PHILIPPINES PANTAWID PAMILYA ONDITIONAL ASH TRANSFER...

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PHILIPPINES PANTAWID PAMILYA CONDITIONAL CASH

TRANSFER AND SANITATION IMPACT EVALUATION: OVERCOMING BARRIERS TO ADOPTION OF SANITATION FOR POOR

HOUSEHOLDS IN THE PHILIPPINES

SIEF BASELINE VALIDATION REPORT

Team composition: Edkarl Galing (Water & Sanitation Specialist, co-TTL), Claire Chase (Economist, co-TTL), Christian Borja-Vega (Economist), Paul Gertler (Principal Investigator),

Joshua Gruber (Co-Principal Investigator), Allan Lalisan (Field Coordinator)

February 2016

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Table of Contents Background ............................................................................................................................................... 3

Implementation Partners and Investigators ............................................................................................. 4

Intervention Design ................................................................................................................................... 5

Data Collection .......................................................................................................................................... 9

Program Assignment to Treatment and Control ...................................................................................... 9

Sampling strategy .................................................................................................................................... 10

Baseline survey implementation ............................................................................................................ 12

Analysis of household income ................................................................................................................ 13

Baseline Balance Checks And ASSET WEALTH DISTRIUBTION ................................................................ 15

Risks and implementation timeline ........................................................................................................ 17

Appendix: Descriptive Statistics and Baseline balance ........................................................................... 19

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BACKGROUND

Access to basic sanitation remains one of the largest development challenges in the Philippines as 26% of the

total population is without access to improved sanitation facilities. In rural areas alone, access to improved

sanitation is less than 70% or about 9.5 million people, with 5.7 million of them defecating in the open and 3.7

million using unimproved toilets1. A study conducted under WSP’s Economics of Sanitation Initiative estimated

that the country lost 1.5 percent of its GDP in 2005 due to the costs of poor sanitation (Hutton et al., 2008). Rural

and poorer populations in the Philippines face the most barriers to accessing basic sanitation services, and

disproportionally incur the greatest economic and human capital losses of living in unsanitary and unhygienic

environments. Household latrines provide substantial health and other welfare benefits to users (Dangour et al.,

2013; Fewtrell et al., 2005; Curtis & Cairncross, 2003; Cairncross, 2010) as well as positive development outcomes

to others in the community (Hammer & Spears, 2013; Andres et al., 2014; Gunther & Fink, 2010), yet ownership

of sanitary household latrines is uncommon among the poor.

With limited capacity for investment from local governments, and the unsustainable nature of top-down

subsidization, it is imperative that sustainable and economically viable approaches are developed to increase

access to sanitation. Since the 1990s, community led total sanitation (CLTS) and similar approaches have

demonstrated success at increasing household demand (Mukherjee & Shatifan, 2010). However, despite some

success with CLTS, it has not proven to be a comprehensive strategy in all contexts (Ahmed, 2008; Mukherjee &

Shatifan, 2010; Tremolet, 2011). Rural sanitation programs have increasingly adopted social marketing as a tool

to reach the poor and underserved, combining demand generation, such as through CLTS, with private sector

marketing tools and sanitation product development to increase availability, affordability and desirability of

toilets. However, the effectiveness of these programs in achieving take-up of household toilets has been uneven,

particularly among the poor. A randomized intervention in Indonesia found households exposed to demand

generation elements of the program built toilets at a higher rate than those in control households; however

there was no significant increase in access to safe sanitation. In other words, either households that already had

access to safe sanitation made improvements, or the toilets constructed did not meet the quality standards to

be considered improved. Moreover, all of the effects on toilet construction were driven by households in the

upper wealth quintiles (Cameron, 2010). Conversely, a similar program in Tanzania that combined CLTS with

marketing of a low-cost sanitary slab for installation over dry pit latrines achieved substantial increases in toilet

construction, which did translate into a 15.7% increase in access to improved sanitation; although these increases

were not sufficient to result in health impacts (Briceno et al., 2014).

The high cost of sanitation is consistently cited by poor respondents as the main barrier to adoption of improved

toilets, yet household surveys show ownership of other durable goods of a similar price range. Poor households

face liquidity constraints that make it difficult to purchase durable goods requiring large lump sums of cash

(Banerjee & He, 2003; Mullainathan, 2009; O’Donahue, 1999), thus easing these constraints, by smoothing

consumption over time, may make them more willing to adopt beneficial durable goods such as household

latrines (Dupas, 2011). Consumer credit has been applied successfully to increase take-up of household piped

water connections (Devoto et al., 2011), clean cookstoves (Levine, 2012) and insecticide-treated bednets (Tarozzi

et al., 2012 ), but there is limited experimental evidence of consumer lending for sanitation, particularly among

1 Family Income and Expenditure Survey, 2009

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poorer households. The only experimental study of consumer lending for sanitation took place in Cambodia, in

which households were randomly offered financing to purchase a latrine at the market price of USD 50; the offer

of financing dramatically increased latrine uptake (IDInsight, 2013). In Vietnam, revolving funds administered by

the Vietnam Bank for Social Policy have been used to finance septic tanks and sewerage connections for low-

income households (Trémolet et al., 2010), while direct toilet micro-loans have been provided through MFIs in

India and Tanzania (Trémolet & Muraka, 2013). Recent experience demonstrates that socially-oriented MFIs can

help to increase access to sanitation among the poor by offering small loan sizes and ensuring that application

processes are poor inclusive (WSP, 2014).

The current consensus in the sanitation sector is that creating demand through promotion and education alone

(e.g. CLTS) will not have a sizeable impact on the uptake and use of sanitation products and services among

households that are financially constrained. Rather, it is necessary to simultaneously address the financial

constraints of these households in order to allow them to act (i.e., make a purchase) in response to demand

created through promotion (Tremolet, 2011; Trémolet et al., 2010; Baskovitch, 2011). While financing and saving

products can enable households that cannot afford a lump sum payment to smooth this cost over time, some

households will never have enough cash to afford a toilet. For these households subsidies may be the only means

of acquiring adequate sanitation.

Thus a key knowledge gap in the sector is how best to address the financial constraints the poorest face in

acquiring sanitation products and services. Leveraging an existing poverty targeting system to identify

households in need of financial support such as savings, loans, or hardware subsidies, and mainstreaming

sanitation promotion and demand generation into a large-scale conditional cash transfer (CCT) program could

substantially reduce the transaction costs of targeting sanitation services to the poor, who are most in need.

When conducted in the context of a robust supply of affordable and aspirational sanitation products, the

approach has vast potential to increase take-up and motivate use and maintenance of household latrines among

the poor.

IMPLEMENTATION PARTNERS AND INVESTIGATORS

The World Bank Water and Sanitation Program (WSP), the Philippines Social Protection Unit and the Department

of Social Welfare and Development (DSWD) will work jointly to integrate for the first time the largest national

anti-poverty and social protection program in the Philippines, the Pantawid Pamilyang Pilipino Program

(hereafter Pantawid Pamilya), with rural sanitation demand generation. This initiative is part of the ‘WASH

convergence strategy’ of DSWD to integrate the three core poverty reduction programs: Pantawid Pamilya,

Kalahi-Cidds Community Driven Development and Sustainable Livelihoods Program (SLP)). The impact evaluation

was designed by a World Bank team led by Claire Chase (Economist, co-TTL), Edkarl Galing (Water & Sanitation

Specialist, co-TTL), Christian Borja-Vega (Economist), Paul Gertler (Principal Investigator) and Joshua Gruber (Co-

Principal Investigator). Allan Lalisan, Local Field Coordinator, supported logistics and oversaw the baseline survey

implementation according to agreed protocols and data quality standards.

The baseline survey was contracted through a competitive selection to D3 Systems to manage the logistics of

field data collection. D3 Systems is headquartered in Northern Virginia, and has a broad experience in evaluation,

household and socioeconomic surveys. D3 Systems sub-contracted Philippine Survey and Research Center

(PSRC), a local research organization in Philippines.

