 3-years.

The NG role is augmentative. Its responsibility is to enable LGUs technically and

financially to provide more and better assistance to their constituents, especially the economically hard up. More generally, NG provides the mechanism for levelling up the ability of communities to respond to disasters – ideally according to some agreed minimum social standards. This NG role keeps national solidarity and social cohesion strong.

Government solutions can be very helpful. As with markets, however, they cannot and

should not be relied upon exclusively. Just as there are market failures, there are also government failures. Government agencies often fail to efficiently deliver on time needed assistance to people that need it most. The reasons for government failures relate to underfunding, weak performance incentives, and other governance issues.

Recent literature looks at the potential of communities as a mechanism for disaster

response.52 Traditionally, discussions on disaster approaches have focused on factors external to affected communities. Today, social science evidence and lessons from experience point to the importance of bringing communities to the forefront of disaster response and risk

52

See Aldrich, Oum, and Swada (2014)

191

management. Studies have shown that communities with high social capital are able to positively influence the trajectory of post-disaster response and recovery.53

Social capital means the network of connections among members of a community that

produce good will, shared values and understandings, motivating and enabling individuals and groups to trust and help one another, work together, and care for each other. In a well-connected community, people know the particularities of their locality. They know each other and relate to each other as relatives, friends and neighbors. They generally agree on social norms for which they have developed enforcement mechanisms (e.g. through naming and shaming). Not surprisingly, therefore, communities with high social capital have better developed schemes for mutual aid and informal safety nets, including micro-insurance and micro-lending. Social capital facilitates pre-disaster and post-disaster collective actions by communities, including self-policing of community-driven projects and social watch over market and government behavior. In the Philippines, social capital is reflected in its “bayanihan” tradition.

In thinking about the role of communities and families in disaster response, it is

important to regard them not just as objects of assistance but also as autonomous human beings responsible and empowered to chart their own future and their responses to challenges. With this perspective, assistance that empowers them and strengthens their social capital should be a central part of the country’s response and recovery process. NCDDP with its focus on community-driven development and Pantawid Pamilya with its active citizenship FDS module can make valuable contributions to building up social capital for disaster response. It is noteworthy that social capital, if not used and reinforced, will deteriorate, if not lost.

Despite promising returns from social capital investments, however, community-based

disaster response has its own weaknesses. First, investment in collective action needed for relief and recovery will remain a challenge. Free riding will remain a temptation, although this could be mitigated by investing in more active citizenship formation and stronger community network connections. Second, issues of equity cannot be addressed adequately by leaving resource-starved communities to their own devices. Some redistributive transfers are needed for which the coercive power of the State is required. Third, limiting risk pooling to actions by individual communities would be inefficient. For efficiency, a wider risk pooling is necessary.

Where does the above discussion leave us? It is clear that each of the

actors/mechanisms portrayed in the diagram above has important roles to play. However, on their own, they cannot offer disaster response solutions that are completely optimal. The conclusion, then, is that there is no single magic bullet for getting the country’s disaster response and risk management system up to standards. Therefore, the sensible thing to do is to choose an approach that combines the best of the free enterprise system, State (NG and LGU) interventions, and communities with their social capital. In this regard, the design of an optimal disaster response system should exploit opportunities for complementarities among the various elements of the system rather than create overlapping substitutes. Finally, government agencies should focus on issues that fit their core mandates and competencies.

53

See Aldrich (2014)

192

3.2 Objective of DSWD’s Disaster Response System Reforms

DSWD seeks to develop a high-performance, compassionate and accountable disaster response system. In line with the above goal, the system’s objective is to adequately assist individuals, families and communities affected by disasters in a way that conforms to global norms and best practices, appropriately adapted to local conditions.

A high performance system has many distinguishing characteristics. Timeliness of

response is one of them. In ordinary and extraordinary times, a high performance system must be able to deliver on time urgently needed assistance. Victims of disasters need immediate comfort as they are unable to provide for their own basic needs, while they deal with their losses. Affected families facing devastation and financial hardships need timely recovery assistance to be able to get back on their feet as soon as possible.

