A PUBLIC EXPENDITURE REVIEW OF THE BASIC EDUCATION SECTOR …

A PUBLIC EXPENDITURE REVIEW OF THE BASIC EDUCATION

SECTOR IN NAMIBIAMinistry of Education, Arts and Culture

REPUBLIC OF NAMIBIA October 2017

PUBLISHER’S CONTACT DETAILS

Directorate of Planning and DevelopmentMinistry of Education, Arts and Culture

Government Office Park, Luther Street, WindhoekPrivate Bag 13186, Windhoek, Namibia

Telephone (+264) (061) 293-3111 (main switchboard)Website: www.moe.gov.na

ISBN: 978-99916-893-4-0

All photos in this report are from the UNICEF Namibia photo bank.

A PUBLIC EXPENDITURE REVIEW OF THE BASIC EDUCATION

SECTOR IN NAMIBIAMinistry of Education, Arts and Culture

REPUBLIC OF NAMIBIA October 2017

ii A Public Expenditure Review of the Basic Education Sector in Namibia

ABBREVIATIONS

KUNENE

AEC Annual Education CensusECD Early Childhood DevelopmentEFA Education for All

EMIS Education Management Information SystemETSIP Education and Training Sector Improvement Programme

FSD Fifteenth School DayGDP Gross Domestic Product

HAMU HIV and AIDS Management Unit (in the MoEAC)HIGCSE Higher International General Certificate for Secondary Education

IGCSE International General Certificate for Secondary EducationLTR Learner-Teacher Ratio

MoEAC Ministry of Education, Arts and CultureMTEF Medium-Term Expenditure Framework

MTP Medium-Term PlanNIED National Institute for Educational DevelopmentNDP4 Fourth National Development Plan NSFP Namibian School Feeding Programme

NSFAF Namibia Students Financial Assistance FundPER Public Expenditure Review R&D Research and Development

ReSEP Research on Socio-Economic Policy (research group, Department of Economics, Stellenbosch University, Western Cape Province, South Africa)

SACU Southern African Customs UnionSACMEQ Southern and Eastern Africa Consortium for Monitoring Educational Quality

SDGs Sustainable Development GoalsUNICEF United Nations Children’s Fund

UPE Universal Primary EducationUSE Universal Secondary Education

OTJOZONDJU

PA

OSHIKOTO

OSHANA

KAVANGOZAMBEZI

OMAHEKE

OMUSATI OHANGWENA

KHOMAS

ERONGO

HARDAP

//KHARAS

EASTWEST

Map of Namibia’s Regions iii

MAP OF NAMIBIA

14 REGIONS

iv A Public Expenditure Review of the Basic Education Sector in Namibia

CONTENTS

FOREWORD ....................................................................................................................................... xiiiPREFACE .............................................................................................................................................. ixACKNOWLEDGEMENTS ..................................................................................................................... x

1 BACKGROUND ...................................................................................................................... 1

1.1 A NOTE TO THE READER ........................................................................................................ 21.2 THE CONTEXT ........................................................................................................................ 21.3 THE REVIEW PROJECT .......................................................................................................... 3

2 FISCAL POLICY AND THE FINANCING OF EDUCATION ................................. 4

2.1 THE POLICY CONTEXT .......................................................................................................... 62.2 THE EXTENT OF EXPENDITURE ON EDUCATION ............................................................. 102.3 THE ADEQUACY AND SUSTAINABILITY OF PUBLIC EDUCATION FINANCING ............. 112.4 ASPECTS OF THE EFFICIENCY OF PUBLIC EXPENDITURE ON EDUCATION .................. 15

2.4.1 Education expenditure by main divisions ................................................................ 162.4.2 Primary and secondary school education ................................................................ 182.4.3 Pre-primary education ............................................................................................... 202.4.4 Education spending by economic classification ...................................................... 212.4.5 Over- and underspending in the education sector .................................................. 222.4.6 Analysis of regional data ........................................................................................... 23

2.5 FISCAL POLICY AND EDUCATION FINANCING IN FUTURE ............................................. 25

3 BROAD EDUCATIONAL ISSUES IN NAMIBIA ................................................... 29

3.1 INTRODUCTION .................................................................................................................... 303.2 ENROLMENT ......................................................................................................................... 303.3 GEOGRAPHY AND EDUCATION .......................................................................................... 313.4 ENROLMENT ACROSS GRADES, REPETITION AND LEARNER FLOWS .......................... 333.5 LANGUAGE ........................................................................................................................... 383.6 BROAD EDUCATION ISSUES: IN SUMMARY .................................................................... 38

4 EDUCATION DATA IN NAMIBIA ................................................................................ 39

4.1 INTRODUCTION .................................................................................................................... 404.2 DATA COLLECTION PROCESSES ........................................................................................ 40

4.2.1 The Fifteenth School Day data collection process ................................................... 404.3 DATA QUALITY ISSUES ....................................................................................................... 41

4.3.1 Comparing the FSD with the AEC in 2015 ................................................................ 414.3.2 Comparing FSD enrolment for each school between two years – 2015 and 2016 ... 424.3.3 Learner-teacher ratios ................................................................................................ 434.3.4 Teacher appointment type and qualifications .......................................................... 43

4.4 CREATING PROPER DATABASES FOR EDUCATION ......................................................... 46

CONTENTS

Contents v

5 FISCAL FLOWS AND SCHOOL FUNDING: POST PROVISIONING ......... 47

5.1 INTRODUCTION .................................................................................................................... 485.2 POST PROVISIONING ........................................................................................................... 485.3 PERSONNEL AND PAYROLL DATA ...................................................................................... 495.4 COMPARING TEACHERS ON PAYROLL WITH ANNUAL SCHOOL CENSUS EMPLOYMENT IN 2014 ......................................................................................................... 53

6 FISCAL FLOWS AND SCHOOL FUNDING: NON-PERSONNEL SPENDING .................................................................................. 55

7 FISCAL INCIDENCE AND EQUITY ............................................................................ 61

7.1 FISCAL INCIDENCE: COST PER LEARNER ......................................................................... 627.2 FISCAL INCIDENCE: WHO GAINS ACCESS TO EDUCATION? ........................................... 667.3 INEQUALITY IN EDUCATIONAL OUTCOMES .................................................................... 677.4 OTHER EQUITY ISSUES ....................................................................................................... 68

7.4.1 Pre-primary education ............................................................................................... 687.4.2 Special schools and schools for learners with special needs ................................. 707.4.3 School feeding ............................................................................................................ 71

8 SUMMARY AND RECOMMENDATIONS .............................................................. 73

8.1 SUMMARY OF ISSUES ........................................................................................................ 748.1.1 Fiscal management and expenditure management ................................................ 748.1.2 Post provisioning and teacher salaries ..................................................................... 748.1.3 Fiscal incidence, spending equity and the need to target rural areas ................... 758.1.4 Non-personnel spending ........................................................................................... 768.1.5 Data consistency and the use of data for management ......................................... 76

8.2 SPECIFIC RECOMMENDATIONS ......................................................................................... 778.2.1 Managing the salary bill ............................................................................................ 778.2.2 Data consistency and ensuring there are no ‘ghost teachers’ ............................... 788.2.3 Private schools ........................................................................................................... 788.2.4 School maintenance ................................................................................................... 808.2.5 Textbooks .................................................................................................................... 818.2.6 Cost of hostels and transport versus cost of providing education to higher grades ... 81

8.3 IN CONCLUSION .................................................................................................................. 84

9 BIBLIOGRAPHY .................................................................................................................. 85

Lists of Figures and Tables

vi A Public Expenditure Review of the Basic Education Sector in Namibia

FIGURES

Figure 1: Government spending on education per capita in 115 countries, 2010 ............................................... 11Figure 2: Government spending on education as a percentage of total government expenditure in

115 countries, 2010 ..................................................................................................................................... 11Figure 3: Government spending on education as a percentage of GDP in 115 countries, 2010 ........................ 12Figure 4: Government expenditure on education in Namibia as a percentage of total government

expenditure, 2007/08-2012/13 .................................................................................................................... 14Figure 5: Government expenditure on education in Namibia as a percentage of GDP, 2007/08-2014/15 ........ 14Figure 6: Real government expenditure on education in Namibia, 2008/09-2014/15 ......................................... 15Figure 7: Education spending shares of selected main divisions, 2007/08-2014/15 ........................................... 16Figure 8: Total school education expenditure as a percentage of total education expenditure,

2008/09-2014/15 .......................................................................................................................................... 18Figure 9: Total school education expenditure as a percentage of GDP, 2007/08-2014/15 .................................. 18Figure 10: Real government spending on education, 2008/09-2014/15 .................................................................. 19Figure 11: School education unit costs, 2014 ............................................................................................................ 19Figure 12: Real national average unit costs of education in primary and secondary schools, 2008-2014 ........ 20Figure 13: Education expenditure by main economic categories, 2007/08-2014/15 ............................................. 21Figure 14: Composition of current expenditure on education, 2007/08-2014/15 .................................................. 22Figure 15: Percentage over- and underspending by economic item, 2007/08-2014/15 ....................................... 22Figure 16: Percentage over/ underspending, by current expenditure item, 2007/08-2014/15 ............................ 23Figure 17: Percentage over/underspending, by current expenditure item, 2007/08-2014/15 ............................. 23Figure 18: The central government debt to GDP ratio in Namibia, 1992/93-2015/16 ........................................... 25Figure 19: Average central government expenditure-to-GDP ratios in 113 countries, 2010-2012 ...................... 28Figure 20: Schools by region and type, 2016 ............................................................................................................ 32Figure 21: Schools sizes in Namibia, 2015 ................................................................................................................ 32Figure 22: Enrolment by remoteness category and region, 2015 .......................................................................... 33Figure 23: Enrolment by grade and year, 2011-2015 ................................................................................................ 33Figure 24: Cross-section vs pseudo-cohort analysis ............................................................................................... 35Figure 25: Enrolment by grade and gender, 2015 .................................................................................................... 35Figure 26: Repetition by grade and gender, 2015 ..................................................................................................... 35Figure 27: Enrolment patterns by grade and year by remoteness category ........................................................ 36Figure 28: Learner-teacher ratio in Namibia, 2015 (number of schools shown) ................................................... 37Figure 29: Comparison of enrolment by schools according to the Fifteenth School Day Survey and

the Annual Education Census of 2015 ..................................................................................................... 42Figure 30: Comparison of enrolment by schools according to the Fifteenth School Day Surveys of

2015 and 2016 ............................................................................................................................................. 43Figure 31: Comparison of number of teachers by schools according to the Fifteenth School Day Surveys

of 2015 and 2016 ......................................................................................................................................... 43Figure 32: Temporary and permanent teachers by region, 2014 (numbers) ......................................................... 44Figure 33: Temporary and permanent teachers by region, 2014 (% of total) ........................................................ 44Figure 34: Teachers by qualification type, 2014 (% of total) .................................................................................... 44Figure 35: Teachers receiving payments per month, 2010-2015 ............................................................................ 45Figure 36: Comparing teacher employment according to the ACE 2014 and Payroll 2014 ................................. 53Figure 37: School attendance by enumerator area wealth decile, 2011 ................................................................ 67Figure 38: School attendance by home language grouping, 2011 ......................................................................... 67Figure 39: Pseudo-survival rates by home language, 2015 .................................................................................... 68Figure 40: Expenditure on school hostels (% of total education expenditure), 2007/08-2014/15 ....................... 82

CONTENTS

TABLES

Table 1: Education-related challenges and responses in the National Development Plan .................................. 8Table 2: Expenditure on education in Namibia, 2007-2015 .................................................................................... 10Table 3: Percentage shares of actual and budgeted total expenditure by vote in Namibia, 2014/15-2016/17 ... 13Table 4: Education expenditure by main divisions, selected years from 2007/08 to 2014/15 ............................ 17Table 5: School enrolment numbers, 2008-2015 ..................................................................................................... 19Table 6: Enrolment in pre-primary education, 2008-2015 ...................................................................................... 20Table 7: Government expenditure on pre-primary education, 2014/15-2015/16 .................................................. 21Table 8: Personnel and non-personnel expenditure in primary and secondary education by region, 2013/14 ... 24Table 9: Personnel expenditure as multiples of non-personnel expenditure in primary and secondary

education by region, 2013/14 ...................................................................................................................... 24Table 10: Fiscal outcomes in Namibia, 2008/09-2015/16 .......................................................................................... 27Table 11: Actual and projected fiscal outcomes in Namibia, 2015/16-2019/20 ...................................................... 27Table 12: The composition of government revenue and grants in Namibia, 2010/11-2014/15 .............................. 28Table 13: Enrolment in Namibian schools, 1992-2015 ............................................................................................... 30Table 14: Number of schools showing the lowest grade and the highest grade offered, 2015 ........................... 32Table 15: Enrolment by grade and year, 1992-2015 ................................................................................................... 34Table 16: Enrolment by home language and grade in 2015 ..................................................................................... 38Table 17: Enrolment per region according to Fifteenth School Day Survey and

Annual Education Census of 2015 .............................................................................................................. 42Table 18: Staff payments within the MoEAC: Teachers, 2014 .................................................................................. 50Table 19: Staff payments within the MoEAC: Non-teaching staff, 2014 ................................................................. 50Table 20: Staff payments within the MoEAC: Teachers plus non-teachers (i.e. all staff), 2014 ........................... 51Table 21: Staff paid (employees) within the MoEAC: Teachers, 2014 ..................................................................... 51Table 22: Staff paid (employees) within the MoEAC: Non-teaching staff, 2014 .................................................... 52Table 23: Staff paid (employees) within the MoEAC: Teachers plus non-teachers (i.e. all staff), 2014 .............. 52Table 24: Part of regional operational budget allocations for 2016/17: Pre-primary ............................................. 56Table 25: Part of regional operational budget allocations for 2016/17: Primary .................................................... 57Table 26: Part of regional operational budget allocations for 2016/17: Secondary ............................................... 57Table 27: Enrolment by region according to the Annual Education Census of 2012 relative to the