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INTERVENTION DESIGN

The proposed intervention leverages key components of the Pantawid Pamilya Program to reach poor

households with a sanitation promotion and supply-side intervention, specifically:

a. Use of the Pantawid Pamilya National Household Targeting System (NHTS-PR) to target poor and remote households most likely to lack access to sanitation;

b. Introduction of Community-led Total Sanitation at the barangay-level and an enhanced sanitation module into Pantawid Pamilya Family Development Sessions (FDS) to provide information on the benefits of sanitation and incorporate evidence-based behavior change messages;

c. Implementation of a supply-side sanitation package at the community level (i.e. de-linked from Pantawid Pamilya), but targeted to poor beneficiary and non-beneficiary households. This includes sanitation product demonstration and financial product offering (savings and loans) through a socially-oriented partner MFI;

d. Incorporation of safeguards to ensure the financial protection of poor households; e. Engagement of local government to apply for and distribute latrine subsidies to eligible households.

Further details on these components are below:

National Household Targeting System for Poverty Reduction

The Pantawid Pamilya utilizes the National Household Targeting System for Poverty Reduction (NHTS-PR) to

target beneficiaries. This is a national database of poor households, containing information on household

eligibility and includes households’ access to sanitation. The intervention uses NHTS-PR to reduce the costs

typically associated with targeting poor and remote households.

Community-led Total Sanitation (CLTS) and Sanitation Promotion through Enhanced Family Development Sessions (FDS)

Introduction of Community-led Total Sanitation at the barangay-level and an enhanced sanitation module into

Family Development Sessions (FDS) will provide information on the benefits of sanitation and incorporate

evidence-based behavior change messages. WSP will facilitate hands-on CLTS Training for Municipal Links

(DSWD frontline workers) and Local Government Links in their joint conduct of the FDS. These activities are

targeted at the entire community, and are intended to stimulate demand for affordable household latrines.

In parallel to broader-scale CLTS activities, the WSP Philippines team, with the support of DSWD national and

regional representation, is also undertaking a modification of the existing FDS Module 3: Preservation of the

Environment to incorporate CLTS and behavior change communication elements. These activities represent an

important initial step towards the goal of integrating a greater focus on improving sanitation and hygiene

behavior among Pantawid Pamilya beneficiary households. The objective of the enhanced module is to

communicate with FDS participants the benefits of sanitation and incorporate evidence-based behavior change

messages. WSP is also helping supervise the process incorporating modifications to the original module and will

work with area municipal links to ensure coordination of pre-testing and pilot activities between DSWD and

program actors. The enhanced participants’ module will seek to incorporate a stronger focus on themes related

to clean water supply, proper waste disposal techniques, disease prevention and community-led total sanitation

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(CLTS). The enhanced module also places a focus on making sanitation and hygiene-related themes easier to

understand for Pantawid Pamilya participants. This includes clearer learning objectives for each section, practical

guidance for facilitators, increased number of hands-on activities for participants and the integration of flip-

charts as a tool for increasing visual prompts. Due to the expansion in the number of topics covered, the

enhanced module will be delivered over two sessions, held on consecutive months, for a total of four hours.

Participation in FDS is a conditional requirement for beneficiaries to receive cash grants2. A RCT of the 4Ps

program conducted in 2011 reports very high attendance at FDS sessions of over 90%.

Supply side sanitation package at community level

The project will implement a supply-side sanitation package at the community level (i.e. de-linked from Pantawid

Pamilya), but targeted to poor beneficiary and non-beneficiary households. This includes sanitation product

demonstration and financial product offering (savings and loans) through a partner MFI. WSP will work with

local government to help establish associations of supply-side actors to include among others masons, suppliers,

and entrepreneurs. Technical support and capacity building will include skills training and support for setting up

strategic production hubs to operationalize sanitation businesses. Development of sanitation products will be

based on past piloting activities and will utilize the Informed Choice Catalogue (ICC), created by WSP and ABCDE

Foundation (See Figure 1). WSP shall likewise forge agreements between potential MFIs and municipal

governments on the packaging of financial products for the poor.

2 Attendance to the monthly FDS is one of the conditions for a beneficiary to claim the health cash grant amounting to PhP500 ($11) per month.

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Figure 1 Informed Choice Catalog of Sanitation Options

Financial safeguards to protect poor consumers

The project will incorporate safeguards to ensure the financial protection of poor households.

Specifically, loan offerings to poor households will be scaled according to household ability to pay to

avoid over indebtedness. The precise structure of loans is still under negotiation with the partner MFI

and the World Bank Social Protection team. Secondly, a regulatory committee will be established to

oversee activities and practices of the partner MFI under the project as well as handle customer

complaints that cannot be resolved directly with the lender. A partnership agreement between the MFI

and the project will be formalized to ensure these protections are adhered to, as well as make provisions

for adequate disclosure of lending terms and conditions, protective measures for collection of debt, and

integration of consumer education into lending services to promote financial literacy. An MFI Specialist

has been hired as an STC to formulate specific guidelines for financial protection of the poor. The main

goal of these safeguards and provisions will be to keep tract of MFI providers’ principles and behaviors

in order to identify aggressive and inappropriate marketing strategies, and instead promote socially-

responsible microfinance principles. Targeted information sessions will help vulnerable borrowers who

lack access to information of their rights; misinformed borrowers can be easily pressured into making

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poor transaction decisions. Four key provisions of the regulatory committee will be encouraged to

protect the poor and vulnerable MFI customers3:

• transparency of transactions;

• implementation of safeguards for MFI practices;

• promotion of consumer literacy; and

• implementation of mechanisms for filing and handling consumer complaints and grievances.

Latrine hardware subsidies

Local government will be engaged to apply for and distribute latrine subsidies to poor households. Since the

evaluation team will not be able to directly control subsidies, the study will adopt an encouragement design –

barangays randomized to subsidy arms will receive assistance from the evaluation team in preparing necessary

proposals to the municipal government to procure national level funding for sanitation subsidies. Currently,

national level funding is administered by line agencies4 and sanitation proposals for subsides are prepared at

barangay level through the process of local poverty reduction action planning, which in turn is consolidated at

the municipal level and endorsed to the relevant national agency for funding. It is anticipated that subsidies will

initially be provided as lump sum funding at barangay level as proposed by the municipality and will then be

distributed to households prior to latrine construction in the form of vouchers, cash, or hardware. Potential

sources of subsidies may come from the Bottom-Up Budgeting or BUB, a national flagship program where DSWD,

DILG and DoH have agreed to jointly fund local infrastructure, including water and sanitation projects through

the local poverty reduction action planning process. Line agencies have earmarked at least 10% of their annual

budget to fund local infrastructure, suggesting funding levels are adequate.

Seventeen municipalities are participating in the experimental study. Selection criteria for municipalities are that

they are implementing Zero Open Defecation projects, have high prevalence of open defecation and unimproved

toilets, high poverty incidence, and with high numbers of barangays (smallest administrative unit). Municipalities

are selected from provinces Negros Oriental, Cebu and Bohol (Region 7), and Leyte and Eastern Samar (Region

8).

The above interventions are expected to respectively address the key barriers that poor households face in

acquiring sanitation, including (i) a lack motivation to improve their sanitation situation (demand), (ii) scarce

access to sanitation products and services (supply), and (iii) financial constraints that impede them from investing

in beneficial durable goods such as sanitation (insufficient household income / liquidity constraints). Specifically,

barangay-level CLTS, and Pantawid Pamilya FDS will generate demand for sanitation by increasing knowledge

and community motivation to improve sanitation, while the supply-side package will address supply constraints

by increasing the availability, affordability and desirability of latrines on the market and providing access to

3 These provisions are based on the Microfinance Consumer Protection Guidebook of Philippines developed by Department of Finance - National Credit Council and the National Anti-Poverty Commission, and the Asian Development Bank. For more information see full report: http://www.bu.edu/bucflp/files/2012/01/Microfinance-Consumer-Protection-Guidebook.pdf 4 The Bottom Up Budgeting or BUB has mandated the Department of Health, Department of Social Welfare and Development and the Department of the Interior and Local Government to allocate at least 10% of their respective agency budget to fund barangay-level WASH projects through local poverty reduction action planning.

http://www.bu.edu/bucflp/files/2012/01/Microfinance-Consumer-Protection-Guidebook.pdf

http://www.bu.edu/bucflp/files/2012/01/Microfinance-Consumer-Protection-Guidebook.pdf

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financial products and partial hardware subsidies to facilitate purchase of latrines. The NHTS-PR will greatly

increase the efficiency of targeting beneficiaries most likely to lack access to safe sanitation.