Aside from being timely, the envisioned system must be effective and efficient. To be

effective, the system must be capable of meeting higher service standards that are affordable and culturally sensitive. Such capability is necessary to satisfy rising public demand for improved disaster response. On this score, Sphere norms, appropriately adapted to local conditions, can be highly useful.

To be efficient, a system must ideally be able to produce and deliver outputs and

outcomes at the lowest cost. In light of the new normal, greater efficiency is necessary to allow expansion of system coverage and to be able to comply with improved service standards, while keeping cost affordable. On this point, a high performance system would benefit from drawing on the advantages of competitive markets and private enterprises, whenever possible.54

Efficiency also means adaptability. Before the new normal phenomenon, it was efficient

to keep just enough number of workers to provide assistance one disaster at a time -- the contingency plan being that existing personnel can be divided up and made to work overtime in multiple shifts to deal with the possibility of an additional disaster coming their way.

In the new normal, however, issues regarding the sustainability of high quality service

could seriously arise when workers are over-utilized and exhausted. Highly motivated and energetic workers run the risk of burning themselves out. This observation means that under the new normal, having some redundancy in manpower and appropriately trained standby reserved force would be efficient. These reserves would help un-burden over-worked personnel and allow them to rest and recover for another disaster.

In regard to the compassionate feature of the envisioned disaster response system,

what does it mean – and why is it important? A compassionate system means providing effective assistance to all affected persons who urgently need help. In the implementation of this inclusiveness principle, however, priority will be given to the poor households and the following population groups: persons most vulnerable to life-threatening and crippling consequences, persons with disabilities, senior citizens, pregnant and lactating mothers, indigenous peoples, children especially orphans, and internally displaced persons. The vision here is to ensure that the response system will be more strongly equitable by prioritizing hard up and highly vulnerable people.

54

Severe market failures can happen during disasters due to destruction of infrastructure, and transportation facilities and security problems. In this case, assistance would have to be delivered using available military and other government assets.

193

The vision articulated above is consistent with the Philippine value system. As eloquently

expressed by President Ramon Magsaysay, the government must give more in law to those who have less in life. In this succinct statement three important ideas converge: the rights-based approach, preferential options for the poor, and the virtue of human compassion.

Disaster assistance is a public good rooted in human compassion. This is an important

concept to recognize because its implications are far-reaching. First, the idea strengthens the claim that indeed spending on disaster relief and early recovery is a public good. This is highly relevant, noting that disaster response and management is currently underfunded (discussed above). Second, nurturing the virtue of compassion among Filipinos would animate voluntary work in disaster response. Third, it would reinforce deeper respect for the human rights approach and the idea of preferential options for the poor, as they apply to disaster response issues. Fourth, nurturing compassion and, therefore, empathy would lead to the development of a greater sense of solidarity and social cohesion among Filipinos -- critical factors for maintaining a stable and progressive society.

Finally, the response system must be accountable. One of the hallmarks of an

accountable system is transparency in regard to achievement of agreed targets and compliance with government budget and financial rules, On this score, performance indicators need to be established. The following are examples of performance indicators that would enhanced the accountability of the country’s disaster response system::

(i) Number of persons and families served out of those affected by disaster and

needing assistance for relief and early recovery relative to agreed targets

(ii) Number of persons and families receiving urgently needed relief and early

recovery assistance according to agreed service standards and relative to

agreed targets

(iii) Percent of high priority affected persons and families served out of the total high

priority affected population urgently needing assistance (relative to agreed target)

(iv) Compliance with government financial and budget reporting requirements and

absence of adverse COA opinion that has not been satisfactorily explained

(v) Indicator of response readiness relative to accepted standards and target

The above measures should be viewed as indicators for the disaster response

performance of the national system as a whole and not of individual agencies concerned.