Fifteenth School Day Survey of 2016 ......................................................................................................... 58Table 28: Provisional operational budget allocations to regions, 2017/18 ............................................................. 59Table 29: Provisional regional allocations of full operational budget, 2017/18 ...................................................... 60Table 30: Provisional regional allocations of development (capital) budget, 2017/18 .......................................... 60Table 31: Enrolment, teacher and non-teacher salaries, and spending per learner per month by

school type, 2014 .......................................................................................................................................... 63Table 32: Enrolment, teacher and non-teacher salaries, and spending per learner by region, 2014

(monthly salaries) ......................................................................................................................................... 64Table 33: Enrolment, teacher and non-teacher salaries, and spending per learner by remoteness category,

2014 (monthly salaries) ................................................................................................................................ 65Table 34: Enrolment, teacher and non-teacher salaries, and spending per learner by decile of school’s

enumerator area, 2014 (monthly salaries) ................................................................................................. 65Table 35: School enrolment of core school-age group 7-18 according to deciles of enumerator area

wealth status, 2011 ....................................................................................................................................... 66Table 36: Pre-primary-aged children (6 years) out of school, in pre-primary and in primary schools by

region, and younger children in pre-primary schools, 2011 ................................................................... 69Table 37: Enrolment in pre-primary education by region, 2008 to 2015 ................................................................. 70Table 38: Special schools listed on Payroll 2014 ....................................................................................................... 71Table 39: Children with physical disabilities as reported by teachers by grade and nature of disability as

captured in the Annual Education Census, 2015 ...................................................................................... 72Table 40: School enrolment and projections, 1950 to 2050 (in thousands) ............................................................ 77

CONTENTS

Contents vii

viii A Public Expenditure Review of the Basic Education Sector in Namibia

During the past decade, Namibia has made great strides in achieving education for all, and for implementing the national Sector Policy on Inclusive Education. The country introduced the

universal free primary and secondary education in 2013 and 2016 respectively, and currently ranks third on the Education for All Development Index. The Inclusive Education policy was reviewed through a vigorous consultative process, and a comprehensive National Framework for Integrated Early Childhood Development (IECD) was developed and is being used to guide and coordinate all ECD-related matters in the country. However, despite the efforts to ensure access to inclusive, equitable and quality education for all Namibian children, the country continues to be faced with a number of challenges. The education system has been characterised by poor teaching and learning outcomes and inequitable distribution of both financial and human resources. The Sustainable Development Goals (SDGs) agenda, introduced in 2015, brings forth opportunities for Namibia to address the challenges remaining in the education sector. SDG4 speaks of inclusive and equitable quality education and lifelong learning for all, and is the foundation that will anchor global efforts to deliver on this ambitious and bold set of promises. Feeding into this global agenda are Namibia’s Vision 2030, Harambee Prosperity Plan and Fifth National Development Plan (NDP5), which places more emphasis on the role of education in sustainable development. We all know that education is one of the most costly services for any government. In Namibia, the existence of a strong positive relationship between GDP per capita and public education spending per capita is evident. Hence, government spending on education is adequate, and we commend the Namibian Government for that. Although this is a reflection of the country’s level of economic development, it is not one that fully satisfies the demand for education services. This report reveals that budget allocation and expenditure favour primary and secondary education, with very little spent on pre-primary education. It also notes that the majority of the financial resources are spent on personnel, which impacts on allocating resources to teaching and learning materials, assistive technologies for learners with disabilities, and the building and maintenance of facilities. While the report indicates challenges in relation to budget allocation and expenditure, it is important to note that the Public Expenditure Review process helped to improve the roleplayers’ awareness and understanding of the human and financial resource constraints that the responsible Ministry faces. We at UNICEF are in agreement that expenditure on education is a vital investment for a country’s future. But it is not only about how much we spend; it is also about how well we spend it. We are hopeful that the data contained in this report will assist all of us involved in the education sector to take the action required to speedily implement the recommendations herein, and to ensure that the Government of Namibia and the Ministry of Education, Arts and Culture are able to meet the national development targets and the SDGs. UNICEF remains committed to engaging with the Ministry, and will provide support for implementing the recommendations flowing from this review.

Rachel OdedeUNICEF Representative in Namibia

FOREWORD PREFACE

Article 20 of the Namibian Constitution makes provision for the right of all persons in Namibia to education, and states that “primary education shall be compulsory and the State shall provide

reasonable facilities to render effective this right for every resident within Namibia, by establishing and maintaining State schools at which primary education will be provided free of charge”. In addition, the Education Act, 2001 (Act No. 16 of 2001), states that “all tuition provided for primary and special education in state schools, including all school books, materials and other related requisites must be provided free of charge to learners until the seventh grade, or until the age of 16 years, whichever occurs first.”

The education sector has received the highest budgetary allocations since Namibia’s attainment of independence in 1990. In addition, the role of education in contributing to sustainable development has been prioritised in all National Development Plans and Namibia’s Vision 2030. However, despite the budgetary allocations and the conducive legislative environment, the education sector remains characterised by high repetition and dropout rates and poor learning outcomes at all levels of basic education (i.e. pre-primary grades to Grade 12). In addition, offering quality education services to remote rural areas in this geographically vast and sparsely populated country poses difficulties, which include qualified teachers’ reluctance to accept positions in remote areas, and a lack of boarding facilities for learners to access schools, particularly in the higher grades. Furthermore, accommodation in school hostels, transportation and school uniforms appear to inhibit access to education for children of poor families, particularly in remote rural areas. Learners with disabilities across all grades also face barriers to education, due to lack of, inter alia, qualified inclusive-education teachers, disability-friendly infrastructure, teaching and learning materials and assistive technologies. To address some of these challenges, Namibia introduced universal free primary education in 2013 and universal free secondary education in 2016.

To acquire a better understanding of the linkages between inputs, outputs and outcomes in basic education, and to assess the efficiency of public spending and resource allocation for basic education, it was necessary to conduct an extensive review of public expenditure on basic education. The Research on Socio-Economic Policy (ReSEP) research group attached to the Department of Economics at the University of Stellenbosch in South Africa, with financial and technical support from UNICEF Namibia, assisted the Ministry of Education, Arts and Culture to conduct the Public Expenditure Review (PER). This report conveys the findings. It evaluates the current effectiveness of the public expenditure on basic education and the resulting service delivery at all levels of basic education in terms of education costs and financing, allocative efficiency, productive efficiency, internal and external efficiency, equity, quality and effectiveness. It also discusses key aspects of the financing of basic education, and identifies challenges which are barriers to quality inclusive education in Namibia. Finally, it offers detailed recommendations. The implementation of these will require collaboration and partnerships with other line ministries. A ministerial task force will be appointed to review the recommendations and to provide guidance as to how to implement them.

Katrina Hanse-Himarwa, MPMinister of Education, Arts and Culture

Preface ix

FOREWORD PREFACE

x A Public Expenditure Review of the Basic Education Sector in Namibia

The Public Expenditure Review (PER) of the Namibian Education Sector was conducted by the Research on Socio-Economic Policy (ReSEP) research group in the Department of Economics

at the University of Stellenbosch in South Africa with both financial and technical support from UNICEF Namibia. A word of thanks and appreciation goes to the team from the University of Stellenbosch, in particular Professor Servaas van der Berg, Dr Chris van Wyk, Dr Ada Jansen, Dr Krige Siebrits, Dr Cobus Burger, Ms Heleen Hofmeyr, Dr Debra Shepherd, Ms Keorapetse Mogorosi and Mr Hendrik van Broekhuizen, who facilitated the review process. They met with senior officials in the Ministry of Education, Arts and Culture and the Ministry of Finance, and undertook visits to regions and schools to gather information and data at the national level, and engaged with regional and school personnel to obtain their views on the functioning of the system.

Conducting the review required considerable inputs from a wide range of people and institutions. We would also like to thank all stakeholders and officials of the Ministry, regional officials and school principals for sharing their insights and data. Special thanks go to the Permanent Secretary, Ms Sanet Steenkamp, who gave her wholehearted support to this review, and in particular also Ms Levinia Karises and Ms Edda Bohn, who went out of their way to provide all the necessary information required for this review.

Finally, we thank UNICEF for the financial, logistical and technical support that made this review possible. UNICEF’s input and guidance as a partner of the MoEAC in promoting and advocating for access to inclusive, equitable and quality education for all children in Namibia, particularly the most vulnerable, are always greatly appreciated.

ACKNOWLEDGEMENTS

Chapter 1: Background 1

1 BACKGROUND

1

2 A Public Expenditure Review of the Basic Education Sector in Namibia

1.1 A NOTE TO THE READER

This report does not contain an Executive Summary, but the final chapter, Chapter 8, was written to contain both a summary and a list of recommendations. Thus the reader with limited time is advised to initially read Chapter 8.

1.2 THE CONTEXT

Despite the attention given to education, factors such as costs related to accommodation in school hostels, transport to school and school uniforms, still appear to inhibit access to education for Namibian children from poor families, particularly in sparsely populated areas. Risks to educational enrolment and retention include poverty, illness, children being sent to other households, extended families taking more children into the household, and maternal death. Considering the commitment of the Ministry of Education, Arts and Culture (MoEAC) to Namibia’s National Development Plans and Vision 2030, and to the Sustainable Development Goals (SDGs) in education and Education for All (EFA), careful planning for the education sector is essential.

Given tight fiscal and personnel resource constraints at national and regional levels, improving educational outcomes requires a fuller understanding of linkages between inputs, outputs and outcomes within the education sector. A Public Expenditure Review (PER) can assist in creating a better awareness and understanding of the resource constraints that the Ministry faces, particularly given the high expectations for education in Namibia’s economic and social development.

Educational quality in Namibia is still relatively weak. In the 2007 SACMEQ assessments, conducted in 15 countries of the Southern and Eastern African region at Grade 6 level, Namibia performed better than in 2001, yet still not very satisfactorily – almost one third of a standard deviation below the average for all SACMEQ countries. Performance also varied greatly across geographic space, including across type of area (cities versus small towns versus isolated rural areas) and between regions.

Namibian education is still characterised by enrolment that is often over-age, weak learning outcomes, high rates of repetition and early dropout. Particular problems relating to the difficulty of offering education services to remote rural areas include the consequent need to encourage teachers to accept positions in such areas, and the need for boarding facilities to make it possible for some children to access schools, particularly in the higher grades. Historically the majority of unqualified teachers have been employed in rural schools, contributing to a learning deficit there which is compounded by high rates of teacher turnover and low socio-economic status of learners in such areas.

Teacher subject knowledge too is not particularly strong, even in the context of the region: whereas the average Grade 6 teacher in all 15 countries of Southern and Eastern Africa surveyed in SACMEQ III scored 814 on the mathematics test, those in Namibia scored only 771, about 40% of a standard deviation lower. For reading the scores were less different, with 748 for the SACMEQ teachers and 739 for Namibian teachers (Spaull, 2012).

Namibia has made great strides in achieving education for all. Education has an important role in national development priorities, as espoused in the Fourth National Development Plan (NDP4) and Vision 2030. The right to education is also protected in the Namibian Constitution, which states that “All persons shall have the right to education” and primary education at state schools will be provided free of charge, and in the Education Act, 2001 (Act No. 16 of 2001), which stipulates:

Chapter 1: Background 3

“All tuition provided for primary and special education in state schools, including all school books, materials and other related requisites must be provided free of charge to learners until the seventh grade, or until the age of 16 years, whichever occurs first.”

Free secondary education was introduced in 2016. Hence parental contributions that are not voluntary were abolished.

In 2005, the Education and Training Sector Improvement Programme (ETSIP) was adopted. This is a 15-year strategic plan (2006-2020) for the education sector to meet the demands of Vision 2030, which aims to achieve higher levels of industrial development and to enhance equity. This review broadly covers the end of the second of the three ETSIP cycles of five years each, and the latter part of the period of NDP4 (2012/13 to 2016/17).

1.3 THE REVIEW PROJECT

The Public Expenditure Review (PER) project was started with an Inception Meeting on 18 August 2016, chaired by Ms Levinia Karises (Director: Finance). At this meeting, arrangements were made for three components of the work, namely for background documents to be made available to the research team, for obtaining the fiscal data required, and for fieldwork visits to regions and schools.

A first task was to conduct a desk review of documents, studies, policy documents, household surveys, education statistics, and the education budget.

A next step required obtaining information from school and regional level about the budgetary and financing process at regional and parti-cularly school level. In September 2016 researchers visited the regions //Kharas, Zambezi and Oshana and held discussions with 10 school principals in each region, drawn from primary, combined and secondary schools. In addition, researchers visited five schools each in Khomas and Erongo to interview prin cipals. The MoEAC kindly assisted with the selection of principals and schools to ensure variety in terms of socio-economic status, primary and secondary schools and schools with and without hostels.

An important part of the work revolved around obtaining the necessary financial and other data to undertake the analysis from the finance directorate in the MoEAC. Although the team could not manage to obtain data for as many years as had been desired, enough data was obtained to allow a broad review of public expenditure in school education and to analyse underlying trends, relationships and issues that may require attention. The payroll data for teachers, non-teachers at schools and administrative staff was of particular value, allowing new insights into fiscal issues of the education system and particularly on the equity issue.

A first draft of this report was presented to a meeting of the Steering Committee and some other stakeholders on 9 February 2017. This meeting was also attended by the Honourable Deputy Minister of Education, Arts and Culture, the Permanent Secretary of the Ministry and several regional directors. A final draft was presented to a meeting on 27 March 2017 in Windhoek, attended by members of the Steering Committee as well as senior managers in the MoEAC.

4 A Public Expenditure Review of the Basic Education Sector in Namibia4 A Public Expenditure Review of the Basic Education Sector in Namibia

2 FISCAL POLICY AND THE FINANCING OF EDUCATION

Chapter 2: Fiscal Policy and the Financing of Education 5

2 FISCAL POLICY AND THE FINANCING OF EDUCATION

5


This chapter discusses various aspects of the financing of education in Namibia in recent years. Following an overview of aspects of the policy context that affects the financing of education,

it addresses the following four sets of questions:

How much was spent on education, and by whom?Was public spending on education adequate and sustainable?Was the allocation of public resources in the education sector efficient?What are the future implications for the public financing of education of current and structural

aspects of fiscal policy?