Box 1. Proposed Theory of Change of the Study

DATA COLLECTION

Baseline data for the study were collected through household and barangay level surveys. Both surveys were

conducted prior to the start of the intervention in all study barangay, and in a random subset of Pantawid

Pamilya-eligible households within each barangay. The barangay survey was administered to a knowledgeable

community leader, and was used to collect data on general barangay characteristics (e.g., the presence of

schools, clinics, markets, access to news media and social welfare promotional programs). The household survey

focused on collecting basic information from households in order to test for balance between treatment and

control groups and to understand financial behaviors and practices of participating households. Modules

included: (i) household roster and demographics; (ii) assets, consumption and expenditure; (iii) sanitation,

hygiene and water infrastructure; (iv) sanitation, hygiene and water behaviors and practices (v) diarrhea; (vi)

financial behaviors and practices.

PROGRAM ASSIGNMENT TO TREATMENT AND CONTROL

Identification Strategy The evaluation is a 4-arm cluster randomized controlled trial, where treatment is randomly assigned at the

cluster (village / barangay) level. Barangays were randomized within municipality to one of the three treatment

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arms, or control (stratified randomization within municipality). Random assignment was conducted using

standard practices using STATA.

Table 1 shows the linkages between the four treatment arms and the control arm; the final column provides

information to link treatment arm comparisons to proposed research questions.

Table 1: Composition of Randomized Treatment Arms

Treatment Arm

Barangay Level Treatment

Pantawid Pamilya

Promotion (CLTS &

FDS)

MFI Products

Subsidy Research Question

T4 Subsidy + MFI + Promotion

✓ ✓ ✓ ✓ Q4

T3 MFI + Promotion ✓ ✓ ✓ Q3 T2 Subsidy +

Promotion ✓ ✓ ✓ Q2

C Control [C] ✓ ✓

The initial study design called for a pure control (a group of barangays receiving Pantawid Pamilya, but no

sanitation promotion. The intention of the pure control was separate the effect of promotion by itself from the

individual and combined effects of financing and subsidies. However, as barangay selection was taking place it

became clear there was a high likelihood of sanitation promotion reaching control arm households through the

FDS. Thus the team decided it would be politically and logistically infeasible to exclude promotional activities

from a control group (all barangay would be exposed to promotional activities). Given this, the pure control

group was dropped from the study, and (the former) T1 group became the de facto control arm.

SAMPLING STRATEGY

The evaluation includes 17 municipalities in the provinces of Negros Oriental, Cebu and Bohol (Region 7), and

Leyte and Eastern Samar (Region 8). A total of 272 barangays were selected across the 17 municipalities

proportional to the number of eligible barangays within a municipality (range [60:539]). Selected barangays were

randomly assigned to one of three treatment arms and a control arm as part of the cRCT.

Using the NHTS list for the 17 municipalities, barangays were selected based on the following criteria: (a) WASH-

priority areas identified for WASH convergence, (ii) participation in the national Zero Open Defecation Program;

(iii) at least 20% of households in the barangay having no toilet (defecating in the open), and (iii) at least 40

households participating in the Pantawid Pamilya. Within each barangay, the NHTS was used as the sampling

frame. This targeting system identifies household eligibility and participation in Pantawid Pamilya, household

composition, and proxy-means test. Within each selected barangay Stata was used to set a seed, assign a random

number to each household, rank the households according to this random number, and select the 1st to 15th

household as the primary sample. The remaining households were reserved in order as replacement households.

Prior to the sample selection the baseline survey firm conducted a verification of the NHTS to determine its

accuracy and reliability. In each province, 3 barangays and 25 households per barangay were randomly selected

for verification. A total of 450 households were verified. Generally, the list was found to be accurate and reliable.

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All of the names were verified to be living in the barangay or were once residents of the barangay. The firm

encountered a few scenarios wherein:

- The name on the list relocated to another area and the membership was transferred to the child

- The recipient passed away and membership was either transferred to the spouse/child

- The name on the list is no longer a 4Ps recipient since he/she did not attend the assembly

Power Calculations

We provide updated power and sample size calculations for a random sample of an average of 15 CCT-eligible

households sampled from each cluster (barangay), with outcome measurements at baseline, and during one post

intervention follow-up visit.

Sample Size Calculations: The cRCT is designed to measure the impact of the respective interventions on

outcomes along the casual chain, including: up take of improved sanitation, open defecation habits, and

childhood diarrhea. The study is powered to detect differences in sanitation take-up (primary outcome) both

between each treatment arm and the control arm, as well as across treatment arms. Below, we report the sample

sizes required to detect differences across the four treatment arms and the control group with 80-90% power;

we use these sample sizes to calculate the analytic power to detect differences between treatment arms for

open defecation. In addition, we report analytic power for secondary outcomes (self-reported diarrhea) given

the sample sizes calculated for primary outcomes. All calculations assume a type-I error rate of 0.05 (one-sided).

Improved Sanitation Coverage and Open Defecation: From baseline data we are able to directly estimate the

proportion of our sample that practices open defecation (OD) and that does not have access to improved

sanitation (unimproved sanitation); open defecation: 40% [SD 49%, ICC 0.27]); unimproved san: 62% (SD 49%,

ICC 0.22). From these data we are able to re-calculate minimal detectable effects for OD and unimproved

sanitation based on baseline data.

Table 2: Expected Power and Sample Sizes for Reductions in Unimproved Sanitation

Treatment Arm Detectable Effect

Mean in Treatment Arm

Required Clusters a

Households (15/cluster)

Power

T4 -12% 49% 68 1020 >80% T3 -12% 49% 68 1020 >80% T2 -12% 49% 68 1020 >80% C - 61% 68 1020 -

Totals: - 272 4080 a C clusters will serve as the comparison group for all T-arms;

Table 3: Expected Power and Sample Size for Open Defecation

Treatment Arm Detectable Effect Expected Mean In Treatment Arm Power T4 -13% 27% >80% T3 -13% 27% >80% T2 -13% 27% >80% C - 40% -

a C clusters will serve as the comparison group for all T-arms;

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Based on recent experiments in Tanzania and India the MDEs for access to sanitation and OD are reasonable: Tanzania (non-subsidy approach) 12% increase in access (vs. 39% control) and 12% reduction in OD (vs. 23% control); India (subsidy approach) 19% increase in access (vs. 22% control) and 10% reduction in OD (vs. 84% control). Diarrhea: We obtained estimates of 1-week under-5 diarrhea prevalence from baseline data. Caregiver reported

1-week prevalence diarrhea was 4% (SD: 19%; ICC 0.02). We would expect the 2-week prevalence to be 8% (SD:

29%) under these conditions, which is lower than anticipated based on national sample estimates (DHS data:

10.5%) use to calculate minimal detectable effects prior to baseline. Below, we report expected treatment effect

sizes and analytic power of our study design in the Table 4, using an ANCOVA approach that leverages baseline

data to reduce variability in effect size estimates.

Table 4: Expected Power and Sample Size for Diarrhea

Treatment Arm Expected Relative Risk (1-week prevalence)

Expected Relative Risk (2-week prevalence)

Power

T4 0.56 0.68 >80% T3 0.56 0.68 >80% T2 0.56 0.68 >80% C 1 1 -

a C clusters will serve as the comparison group for all T-arms

The study is likely underpowered to detect differences in the 1-week prevalence of under-5 diarrhea. While the

estimated 2-week prevalence is lower than expected, the study could still detect a reasonable drop in diarrhea

at endline. The study team will consider incorporating measurements of the 2-week prevalence of diarrhea at

endline, but notes that based on feedback from reviewers during the proposal stage, the objective of the

evaluation is focused on improved latrine adoption, for which it is well powered, not health impacts.

BASELINE SURVEY IMPLEMENTATION

DSWD regional directors, municipal mayors and barangay captains were provided official World Bank letters to

announce dates and locations of baseline survey implementation. Letters were followed up by courtesy calls or

personal visits to inform on the purpose of the study and broad operational plans and to request support for

logistical details of how to navigate barangays.

Most of these letters and personal visits went smoothly, however in a few cases mayors had not received notice

from the DSWD of the baseline survey operation and did not initially permit surveyors entry until they received

a letter directly from the DSWD. These cases were resolved either by obtaining the necessary letter or through

discussion directly with the mayor.

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There were a few cases of security risk during the baseline survey. Survey teams encountered domestic quarrels

between neighbors in two barangays in Negros leading to shootouts.5

Field observation of survey implementation concluded that the modules were relatively straightforward and easy

for respondents to understand. However modules on risk and time preference were more difficult to administer

as respondents had trouble understanding them. Despite the clarity of the translation, at times the length of the

questions themselves (especially in Philippine languages, which are not as brief as English) confused the

respondents. Field visit observation indicates that respondents with higher education, especially high school

graduates, may have encountered similar types of questions before and thus were more comfortable. The

baseline had a refusal rate of 7%. Field visits encountered a few households who refused to show their toilet

facilities out of shame.