For the accountability of DSWD’s disaster response performance itself, the focus

will have to be on its accomplishments in assisting LGUs, NGOs and other civil societies. The indicators should relate to DSWD’s core mandate of enabling and motivating them to deliver the assistance urgently needed by affected people, in accordance with agreed service standards mentioned above. This definition of what should be the focus of DSWD performance accountability is consistent with current laws and executive orders on the mandate, roles, and functions of DSWD and LGUs (discussed above). With this focus in mind, DSWD’s performance indicators will be measured along the follow lines:

194

a. Value of DSWD financial and technical (cash and in-kind) assistance received by

LGUs for relief and early recovery relative to LGUs’ needs and capacity

b. Number of LGUs receiving needed disaster relief and early recovery assistance from

DSWD according to agreed service standards

c. LGU satisfaction rating of the timeliness and adequacy of DSWD financial and

technical assistance provided to LGUs needing disaster assistance for relief and

early recovery

d. Percent of highly vulnerable and low income LGUs receiving financial and technical

assistance for relief and early recovery assistance (relative to total LGUs)

e. Indicator of DSWD response readiness to provide affected LGUs urgently needed

assistance for relief and early recovery

f. Compliance with government financial and budget reporting requirements and

absence of adverse COA opinion that has not been satisfactorily explained in regard

to DSWD disaster relief and early recovery assistance.

3.3 Policies No one shall be left behind, but assistance should be prioritized according to urgency of needs and financial ability.

Disaster response must be inclusive, prioritizing highly vulnerable people, families and communities with urgent needs, and the poor who are unable to provide for their own needs. It is important to have knowledge of these potentially affected groups: who they are, where they are, what their needs are, and what their capabilities are. Empowering individuals, families and communities to help themselves.

The DSWD will bring to the forefront the role of individuals, families, and communities in disaster response and risk management. The policy idea here is to build up the social capital of communities (defined in Section 3.1 above), utilizing it (i) to organize, plan, and implement their disaster response plans and (ii) to facilitate collective action for pre-disaster preparedness and for post-disaster response and early recovery. As mentioned, communities, families and individuals should be viewed not just a recipients of assistance but, equally important, also as contributors to the development of a high performance and compassionate disaster response system.

Through the LGUs and civil societies, including faith-based organizations, DSWD will provide technical and financial support to the communities. A part of DSWD assistance to build social capital for disaster response can be done through the NCDDP. Another part of the support can be undertaken through the Pantawid Pamilya, particularly through the active citizenship module of the FDS as well as the Municipal Action Teams (MAT) and their Municipal Transition Planning. Prepared individuals, families and communities will help reduce the scale of disasters in terms of affected persons. They can be counted on to reduce their hazards, have their own emergency plans, organize themselves for safe evacuation, and provide rescue assistance when needed.

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LGU-NG alignment of responsibilities and resources through strategic proactive augmentation, capacity building, and knowledge management

The responsibility for responding to disasters begins at the local level. Disaster management, including preparation and training for effective response, is a core obligation of local government units in the Philippines. However, local governments are differently situated. Some are more vulnerable than others in terms of geographical location. They have different income levels for disaster risk reduction and management.

DSWD seek to implement its augmentation policy more proactively. In general, augmentation shall be upon request, but in local governments that have historically been unable to stockpile enough goods, strategic proactive augmentation shall be adopted ensuring that field offices have pre-positioned goods ready to augment local supplies. Overtime, LGUs shall be capacitated to raise their capacity levels for response, starting with a good set of information on individuals and families and their vulnerabilities. This will require disaster response planning and a monitoring scheme to regularly update the database and track assistance provided. Focus on DSWD’s fundamental mandates and develop its core competencies accordingly and take advantage of its current social protection programs