2.1 THE POLICY CONTEXT

The Constitution of the Republic of Namibia is the fundamental law of the country. An indicative planning system guides policymaking and implementation to realise the Constitution’s provisions. Vision 2030, the national policy framework for long-term development adopted in 2004, is the foundation of the planning system. This document serves as a unifying vision that provides direction to role-players in the public, private and non-governmental sectors and guides all decisions on development policies. Five-year National Development Plans (NDPs) are the mechanisms for realising Vision 2030. The previous plan, NDP4, was complemented since 2016 by the Harambee Prosperity Plan, which focuses on high-impact interventions in priority areas. NDP4 came to an end in March 2017. The National Planning Commission recently released a draft version of NDP5 for comments. The launching of the new plan was scheduled for the end of March 2017.

The Namibian Government has been prioritising the provision of education throughout the post-Independence period. Hence, major policy documents have consistently emphasised the importance of education and training. Article 20 of the Constitution (Republic of Namibia, 1990: 14-15) enshrines the right to education, makes primary education compulsory and obligates the State to establish and maintain schools at which primary schooling is provided free of charge. Furthermore, it establishes that children should stay in school until completing their primary education or until they reach the age of 16, whichever is sooner. Article 20 also enshrines the right to establish and maintain private institutions providing education, provided that such institutions are registered with the Government, maintain at least the same standards as similar State-funded ones, and do not discriminate in the recruitment of personnel and the admission of learners.

Education and training feature prominently in Vision 2030. The document contains the following three broad objectives for the education system (Office of the President, 2004: 95):

To ensure an integrated, unified and flexible education and training system which is accessible to all Namibians from early childhood.

To achieve an affordable and pragmatic education and training system, capable of producing a balanced supply of human resources, in response to demands in the labour market.

To ensure that the society is comprised of people who are literate, skilled, articulate, innovative, informed and proactive.

Vision 2030 also contains concrete targets for the education and training system and identifies strategies for achieving these targets. The targets set are as follows (Office of the President, 2004: 91):

Expand access to secondary schools for the target age group by 2006.Provide all schools with drinking water and electricity where the necessary infrastructure will

be constructed by 2006.


Equip all schools with school fur-niture by 2006.

By 2015, there should be at least one teacher for every 35 learners in primary schools, and for every 30 learners in secondary schools. Government is working towards having 90% of the teaching posts per manent by 2015 as opposed to the current 84% perma nent and 16% non-permanent.

By 2010, no more unqualified or under-qualified teachers in the country’s schools.

The minimum qualification required for being appointed as a teacher is a Teacher’s Diploma for primary schools and a Bachelor of Education Degree for secon dary schools.

By 2005 a coherent Vocational Education and Training Policy Framework will be in place.By 2005 the National Examination, Assessment and Certification Board is established and has

localised the IGSCE and HIGSE Examination System.By 2030 Vocational Training Centres are established in all regions.The literacy education rate for adults was 80% in 2001, expected to increase to 90% in 2015

and ultimately 100% by the year 2030.Achieving a 50% improvement in levels of adult literacy by 2015, especially for women, and

equitable access to basic and continuing education for all adults.Eliminating gender disparities in primary and secondary education by 2005, and achieving

gender equality in education by 2015, emphasising girls’ full and equal access to and achievement in basic education of good quality.

Provide those who live with disabilities, access to lifelong learning by 2030.Encourage the development of lifelong learning in Namibia through institutional and staff

development by 2006.

In addition, the document specifically emphasises the importance of ensuring access to high-quality Early Childhood Development (ECD) by means of the curriculum and programme development and capacity building among caregivers and trainers (Office of the President, 2004: 98-99).

The current national development plan (NDP4) lists education and skills among the basic enablers for the realisation of Vision 2030. It highlights various education-related achievements during the post-Independence period, but also acknowledges the realities of wide-ranging quality problems in the education and training system and a mismatch between the demand for and the supply of skills in the country. Specific mention is made of the country’s large investment in education and of the need “to ensure that we achieve the intended returns on these investments, so that this expenditure requirement remains manageable and its yields positive” (National Planning Commission, 2012b: 46). The NDP4 identifies the following six education-related challenges:

The quality of graduates from all levels of education remains below desired levels.The limited provision and affordability of Early Childhood Development centres and educarers.Investment to quality ratios in primary education are lower than desired.Insufficient numbers of students obtain Grade 12 qualifications.The underdevelopment of research and development in Namibia – few institutions undertake

R&D on a significant scale.Limited (insufficient) provision of vocational and technical education, as well as poor (and

inaccurate) perceptions of vocational and technical education.


NDP4 also presents 23 responses to these challenges. Table 1 below lists these responses.

Table 1: Education-related challenges and responses in the National Development Plan

CHALLENGES RESPONSES

The quality of graduates from all levels of education remains below desired levels

Improved learning standards and curricular development

Teacher development

Improved availability of textbooks and material

Improved stringent learner assessment

Improved hard and soft infrastructure

Improved alignment between market demand and institutional supply

The limited provision and affordability of Early Childhood Development centres and educarers

Provision of 100 free, government-run, strategically located ECD centres by 2017, focusing on the poorest sections of society

Increased provision of and support for ECD teacher training

Increased ministerial capacity to implement and support ECD centres

Transfer responsibility for ECD from the Ministry of Gender Equality and Child Welfare to the Ministry of Education, Arts and Culture

Investment to quality ratios in primary education are lower than desired

Increased availability of pre-primary and primary education

Increased focus on quality, particularly regarding numeracy and literacy

Improved efficiency in the use of resources, focusing on value for money

Insufficient numbers of students obtain Grade 12 qualifications

Increased availability of opportunities and places in senior secondary education

Improved conditions of service for teachers and the quality of the education they need to provide in the secondary phase

Improved availability of secondary education textbooks and other teaching and learning materials

The under development of research and development (R&D) in Namibia

Increased spending on R&D to at least 0.3% of GDP by 2017

Limited (insufficient) provision of vocational and technical education, and poor (and inaccurate) perceptions of vocational and technical education

Linking of VET and technical education in general to envisaged NDP4 priority areas

Increased provision of VET and technical education, targeting especially impoverished areas

Introducing competency-based education and training

Improved standard of qualifications for educators, and increased throughputs of educators

Provision of adequate equipment and infrastructure for VET centres

Certification of acquired skills in the informal sector

Source: National Planning Commission (2012b: 50-52).


The Harambee Prosperity Plan runs from the 2016/17 to 2019/20 fiscal years. The Plan maintains the accent on vocational and technical education, both as a mechanism for social progression and for improving the competitiveness of the Namibian economy.

The Namibian budget process has incorporated a Medium-Term Expenditure Framework (MTEF) since 2001. The MTEF is the main budget document. Two other documents, namely the Estimates of Revenue, Income and Expenditure and the Development Programmes Estimates of Expenditure, provide detailed information about the budgeted outlays of the various budget votes. The MTEF contains the macro-fiscal framework for the next three years, accompanied by spending ceilings for each vote that are revised annually. The priorities and allocation of resources in each MTEF are set in line with Vision 2030 and the current National Development Plan. Alignment with Namibia’s national development goals is also facilitated by the Medium-Term Plans (MTPs) introduced in the 2003/04 fiscal year. Each budget vote’s MTP sets out its allocated resources, key activities and the contributions of the various programmes to national develop ment objectives. The Accountability Reports published since 2005 is another important aspect of Namibia’s MTEF. These documents report on budget outcomes at the aggregate, vote and programme levels, and provide detailed information about the achievements and challenges of each ministry, office and agency.

The education and training sector’s response to the call of Vision 2030 is the Education and Training Sector Improvement Programme (ETSIP), which was released in 2007. ETSIP is a comprehensive programme with detailed targets for all components of the education and training system (early childhood development and pre-primary education; general education; vocational education and training; tertiary education and training; knowledge and innovation; and information, adult and lifelong learning), along with cost estimates and implementation plans. Namibia has also prepared an Education for All National Plan of Action for the period 2002 to 2015. This plan focuses on the attainment of access to good quality education for all Namibian children, including ethnic minorities and those in difficult circumstances.

Several new education-related laws and policies have been adopted since the turn of the century, including the Education Act (2001), Namibia Students Financial Assistance Fund Policy (2005), Sector Policy for Orphans and Vulnerable Children (2008), National Textbook Policy (2008) and Sector Policy on Inclusive Education (2013). In 2016, a review of the Education Act of 2001 was initiated with three purposes (Ministry of Education, Arts and Culture, 2016: iii):

To reflect the rights-based evolution of the education sector.To enhance the provision of access to free, equitable, inclusive and quality education for all

children in Namibia.To strengthen the foundations of lifelong learning through the provision of integrated early

childhood development services.

The emphasis on planning in Namibia and the creation of mechanisms to link national development goals to the annual budget cycle via the MTEF are commendable. Compliance with the reporting and monitoring elements of the planning system may well have become time- and resource-intensive tasks for officials of the Ministry of Education, Arts and Culture, though. Moreover, the many goals in the various plans represent an ambitious policy agenda, even if the focus is restricted to the priorities identified in the NDP4. It is not clear whether the planning system provides adequate mechanisms for prioritising goals when financial and human resource constraints become binding, for example, in times of fiscal stress such as that currently experienced.


2.2 THE EXTENT OF EXPENDITURE ON EDUCATION

This subsection shows the evolution of spending on education by the Government, individuals and donors from 2007 to 2015. As one would expect, the Government undertakes the bulk of spending on education in Namibia. Table 2 shows that government expenditure on education increased from N$4 244 million in 2007 to N$13 685 million in 2015 (these numbers are from the production or gross value added table in the national accounts). The portion of general government spending devoted to education increased slightly from 21.6% in 2007 to 22.4% in 2015, despite a significant drop in 2010. As a percentage of the gross domestic product (GDP) at market prices, government expenditure on education increased steadily from 6.9% to 9.3%. Sections 2.3 and 2.4 of this report analyse these expenditures in more detail.

Table 2: Expenditure on education in Namibia, 2007-2015

2007 2008 2009 2010 2011 2012 2013 2014 2015

Government

N$ millions 4 244 4 844 5 546 5 872 7 403 8 827 10 524 12 863 13 685

% of government spending 21.6 22.9 22.4 19.6 23.2 21.9 21.8 22.9 22.4

% of GDP at market prices 6.9 6.9 7.4 7.1 8.2 8.3 8.6 9.2 9.3

Households

N$ millions 1 995 2 424 2 662 2 438 3 547 4 100 4 485 5 271 5 606

% of consumption spending 5.3 5.2 4.8 4.5 5.7 5.7 5.4 5.9 5.9

% of GDP at market prices 3.2 3.5 3.5 3.0 3.9 3.8 3.7 3.8 3.8

Donors

N$ millions 0 31 83 n/a 24 169 168 n/a n/a

Sources: Office of the Auditor General (2009b; 2010b; 2011b; 2012b; 2013b; 2014a; 2014c; 2015; 2016); Namibia Statistics Agency (2016).

Note: Figures for the Government and individuals are from the national accounts and reflect expenditures in calendar years. Donor aid numbers are fiscal-year figures from reports by the Office of the Auditor General.

Households augment their tax contributions to the financing of education with substantial out-of-pocket spending. From 2007 to 2015, private consumption expenditure on education increased from N$1 995 million to N$5 606 million. The figures indicate that household expenditure on education services ranged from 41% to 50% of government spending on education. As a percentage of total private consumption expenditure, spending on education services averaged 5.5% during this period. While much smaller than the share of total household expenditure on food, beverages and tobacco (30.0%), households did not spend markedly less on education services than on transport and healthcare (7.2% and 6.6% of total private consumption expenditure, respectively) (Namibia Statistics Agency, 2016: 24).

As is the case in most middle-income countries, Namibia receives little donor aid. Furthermore, the volume of donor aid varies greatly from year to year. The Ministry of Education, Arts and Culture (formerly known as the Ministry of Education) received the bulk of the donor aid reported by the Office of the Auditor General from 2006/07 to 2012/13. In this period, donor aid to the Ministry amounted to N$474 million. This constituted 81.5% of the total reported donor aid to the Namibian Government.


2.3 THE ADEQUACY AND SUSTAINABILITY OF PUBLIC EDUCATION FINANCING

Education services are in high demand worldwide, and the reality that households everywhere undertake out-of-pocket expenditures on such services shows that no government meets this demand in full. In practice, countries’ levels of government spending on education are linked closely to their levels of economic development: the more developed a country, the more its government is likely to spend on education per head of the population. This relationship is confirmed by which shows public spending on education per capita in US dollars in 115 countries in 2010.1 The countries are arranged from the poorest to the richest based on their levels of GDP per capita in 2014 (GDP per capita being a common, albeit imperfect, proxy of economic development). The existence of a strong positive relationship between GDP per capita and public education spending per capita is evident. Hence, this review defines an “adequate” level of government spending on education as one that is reasonable in the context of a country’s level of economic development, as opposed to one that fully satisfies the demand for education services.

Figure 1: Government spending on education per capita in 115 countries, 2010

Source: Compiled from information in World Bank (2016).

This perspective suggests that international comparisons of the ratio between government spending on education and total government spending and the ratio between government spending on education and GDP are useful for gauging the adequacy of governments’ education expenditures. and Figure 3 depict these ratios for the same 115 countries compared in Figure 1.

Figure 2: Government spending on education as a percentage of total government expenditure in 115 countries, 2010

Note: Namibia’s ratio is indicated by the black dot. Source: Compiled from information in World Bank (2016).

1 2010 is the last year for which data are available for a large number of countries. The source of the data is the Word Development Indicators database of the World Bank (2016). The education spending data in this database differ somewhat from the national accounts data in Table 2.


Figure 3: Government spending on education as a percentage of GDP in 115 countries, 2010

Note: Namibia’s ratio is indicated by the black dot. Source: Compiled from information in World Bank (2016).