ANALYSIS OF HOUSEHOLD INCOME

The baseline survey collected detailed data on income for each household member of working age. Each

household members, a respondent with the best knowledge, reported income derived from direct labor income

(e.g. from an employer, from a business or farm), direct non-labor income (e.g., cash transfers, remittances), and

in-direct, “in-kind” income (e.g., tuition paid directly to schools from a scholarship). For labor income from

employment, households were asked to report income over the previous month. For business, farm and all non-

labor direct and in-kind income, households reported income for the previous 12 months, from which an average

monthly income was derived.

An assessment of total direct income will allow the research and implementation teams to better understand

the appropriateness and best design for financial and sanitation products being offered to the target population

as part of the intervention. The figures below show the distribution of total monthly direct income (labor and

non-labor combined) over the study population (mean total monthly income: 3583 PHP), and income broken out

respectively by labor (mean: 3178 PHP) and non-labor (mean: 1417 PHP) direct income. Table 3 in the Appendix

shows which proposed financial and sanitation products would be appropriate for households within each

income quintile.

5 Police advised the survey teams to avoid these barangays. In addition there were two barangays in Mabinay province--Barras and Arebasore--in which security issues forced the team to complete the interviews very quickly. Both barangays were reputed to be hideouts for the New People's Army (NPA), a communist rebel separatist group operating in various parts of the Philippine countryside. The survey team reported that the NPA was on the way to the barangay in response to news that there was a survey team there, possibly acting on the suspicion that the survey team was spying on them. The team entered this barangay in the early morning and left by noontime to avoid a possible encounter. The rushed nature of the surveys in these barangays could have affected quality. Fortunately the team was not harmed.

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BASELINE BALANCE CHECKS AND ASSET WEALTH DISTRIUBTION

The team has assessed the success of randomization by comparing household and barangay characteristics

across treatment and control arms (balance tests). The results of the balance tests are presented in the appendix.

These results include the means and standard deviations for each indicator across each control and treatment

arm. The appendix also provides the p-values (adjusted for clustering at the barangay level) for means tests

comparing each respective treatment arm to the control arm (p-values less <0.05 suggest that there are

significant differences between treatment and control means or proportions for a specific indicator, after

adjusting for correlated outcomes at the barangay level).

In Tables 10-12 of the appendix we present balance data for demographic, head of household, child health, and

water and sanitation infrastructure; the results in these tables complement Tables 1, 4 and 5 which show the

distribution (balance) of income and borrowing behaviors by households across the control and treatment arms.

Overall, there is strong evidence that randomization was successful: we observe far few than expected significant

differences in between treatment arms and control by means tests (expected: 5%).

In order to assess the distribution of wealth within the evaluation sample, and across treatment arms, a

standardized wealth index was created from household ownership of specific assets and infrastructure. The

wealth index was created by summing the first component weight from a principle component analysis (PCA) for

each asset owned by a household; the asset wealth index was then used to create wealth quintiles within the

evaluation sample. The figures below show the wealth distribution by quintile, over the entire sample, and then

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over each respective and control and treatment arm. These figures suggest that all treatment arms have a very

similar distribution of wealth assets. In the appendix, Tables 13-15 show the mean wealth quintiles and the

distribution of specific assets across the treatment arms. Results from Tables 13-15 similarly suggest good

balance of asset wealth across the treatment arms. Table 16 shows the distribution of assets by quintile; results

suggest that the assets index is working as expected (e.g., proportion of households with a television increases

with wealth quintile, while proportion of households with an unprotected water source decreases with wealth

quintile). Finally, Table 17 shows results from the PCA analysis, including the mean, standard deviations and

asset weights derived from the first principal component.

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Figure 9: Distribution of Household Wealth Scores for Baseline Treatment and Control Groups (Gruber, 2016)

RISKS AND IMPLEMENTATION TIMELINE

The Impact Evaluation faced and addressed several risks in the baseline data collection preparation, planning and implementation, as follows: Addressing risks of contamination:

1. Wide intra-and inter-cluster variation exists and signals dynamic flows of information between

comparison units. This evaluation randomized at a level larger than the individual (cluster).

Randomizing at the cluster level addresses potential contamination between treatment and control

groups: where treated individuals mix and chat and potentially “share” treatment with individuals in

the control group. This would “contaminate” the impact, and the control group would no longer be a

good comparison. Randomizing at the cluster level minimizes the risk of this happening. In addition,

one of the key activities to address contamination is to collect and monitor knowledge of sanitation

and MFI information among participants. Monitoring of these indicators will be targeted towards one

or two treatment arms. Survey instruments after baseline will collect intervention-related information

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of both comparison groups in order to estimate the presence of contamination and address these risks

by identifying potential threats to internal validity and substitute comparison groups as needed.

Addressing risks of misinterpretation of survey questions:

1. Risk aversion questions were observed as extremely difficult for most respondents, many of whom had

very little formal education. Based on observation those who were more likely to understand the

questions were the ones who had achieved higher levels of education, such as high school graduates.

This variation should be taken into account when analyzing the data.

Anticipated Timeline:

Current activities Expected Delivery date

Baseline Data collection completed December 2015

Cleaned Database received WBG February 2016

Delivery of baseline report May 2016

Upload macro-data in WB repository May 2016

Subsequent activities Expected Delivery date

Endline survey data collection December 2017

Final End line report to SIEF June 2018

19

APPENDIX: DESCRIPTIVE STATISTICS AND BASELINE BALANCE

Earned and Unearned Income Table 1: Baseline Household Income, Overall and by Treatment Arm, in Philippine Peso (PHP)

Baseline - overall Control Treatment 2 Treatment 3 Treatment 4

Baseline characteristics N=4080 N=1021 N=1020 N=1019 N=1020

Obs. Mean (SD) Obs. Mean (SD) Obs. Mean (SD) Obs. Mean (SD) Obs. Mean (SD)

Aggregated Direct HH Income

Earned income1 2782 3178 (4548) 746 3093 (4424) 697 3028 (3993) 637 3354 (4339) 702 3256 (5319)

Non-earned Income2 4080 1417 (1390) 1021 1510 (1337) 1020 1315 (1286) 1019 1376 (1333) 1020 1466 (1576)

Combined Income 3 4080 3583 (4321) 1021 3770 (4290) 1020 3384 (3844) 1019 3472 (4109) 1020 3707 (4956)

Direct Non-Earned Income

Sources

Interest/Investment 146 920 (1496) 34 763 (1235) 33 897 (1182) 38 957 (1472) 41 1033 (1922)

Remittances 667 793 (1890) 152 901 (1915) 175 559 (900) 165 776 (1522) 175 949 (2721)

Rental

(Property/Equipment) 55 400 (421) 19 496 (400) 12 228 (158)*** 13 525 (493) 11 276 (510)

Scholarship 126 602 (865) 30 505 (654) 34 536 (601) 39 680 (1098) 23 693 (1012)

Gov’t Transfer (4Ps) 3993 884 (617) 1002 876 (493) 992 899 (827) 1000 847 (514) 999 914 (578)

NGO Transfer 824 1389 (991) 252 1550 (940) 173 1317 (1173) 199 1269 (970) 200 1368 (879)

Pension/Retirement 41 935 (1156) 12 354 (434) 7 725 (568) 13 1292 (1597) 9 1356 (1184)**

Selling Goods/Services 198 551 (800) 49 471 (442) 56 612 (980) 48 618 (897) 45 488 (755)

Other 312 633 (934) 65 900 (1264) 70 484 (675) 99 587 (887) 78 601 (838)

Non-Earned In-kind Income4

Total In-kind Value 4080 74 (463) 1021 68 (341) 1020 82 (654) 1019 78 (403) 1020 68 (388)

20

**: pvalue <=0.05 on t-statistic comparing treatment mean to control mean; ***: pvalue <=0.01 on t-statistic comparing treatment mean to control mean

HH: Household; Gov’t: Government; NGO: Non-governmental Organization; 4Ps: 1 Income from Employment, Agriculture and Non-Agriculture Businesses; 2Total household income from “Direct Income Sources”; 3Combined Income

from Earned and Non-Earned Direct Income; 4In-kind sources same as Direct Income sources, but not shown due to low cell counts