Disaster response is urgent, complex, and multidimensional. Building core competencies takes time, as disasters bring in new challenges and lessons, constantly innovating in order to keep ahead. For an agency with social protection as primary mandate, it will always try to find ways to deliver the needs of affected people. While this may be acceptable as short-term adjustments, it is important to redirect activities outside their fundamental mandates back to whoever is responsible and have the resources and capabilities to do these. Instead, cross-pollination of internal programs can be done among social protection programs such as Pantawid Pamilya, Livelihood Support Program and the NCDDP to build their adaptive capacities that will allow individuals and communities to bounce back to normalcy. By not compartmentalizing mandate as disaster or non-disaster related, each group can benefit from each other as they work on common beneficiaries, common databases, and shared objectives of poverty alleviation. Use more cash instead of in-kind assistance, whenever feasible

In designing social protection programs, it is mandatory to employ the most efficient design and means for delivery of safety net program benefits to their target beneficiaries. A critically important issue here is the use of cash versus in-kind assistance. Until recently, the Philippines and most other countries relied mainly on in-kind assistance. Global experience with cash transfers programs (e.g. Pantawid Pamilya and Cash for Work programs), however, indicates that designed appropriately with the right safeguards, social assistance in the form of cash transfer could be cost-effective. It would reduce waste and other leakages. It would also lower the burden on DSWD workers, freeing up their valuable time to serve more affected people, especially those in hard-to-reach and isolated areas that are unconnected to modern communication and banking facilities. Equally important, cash is a flexible form of assistance that would allow beneficiaries to buy things according to their specific needs and conditions.

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Collaboration with private enterprises and nongovernment organizations, taking advantage of their unique strengths and the efficiency of markets

To build an optimal disaster response system, the country should follow an approach that combines the use of markets and private enterprises, the power of the State through NG and LGUs, and the social capital of communities, families, and individuals. Private enterprises, in a competitive market setting, have the incentive to be efficient and timely in the pre-positioning and delivering goods to beneficiaries. The social capital of communities should be tapped to raise the contributions of communities, families and individuals to the country’s disaster response system.

Government cannot work alone in protecting the lives and property of citizens. In all facets of disaster response, private enterprises and nongovernment organizations are partners. Government count on private enterprises to provide protection of their employees in the workplace, they provide much needed lifelines such as water, power, communication, transportation, medicines, hospital care. They are counted on to ensure that supply chains are functioning and goods are made available to affected persons.

A quick rebound of businesses will also lessen the impact of disasters as affected employees regain back their income and normalcy in the economy is achieved as well. Private enterprises and nongovernment organizations are also important partners of government in disaster response: in mobilizing donations in cash and in kind, mobilizing volunteers for disaster response, and even in the actual provision of disaster response. Government can learn from good business practices of these groups.

For the markets and private enterprises, however, to be able to play their roles well, the functions of price signals in a competitive free enterprise system (as explained above) must be better understood by national and local officials as well as the general public. On this score, government agencies should be careful about imposing prolonged price controls in disaster areas. Note that in an area declared to be in a state of calamity could mean that price control of basic commodities can last for up to two years. These controls could lead to price distortions that discourage delivery of basic commodities to affected areas. Counter to good intentions, price controls can prolong shortages and delay return to normal prices. Moreover, the controls could blunt anticipatory behavior of enterprises. On this score, it would be desirable to conduct research about the time it takes for markets to function normally in the allocation of basic commodities and resources. Accountability and transparency appropriate to an emergency

DSWD will work with DBM and COA to develop budget rules and financial controls appropriate to disaster situations. Disaster situations shall not be an excuse for not being able to maintain accountability and transparency in the management and appropriation of funds. Based on past lessons, the agency shall institute safeguards to meet documentation and process requirements prescribed by law, including alternate signatories to financial transactions. It may also put in place systems and processes to be able to monitor use of funds, anticipate emergency spending to allow enough lead time for compliance, while at the same time ensuring that the funds spent and services delivered are appropriate and effective. For example, pre-approved safe transition housing locations will do away with problems of identification, geo-hazard assessments and negotiations for use of land for temporary shelter when disaster comes. Accountability and transparency shall also be exercised in handling donations and in

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meeting the disaster response needs of the population. All these arrangements could minimize delays in execution and liquidation of funds.55 Learning from experience and knowledge management