In these figures too, the countries are arranged from poorest to richest. This makes it possible to compare the public education spending ratios of each country with those of other countries with similar levels of economic development. Both figures suggest that government spending on education in Namibia is high by international standards. This is true whether Namibia is compared with its peer countries (those with roughly similar GDP per capita figures) or with all other countries. Namibia had the third highest public education expenditure to total government spending ratio among the 115 countries, and the seventh highest public education expenditure to GDP ratio. While the level of household expenditure on education services is a reminder of the extent of the unmet demand, the volume of resources made available by the Namibian Government for the provision of education is probably close to the maximum that an upper-middle-income country can afford.

The adequacy of public education expenditure can also be established by ascertaining whether the education function receives a reasonable share of the Government’s budget. Ideally, this requires a detailed comparative analysis of the needs of all spending units. Such an analysis falls outside the scope of this review. Suffice it to say that the allocation of the MoEAC has long been markedly larger than that of any other government office, agency or ministry in Namibia. In 2014/15 – the most recent fiscal year for which actual outlays are available – the MoEAC undertook 18.1% of total government spending (cf. Table 3). The outlays of the following ministries also exceeded 4% of total government spending in that year: Defence (11.0%), Finance (10.2%), Health and Social Services (9.7%), Safety and Security (8.6%), Transport (6.8%), Higher Education (4.7%), Urban and Rural Development (4.5%) and Agriculture, Water and Forestry (4.1%). The increase in the expenditure share of the MoEAC from 2015/16 to 2016/17 partly reflected the transfer of the arts, heritage and culture functions from the then Ministry of Youth, National Service, Sport and Culture to what was until then the Ministry of Education. Education, Arts and Culture will remain the biggest budget vote throughout the 2017/18-2019/20 MTEF period (Ministry of Finance, 2017: vi).

The sustainability of the budget as a whole is a critical element of the sustainability of its components. Section 2.5 discusses this aspect of the sustainability of public spending on education in Namibia. The remainder of this subsection considers two other sustainability measures, namely trends in the ratios of public education spending to total government spending and to GDP. Regular decreases and considerable volatility in these ratios are likely to be indicative of emerging sustainability problems.

Figure 4 and Figure 5 show how the ratio between government spending on education and total government expenditure and the ratio between such government spending on education and GDP evolved from the 2007/08 fiscal year onwards. The public education and total government spending figures are from the reports of the Office of the Auditor General on the accounts of the MoEAC (in earlier years, the Ministry of Education) and the accounts of the Government of Namibia, respectively. The most recent report on the accounts of the MoEAC on the website of the Office of the Auditor General is for 2014/15. Hence, the spending numbers in the two figures


exclude outlays on arts, heritage and culture and include outlays on higher education. (The Ministry of Higher Education was established in 2015.) Each figure shows trends in two public education spending aggregates, namely “total” education expenditure and “core” education expenditure. “Total” education expenditure includes all outlays reflected in the reports on the Ministry’s accounts. “Core” education expenditure includes outlays on the components of the education budget focused on in this review. As such, the latter excludes spending by the following divisions of the budget vote: the Namibian Library and Information Services; Science, Technology and Innovation; and the HIV and Aids Management Unit. Outlays on pre-primary education – which are available for only two years in the accounts of the MoEAC – are also excluded from “core” education expenditure. (Section 2.4.3 briefly discusses aspects of the financing of pre-primary education in Namibia.) The most recent report on the accounts of the Government of Namibia on the website of the Office of the Auditor General is for 2012/13.

Table 3: Percentage shares of actual and budgeted total expenditure by vote in Namibia, 2014/15-2016/17

BUDGET VOTES2014/15 2015/16 2016/17Actual Revised Original Revised

President 1.0 1.1 1.0 1.0Prime Minister 1.0 1.6 0.7 0.8National Assembly 0.3 0.3 0.3 0.3Auditor General 0.1 0.1 0.1 0.1Home Affairs and Immigration 0.9 0.9 0.8 0.8Safety and Security 8.6 8.6 7.8 8.1International Relations and Cooperation 1.5 1.4 1.4 1.4Defence 11.0 10.6 10.0 9.7Finance 10.2 10.4 12.4 11.3Education, Arts and Culture 18.1 17.2 19.4 20.0National Council 0.2 0.1 0.2 0.2Gender Equality and Child Welfare 1.2 1.2 1.3 1.6Health and Social Services 9.7 9.4 11.0 11.3Labour, Industrial Relations and Employment Creation 2.8 0.5 0.3 0.3Mines and Energy 0.6 0.4 0.4 0.3Justice 1.2 0.9 0.5 0.5Urban and Rural Development 4.5 4.7 4.3 4.3Environment and Tourism 1.2 1.0 0.9 0.8Industrialisation, Trade and SME Development 1.7 1.3 1.3 0.9Agriculture, Water and Forestry 4.1 4.5 3.5 4.1Judiciary 0.0 0.0 0.4 0.4Fisheries and Marine Resources 0.6 0.5 0.4 0.4Works 1.1 1.0 1.0 1.0Transport 6.8 6.9 6.3 5.6Land Reform 1.0 1.6 0.9 0.8National Planning Commission 0.4 0.3 0.3 0.3Sport, Youth and National Service 1.2 0.7 0.7 0.6Electoral Commission 0.6 0.4 0.3 0.2Information and Communication Technology 0.9 0.9 0.8 0.7Anti-Corruption Commission 0.1 0.1 0.1 0.1Veteran Affairs 2.6 1.2 1.4 1.3Higher Education, Training and Innovation 4.7 6.0 5.2 5.7Poverty Eradication and Social Welfare n/a 3.9 4.4 4.7Public Enterprises n/a n/a 0.1 0.1Office of the Attorney General n/a 0.2 0.2 0.2Total 100.0 100.0 100.0 100.0

Source: Ministry of Finance (2016d: 50-84).


Figure 4: Government expenditure on education in Namibia as a percentage of total government expenditure, 2007/08-2012/13

Sources: Office of the Auditor General (2009a; 2009b; 2010a; 2010b; 2011a; 2011b; 2012a; 2012b; 2013a; 2013b; 2014a; 2014c).

Figure 5: Government expenditure on education in Namibia as a percentage of GDP, 2007/08-2014/15

Sources: Namibia Statistics Agency (2016); Office of the Auditor General (2009b; 2010b; 2011b; 2012b; 2013b; 2014c; 2015; 2016).

On balance, “total” and “core” education expenditure increased as percentages of total govern-ment expenditure and of GDP. “Total” education expenditure, for example, increased from 22.1% of total government expenditure in 2007/08 to 24.7% in 2012/13. As a percentage of GDP, it increased from 6.0% in 2007/08 to 9.2% in 2014/15. Furthermore, shows that “total” education expenditure at constant 2012 prices increased in real terms from N$6 213 million in 2008/09 to N$12 210 million in 2014/15. These trends occurred during a period of brisk economic growth: the real rate of growth in GDP at market prices exceeded 5% in every year from 2007 onwards except in 2008 and 2009 (that is, when the world economy experienced the so-called “Great Recession” after the international financial crisis in 2007/08). Hence, there seems to be little reason for concern about the sustainability of public spending on education in Namibia in times of good economic performance. This conclusion, however, does not rule out the possibility of pressure on the education budget in times of severe fiscal stress. Section 2.5 returns to this issue in the context of a discussion of the implications of the current pressure on the public finances for public education financing.


Figure 6: Real government expenditure on education in Namibia, 2008/09-2014/15


2.4 ASPECTS OF THE EFFICIENCY OF PUBLIC EXPENDITURE ON EDUCATION

The volume of resources that governments make available for the financing of education is very important. Ultimately, however, it is the outputs of the education system that matter. Burger, Smith, Spaull and Van der Berg (2015: 150) had the following to say about the relationship between inputs – which include allocated funds – and outputs in the delivery of social services:

“It is useful to acknowledge that there is no reason to assume that there should be any correlation between funds allocated to a … policy or intervention and improved outcomes. Only when funding is spent on resources that reach their intended destination and are utilised effectively will there be a strong likelihood of an improvement in social outcomes.”

One of the critical aspects of relationship between inputs and outcomes is the pursuit of technical efficiency (that is, obtaining the maximum possible output from a given set of resources).2 Much of this report deals with issues of technical efficiency in the Namibian education system. This section, however, focuses on aspects of the allocative efficiency of public education spending. More specifically, it considers whether funds are allocated among parts of the education system (e.g. pre-primary, primary and secondary education) and among categories of expenditure (e.g. remuneration of employees, purchases of goods and services and capital expenditures) in a manner that facilitates the provision of an optimal mix of education services. Two sets of criteria are used to assess the allocation of funds: the education-related priorities of the Namibian Government as stated in key policy documents (cf. Section 2.1) and lessons from the experiences of Namibia and other countries. It is well established internationally, for example, that personnel spending often crowds out other important expenditures to the detriment of the performance of education systems (cf. Pritchett and Filmer, 1999; Glewwe, 2014).

2 Burger et al. (2015: 150) define outputs as “deliverables that are usually easy to observe, count and verify, and are usually intermediary aims that are necessary but not sufficient conditions for meeting the ultimate goal of a programme”. The number of children enrolled in school is an output. Outcomes, by contrast, are “deliverables that are more difficult to observe, count and verify, but are linked to the ultimate goal of a programme” (Burger et al., 2015: 150) – for example, whether children enrolled in school are learning at the expected pace.


This section uses two sources of data on public education spending. Where possible, use is made of the audited figures in the reports of the Office of the Auditor General on the accounts of the Ministry of Education and, more recently, the MoEAC. For the purposes of this review these reports have two shortcomings. As was mentioned earlier, the latest report covers the 2014/15 fiscal year. In addition, the reports lack data on the composition of expenditures by the various main divisions of the budget vote Education, Arts and Culture: information on the various forms of current and capital spending are provided for the budget vote as a whole, but not for its main divisions. Hence, actual expenditure data reported by the Ministry of Finance in budget documents are used for some analyses. These data are not available as a single time series, and were compiled from issues of the Estimates of Revenue, Income and Expenditure and the MTEF available on the website of the Ministry of Finance. Each number is taken from the most recent publication with information about actual expenditures in a specific year. These numbers are not necessarily final, however, and some differ from the corresponding ones in the reports of the Office of the Auditor General.

2.4.1 Education expenditure by main divisions

In 2014/15 the budget vote Education, Arts and Culture consisted of 21 main divisions. Table 4 shows the amounts spent by each main division in selected years from 2008/08 to 2014/15, as well as the shares of the total spending of the vote attributable to the largest divisions. These numbers should be interpreted with caution because some items were moved between divisions in this period (note, for example, the effect of the temporary inclusion of transfers to regional councils on the outlays of the Administration division in 2010/11). It is clear, though, that three divisions (primary education, secondary education and tertiary education, including the Namibian Student Financial Assistance Fund) dominate the outlays of the budget vote Education, Arts and Culture. Their combined share of the Ministry’s spending was 77.1% in 2007/08 and 88.0% in 2014/15 (cf. also Figure 7).

The policy documents referred to in Section 2.1 do not contain quantitative targets for the expenditure shares of the various divisions. Furthermore, the policy goals in these documents imply the need for more spending on all delivery components of the education system (pre-primary education, primary education, secondary education, higher education, vocational and technical training and adult education). Hence, there is no obvious way to assess the changes in the composition of expenditures by the MoEAC with reference to the education policy goals of the Namibian Government. The increases in the expenditure shares of pre-primary education and vocational and technical training (albeit from very low bases) are significant in view of the emphasis on these programme in NDP4 and the Harambee Prosperity Plan, though. The increase in the spending share of secondary education, too, is in line with the NDP4 goals.

Figure 7: Education spending shares of selected main divisions, 2007/08-2014/15

Sources: Office of the Auditor General (2009b; 2010b; 2011b; 2012b; 2013b; 2014c; 2015; 2016b).


Table 4: Education expenditure by main divisions, selected years from 2007/08 to 2014/15

DIVISIONS 2007/08 2010/11 2013/14 2014/15

N$ millions

Office of the Minister 2 3 3 4

Administration 107 828 205 122

Programme quality assurance 196 271 284 131

Primary education 1 895 3 101 5 966 6 581

Secondary education 695 1 019 2 142 3 056

Namibia library and information services 30 44 90 113

Adult education 73 125 214 292

Higher education 367 1 008 1 085 2 215

Planning, research and development 115 54 13 1

Vocational and technical training 78 197 292 497

Hostels 277 123 183 108

Science, technology, and innovation - 9 41 63

HAMU (HIV and Aids Management Unit) - 7 6 9

Pre-primary education - - 81 172

National Institute for Educational Development - - 25 2

Examinations - - 66 1

Building infrastructure - - 17 80

Namibia Students Financial Assistance Fund (NSFAF) - - 618 1

Information and communication technologies - - 18 1

Namibia National Commission for UNESCO - - 6 8

Namibia Qualifications Authority - - 23 -

Percentages of total education expenditure

Administration 2.8 12.2 1.8 0.9

Programme quality assurance 5.1 4.0 2.5 1.0

Primary education 49.4 45.7 52.4 48.9

Secondary education 18.1 15.0 18.8 22.7

Namibia library and information services 0.8 0.6 0.8 0.8

Adult education 1.9 1.8 1.9 2.2

Higher education and NSFAF 9.6 14.8 15.0 16.4

Vocational and technical training 2.0 2.9 2.6 3.7

Hostels 7.2 1.8 1.6 0.8

Pre-primary education - - 0.7 1.3

Other 3.1 1.2 1.9 1.3

Total 100.0 100.0 100.0 100.0

Sources: Office of the Auditor General (2009b; 2012b; 2015; 2016).

The remainder of Section 2.4 discusses some of the trends summarised in Table 4 and Figure 7 and their implications in more detail.