Table 2: Mean and Range for Average Monthly Household Total and Per Capita Earned and Unearned Income by Income Quintile

Average HH

Income by

Quintile

Total Income (PHP) Quintile Range Total Per Capita

Income (PHP)

Quintile Range

Obs Mean SD Min Max Mean SD Min Max

Poorest Quintile 816 555 284 0 983 107 55 0 190

Second Quintile 816 1332 212 983 1717 260 42 190 336

Third Quintile 816 2297 364 1725 2958 435 59 337 551

Fourth Quintile 817 3966 649 2967 5233 742 123 552 972

Richest Quintile 815 9774 6197 5233 65900 1751 1090 974 13175

Average HH

Income-Overall

Earned Income 2782 3178 4548 554 773

Non-Earned

Income (incl. 4Ps

transfers)

4080 1417 1390 260 309

Combined 4080 3583 4321 658 764

21

Toilet Loan Product Options and Income

Table 3: Proportion of income required for different types of consumer loan options

WaSaFin WSP promoted options

Average HH Income by

Quintile

High-end

(20,000 Php

1800 Php/mo)

Option 1

(4125 Php

412 Php/mo)

Option 2

(4925 Php

496 Php/mo)

Option 3

(7300 Php

732 Php/mo)

Poorest Quintile 555 324% 74% 89% 132%

Second Quintile 1332 135% 31% 37% 55%

Third Quintile 2297 78% 18% 22% 32%

Fourth Quintile 3966 45% 10% 13% 18%

Richest Quintile 9774 18% 4% 5% 7%

Average HH Income-

Overall

Earnings 3178 57% 13% 16% 23%

Non-Earnings (incl. 4Ps

transfers) 1417 127% 29% 35% 52%

Combined 3583 50% 11% 14% 20%

Notes: (i) Monthly payment values greater than 50% highlighted in red; (ii) assumes 7.5% interest rate paid in weekly

installments over 46 weeks

22

Household Borrowing Behavior

Table 4: Baseline Loan Behavior, Overall and by Treatment Arm


Baseline Loan Activity N=4080 N=1021 N=1020 N=1019 N=1020


Loan Behavior

HH has active loan 4080 23% (42%) 1021 24% (42%) 1020 23% (42%) 1019 24% (43%) 1020 22% (41%) Number of active loans 940 1.13 (.42) 240 1.13 (.46) 237 1.11 (0) 243 1.14 (.44) 220 1.11 (.39)

Loan Source

Friends 940 24% (42%) 240 22% (41%) 237 20% (40%) 243 24% (43%) 220 28% (45%)

Ag. Dev. Bank 940 2% (13%) 240 1% (9%) 237 1% (11%) 243 2% (16%) 220 2% (13%) Commercial Bank 940 2% (15%) 240 3% (17%) 237 3% (17%) 243 2% (14%) 220 2% (13%)

MFI 940 34% (47%) 240 34% (47%) 237 27% (44%) 243 38% (49%) 220 37% (48%) Other Financial Inst. 940 3% (17%) 240 5% (21%) 237 2% (13%) 243 2% (16%) 220 3% (18%)

NGO 940 2% (14%) 240 3% (16%) 237 3% (17%) 243 2% (13%) 220 1% (10%) Landlord/Employer 940 1% (12%) 240 1% (9%) 237 1% (9%) 243 1% (11%) 220 3% (16%)

Shopkeeper 940 12% (32%) 240 10% (31%) 237 16% (37%) 243 10% (30%) 220 10% (29%)

Money Lender 940 9% (29%) 240 10% (30%) 237 11% (31%) 243 9% (29%) 220 8% (27%)

Cooperative 940 11% (31%) 240 13% (34%) 237 14% (34%) 243 9% (28%) 220 8% (27%)

Loan Purpose Agriculture Inputs 939 11% (31%) 240 5% (21%) 237 11% (31%)** 242 15% (36%)*** 220 12% (32%)*** Equipment Purchase 939 5% (22%) 240 8% (28%) 237 5% (23%) 242 3% (18%)** 220 3% (18%)**

Land Purchase 939 0% (6%) 240 0% (6%) 237 1% (9%) 242 0% (0%) 220 0% (0%) Livestock Purchase 939 7% (25%) 240 10% (30%) 237 8% (27%) 242 5% (23%) 220 3% (16%)**

23

Business Improvement 939 1% (8%) 240 1% (9%) 237 1% (11%) 242 0% (6%) 220 0% (0%) Other Farm/Business 939 6% (23%) 240 5% (22%) 237 6% (24%) 242 7% (26%) 220 5% (22%) Household: Consumption 939 41% (49%) 240 36% (48%) 237 38% (49%) 242 41% (49%) 220 48% (50%)** Household: Dwelling 939 15% (36%) 240 15% (36%) 237 15% (36%) 242 15% (36%) 220 15% (36%) Marriage/Family Even 939 1% (9%) 240 1% (9%) 237 0% (6%) 242 1% (9%) 220 1% (10%) Consumer Durables 939 7% (25%) 240 7% (26%) 237 8% (27%) 242 7% (25%) 220 5% (23%)

Travel 939 0% (7%) 240 0% (6%) 237 0% (0%) 242 1% (9%) 220 0% (7%) Other Personal Use 939 11% (31%) 240 15% (36%) 237 12% (33%) 242 7% (25%)** 220 9% (29%)

Loan Amounts (PHP)

Principal 940 8474 (15167) 240 10239 (22038) 237 7571 (12759) 243 8684 (12388) 220 7288 (10279)

Total Interest 940 2288 (8737) 240 3541 (15042) 237 1855 (4788) 243 2004 (5829) 220 1700 (3973)

**: pvalue <=0.05 on t-statistic comparing treatment mean to control mean; ***: pvalue <=0.01 on t-statistic comparing treatment mean to control mean HH: Household; MFI: Micro Finance Institution; NGO: Non-governmental Organization;:

24

Table 5: Baseline Loan Behavior, Overall and by Combined Direct Income Quintile

Lowest Income Quintile Second Quintile Third Quintile Fourth Quintile Highest Income

Quintile

Baseline Loan Activity N=816 N=816 N=816 N=1019 N=1020


Loan Behavior

HH has active loan 816 15% (35%) 816 20% (0%) 816 22% (42%) 817 25% (43%) 815 34% (47%) Number of active loans 119 1.08 (.32) 162 1.12 (0) 183 1.11 (.44) 201 1.16 (.47) 275 1.13 (.42)

Loan Source

Friends 119 29% (45%) 162 30% (0%) 183 27% (45%) 201 21% (41%) 275 17% (37%)

Ag. Dev. Bank 119 6% (24%) 162 1% (0%) 183 2% (13%) 201 0% (7%) 275 1% (10%) Commercial Bank 119 1% (9%) 162 3% (0%) 183 3% (18%) 201 3% (17%) 275 2% (13%)

MFI 119 24% (43%) 162 32% (0%) 183 30% (46%) 201 31% (46%) 275 45% (50%) Other Financial Inst. 119 3% (16%) 162 2% (0%) 183 4% (21%) 201 4% (21%) 275 1% (12%)

NGO 119 1% (9%) 162 2% (0%) 183 2% (15%) 201 2% (14%) 275 3% (16%) Landlord/Employer 119 4% (20%) 162 1% (0%) 183 0% (0%) 201 1% (10%) 275 2% (13%)

Shopkeeper 119 13% (34%) 162 10% (0%) 183 14% (34%) 201 14% (35%) 275 9% (28%)

Money Lender 119 12% (32%) 162 10% (0%) 183 8% (28%) 201 11% (31%) 275 8% (27%)

Cooperative 119 8% (27%) 162 10% (0%) 183 10% (31%) 201 11% (32%) 275 13% (33%)

Loan Purpose Agriculture Inputs 119 9% (29%) 162 7% (0%) 183 13% (33%) 200 8% (27%) 275 14% (35%) Equipment Purchase 119 5% (22%) 162 3% (0%) 183 8% (27%) 200 6% (24%) 275 4% (20%)

Land Purchase 119 1% (9%) 162 1% (0%) 183 0% (0%) 200 0% (0%) 275 0% (6%) Livestock Purchase 119 11% (31%) 162 11% (0%) 183 7% (25%) 200 5% (21%) 275 4% (19%)