Preparedness to respond is a critical aspect of DSWD’s disaster response system. DSWD should go through the collection of data, development of policies, procedures, assistance agreements, training and equipping agency responders and volunteers. Beyond these, the agency shall strengthen preparedness to respond by executing drills and simulation exercises. This activity will provide opportunity to test disaster response plans, policies and procedures to improve proficiency. As post-disaster response operations review has been institutionalized and lessons learned as basis for adjustments, drills and exercises will further strengthen the culture of evaluation and learning within the agency. 3.4 Strategies

Following the objectives and policies laid out above, DSWD will pursue the goal of establishing a high performance and compassionate disaster response system through the following strategies: Implement a human resource development program covering back-up manpower support, capacity building, incentives, volunteer mobilization, safety and insurance protection plus other legally allowable benefits, to prepare DSWD to respond adequately and sustainably to disasters

DSWD will establish an adequate back-up support system that is capable of efficiently

meeting huge surges in demand for DSWD disaster response assistance. The agency will

accordingly lay down required qualifications, skills, and proficiencies to meet standards

comparable to international norms and practices. Recruitment, human resource development

and performance assessment programs shall then be built on those standards. Responders

from the agency must be trained to manage and anticipate risks in the disaster scenes, properly

equipped with personal safety kits and provided with insurance protection commensurate to the

risks they face.

A unified agency response requires mutually supporting capabilities. Thus, management

and staff alike shall be equipped with appropriate knowledge and skills that match their levels of

responsibilities. In times of disasters, it is critical for DSWD to bring together volunteers to

assist agency responders. In partnership with local governments, other government agencies,

and non-government organizations, DSWD shall aim for a systematic program for volunteers

that produce the required skills and proficiency. It will also work towards certification standards

of its volunteers, consistent with agency baseline performance requirements. All of the above

ideas will be carried out in the context of a strengthened recruitment system that supports quick

manpower expansion and demobilization when needed. They will also be implemented in close

collaboration with the LGUs, noting its role as primary responders and the issue of the lack of

training of their workers in part because of their high turnover rate due in part to the short 3-year

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These arrangements could alleviate negative findings of COA in the use of government funds for disaster response.

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local political cycle.

Secure adequate financial support for DSWD to be able to comply with higher standards of disaster assistance

National standards are often compared with the higher standards of disaster assistance provided by Sphere-compliant organizations. Additional resources will be needed for DSWD to meet Sphere56 standards adapted to local conditions. The most critical is the space per person of evacuation centers. These additional resources must be secured to address this basic concern on evacuation centers. Enough additional resources must be obtained to also address the issue of disturbance in children’s and youth’s education caused by the use of public schools as evacuation centers. DSWD shall promote the adoption of guidelines for the construction of new evacuation centers that meet global space standards. Implement on-demand logistics systems that relies on market-based strategies and private enterprises, except in situations when it is not feasible and will require military assets to be employed

Disaster response material resources need pre-positioning and timely replenishment. Large-scale incidents may require sophisticated coordination and deployment of resources through an integrated logistics system which must be in place ready to support ongoing disaster response operations. DSWD must explore new schemes involving prearranged agreements and contracts with private enterprises so that goods are made available at the right time and at the right places. Advanced contracting will improve the agency’s ability to secure supplies and streamline processes for procurement, delivery, and distribution of resources when needed.

Parallel to this, DSWD may also use as alternative, cash assistance when shown to be feasible and more efficient than in-kind assistance.57 This will lessen the burden of disaster response operations involving securing food and material needs for a large number of displaced people. Adopt with DILG as Vice-Chairman for Disaster Preparedness an operational set of guidelines that will implement the strategic proactive augmentation policy and provide assistance to build capacities of LGUs to meet disaster response mandates

A joint circular with DILG shall be pursued to clearly define when DSWD augmentation shall be provided, cognizant of LGU primary roles in disaster response. Local government responsibility and resources for disaster risk reduction and management was strengthened under the PDRRMA of 2010. However, LGUs are not able to uniformly comply given different levels of capacities -- in terms of manpower, financial resources and know how. It is likely that there is considerable mismatch in responsibilities and financial support especially in high-risk rural areas.