2.4.2 Primary and secondary school education

The information presented in Section 2.4.1 shows that expenditures on primary and secondary school education remain the largest components of the Namibian education budget. Figures 8 and 9 confirm the prominence of these two divisions. It transpires from Figure 8 that their combined share of total education expenditure increased from 67.5% in 2007/08 to 71.6% in 2014/15. The decrease in this share from 2007/08 to 2012/13 should be ignored, because it reflected the temporary placement of transfers to the regional councils in the Administration division. Over the same period, expenditures on primary and secondary education increased from 4.0% of GDP to 6.6%. The ratios in the intervening years were also affected by the placement of transfer payments. These increases reflected significant growth in the inflation-adjusted allocations of resources to the two divisions: even without correcting for this accounting-related distortion, expenditure on primary and secondary education at constant 2012 prices increased from N$4 026 million in 2008/09 to N$8 744 million in 2014/15 (cf. Figure 10).

Figure 8: Total school education expenditure as a percentage of total education expenditure, 2008/09-2014/15

Sources: Office of the Auditor General (2009b; 2010b; 2011b; 2012b; 2013b; 2014c; 2015; 2016).

Figure 9: Total school education expenditure as a percentage of GDP, 2007/08-2014/15


The information above suggests that expenditure on secondary education increased more rapidly than that on primary education. This implies a change in the composition of total expenditure on school education: the expenditure share of secondary education increased from 26.8% in 2007/08 to 31.7% in 2014/15. It should be kept in mind when interpreting these numbers that Namibia has many combined schools. Budget documents do not indicate how the outlays of such schools are divided between primary education and secondary education. Be that as it may, these figures should be interpreted with reference to the enrolments trends outlines in Sections 3.2 and 3.4.


Figure 10: Real government spending on education, 2008/09-2014/15

Sources: Bank of Namibia (2016); Office of the Auditor General (2010b; 2011b; 2012b; 2013b; 2014c; 2015; 2016).

An earlier review of public expenditure in education found that the national average unit costs of providing primary and secondary education in Namibia in 2010 were N$5 893 and N$5 416, respectively (Ecorys, 2011: 139, 140). These amounts represented 19% and 17% of the GDP per capita at the time. According to the same source, the unit cost of providing primary education in Namibia was significantly higher than what the review typified as an international norm of 10% of GDP per capita, while that of providing secondary education was below an international norm of 20% (Ecorys, 2011: 139, 140). These calculations were based on recurrent education spending by the Government. Figure 11 provides updated national average unit costs for primary education, secondary education and school education in toto, while Figure 12 shows the evolution of real unit costs in primary and secondary education from 2008 to 2014. Recurrent and capital expenditures on education were taken into account when calculating these unit costs. The calculations are based on enrolment figures from the education censuses undertaken in September and October every year. These numbers are reproduced in Table 5.

Table 5: School enrolment numbers, 2008-2015

Phases 2008 2009 2010 2011 2012 2013 2014 2015

Primary 408 937 409 944 408 621 410 761 417 310 426 850 420 861 435 472

Secondary 163 631 169 305 174 260 181 407 182 945 187 194 189 260 193 887

Total 572 568 579 249 582 881 592 168 600 255 614 044 610 121 629 359

Sources: Annual education censuses.

Figure 11: School education unit costs, 2014

Sources: Office of the Auditor General (2016); School enrolment data (cf. Table 5).


Figure 12: Real national average unit costs of education in primary and secondary schools, 2008-2014

Sources: Bank of Namibia (2016); Office of the Auditor General (2016); School enrolment data (cf. Table 5).

The unit cost figures are for the calendar years rather than fiscal years. The figure for 2014, for example, was calculated by adding 25% of the education spending in 2013/14 to 75% of the education spending in 2014/15 and dividing the sum by the 2014 school enrolment figure. Unit cost for school education (that is, primary and secondary schools) in 2014 amounted to N$15 169 per learner. The unit cost of providing primary education calculated from these figures remained slightly higher than that of providing secondary education, but elsewhere in this report alternative calculations show unit cost in secondary education to be higher than in primary education, in line with international experience. The unit cost of providing pre-primary education in 2014 was much lower (N$5 334). In real terms, the primary education unit cost increased steadily from 2008 to 2014, while the secondary education unit cost decreased until 2011 before rising sharply in 2013 and 2014.

2.4.3 Pre-primary education

A decision by the Namibian Cabinet mandated the MoEAC to provide free pre-primary, primary and secondary education (Ministry of Finance, 2015c: 151). Hence, the Ministry set specific targets to accelerate access to pre-primary education and to improve pre-school education. Enrolment numbers have grown significantly from 2008 onwards (cf. Table 6), but inadequate funding has prevented achievement of the Ministry’s targets for the provision of free pre-primary education (Ministry of Finance, 2015c: 151). According to Auditor-General reports, spending on pre-primary education was only 0.7% of total education expenditure in 2013-14, and grew to only 1.3% in 2014-15.

Table 6: Enrolment in pre-primary education, 2008-2015

Number of learners enrolled in pre-primary grades per year

2008 2009 2010 2011 2012 2013 2014 2015

3 146 6 116 8 475 13 459 17 572 24 745 28 013 31 932

Sources: Annual education censuses.

Table 7 shows the economic composition of government expenditure on pre-primary education in 2014/15 and 2015/16. As is the case in other components of the education system, personnel expenditure absorbs a large share of the available funding. This limits the scope for realising some set policy objectives, for example, increasing the procurement of textbooks and building more classrooms. Section 7.4.1 and Section 8 return to issues related to pre-primary education in Namibia.


Table 7: Government expenditure on pre-primary education, 2014/15-2015/16

TYPES OF OUTLAYPERCENTAGES OF PRE-PRIMARY SPENDING

2014/15 (Actual) 2015/16 (Estimated)

Current expenditure 83 85

of which: Personnel 38 52

Goods and services 13 8

Subsidies and transfers 31 25

Capital expenditure 17 15

Total expenditure 100 100

Sources: Ministry of Finance (2016a: 151-153); Office of the Auditor General, 2014a.

2.4.4 Education spending by economic classification

Maintaining an appropriate mix of the three main types of outlays (personnel expenditure, purchases of goods and services and capital expenditure) is an important determinant of the efficiency of public education expenditure. As stated earlier, it is well established that educational outcomes in many developing countries are hampered by governments’ tendency to spend excessive portions of education budgets on the compensation of teachers and too little on other inputs such as textbooks and other instructional materials (Pradhan, 1996: 76; Pritchett and Filmer, 1999: 224). An earlier review of Namibia’s education sector found that personnel expenditure is relatively high at primary and secondary school levels, and is crowding out spending on other important items, including teaching materials and supplies, transport, services provided by utilities and maintenance of facilities (Ecorys, 2011: 117, 120, 125). This section shows recent trends in the economic composition of government expenditure on education in Namibia. Key policy implications of these trends are discussed in the sections which focus on post provisioning and non-personnel expenditure. Imbalances in the economic composition of education spending also have important implications for expanding access to schooling to children in remote areas of the country, which requires additional capital spending to provide more schools or more hostels (cf. Section 1.1 and Section 8.2.6).

Figure 13 shows that the Namibian education budget remains dominated by current expenditures. In fact, following a drop from 96.7% of total public education spending in 2007/08 to 92.4% in 2008/09, current expenditures recovered to 94.7% in 2014/15 (Figure 13). The composition of current expenditures changed significantly during this period, though (cf. Figure 14). The most notable development was the drop in the current expenditure share of personnel spending from 73.1% in 2007/08 to 63.8% in 2014/15. Reflecting the influence of the decentralisation policy, the current expenditure share of subsidies and other current transfers increased from 12.0% in 2007/08 to 33.8% in 2014/15. The bulk of the funds recorded earlier as expenditures on goods and services was by the end of the period included in subsidies and other current transfers.

Figure 13: Education expenditure by main economic categories, 2007/08-2014/15

Sources: Office of the Auditor General (2009b; 2010b; 2011b; 2013b; 2014c; 2015; 2016).


Figure 14: Composition of current expenditure on education, 2007/08-2014/15


2.4.5 Over- and underspending in the education sector

Spending in excess and failure to spend allocated amounts tend to be indicative of problems ranging from deficient capacity at the planning or implementation levels to inadequate monitoring of spending units. This section uses information from the Auditor General’s reports on the accounts of the MoEAC from 2007/08 to 2014/15 to quantify the extent of over- and underspending on budgets. The analysis focuses on discrepancies between authorised and actual expenditures within the Ministry. Hence, it relies on a simple measure of over- and underspending obtained by expressing the difference between actual and authorised expenditure as a proportion of authorised expenditure. In all the graphs, positive percentages indicate overspending and negative percentages underspending.

Figure 15 shows the degree of over- and underspending of each of the main economic categories of education expenditure. Total education expenditure exhibited overspending in the first four fiscal years of the period 2007/08-2014/15, albeit at a decreasing rate, and again in 2013/14 and 2014/15. This mainly reflected pressure on current spending. The authorised budget for capital expenditure was underspent throughout except in the 2009/10 fiscal year. The budget for current spending, however, was exceeded in most fiscal years during this period, as the following figures show. Elements of personnel expenditure (remuneration, other conditions of service and employers’ contributions to the government employees’ pension fund) contributed markedly to aggregate overspending of allocations for current expenditure spending. Other sub-categories of current spending – such as utilities and maintenance – also contributed to the problem from time to time.

Figure 15: Percentage over- and underspending by economic item, 2007/08-2014/15



Figure 16: Percentage over/underspending, by current expenditure item, 2007/08-2014/15


Figure 17: Percentage over/underspending, by current expenditure item, 2007/08-2014/15

Sources: Office of the Auditor General (2009b; 2010b; 2011b; 2013b; 2014c; 2015; 2016.

2.4.6 Analysis of regional data

This section calculates personnel and non-personnel expenditure costs for school education (i.e. primary and secondary education) on a regional basis. The calculations are based on expenditure data obtained from the MoEAC for 2013/14. For the purpose of the calculations, personnel expenditure is defined as the sum of remuneration, employer contribution to the government employees’ pension fund, and other conditions of service. Non-personnel expenditure consists of transfers to regions to finance purchases of consumable goods and services. (These transfers are shown in the accounts as sub-division 043 expenditures.)

Table 8 shows the calculated amounts, while Table 9 expresses personnel expenditures as multiples of non-personnel expenditures. It is evident that personnel spending markedly exceeds non-personnel spending in all regions and in both levels of school education. The multiples are bigger in secondary education, though, and vary considerably from region to region.

Sections 2.5 and 2.6 return to aspects of the balance between personnel and non-personnel expenditure in the Namibian education sector.


Table 8: Personnel and non-personnel expenditure in primary and secondary education by region, 2013/14 (N$ millions)

REGIONSPERSONNEL EXPENDITURE NON-PERSONNEL EXPENDITURE

Primary Secondary Total Primary Secondary Total

//Kharas 114 80 194 42 33 75

Erongo 204 109 313 37 26 63

Hardap 145 83 228 44 34 78

Kavango 660 103 763 76 46 122

Khomas 374 230 604 74 52 126

Kunene 151 69 220 41 32 73

Ohangwena 820 103 923 82 49 131

Omaheke 147 42 188 36 31 67

Omusati 806 169 975 78 47 125

Oshana 389 171 560 51 34 85

Oshikoto 538 116 654 51 30 81

Otjozondjupa 249 77 326 52 38 90

Zambezi 163 239 403 30 19 48

Total 4 761 1 591 6 352 696 469 1 165

Note: Figures may not add up due to rounding. Source: Expenditure data obtained from the MoEAC.

Table 9: Personnel expenditure as multiples of non-personnel expenditure in primary and secondary education by region, 2013/14

REGIONSMULTIPLES

Primary Secondary Total

//Kharas 3 2 3

Erongo 5 4 5

Hardap 3 2 3

Kavango 9 2 6

Khomas 5 4 5

Kunene 4 2 3

Ohangwena 10 2 7

Omaheke 4 1 3

Omusati 10 4 8

Oshana 8 5 7

Oshikoto 10 4 8

Otjozondjupa 5 2 4

Zambezi 6 13 8

Total 7 3 5

Source: Expenditure data obtained from the MoEAC.


2.5 FISCAL POLICY AND EDUCATION FINANCING IN FUTURE

Sustained fiscal profligacy invariably culminates in public debt crises. Such crises and the required remedial measures tend to disrupt flows of funds to finance the various activities of governments. Prudent management of the public finances is therefore a prerequisite for adequate and stable financing of government expenditure programmes, including those linked to the provision of education. Formal analyses of the prudence of fiscal policy assess the solvency of the government sector and the sustainability of the public debt (cf. Calitz, Du Plessis and Siebrits, 2014: 58-59). A govern-ment is solvent if it can meet its long-term spending commitments, i.e. if the present value of the flow of all future revenues exceeds the value of outstanding debt plus the discounted value of future outlays. Fiscal policy is sustainable if the public finances are regarded as solvent without the need for changes to the present policy stance.

On balance, the Namibian fiscal authorities have managed the public finances in a prudent manner. The country recorded good fiscal outcomes during the first two decades of independence, as reflected in a moderate (albeit increasing) public debt burden (cf. Figure 18). From 1992/93 to 2008/09, the lowest and highest values of the public debt to GDP ratio were 15.5% and 33.6%. Formal analyses undertaken in this period (e.g. Zaaruka, Ndove and Tjipe, 2004) concluded that the public debt was sustainable. The low public debt burden meant that the fiscal authorities had ample room to use expansionary measures to boost aggregate demand during economic downturns.

Figure 18: The central government debt to GDP ratio in Namibia, 1992/93-2015/16

Sources: Bank of Namibia (various issues); Zaaruka, Ndove and Tjipe (2004: 4).

In 2008/09, Namibia had a budget surplus equivalent to 2.0% of GDP, and the public debt amounted to only 18.2% of GDP (cf. Table 10). In that year, the so-called Great Recession erupted in the wake of the international financial crisis of 2007 and 2008. The Namibian authorities responded to this threat to the level of economic activity by accommodating the downward pressure on tax revenues and by expanding government spending. This expansionary response prevented a recession, but contributed to the emergence of budget deficits and, following a one-year lag, a significant increase in the public debt burden. By 2011/12, Namibia had a budget deficit of 7% of GDP and a public debt ratio of 26% of GDP.