25

Business Improvement 119 0% (0%) 162 0% (0%) 183 1% (7%) 200 0% (0%) 275 2% (13%) Other Farm/Business 119 4% (20%) 162 6% (0%) 183 5% (22%) 200 7% (25%) 275 7% (25%) Household: Consumption 119 40% (49%) 162 43% (0%) 183 41% (49%) 200 41% (49%) 275 40% (49%) Household: Dwelling 119 14% (35%) 162 12% (0%) 183 10% (31%) 200 19% (39%) 275 17% (38%) Marriage/Family Even 119 1% (9%) 162 2% (0%) 183 1% (7%) 200 0% (0%) 275 1% (9%) Consumer Durables 119 7% (25%) 162 7% (0%) 183 9% (29%) 200 6% (24%) 275 5% (23%)

Travel 119 0% (0%) 162 0% (0%) 183 0% (0%) 200 1% (10%) 275 1% (9%) Other Personal Use 119 8% (28%) 162 13% (0%) 183 10% (30%) 200 13% (33%) 275 10% (30%)

Loan Amounts (PHP) Principal 119 8432 (14129) 162 6325 (8956) 183 5787 (8382) 201 10664 (19070) 275 9945 (18166)

Total Interest 119 1633 (3757) 162 1444 (3146) 183 1358 (2777) 201 2894 (8408) 275 3243 (13806)

**: pvalue <=0.05 on t-statistic comparing treatment mean to control mean; ***: pvalue <=0.01 on t-statistic comparing treatment mean to control mean HH: Household; MFI: Micro Finance Institution; NGO: Non-governmental Organization;:

26

Sanitation Demand and Baseline Water and Sanitation Characteristics of Households

Table 6: Aggregated Toilet Type and Satisfaction

Toilet Type Satisfied with Toilet

N* Percent N Percent

Flush/Pour Flush 1688 42% 1523 90%

Latrine 606 15% 484 81%

No Facility 1683 42% 199 13%

Households not categorized n=103

Table 7: Flush and Latrine Toilet Characteristics

Toilet Characteristics

Pour Flush/Flush N=1688

Latrine N=606

Obs. Mean (sd) Obs. Mean (sd)

JMP Improved 1688 67% (47%) 606 65% (48%) Share Toilet 1684 32% (47%) 603 26% (44%)

HHs that share 530 4.52 (9.18) 154 3.83 (3.44) Located in HH Compound 1686 88% (33%) 599 90% (30%) Earth Floor 1687 11% (31%) 598 22% (41%) Ceramic/Vinyl Tile 1687 4% (19%) 598 2% (14%) Wood 1687 2% (14%) 598 4% (20%) Plastic Slab 1687 1% (9%) 598 1% (9%) Cement Floor 1687 82% (38%) 598 71% (45%) Seepage Observed 1681 9% (29%) 597 24% (43%) Enclosed Walls 1686 65% (48%) 600 49% (50%) Full Roof 1682 68% (47%) 601 54% (50%) Door 1686 84% (36%) 602 71% (46%)

27

Table 8: Current and Planned Repairs, Improvements and Upgrades

Sanitation Demand

Pour Flush/Flush

N=1688

Latrine

N=606

Informal Facility/ Open

Def

N=1683

Obs. Mean (sd) Obs. Mean (sd) Obs. Mean (sd)

Current Repair/Upgrade

No 1680 81% (39%) 585 74% (44%) 1586 82% (38%)

Repairing 1680 10% (30%) 585 14% (35%) 1586 11% (31%)

Upgrading 1680 9% (28%) 585 12% (32%) 1586 6% (25%)

Upgrade Type

Flush (Septic) 148 77% (42%) 68 53% (50%) 101 71% (45%)

Flush (Latrine) 148 11% (32%) 68 3% (17%) 101 9% (29%)

Improved Latrine 148 5% (23%) 68 37% (49%) 101 14% (35%)

Desired Improvements

Nothing 1688 22% (41%) 606 21% (41%) 1683 41% (49%)

Build Superstructure 1688 27% (44%) 606 23% (42%) 1683 30% (46%)

Repair Superstructure 1688 42% (49%) 606 42% (49%) 1683 8% (27%)

Repair Slab 1688 9% (29%) 606 8% (27%) 1683 1% (11%)

Repair Platform 1688 13% (33%) 606 11% (31%) 1683 4% (20%)

Intend to improve in

next 12m 1294 85% (36%) 456 74% (44%) 855 86% (35%)

28

Table 9: Resources for and Constraints to Sanitation Improvements

Sanitation Demand

Pour Flush/Flush

N=1688

Latrine

N=606

Informal Facility/ Open

Def

N=1683

Obs. Mean (sd) Obs. Mean (sd) Obs. Mean (sd)

Potential Sources of

Money for Improvement

Cash Casual Labor 1688 46% (50%) 606 44% (50%) 1683 28% (45%)

Borrow MFI 1688 2% (14%) 606 1% (11%) 1683 1% (7%)

Borrow (Friend/Family) 1688 6% (24%) 606 7% (26%) 1683 4% (20%)

Own Savings 1688 12% (32%) 606 10% (30%) 1683 12% (33%)

Direct Income (Earnings

and Non-Labor)

Combined Direct

Income (PHP) 1688 4164 (4826) 606 3553 (4363) 1683 3081 (3717)

Biggest Constraints

Materials Not Available 1688 10% (30%) 606 7% (25%) 1683 6% (24%)

Competing Priorities 1688 33% (47%) 606 30% (46%) 1683 21% (41%)

High Costs 1688 59% (49%) 606 64% (48%) 1683 47% (50%)

Baseline Balance Tables

29

Table 10: Baseline Balance for Demographic and Head of Household Characteristics



Obs. mean Obs. mean Obs. mean Obs. mean Obs. mean

Demographics

All members 4080 5.66 (2.04) 1021 5.69 (1.93) 1020 5.69 (2.02) 1019 5.63 (2.14) 1020 5.63 (2.05)

Members 0-5y 4080 .72 (.88) 1021 .7 (.86) 1020 .75 (.9) 1019 .71 (.87) 1020 .71 (.87)

Members 6-13y 4080 1.55 (1.16) 1021 1.58 (1.13) 1020 1.55 (1.18) 1019 1.54 (1.14) 1020 1.53 (1.18)

Members 14-30y 4080 1.54 (1.31) 1021 1.57 (1.23) 1020 1.55 (1.4) 1019 1.52 (1.32) 1020 1.54 (1.3)

Members 31-65y 4080 1.71 (.7) 1021 1.69 (.69) 1020 1.73 (.66) 1019 1.7 (.75) 1020 1.73 (.69)

Members >65y 4080 .14 (.43) 1021 .14 (.42) 1020 .12 (.39) 1019 .18 (.49) 1020 .13 (.42)

Head of Household

Gender (Female) 3072 39% (49%) 811 38% (49%) 725 36% (48%) 763 44% (50%) 773 39% (49%)

Can read 3072 83% (37%) 811 84% (37%) 725 87% (33%) 763 78% (41%) 773 84% (37%)

Can write 3072 86% (35%) 811 86% (34%) 725 90% (31%) 763 80% (40%) 773 87% (33%)

Reported employment in

prior month 3072 56% (50%) 811 57% (50%) 725 61% (49%) 763 50% (50%) 773 54% (50%)

No formal education 3072 3% (16%) 811 2% (15%) 725 2% (14%) 763 3% (18%) 773 3% (16%)

Completed pre-school 3072 47% (50%) 811 49% (50%) 725 48% (50%) 763 46% (50%) 773 47% (50%)

Completed elementary

school 3072 35% (48%) 811 34% (47%) 725 35% (48%) 763 36% (48%) 773 35% (48%)

Completed high school 3072 14% (35%) 811 15% (36%) 725 14% (35%) 763 15% (35%) 773 14% (34%)

Completed some university 3072 1% (8%) 811 0% (7%) 725 1% (8%) 763 1% (8%) 773 1% (9%)

Child Health (Under 5y n=2246) Diarrhea (7-day

prevalence.)a 2235 4% (19%) 546 5% (21%) 584 3% (17%) 555 4% (20%) 550 4% (19%)

Worms Tx (prior 12m) 2246 72% (45%) 551 74% (44%) 587 72% (45%) 555 74% (44%) 553 70% (46%)

**: pvalue <=0.05 on t-statistic comparing treatment mean to control mean; ***: pvalue <=0.01 on t-statistic comparing treatment mean to control

mean; a Caregiver reported diarrhea using local tem

30

Table 11: Baseline Balance for Water Infrastructure




Last Drink of Water

Piped into dwelling 4076 2% (13%) 1021 2% (15%) 1018 1% (10%) 1018 2% (13%) 1019 2% (13%)