Local governments must be classified in terms of risks and vulnerabilities; and their financing capacities, at least for response, must be evaluated for sufficiency. A precondition for

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Sphere standards are internationally recognized sets of common principles and universal minimum standards in life-saving areas of humanitarian response. These standards were developed by the Sphere Project which is governed by representatives of global networks of humanitarian agencies. (http://www.sphereproject.org/about/)

57

Refer to Cash for Work and Pantawid Pamilya Cash Transfers for Yolanda victims

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this is that DILG is able to classify the local government units with assistance from agencies mandated to analyze the risk from various hazards such as PAGASA, PHIVOLCS and MGB. For low risk areas, high-income local governments, the policy of augmentation can be upon request by the local governments to DSWD. However, for high-risk low-income local governments, helping them fill up the gaps of potential demand and their resources for quick response, may be fulfilled by providing budget subsidy or augmenting stockpiles. DSWD field offices in these areas can build on more stockpiles, or should have ready mechanisms for augmentation from other field offices. Harmonize information management tools on disaster response and social protection to strengthen targeting, prioritization and impact evaluation.

DSWD is implementing and managing several databases for its social protection programs as well as for disaster response, most likely covering the same population segment. To avoid respondent fatigue and at the same time promote operational efficiency and effectiveness within the agency, these information tools must be harmonized if not unified into one. The end objective is to come up with an information system that allows for effective targeting, prioritization and impact evaluation both of its disaster response and social protection programs. DSWD will endeavor to harmonize its data collection with local government units which already employ several instruments for data gathering and databasing. Develop in collaboration with appropriate government agencies and private stakeholders disaster insurance models for relief and early recovery, including schemes providing premium subsidies targeted to Pantawid Pamilya beneficiaries and other poor and near-poor households

DSWD’s social protection programs such as the Pantawid Pamilya, SLP, and NCDDP provide opportunities for building adaptive capacities to mitigate the impacts of disasters on the poor as well as facilitate early recovery. In the light of increasing intensity and impact of disasters, DSWD, in collaboration with other stakeholders, can develop micro insurance and other risk-pooling schemes as instruments for spreading risks and protecting low-income households and businesses against catastrophic disaster losses. Micro insurance can provide access to post-disaster liquidity thus protecting assets and livelihoods, particularly of the poor. But other schemes such as weather index-based national disaster insurance system should be explored. These schemes can help build the coping capacities of the poor and near poor who reside in disaster prone areas, hopefully reducing the number of families needing response assistance in the event of a disaster. The development of a combination of disaster insurance schemes covering families, communities and LGUs would reduce the burden on DSWD manpower and allow their redeployment to meet surges in demand for assistance.

In crafting disaster risk sharing schemes, public subsidy of premium could be consider but it is critically important to avoid seriously distorting people’s incentive to work hard and save money for the rainy days. Formulate operational guidelines for DSWD as Vice-Chair for Response of NDRRMC

In large-scale disasters requiring activation of “whole of” government actions through the NDRRMC, the Secretary of DSWD as Vice-Chair for Response is expected to provide leadership in the response effort. When response also involves the international aid community, the UN Interagency Standing Committee’s Humanitarian Clusters are activated with DSWD as country lead for the Protection, Camp Coordination and Management, and the Food and Non-

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food Items. These bodies bring together Cabinet officers and other department or agency heads to ensure coordinated efforts, provide strategic directions, and update the President on the status of response efforts. Coordinating structures and leadership are in place, but there is a need to clearly define processes and protocols, delineate roles and responsibilities, and establish coordination mechanisms. The recently adopted pre-disaster risk assessment can likewise be built into response protocols as this would involve assembling interagency resources ready for pre-positioning.