In 2012/13 the Namibian authorities initiated fiscal consolidation to improve the fiscal situation. A combination of expenditure restraint, buoyant revenues from the Southern African Customs


Union (SACU) pool and a marked increase in individual income tax receipts nearly eliminated the deficit and arrested the upward trend in the public debt to GDP ratio. This strengthening of the public finances did not last, though. In the wake of weaker-than-expected economic growth in the Southern African region and further afield, fiscal policy returned to a more expansionary stance in 2013/14. Public spending growth subsequently outpaced the growth in tax revenue during the 2014/15 and 2015/16 fiscal years. As a result, the budget deficit mushroomed to 8.3% of GDP in 2015/16. In the same year, the Namibian Government floated large bond issues on the Johannesburg Stock Exchange and in the Eurobond market, mainly to mitigate the SACU revenue shock and to strengthen the country’s international reserves.3 The outcome of these issues and substantial domestic borrowing was a sharp increase in central government debt from 23.9% of GDP at the end of the first quarter of 2015 to 40.0% of GDP one year later. In the process, external public debt increased to more than 40% of total central government debt for the first time in the country’s history.

In his 2016 Budget Speech, the Namibian Minister of Finance announced a renewed focus on fiscal consolidation. The aim of the consolidation plan, which contained revenue enhancement as well as expenditure containment measures, was to reduce the budget deficit from 5.2% of GDP in 2015/16 to 1.8% at the end of the MTEF period (2018/19). The limited success of the original plan gave rise to the announcement of a significant intensification of the consolidation effort at the time of the mid-term review of the 2016/17 budget. In response to the large revenue shortfalls in recent years, the Minister announced downward adjustments to the medium-term revenue projections and to the expenditure allocations of all offices, agencies and ministries (cf. Table 11.).

It is clear that cyclical factors (e.g. weak growth in some of Namibia’s main trading partners) contributed to the country’s current fiscal malaise. Hence, the fiscal situation should improve when the growth rate of the world economy accelerates. Furthermore, Namibia’s experience from 2009 onwards has confirmed the wisdom of erring on the side of caution in the normal course of things in order to have sufficient fiscal space for countercyclical policy responses to economic shocks. The current focus on fiscal consolidation therefore seems appropriate. Yet these events have also confirmed the sensitivity of the Namibian economy to economic shocks in other countries. Because Namibia is a typical small, open economy, negative effects of such shocks on its levels of economic activity and, hence, tax revenues should be expected from time to time. Policy responses to these effects in the form of fiscal consolidation programmes are likely to strain education budgets, among others.

Recent trends also raise questions about the sustainability of Namibia’s current level of government expenditure. Public spending has grown markedly in Namibia over time: from 2008/09 to 2015/16, for example, it more than tripled in nominal terms and increased from 29.9% of the GDP to 43.3% (cf. Table 10). To be sure, there are reasons why one might expect government spending to be relatively high in Namibia. The country’s large land area and sparse population, for example, raise administration costs in per capita terms and the cost of providing economic and social infrastructure. Second, it is one of a number of Southern African countries afflicted by legacies of race-based discriminatory policies that long denied most citizens access to public services and economic opportunities. These legacies manifest in exceptionally high levels of income inequality, poverty rates well above those associated with the countries’ levels of income per capita, and relatively poor health and education outcomes (National Planning Commission, 2012b: ix-x). Adequate levels of social spending by the Government to provide education and healthcare services as well as social security programmes are necessary to deal with these legacies.

3 This step was in line with a recommendation in an International Monetary Fund (IMF) staff report prepared for the 2015 IV Consultation with the Namibian authorities (IMF, 2015: 11).


Table 10: Fiscal outcomes in Namibia, 2008/09-2015/162008/09 2009/10 2010/11 2011/12 2012/13 2013/14 2014/15 2015/16

Amounts (N$ millions)Revenue and grants 23 447 24 017 23 375 29 922 37 997 41 910 49 931 52 215Expenditure 21 946 27 914 27 253 36 611 38 112 46 734 58 705 64 638Budget balance 1 501 -897 -3 879 -6 689 -115 -4 824 -8 774 -12 423Total debt 13 389 11 923 13 893 24 734 27 489 30 852 35 950 59 789Percentages of GDPRevenue and grants 31.9 31.7 27.9 31.4 33.7 32.8 35.3 35.0Expenditure 29.9 32.9 32.5 38.4 33.8 36.6 41.6 43.3Budget balance 2.0 -1.2 -4.6 -7.0 -0.1 -3.8 -6.2 -8.3Total debt 18.2 15.7 16.6 26.0 24.4 24.2 25.4 40.1

Sources: Ministry of Finance (2015b: 43); Ministry of Finance (2016b: 17); Ministry of Finance (2016d: 29).

Table 11: Actual and projected fiscal outcomes in Namibia, 2015/16-2019/202015/16 2016/17 2017/18 2018/19 2019/20Actual Original Revised Original Revised Original Revised Projected

Amounts (N$ millions)Revenue and grants 52 215 57 845 51 511 68 156 54 595 69 816 58 445 65 465Expenditure 64 638 65 996 61 496 69 858 59 854 74 418 62 292 64 425Budget balance -12 423 -8 151 -9 985 -1 702 -5 260 -4 602 -3 847 1 040

Source: Ministry of Finance (2016d: 26, 27).

Yet, at least two considerations suggest that government spending may be at, if not beyond, the optimal level. The first follows from comparisons: Namibia’s central government expenditure-to-GDP ratio already exceeds those of most other countries (including most of its middle-income country peers). This is evident from Figure 19, which plots the average values of central government spending-to-GDP ratios in 114 countries for the period 2010-2012 against estimates of these countries’ GDPs per capita in 2014. Namibia’s ratio of 30.5% was exceeded by only 36 of the other 113 countries.4 The majority of these 36 countries are high-income countries with markedly larger tax bases than that of Namibia.

The second consideration follows from the rapid increases in budget deficits from 2009/10 onwards and again from 2013/14 onwards: it seems that the capacity of the tax system to generate sufficient revenue to finance current levels of government spending is already under strain. These deficits arose despite the fact that government revenue and grants more than doubled in nominal terms from 2008/09 to 2015/16; this represented an increase of more than 3 percentage points of GDP (cf. Table 10). Furthermore, the tax system is well developed already and exploits the most important tax bases available to middle-income countries. From 2010/11 to 2014/15, the tax system supplied the bulk of government income: the contributions to total revenue of non-tax revenue varied between 6.3% and 8.7% (it mainly consisted of entrepreneurial and property income) and that of grants between 0.0% and 0.7% (cf. Table 12). Four types of taxes yield the bulk of total tax revenues: the SACU revenue pool share (35.8% of total government revenue in 2014/15), income tax on individuals and value-added and sales taxes (20.4% each) and company taxes (14.1%). The Government introduced an environmental tax on cars, lamps and tyres in July 2016. According to the Fiscal Policy Strategy for the 2016/17 to 2018/19 MTEF (Ministry of Finance, 2016b: 29), consideration is also being given to the introduction of presumptive taxation on the informal sector and a progressive solidarity tax. None of these taxes, however, is likely to generate large amounts of revenue.

4 The central government expenditure-to-GDP ratios in the World Bank’s World Development Indicators are not calculated in exactly the same manner as the ratios reported in publications of the Ministry of Finance. This explains why the average of 30.5% is smaller than the corresponding annual figures reported in Table 10.


Figure 19: Average central government expenditure-to-GDP ratios in 113 countries, 2010-2012

Note: Namibia’s ratio is indicated by the black dot.Source: Compiled from information in World Bank World Development Indicators (2017).

Table 12: The composition of government revenue and grants in Namibia, 2010/11-2014/15

ComponentsPercentages of total government revenue and grants

2010/11 2011/12 2012/13 2013/14 2014/15Taxes on income and profits 42.6 38.7 38.3 33.5 35.6Taxes on property 0.6 0.8 0.8 0.6 0.6Domestic taxes on goods/services 22.7 26.7 16.9 23.0 20.5Taxes on international trade 25.7 23.8 36.3 35.1 36.3Other taxes 0.9 0.7 0.7 0.6 0.5Non-tax revenue 7.3 8.7 7.0 6.5 6.3Grants 0.2 0.6 0.0 0.7 0.2Total 100.0 100.0 100.0 100.0 100.0

Sources: Ministry of Finance (2012; 2013; 2014; 2015d; 2016c).

Of late, the Government has been implementing tax administration reforms to generate additional tax revenue. It envisages more reforms, including the establishment of a semi-autonomous revenue agency (Ministry of Finance, 2016b: 30). While experience, including that of South Africa, indicates that this step can enhance the operational efficiency of tax administration and in this way improve the exploitation of existing tax bases, it is hard to predict the scale of this effect in the Namibian context.

Viewed from a longer-term perspective, structural features of the Namibian economy hamper the Government’s ability to mobilise sufficient tax revenue to meet the demand for publicly provided goods and services. The small size of the private sector and high unemployment rate (which is linked to skills shortages and is an important reason for the high levels of poverty and income inequality) constrain the income and consumption tax bases. Furthermore, Namibia is a typical small open economy: economic shocks in major trading partners (such as Angola, Botswana and South Africa) markedly affect economic activity in the country and, hence, the Government’s tax revenues. This partly reflects the reality that Namibia continues to derive a large portion of its export earnings from primary commodities, which tend to be subject to considerable price instability. Moreover, Namibia’s membership of SACU is a mixed blessing from a fiscal point of view: the revenue-sharing arrangement adds significantly to the Government’s coffers, but also reinforces the influence on Namibia’s tax revenues of the performance of the South African economy.

At least two implications for the financing of the education sector follow from this synopsis of the fiscal situation in Namibia. First, periodic pressure on allocations for education spending are to be expected given the country’s relatively high level of government expenditure and limited revenue base. Second, the extent of public spending and the pressure on the tax system suggest that little, if any, scope remains for mobilising more money for the financing of the education sector via further increases in the government spending-to-GDP ratio. Further expansion or improvement of the education sector is likely to depend on more efficient utilisation of existing resources, and on economic growth, which expands the pool of resources available to the sector.

Chapter 3: Broad Educational Issues in Namibia 2929

3 BROAD EDUCATIONAL ISSUES IN NAMIBIA


3.1 INTRODUCTION

To understand some of the fiscal choices that Namibia faces regarding school education spending, a brief discussion of broad educational issues in Namibia is necessary. The ReSEP team has undertaken considerable work on Namibian education, thus more details are available in other reports. Here, the description of the Namibian education system and the issues it faces is purely to serve as a background to understanding the issue at hand, being public expenditure in education.

3.2 ENROLMENT

Levels of education have improved considerably over time in Namibia. From 1992 to 2015, enrolment in Namibian schools (pre-primary excluded) increased from 432 230 to 638 436, as Table 13 shows. This implies an expansion of 48%, or an average expansion of 1.7% per year in total. Considering that the population of school-going age was also growing fairly strongly in this period, the expansion was perhaps not as strong as could have been expected. This was partly because enrolment rates were not so low to start with. What happened over the period is that there was a much greater expansion in senior secondary schools (236%) and in junior secondary schools (115%), while the numbers in primary education grew by only 27%. The slower primary growth could be ascribed to the fact that fewer children remained stuck in the early grades due to reduced repetition rates, while at the same time a larger proportion of the population did attend school. The growth rates per year allow an analysis of time trends. Note that the very high growth rates in senior secondary education (8.0% per year from 1992 to 2000 and 5.8% from 2000 to 2010) have slowed considerably to only 0.8% per year in the last five years for which data are available. This is an indication that flows of learners to the higher grades are no longer improving, which is symptomatic of poor quality earlier in the education system, as reflected by high repetition, high dropout rates at junior secondary level, and high failure rates in the Grade 10 examination.

Table 13: Enrolment in Namibian schools, 1992-2015

Grades 1992 2000 2010 2015

Growth rate per year Total growth 1992 to

2015

1992 to

2000

2000to

2010

2010 to

2015

1992 to

2015Grade 1 86 226 64 805 65 386 78 120 -3.5% 0.1% 3.6% -0.4% -9%Grade 2 61 799 57 761 58 175 67 941 -0.8% 0.1% 3.2% 0.4% 10%Grade 3 49 444 54 825 58 160 64 157 1.3% 0.6% 2.0% 1.1% 30%Grade 4 44 309 54 995 57 508 61 384 2.7% 0.4% 1.3% 1.4% 39%Grade 5 39 380 60 531 62 975 64 524 5.5% 0.4% 0.5% 2.2% 64%Grade 6 34 335 50 557 54 677 55 528 5.0% 0.8% 0.3% 2.1% 62%Grade 7 32 918 45 023 49 654 51 075 4.0% 1.0% 0.6% 1.9% 55%Primary 348 411 388 497 406 535 442 729 1.4% 0.5% 1.7% 1.0% 27%Grade 8 25 454 44 326 55 917 64 581 7.2% 2.4% 2.9% 4.1% 154%Grade 9 23 567 33 403 43 381 50 334 4.5% 2.6% 3.0% 3.4% 114%Grade 10 22 113 22 538 33 959 38 210 0.2% 4.2% 2.4% 2.4% 73%Junior Secondary 71 134 100 267 133 257 153 125 4.4% 2.9% 2.8% 3.4% 115%Grade 11 7 279 12 170 21 054 22 384 6.6% 5.6% 1.2% 5.0% 208%Grade 12 5 406 11 360 19 949 20 198 9.7% 5.8% 0.2% 5.9% 274%Senior Secondary 12 685 23 530 41 003 42 582 8.0% 5.7% 0.8% 5.4% 236%Total 432 230 512 294 580 795 638 436 2.1% 1.3% 1.9% 1.7% 48%

Note: To maintain comparability over time, pre-primary enrolment is excluded as it was introduced only much later.Source: Own calculations from Annual Education Censuses 1992-2015.


Between 2010 and 2015 the number of schools increased by 85, from 1 697 to 1 782. The most rapid growth was in Kunene Region, where the number of schools increased from 55 to 68 or by almost one-quarter. This had the consequences that school enrolment in Kunene grew by even more, i.e. 38%, illustrating that there is an unsatiated demand for education which can often only be met through the education system attempting to reach into more isolated locations.