Piped into yard/plot 4076 6% (23%) 1021 8% (27%) 1018 5% (22%) 1018 5% (22%) 1019 5% (23%)

Public tap/Standpipe 4076 18% (38%) 1021 21% (41%) 1018 14% (35%) 1018 20% (40%) 1019 16% (36%)

Protected Well 4076 17% (38%) 1021 19% (39%) 1018 15% (36%) 1018 15% (36%) 1019 20% (40%)

Unprotected Well 4076 11% (31%) 1021 10% (30%) 1018 11% (32%) 1018 12% (33%) 1019 10% (30%)

Protected spring 4076 10% (29%) 1021 7% (26%) 1018 9% (29%) 1018 11% (31%) 1019 11% (31%)

Unprotected spring 4076 5% (22%) 1021 4% (18%) 1018 5% (22%) 1018 6% (23%) 1019 6% (24%)**

Tube well or borehole 4076 14% (35%) 1021 11% (31%) 1018 17% (38%)** 1018 14% (34%) 1019 14% (34%)

Rainwater 4076 1% (11%) 1021 1% (8%) 1018 2% (13%) 1018 2% (14%) 1019 1% (9%)

Tanker truck 4076 0% (5%) 1021 0% (6%) 1018 0% (6%) 1018 0% (3%) 1019 0% (4%)

Cart with small tank 4076 0% (6%) 1021 0% (5%) 1018 0% (3%) 1018 1% (8%) 1019 0% (6%)

Surface water (river, dam,

lake, pond) 4076 2% (12%) 1021 1% (11%) 1018 3% (17%) 1018 1% (12%) 1019 0% (7%)

Bottled water 4076 14% (35%) 1021 15% (36%) 1018 15% (36%) 1018 12% (32%) 1019 14% (35%)


31

Table 12: Baseline Balance for Sanitation Infrastructure




Sanitation

Flush/pour flush (sewer) 3977 4% (19%) 994 4% (21%) 997 3% (17%) 990 3% (18%) 996 4% (19%)

Flush/pour flush (septic) 3977 31% (46%) 994 30% (46%) 997 32% (47%) 990 29% (45%) 996 32% (47%)

Flush/pour flush (pit latrine) 3977 7% (26%) 994 6% (23%) 997 7% (26%) 990 7% (26%) 996 8% (28%)

Flush/pour flush (elsewhere) 3977 0% (6%) 994 0% (5%) 997 0% (3%) 990 1% (9%) 996 0% (6%)

Flush/pour flush (unkown) 3977 1% (8%) 994 1% (7%) 997 1% (9%) 990 0% (6%) 996 1% (7%)

Ventilated improved pit latrine 3977 3% (18%) 994 3% (18%) 997 5% (21%) 990 3% (16%) 996 3% (17%)

Pit latrine with slab 3977 7% (26%) 994 8% (27%) 997 8% (28%) 990 7% (26%) 996 6% (24%)

Composting toilet 3977 2% (15%) 994 2% (14%) 997 3% (18%) 990 2% (15%) 996 2% (13%)

Pit latrine (no slab/open pit) 3977 2% (14%) 994 2% (15%) 997 2% (14%) 990 2% (13%) 996 2% (14%)

Bucket latrine 3977 0% (6%) 994 1% (10%) 997 0% (0%) 990 0% (4%) 996 0% (6%)

Drop/hanging toilet 3977 1% (8%) 994 0% (4%) 997 1% (8%) 990 1% (10%) 996 1% (8%)

No facility/bush/field/river 3977 40% (49%) 994 40% (49%) 997 37% (48%) 990 43% (50%) 996 41% (49%)


mean

32

Table 13: Baseline Balance for Wealth Quintile, Household Infrastructure and Ownership




Wealth Quintiles

Mean Quintile 4076 3.00 (1.41) 1020 3.09 (1.41) 1020 2.99 (1.41) 1018 2.93 (1.45) 1018 2.99 (1.39)

Poorest Quintile 4076 20% (40%) 1020 18% (38%) 1020 20% (40%) 1018 23% (42%) 1018 20% (40%)

Second Quintile 4076 20% (40%) 1020 20% (40%) 1020 21% (41%) 1018 20% (40%) 1018 19% (39%)

Third Quintile 4076 20% (40%) 1020 20% (40%) 1020 21% (41%) 1018 18% (38%) 1018 21% (40%)

Fourth Quintile 4076 20% (40%) 1020 20% (40%) 1020 18% (39%) 1018 19% (40%) 1018 22% (42%)

Richest Quintil 4076 20% (40%) 1020 22% (41%) 1020 20% (40%) 1018 20% (40%) 1018 18% (38%)

Infrastructure/Ownership

Own Land 4078 29% (45%) 1021 27% (44%) 1020 27% (45%) 1019 30% (46%) 1018 30% (46%)

Own Dwelling 4073 75% (43%) 1019 76% (43%) 1017 74% (44%) 1019 75% (43%) 1018 76% (43%)

Strong Roof Materials 4075 62% (49%) 1019 62% (49%) 1020 62% (49%) 1018 62% (49%) 1018 62% (49%)

Strong Wall Materials 4075 15% (35%) 1020 12% (33%) 1019 16% (37%) 1018 16% (37%) 1018 14% (35%)

Firm Floor (cement, tile) 4076 85% (36%) 1020 86% (35%) 1020 83% (38%) 1018 86% (35%) 1018 84% (36%)

Number Of Rooms 4059 1.49 (.69) 1015 1.51 (.73) 1014 1.5 (.7) 1015 1.48 (.66) 1015 1.49 (.68)

Electric Lighting 4076 72% (45%) 1020 74% (44%) 1018 73% (44%) 1019 70% (46%) 1019 71% (45%) **: pvalue <=0.05 on t-statistic comparing treatment mean to control mean; ***: pvalue <=0.01 on t-statistic comparing treatment mean to control

mean

33

Table 14: Baseline Balance for Household Asset Ownership




Household Assets

Radio 4065 36% (48%) 1018 35% (48%) 1016 35% (48%) 1016 36% (48%) 1015 37% (48%)

Television 4065 44% (50%) 1016 45% (50%) 1019 45% (50%) 1015 42% (49%) 1015 44% (50%)

Landline Telephone 4046 0% (4%) 1004 0% (4%) 1017 0% (0%) 1012 0% (5%) 1013 0% (0%)

Mobile Telephone 4072 66% (48%) 1018 68% (47%) 1016 65% (48%) 1019 65% (48%) 1019 65% (48%)

Washing Machine 4048 1% (11%) 1008 1% (12%) 1011 1% (10%) 1014 1% (11%) 1015 1% (10%)

Refrigerator/Freeze 4047 5% (21%) 1007 5% (21%) 1015 5% (22%) 1013 5% (21%) 1012 5% (21%)

CD, VCD, DVD Player 4059 22% (41%) 1014 24% (43%) 1012 22% (41%) 1017 19% (39%) 1016 22% (42%)

Karaoke Component 4051 6% (24%) 1008 7% (25%) 1012 6% (24%) 1015 5% (22%) 1016 7% (25%)

Computer/Laptop 4047 0% (4%) 1009 0% (4%) 1011 0% (4%) 1015 0% (5%) 1012 0% (3%)

Bicycle 4060 7% (25%) 1014 8% (27%) 1018 7% (25%) 1014 7% (25%) 1014 7% (25%)

Animal Drawn Cart 4046 2% (13%) 1009 2% (16%) 1014 1% (12%) 1012 1% (12%) 1011 2% (13%)

Motorcycle, Tricycle 4057 12% (32%) 1015 11% (32%) 1016 13% (33%) 1013 12% (32%) 1013 11% (32%)

Car/Truck, Jeep, Van 4040 0% (2%) 1006 0% (0%) 1013 0% (0%) 1010 0% (0%) 1011 0% (4%)

Tractor 4050 0% (3%) 1009 0% (0%) 1012 0% (3%) 1015 0% (3%) 1014 0% (3%)

Non-Motorized Boat 4043 4% (20%) 1010 4% (21%) 1014 5% (21%) 1007 4% (20%) 1012 3% (16%)

Boat Or Banca (Motor) 4049 4% (20%) 1007 4% (20%) 1015 4% (19%) 1012 5% (21%) 1015 3% (17%)


mean

34

Table 15: Baseline Balance for Agricultural Asset Ownership




Agricultural Assets

Goat 4059 18% (38%) 1016 16% (37%) 1016 17% (38%) 1012 19% (39%) 1015 19% (39%)