DSWD can likewise orchestrate drills and exercises within these interagency bodies to simulate interagency coordination and communications, determine gaps, and identify opportunities for improvement. DSWD can benefit from these operational guidelines and interagency drills, as succession in leadership and Secretariat support are needed to ensure management and coordination of interagency response initiatives. Adopt in collaboration with DBM guidelines and control measures for program planning and expenditure management appropriate for disaster situations; and institute financial, allocation, disbursement, utilization, reporting and liquidation procedures adaptive to emergency situations and consistent with COA rules and regulations

DSWD shall institute reforms in financial management starting with a clear delegation of authority during disasters. This is essential in order to define principal and alternate signatories and to pinpoint responsibilities and accountabilities.

It shall advocate for clearer rules in the utilization of the QRF, particularly in the use of allocations that have not been fully spent after a particular disaster. A mechanism may be developed to allow DSWD to use these unutilized balances in the event of a large-scale disaster response.

A system of expenditure component classification must be identified (e.g. cash for work, core shelter assistance etc.) for better reporting and accountability of disaster response activities. This expenditure component classification can serve as the basis for a unified database at DSWD.

Funds for disaster response must allocate a portion for administrative cost as certain activities require special skills that may not be available from existing manpower resources. 4. Way forward

DSWD is determined to immediately improve its disaster response and management in accordance with the policies and strategies articulated in this paper. Towards this end, it is launching a three-point start-up program for their effective and sustained implementation. The program includes the following actions: Development of a road map, multi-year action plan, and research and development agenda. These documents will provide the details of time-bound actions that DSWD is committed to take to level up its capabilities and practices to the needs of a compassionate high performance disaster response system. This will include among others the establishment of service standards and indicators to monitor disaster response outputs and outcomes and track progress in the implementation of the action plan. Activities here would include studies on budgetary and

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manpower needs and pre-positioning strategies that would meet the requirements of the new normal and improved standards based international best practices adapted to local conditions. It will also look at the viability of alternative disaster response schemes being proposed in this framework such as the cash assistance and risk insurance, among others. Review, revision and compilation of DSWD’s operations guidelines, including the establishment of guidelines spelling out the responsibilities of DSWD as Vice Chairman for the Response cluster

The output of the activities here is the compilation of written and unwritten operational guidelines. They are updated to ensure that they are consistent with the provisions of the DSWD’s strategic policy framework and that current weaknesses and gaps in the operations guidelines are effectively address. On this score, the DSWD is currently in the process of completing DSWD Disaster Response Operations Guidelines. This document is a major part of DSWD efforts to adapt its disaster response to the new normal. It lays out the roles, responsibilities and functions of DSWD personnel during times of disaster for different alert levels. The underlying purpose of the Guidelines is: (i) to make DSWD personnel understand that all have specific roles, duties and functions during disasters; and (ii) to let each of them know what specifically their responsibilities are, for which they will be held to account.

Development and implementation of orientation and communication programs on DSWD’s Strategic Policy Framework

These programs are intended to secure three things: (i) the informed support of DSWD staff, its partners and the general public to its Strategic Policy Framework ; (ii) political support for the implementation of the Framework; and (iii) training of DSWD personnel for mastery the DSWD Disaster Response Operations Guidelines, including drills and simulation exercises.

Producing and making available user friendly pull-outs containing operations guidelines for a series of specific topics This is to facilitate easy access by DSWD staff and partners to user friendly references. 5. Conclusion

DSWD is committed to assisting all Filipinos in the aftermath of disasters to help them through desperate times and get them back on their feet to carry on with their lives. It is also committed to help the country prepare for multiple and more devastating disasters to come.

Over the years, the agency and its partners have provided millions of affected families

and individuals urgently needed assistance. This came in the form of basic food and non-food commodities, temporary shelter and early rehabilitation activities.

Arguably, DSWD’s current disaster response system works – but up to a point only and

imperfectly. Some improvements in the system had been made, learning from the weaknesses and gaps in current capabilities and practices exposed by recent disasters like Yolanda.