3.3 GEOGRAPHY AND EDUCATION

The sparse population in Namibia makes it difficult to provide education within walking or easy travelling distance to all learners. Providing education to even the most remote locations requires a large number of schools, but with relatively high dropout rates in such isolated areas and the need for more highly qualified teachers to offer education in higher grades, it is difficult to sustain such closeness of schools to the population served in the higher grades. Previous research by ReSEP for the MoEAC found that 11% of Grade 1 learners would have to move to schools that are at least 2 km away from their current schools when they later wish to attend Grade 7. (Gustafsson, 2015b).

The map on the right shows all schools (dots) in Namibia. Note that the former Kavango Region has been divided into Kavango East and Kavango West, and the former Caprivi Region is now named Zambezi. Namibia’s 14 regions are subdivided into education inspection circuits, also shown on the map.

These geographic patterns of education provision and edu-cation demand explain the mix of schools seen in Namibia, with many primary schools not offering all primary grades, and some extending beyond the primary grades to become so-called combined schools (see for instance Figure 20 on the mix of school types by region). This makes it quite difficult to separate fiscal costs of primary and secondary education, a factor that had to be considered in the preceding fiscal analysis. Small school sizes (see Figure 21) also make it more difficult to provide the full offering of subjects.

The effect of geographic factors on school composition is well illustrated by Table 14. It shows the lowest grade (on the left) to the highest grade offered, and how many schools offer particular combinations of lowest to highest grade. Thus the first line of data shows the number of schools offering education from pre-primary level, and the columns show the maximum grade offered in those schools. The table then presents the number of schools offering that combination. Thus there is one school offering only pre-primary (this being both the lowest and highest grade), two schools offering only pre-primary and Grade 1, four offering pre-primary to Grade 2, and so on. If the highest grade that a school offers is relatively low, this implies that parents and learners have to take further steps if they wish to continue their studies to higher grades. Thus some children have to change schools even after pre-primary, others after Grade 1, and so forth. The number of schools extending only to Grade 4 is quite large (see the column headed “Grade 4”): altogether 250 schools have Grade 4 as the highest level they offer, thus many children have to move to other schools in Grade 5. Altogether 324 schools offer education only up to Grade 4 or lower, and 369 schools (more than one in five) do not cover the full primary phases up to Grade 7. Thus, whereas 1 408 schools offer education up to Grade 4, only 1 127 (20% fewer) offer Grade 7 or higher (the sum of all the schools shown in the last six columns).


Figure 20: Schools by region and type, 2016

Note: “To be updated” implies that the classification is unknown or not provided.

Source: Namibia Fifteenth School Day (FSD) Survey 2016.

Table 14: Number of schools showing the lowest grade and the highest grade offered, 2015

LOWEST GRADE

OFFERED

HIGHEST GRADE OFFERED

Pre-p

rimary

Grad

e 1

Grad

e 2

Grad

e 3

Grad

e 4

Grad

e 5

Grad

e 6

Grad

e 7

Grad

e 8

Grad

e 9

Grad

e 10

Grad

e 11

Grad

e 12

Pre-primary 1 2 4 6 79 12 11 445 13 22 389 30

Grade 1 1 34 26 171 10 12 142 5 9 46 12

Grade 5 4 1 1 8

Grade 6 2

Grade 7 1 1

Grade 8 58 1 140

Grade 11 3

Total 1 3 38 32 250 22 23 591 19 32 504 1 186

This issue is of great pertinence to educational equity, therefore it is an issue that the MoEAC should consider often and thoroughly, with consideration of both fiscal and equity issues. It is important to avoid as far as possible that so many relatively young children have to walk long distances to school, travel to school or be accommodated in hostels. This has consequences for their security (physical and emotional) and large costs for poor parents. That it is children in the most remote areas who are also most excluded from both education and the mainstream of the economy, makes this an important equity issue. This will again be broached in the recommendations.

Figure 21: Schools sizes in Namibia, 2015

Source: FSD Survey 2016.


Due to the remoteness of many schools in Namibia, the Government introduced special allowances for qualified teachers teaching in remote locations. Four remoteness categories are distinguished, Category 1 being the most remote and Category 4 the least remote. As Figure 22 shows, more remote schools are particularly common in largely rural regions such as Kunene and Oshikoto, while virtually all schools in Khomas and a little fewer in Erongo fall in Category 4. An earlier assessment of the success of this scheme was undertaken by the same team responsible for this report (i.e. ReSEP) for the Ministry and UNICEF.

Figure 22: Enrolment by remoteness category and region, 2015

Sources: Annual Education Censuses.

Remoteness does have a clear implication for the likelihood that children will progress to high levels of education, as will be illustrated a little later where the four categories are compared.

3.4 ENROLMENT ACROSS GRADES, REPETITION AND LEARNER FLOWS

Figure 23 shows enrolment per grade for the different years since 2011. As referred to before, there is now little growth in the numbers in higher grades, although numbers in the lower grades still seem to be increasing moderately, as the data in Table 15 also showed. This last phenomenon (rising numbers in the early grades) could be the result of higher repetition in these grades than in the past (for instance, retaining more than one cohort of children in Grade 1), but more likely it is indicative of the further successes to ensure that all children attend at least a few years of school. The lack of growth in numbers at the higher grades is disappointing, however, as this indicates that there is no further improvement in flows of learners through the system. The most likely reason for that is weak quality of teaching that leads to high rates of repetition, along with relatively high dropout that is in turn also influenced by repetition.

Figure 23: Enrolment by grade and year, 2011-2015

Source: Own calculations from Annual Education Censuses 2011-2015.


Table 15 shows enrolment in every grade for every year since 1992. The value of this table is that not only the cross-sectional data from one year to the next can be compared, as in the previous figure, but also that it is possible to track “pseudo cohorts” through the school system. This can be illustrated by reading diagonally, as shown by the highlighted numbers: the 86 226 Grade 1s in 1992 would have been in Grade 12 in 2001 if they had passed every year and did not drop out. As can be seen, there were 12 638 Grade 12s in 2003, and many of them would not have been in Grade 1 in 1992, but earlier, as they may have repeated one or more years before reaching Grade 12. Thus comparing these two numbers is not a full reflection of what happens with a cohort of children, but expressing the Grade 12s as a percentage of the Grade 1s 11 years earlier gives a good indication of the flows through the system. The fact that the Grade 12s were only 15% of the Grades 1s on the top highlighted diagonal shown in the table, and that this ratio had increased to 32% for the lower highlighted diagonal, is a sure sign that flows through the system to the higher grades are generally improving. This is less so for the most recent years, as can be seen from the fact that the largest number of Grade 12s was in 2010.

Figure 24 compares the patterns of a cross-section and the most recent pseudo cohort. Note that the cross-section will be more responsive to short-term changes in flows within the system.

Table 15: Enrolment by grade and year, 1992-2015

YearsGrade

1Grade

2Grade

3Grade

4Grade

5Grade

6Grade

7Grade

8Grade

9Grade

10Grade

11Grade

12

1992 86226 61799 49444 44309 39380 34335 32918 25454 23567 22113 7279 5406

1993 80442 63933 53690 47481 39954 33725 32875 28345 21820 22717 12415 6805

1994 78748 65118 57570 53385 43363 34309 34173 29926 23803 24113 11551 12379

1995 65258 65250 59889 59248 46966 37541 33097 29760 25098 25432 11988 10871

1996 57377 64498 60821 61542 52503 39909 35606 29923 25542 24888 12803 11324

1997 59651 54497 63752 62992 54186 47296 37517 32662 25785 24646 13610 12046

1998 61373 55217 55584 64649 56464 48299 44352 34369 28148 22689 11600 12880

1999 63103 55721 54570 57185 59415 48662 43635 41405 29101 22457 11880 10928

2000 64805 57761 54825 54995 60531 50557 45023 44326 33403 22538 12170 11360

2001 66736 59098 56799 54641 60527 51448 47003 44216 36133 25294 13274 11660

2002 68165 60734 57754 57102 59827 52500 48698 45681 37409 27908 13355 12746

2003 68400 60829 58602 57836 61462 51195 50273 47987 37286 29168 14673 12638

2004 63265 60406 57867 57869 61557 52694 49754 48949 38138 28907 14301 13994

2005 66210 57253 58217 57910 61589 51972 51047 49692 39741 30172 14777 13722

2006 65993 58059 55469 58251 62412 51482 50638 48824 40486 31260 17226 14334

2007 68851 58944 57158 56708 64447 51887 51325 50469 41441 32169 16849 16665

2008 66819 60256 57130 56536 63240 53877 49588 52304 41514 36660 17376 16025

2009 65161 59362 58262 56804 62783 53326 51226 53020 42126 36220 20690 17249

2010 65386 58175 58160 57508 62975 54677 49654 55917 43381 33959 21054 19949

2011 67071 58397 56230 58364 62755 55533 50454 60596 44241 36194 20057 20319

2012 71074 60086 56693 57207 63987 55422 50985 62545 46389 34255 20674 19082

2013 74949 62999 58288 57170 63249 55075 50792 63141 48454 34644 20568 19264

2014 75340 65765 60314 58735 63290 55349 51022 63683 49656 36187 21259 19068

2015 78120 67941 64157 61384 64524 55528 51075 64581 50334 38210 22384 20198



Figure 24: Cross-section vs pseudo-cohort analysis

Source: Own calculations from Annual Education Censuses.

Note how the cross-section and the pseudo cohort have the same pattern: enrolment in Namibia is very stable over time.

Like many other countries in Southern Africa, the gender pattern of school education generally has not been biased against girls. Boys in schools in the lower grades outnumber girls, as can be seen in Figure 25, but this simply reflects the fact that boys are generally more likely to repeat (see Figure 26) and often remain longer in the lower grades before dropping out, while girls repeat less often and are less inclined to drop out in the higher grades.

Figure 25: Enrolment by grade and gender, 2015


Figure 26: Repetition by grade and gender, 2015



The effect of repetition and dropout across regions and remoteness categories would have been best measured if all individuals of the same cohort of learners could have been tracked through their school-age years within and between grades and schools, and also when they exit the school system. Such data are not available. However, it is possible to use simple cross-section patterns for a few successive years in order to compare remoteness categories. This is shown in Figure 27. From this figure it is apparent that the numbers of Grade 12 children in remoteness Categories 1 and 2 are far less than 1 000, while in recent years more than 12 000 children were in Grade 1 in these categories. In contrast, the Grade 12s constitute a far higher proportion of the Grade 1s in Category 4. Although these are cross-sectional data for a few successive years, the quite stable patterns in each category indicate that this is really the underlying pattern. It may appear slightly worse than it actually is because some learners from remote areas may attend schools in less remote areas in higher grades, thus exaggerating the difference between these location types. But there can be no doubt that there is a considerable problem of dropping out in the more remote schools, something that will be addressed again when looking at fiscal incidence patterns.

Figure 27: Enrolment patterns by grade and year by remoteness category

Category 1: Over 100 km from a centre Category 2: 50-99 km from a centre

Category 3: 11-49 km from a centre Category 4: Not remote – in an urban centre



Aggregate flow rates (dropout, repetition and promotion) between 2014 and 2015 can be used to estimate the proportion of learners who will graduate without repeating any grade. Out of every 1 000 who start school, 78 should do so, 126 are estimated to repeat one grade, and 113 two grades. Based on these flow rates, only 459 learners out of the starting 1 000 pupils, or 45.9%, will eventually pass Grade 12. It is also possible to calculate the coefficient of efficiency as a measure of internal efficiency. The learner-years required per promotee for Grade 12 is 25.9, i.e. 2.1 times the ideal 12 years that it should take. The input-output ratio for Grade 12 is thus 25.9/12 = 2.1. This means that Namibia’s education system is characterised by an input-output ratio of 2.1, compared to the ideal where this ratio would be unity, i.e. if there were no repeaters or dropouts. Thus Grade 12 promotees are being educated at a cost that is 110% higher than the ideal, in terms of resources required over the school cycle to achieve every Grade 12 pass.

As can be seen from Figure 28, most schools in Namibia have quite low learner-teacher ratios. The reason for this is not only that the post-provisioning system is very favourable. (The post-provisioning rules imply that schools can obtain an additional teacher for every 35 primary learners or 30 secondary learners, but in practice provisioning is even more favourable.) Another factor is simply that the many small schools often require more teachers to make them viable, thus reducing the average even more, particularly in some of the more rural regions.

Figure 28: Learner-teacher ratio in Namibia, 2015 (number of schools shown)

Source: Annual Education Censuses 2015.


3.5 LANGUAGE

A factor that makes education in Namibia even more difficult to offer on an equitable basis to the whole population is the large number of languages, quite a few of them spoken by relatively few speakers. This situation becomes even worse when many children of such groups attend school for only a few years, if at all, and as many language communities are geographically dispersed. This makes the provision of home language instruction in the early grades, and offering the home language for learners from those language communities, difficult and costly.

Table 16 shows the home languages and grades of learners in 2015. As can be seen, the numbers of learners from some language groups in particular grades are very small. If it is further considered that many of them are also spread across many schools, the numbers of children who need to be served in a particular home language in the early grades (where home language instruction is the policy) and at higher grades (where the policy is that schools should be able to offer the learners’ own language as Home Language subject) can be quite small. Moreover, it is extremely difficult to find and allocate the teachers to serve these populations.