Pig 4052 24% (43%) 1010 24% (43%) 1015 24% (43%) 1014 24% (43%) 1013 25% (43%)

Piglet 4056 9% (29%) 1013 9% (28%) 1019 10% (30%) 1010 9% (29%) 1014 9% (29%)

Cow 4059 9% (29%) 1013 9% (28%) 1016 8% (27%) 1016 11% (31%) 1014 9% (29%)

Carabao 4051 16% (37%) 1013 15% (36%) 1015 17% (38%) 1009 18% (38%) 1014 14% (34%)

Chicken 4065 64% (48%) 1016 63% (48%) 1019 65% (48%) 1013 63% (48%) 1017 63% (48%)

Rooster 4053 23% (42%) 1009 21% (41%) 1015 25% (44%) 1015 22% (41%) 1014 26% (44%)

Water Pump 4052 1% (8%) 1008 0% (5%) 1016 0% (6%) 1015 1% (9%) 1013 1% (10%)

Thresher 4054 0% (4%) 1012 0% (4%) 1016 0% (4%) 1012 0% (3%) 1014 0% (5%)

Hand Tractor 4044 0% (6%) 1011 0% (6%) 1011 0% (7%) 1011 1% (8%) 1011 0% (3%)

Irrigation Equipment 4046 0% (4%) 1014 0% (4%) 1010 0% (0%) 1009 0% (0%) 1013 0% (5%)

Power Saw 4040 0% (3%) 1007 0% (3%) 1013 0% (0%) 1008 0% (3%) 1012 0% (4%)


mean

Table 16: Household Infrastructure and Assets Indicators, by Wealth Quintile

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Poorest Quintile Second Quintile Third Quintile Fourth Quintile Richest Quintile Assets



Own Land 97 12% (.32) 195 24% (.43) 173 21% (.41) 257 32% (.46) 439 54% (.5)

Own Dwelling 493 60% (.49) 571 70% (.46) 612 75% (.43) 652 80% (.4) 741 91% (.29)

Strong Roof Materials 261 32% (.47) 396 49% (.5) 522 64% (.48) 613 75% (.43) 726 89% (.31)

Strong Wall Materials 10 1% (.11) 31 4% (.19) 67 8% (.27) 137 17% (.37) 354 43% (.5)

Firm Floor (cement, tile) 621 76% (.43) 676 83% (.38) 677 83% (.38) 716 88% (.33) 759 93% (.25)

Electric Lighting 79 10% (.3) 465 57% (.5) 777 95% (.21) 810 99% (.08) 811 100% (.07)

Household Assets

Radio 272 33% (.47) 299 37% (.48) 277 34% (.47) 292 36% (.48) 306 38% (.48)

Television 10 1% (.11) 141 17% (.38) 347 43% (.49) 555 68% (.47) 730 90% (.31)

Landline Telephone 0 0% (0) 0 0% (0) 0 0% (0) 0 0% (0) 5 1% (.08)

Mobile Telephone 352 43% (.5) 481 59% (.49) 520 64% (.48) 606 74% (.44) 707 87% (.34)

Washing Machine 1 0% (.04) 0 0% (0) 2 0% (.05) 4 0% (.07) 42 5% (.22)

Refrigerator/Freeze 0 0% (0) 1 0% (.04) 6 1% (.09) 26 3% (.18) 161 20% (.4)

CD, VCD, DVD Player 0 0% (0) 26 3% (.18) 111 14% (.34) 263 32% (.47) 485 60% (.49)

Karaoke Component 1 0% (.04) 5 1% (.08) 15 2% (.13) 54 7% (.25) 172 21% (.41)

Computer/Laptop 0 0% (0) 0 0% (0) 0 0% (0) 0 0% (0) 8 1% (.1)

Bicycle 12 1% (.12) 32 4% (.19) 41 5% (.22) 55 7% (.25) 137 17% (.37)

Animal Drawn Cart 11 1% (.12) 16 2% (.14) 12 1% (.12) 14 2% (.13) 19 2% (.15)

Motorcycle, Tricycle 17 2% (.14) 58 7% (.26) 78 10% (.29) 124 15% (.36) 203 25% (.43)

Car/Truck, Jeep, Van 0 0% (0) 0 0% (0) 0 0% (0) 0 0% (0) 2 0% (.05)

Tractor 0 0% (0) 0 0% (0) 0 0% (0) 1 0% (.04) 2 0% (.05)

Non-Motorized Boat 11 1% (.12) 30 4% (.19) 26 3% (.18) 41 5% (.22) 53 7% (.25)

Boat Or Banca (Motor) 5 1% (.08) 16 2% (.14) 25 3% (.17) 31 4% (.19) 85 10% (.31)


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Table 16a: Household Agricultural Asset Ownership, by Quintile

Assets Poorest Quintile Second Quintile Third Quintile Fourth Quintile Richest Quintile


Agricultural Assets

Goat 151 19% (.39) 159 20% (.4) 129 16% (.37) 142 17% (.38) 145 18% (.38)

Pig 157 19% (.39) 172 21% (.41) 179 22% (.41) 236 29% (.45) 236 29% (.45)

Piglet 60 7% (.26) 80 10% (.3) 59 7% (.26) 74 9% (.29) 103 13% (.33)

Cow 68 8% (.28) 79 10% (.3) 67 8% (.27) 79 10% (.3) 81 10% (.3)

Carabao 133 16% (.37) 124 15% (.36) 105 13% (.34) 143 18% (.38) 143 18% (.38)

Chicken 519 64% (.48) 507 62% (.49) 491 60% (.49) 521 64% (.48) 550 67% (.47)

Rooster 183 22% (.42) 174 21% (.41) 144 18% (.38) 192 24% (.42) 259 32% (.47)

Water Pump 2 0% (.05) 1 0% (.04) 7 1% (.09) 7 1% (.09) 8 1% (.1)

Thresher 1 0% (.04) 0 0% (0) 1 0% (.04) 3 0% (.06) 3 0% (.06)

Hand Tractor 7 1% (.09) 1 0% (.04) 1 0% (.04) 3 0% (.06) 4 0% (.07)

Irrigation Equipment 1 0% (.04) 0 0% (0) 1 0% (.04) 1 0% (.04) 2 0% (.05)

Power Saw 0 0% (0) 0 0% (0) 0 0% (0) 0 0% (0) 4 0% (.07)


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Table 17:Prinicipal Component Analysis Results

PCA Results Assets

Mean SD Comp. 1 Wgt.


Own Land 0.28 0.45 0.156

Own Dwelling 0.75 0.43 0.140

Strong Roof Materials 0.62 0.49 0.221

Strong Wall Materials 0.15 0.35 0.212

Firm Floor (cement, tile) 0.85 0.36 0.082

Electric Lighting 0.72 0.45 0.370

Household Assets

Radio 0.35 0.48 0.016

Television 0.44 0.50 0.335

Landline Telephone 0.00 0.04 0.040

Mobile Telephone 0.65 0.48 0.161

Washing Machine 0.01 0.11 0.099

Refrigerator/Freeze 0.05 0.21 0.181

CD, VCD, DVD Player 0.22 0.41 0.271

Karaoke Component 0.06 0.24 0.166

Computer/Laptop 0.00 0.04 0.042

Bicycle 0.07 0.25 0.106

Animal Drawn Cart 0.02 0.13 0.011

Motorcycle, Tricycle 0.12 0.32 0.136

Car/Truck, Jeep, Van 0.00 0.02 0.027

Tractor 0.00 0.03 0.018

Non-Motorized Boat 0.04 0.19 0.047

Boat Or Banca (Motor) 0.04 0.20 0.092

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Table 17a: Principal Component Analysis Results

PCA Results Assets

Mean SD Comp. 1 Wgt.

Agricultural Assets

Goat 0.18 0.38 -0.008

Pig 0.24 0.43 0.050

Piglet 0.09 0.29 0.033

Cow 0.09 0.29 0.011

Carabao 0.16 0.37 0.013

Chicken 0.63 0.48 0.016

Rooster 0.23 0.42 0.042

Water Pump 0.01 0.08 0.021

Thresher 0 0.04 0.017

Hand Tractor 0 0.06 -0.007

Irrigation Equipment 0 0.04 0.008

Power Saw 0 0.03 0.043

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