But much more needs to be done and can be done to meet the challenges of the new

normal and the public demand for higher standards of service. This message is supported by several post-disaster assessment reports, feedback from victims and frontline workers, and predictions about climate change.

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DSWD has taken the above message to heart and is resolved to meet those challenges head on. The strategic policy framework articulated in this paper lays out how DSWD will deal with those challenges. On this score, the framework calls for sustained step by step establishment of a high performing, compassionate and accountable disaster response system.

The envisioned system would be capable of meeting the challenges of the new normal

and the higher service standards demanded by the Filipino people. DSWD is firmly resolved to follow the course of action prescribed in its strategic policy

framework. And it is optimistic that following the framework, it will attain the envisioned disaster response system.

Nonetheless, the agency does not underestimate the implementation tasks ahead.

Therefore, it will pursue proactive collaboration with its partners and other relevant institutions like the DBM, COA, LGUs and DILG.

The success of establishing a high performing, compassionate and accountable disaster

response system worthy of a modern society will critically depend on that collaboration. But most of all, it would depend on people helping people in good times and in bad

times. DSWD will, therefore, seek to unlock people’s energy, enthusiasm and ability to help themselves and their neighbors. The plan is to engage ordinary folks, civil societies and business in sustained dialogue and active collaboration.

Establishing an adequate disaster response system requires sacrifice and devotion by

DSWD personnel and its partners. But the rewards are worth it. Beyond the enjoyment of timely and expanded assistance, the rewards will come in the form of development of a caring, secure, inclusive and stable society – a necessary foundation for social and economic progress. More concretely, a successful disaster response system should make our poor, vulnerable and disenfranchised people feel the helping hand of the State. It will show that DSWD is on their side at precisely those moments when they are desperately in need of help.

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References: Daniel P. Aldrich, Southea Oum, and Yasuyuki Sawada. 2014. Resilience and Recovery in Asian Disasters: Community Ties, Market Mechanisms, and Governance, Economic Research Institute for ASEAN and East Asia (ERIA), Springer Tokyo.

Daniel P. Aldrich, 2014. Social Capital in Post Disaster Recoverty: Strong Networks and Communities Create a Resilient East Asian Community. In Aldrich, Oum and Sawada (2014).

Danilo C. Israel and Roehlano M. Briones. 2012. Impacts of Natural Disasters on Agriculture,Food Security, and Natural Resources and Environment in the Philippines. Philippine Institute of Development Studies. Makati City.

Danilo C. Israel and Roehlano M. Briones. 2014. Disasters, Poverty, and Coping Strategies:The Framework and Empirical Evidencefrom Micro/Household Data - Philippine Case. Philippine Institute of Development Studies. Makati City.

Department of Budget and Management. Basic Information on the Calamity and Quick Response Funds. Manila. www.dbm.gov.ph Department of Social Welfare and Development (DSWD). March 2014. Post-Disaster Operations Review. Quezon City. DSWD. June 2014. National Disaster Response Plan for Hydrometeorological Hazards (Draft). Quezon City. Internally Displaced Monitoring Centre. 2014. Global IDP Figures. http://www.internal-displacement.org National Disaster Risk Reduction and Management Council (NDRRMC). 2011. National Disaster Risk Reduction Management Plan: 2011-2028. Quezon City. Official Gazette of the Philippines. Republic Act No. 10121 of 2010, An Act Strengthening the Philippine Disaster Risk Reduction and Management System, Providing for the National Disaster Risk Reduction and Management Plan. Manila. Official Gazette of the Philippines. Republic Act No. 7160 of 1991. Local Government Code. Manila. Sphere Project. 2011. Humanitarian Charter and Minimum Sandards in Humanitarian Response. www.sphereproject.org

UNU-EHS, Alliance Development Works, et.al. World Risk Report. 2014. www.WorldRiskReport.org

TA 7733-PHI - Support for Social Protection Reform: Final Report

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