Table 16: Enrolment by home language and grade in 2015Language Gr R Gr 1 Gr 2 Gr 3 Gr 4 Gr 5 Gr 6 Gr 7 Gr 8 Gr 9 Gr 10 Gr 11 Gr 12

Afrikaans 2548 3834 3531 3267 3137 3403 3335 3042 3739 3229 3061 1833 1694English 528 551 469 393 460 516 510 504 418 478 494 321 254German 67 197 165 250 326 237 174 215 187 165 133 132 133Khoekhoegowab 3818 9028 8379 8412 7395 8319 6934 6078 6788 4572 3686 1272 1217Oshikwanyama 5906 17247 15467 14708 15139 15648 13297 12633 16966 13120 9264 5716 5128Oshindonga 4474 8583 7301 6988 6780 6822 6284 5944 8294 6591 4752 3544 3407Other Caprivi 1597 2780 2514 2303 2172 2416 2246 2018 2507 2576 2202 1394 1024Other European 100 73 106 101 75 102 124 122 277 254 212 225 108Other Languages 1456 4587 3789 3680 3459 3475 2865 2854 3366 2623 1731 749 677Other Oshiwambo 4169 10239 8948 8159 8085 9599 8092 7488 9961 7659 5913 3825 3559Otjiherero 2989 6806 5813 5481 5156 5370 4274 4086 4779 3694 2962 1346 1304Rigciriku 595 2179 1768 1446 1276 1280 1243 847 975 841 534 205 195Rukwangali 2182 6480 5260 4757 4198 4116 3422 2891 3472 2338 1674 936 712Rumanyo 18 14 13 40 4 40 6 84 34 41 200Rushambyu 180 399 310 299 328 245 197 233 214 179 131 55 35San (Ju/’hoansi) 643 2211 1705 1478 1138 949 641 505 514 258 128 32 21Setswana 68 166 133 171 132 130 140 121 185 191 151 76 59Sign Language 63 96 111 64 158 98 109 69 68 29 45 11 43Silozi 839 958 815 888 846 718 618 565 889 626 598 341 245Thimbukushu 475 1671 1314 1242 1081 1081 885 794 976 827 505 330 183

Source: Annual Education Census 2015 (preliminary data).

3.6 BROAD EDUCATION ISSUES: IN SUMMARY

The issues mentioned in the discussion above illustrate some of the many educational challenges that the MoEAC has to confront. These challenges are not all of a fiscal nature, but the choices made have important fiscal implications. A case in point is the trade-off between providing more schools serving children to higher grades in remote areas, and having them either travel or attend hostels. Both options are costly, both have vast implications as to where fiscal resources need to be applied, and both have difficult educational and human rights angles attached. This issue will be returned to later in this report.

4 EDUCATION DATA IN NAMIBIA

Chapter 4: Education Data in Namibia 39

4 EDUCATION DATA IN NAMIBIA

39


4.1 INTRODUCTION

In education, two important types of data are crucial for understanding expenditure: enrolment numbers influence factors such as post provisioning and allocations to schools, while teacher numbers, to some extent derived from enrolment numbers, determine by far the largest item of the budget, being teacher salaries. This make the data that generate these financial flows so important, and their quality and monitoring such an essential part of a good financial management system in education.

Information is a necessary resource, produced by information systems, and is a key building block for management and decision-making in the MoEAC. The MoEAC guidelines to establish the Education Management Information System (EMIS) in regional offices is a recognition that proper management, planning and evaluation are contingent on data of high quality that are complete, relevant, accurate, timely and accessible. An EMIS should not be thought of as a technological solution alone: it is the information system that provides the information to manage the entire education system, along with important other information such as that drawn from the payroll or the examinations systems. It is essential that all these data be attuned to linking information across the whole education system in order to make informed management decisions.

4.2 DATA COLLECTION PROCESSES

The MoEAC collects data from schools pertaining to the school system twice per year. At the primary and secondary levels, both public and private, a short questionnaire commonly referred to as the Fifteenth School Day (FSD) Survey uses February enrolment data for budgeting and planning purposes. The Annual Education Census (AEC) arises from the second annual collection of data from schools. It occurs in September and uses a more comprehensive questionnaire that addresses the entire school system, both public and private.

The EMIS Unit is responsible for the design of the questionnaires, collection, processing, analysis and dissemination of data for all primary, combined and secondary schools, as well as schools for learners with special educational needs. Figure 20 (page 32) shows the distribution of schools in all regions of Namibia according to school type.

4.2.1 The Fifteenth School Day data collection process

The Fifteenth School Day Survey captures data about schools as recorded on the fifteenth school day of every year. Four copies of the questionnaire per school are sent to the MoEAC Regional Education Offices for dissemination to all schools: one copy stays at the school, one is kept at the inspection circuit, one at the regional office, and the fourth is sent via the regional office to the MoEAC headquarters in Windhoek. All schools have one day to complete the questionnaire. All these copies should be verified for accuracy and completeness by the circuit inspector.

Once the questionnaire has reached the regional office, the information of the region is summarised digitally and checked for outliers on a template provided by the EMIS Unit. The purpose of this step is to make data available quickly, but also to quickly discover data errors and to correct those.

At this point some concerns must be noted: Firstly, the FSD questionnaire is too comprehensive, therefore it takes an unnecessarily long time

for the data to be released. Sometimes this does not even occur within the same calendar year. Secondly, the data collected through the FSD process are not captured electronically at all.


A comprehensive assessment of the EMIS internal data collection processes has been carried out and a set of action-able recommendations was put forward. These recommendations are yet to be implemented.

It is important to note that the units res-ponsible for hostels and school feeding have their own data collection processes. However, this seems to be an ad hoc initiative with no official data collection processes in place. There is a clear need to unify such data collection processes and to link the data obtained from the different processes using school identi fi-cation numbers.

The data collected through these processes are used primarily to support the budget planning process and provide enrolment and teacher counts. The FSD data specifically are an important source for the allocation of funds per learner based on the Universal Primary Education (UPE) and Universal Secondary Education (USE) policy, the allocation of teachers (post provisioning) to schools and the annual publication of education data.

4.3 DATA QUALITY ISSUES

How good is the quality of the EMIS data in Namibia? Investigating this question is aimed at measuring the completeness and accuracy of the EMIS data and identifying possible causes for EMIS data quality problems. Some practical suggestions for improving the quality of EMIS data collection in Namibia are presented in this section. This section deals with the steps in assessing the quality of data, and provides general guidance to the EMIS Unit on assessing the quality of the EMIS data used for budgetary purposes.

4.3.1 Comparing the FSD with the AEC in 2015

Table 17 shows the total enrolment as recorded for the AEC and FSD for each region in 2015. These totals are collected from surveys at different times of the year. It is used here to verify the quality of the FSD data. The table shows relatively small differences between the FSD data and the AEC preliminary data in each region. However, the aggregate difference for the country amounts to a sizable number of learners, although it may only be a relatively small percentage difference. Also, sometimes differences largely balance out at the regional level, although the under lying data differences may be substantial.

In Figure 29 the FSD data are compared with the AEC data for each school in the country for 2015. The goal of this step is to identify relationships, patterns and trends in the data that might go unnoticed at the regional level. A scatter plot is used as a tool to identify the correlation (relationship) between the variables, possible errors in the data, potential outliers from the paired variables, and possible duplicates and other obvious errors. There are 72 schools where the difference between the FSD and AEC in 2015 is 20% or more. These differences clearly require investigation. This has been addressed through the EMIS assessment as outlined above and corrected in the FSD for 2017.


Table 17: Enrolment per region according to Fifteenth School Day Survey and Annual Education Census of 2015

Regions AEC 2015 FSD 2015 Difference % Difference

//Kharas 21 216 21 501 285 1%

Erongo 36 602 37 524 922 2%

Hardap 23 311 23 868 557 2%

Kavango East 53 068 54 981 1 913 3%

Kavango West 36 154 37 602 1 448 4%

Khomas 79 894 80 238 344 0%

Kunene 25 446 26 828 1 382 5%

Ohangwena 95 579 97 258 1 679 2%

Omaheke 20 571 21 457 886 4%

Omusati 87 935 89 207 1 272 1%

Oshana 51 480 52 037 557 1%

Oshikoto 64 514 65 527 1 013 2%

Otjozondjupa 41 207 42 987 1 780 4%

Zambezi 33 380 34 791 1 411 4%

Total 670 357 685 806 15 449 2%

Sources: Annual Education Census 2015 (preliminary data) and FSD Survey 2015.

Figure 29: Comparison of enrolment by schools according to the Fifteenth School Day Survey and the Annual Education Census of 2015

Note: As Ondao Mobile Primary School, with an enrolment of more than 3 000, is unique, it was not considered in drawing this graph.

Sources: Annual Education Census 2015 (preliminary data) and FSD 2015.

4.3.2 Comparing FSD enrolment for each school between two years – 2015 and 2016

The scatter plot in Figure 30 comparing enrolment in the FSD for two successive years, 2015 and 2016, can also help to identify schools where there may be data error issues. It is obvious from this graphical representation that in most schools enrolment changes between 2015 and 2016 are small, but there are also some large changes. Each dot in the plot represents a school, and the dots (schools) not on the line are changes. The further the school is from the line, the greater the change in the enrolment – this should be checked. There are more than 200 schools where the implied difference in enrolment according to these successive FSD Surveys is more than 20%, and there are some schools where these differences are large. This may be indicative of insufficient quality control of the FSD data.


Figure 30: Comparison of enrolment by schools according to the Fifteenth School Day Surveys of 2015 and 2016


Sources: FSD Surveys 2015 and 2016.

Figure 31: Comparison of number of teachers by schools according to the Fifteenth School Day Surveys of 2015 and 2016


Sources: FSD Surveys 2015 and 2016

4.3.3 Learner-teacher ratios

The learner-teacher ratio (LTR) is another indicator that could shed some light on the quality of the FSD data. Schools where there is extreme deviation from the norm (35:1) should be checked as it could be an error in the data. The histogram in the previous chapter on learner-teacher ratios shows 23 schools with an LTR of 50 and above and over 100 schools where the LTR is below 15.

4.3.4 Teacher appointment type and qualifications

Teacher appointments are very important in determining the MoEAC’s expenditure. Important in this regard is not only the overall number of teachers employed, but also their distribution by qualification, which is the main factor determining their salaries and also the nature of their appointment (temporary or permanent). The next three figures provide information in this regard from the ACE of 2014. It shows that most teachers are permanent, but that there are nevertheless large numbers of temporary teachers. Proportionally, such temporary teachers are most common in Kunene, one of the more isolated regions where it is difficult to attract qualified teachers to fill permanent positions.


Figure 32: Temporary and permanent teachers by region, 2014 (numbers)

Source: Annual Education Census 2014.

Figure 33: Temporary and permanent teachers by region, 2014 (% of total)


Figure 34: Teachers by qualification type, 2014 (% of total)



Currently temporary teachers earn on average only about two-thirds of what ordinary permanent teachers earn. The appointment of temporary teachers thus helps regions to remain within budget, and the shortage of qualified teachers makes such appointments inevitable. Many teacherscurrently appointed in temporary positions are studying to improve their qualifications, which would not only allow them to obtain permanent positions but would also be accompanied by a large salary increase. This may tend to raise the salary bill. This needs to be placed in perspective, though: even if all temporary teachers would overnight become permanent teachers through having improved their qualifications, the salary bill would only increase by 19%. In reality, it would take many years before all or almost all Namibian teachers meet the requirements for permanent appointment.

Figure 35, showing monthly payments in the payroll, well illustrates that many appointments are temporary and often therefore not for the full year. The annual pattern is very similar, despite the generally upward trend of the graph, reflecting rising employment in the MoEAC. The rise of around 25% in the past five years is quite large and a source for concern in a situation where fiscal resources are scarcer than was the case before.

Figure 35: Teachers receiving payments per month, 2010-2015

Source: Monthly Payroll Data 2010-2015.


4.4 CREATING PROPER DATABASES FOR EDUCATION

In all the databases (EMIS, FSD, Examination, Payroll, etc.), the school unique number is a core element that makes it possible to link these datasets from different information systems into one. Not all the datasets received from the MoEAC contained the unique school identifier, thus a database table with a unique school identifier between payroll and EMIS had to be created. This table was used to link all EMIS and payroll datasets, and will be made available for future use in the MoEAC.

Thus the following recommendations are made regarding school data:

Ensure all data collection processes within the EMIS take place according to the EMIS life cycle, consisting of the following:

�Design of the questionnaire with input from key role players.�Dissemination of questionnaire to schools with verification against the master list.�Completion of the questionnaire.�Collection and verification of the completed questionnaires.�Data capturing and data validation.�Release of data within specified timelines to serve planning and managerial needs at school,

region and national level.�Data use.

Simplify the FSD form. This will help to ensure that the data becomes available within the same year. It is recommended that the following should be included in the questionnaire for each school in the country:

�Number of Learners by Grade and Gender.�Number of Teachers by Gender.�Number of Support Staff by Gender.

Develop an official form for hostels that includes the following:

�Number of Learners by Grade and Gender.�Number of Support Staff by Gender.

Develop an official form for the school feeding programme including the following:

�Number of learners by Grade and Gender.

All these data collection processes should be harmonised through the control and management of the EMIS, taking into account the data needs for budgeting purposes. In addition, an EMIS policy should be developed that sets out data collection processes and data dissemination procedures. This policy could create a framework that allows for the coordinated and sustainable development of data collection processes.

5 FISCAL FLOWS AND SCHOOL FUNDING: POST PROVISIONING

Chapter 5: Fiscal Flows and School Funding: Post Provisioning 47

5 FISCAL FLOWS AND SCHOOL FUNDING: POST PROVISIONING

47


5.1 INTRODUCTION

ReSEP (Research on Socio-Economic Policy), the research team responsible for this report, recently drew up a Human Resources Development Plan (HRDP) and Implementation Strategy for the Namibian Education Sector, including an analysis on post provisioning (Gustafsson, 2015a & 2015b)1. Five main recommended actions, or areas of action, were identified:

Establish a proper annual monitoring system based largely on existing data. Establish a more pro-active approach to teacher supply. Establish a truly national and budget-sensitive formula on the distribution of school posts.Provide sufficient policy guidance with respect to contingency measures, in particular the

employment of temporary teachers.Establish clear dispute resolution procedures to deal with disagreements between the School

Board and the region with regard to teacher selections.

This section will be somewhat briefer on this topic, since more detailed recommendations regarding post provisioning and human resources are made in those reports. Yet, because of the pertinence of these issues for a Public Expenditure Review (PER) of the education sector in Namibia, this section will deal with some of the important aspects as they relate to public expenditure, drawing from these two earlier reports. But importantly, this section will supplement that analysis with analysis of a valuable data source that has received no thorough analysis hitherto for policy purposes, namely the MoEAC’s payroll system through which it pays all teachers, non-teaching staff employed at schools, hostel staff, regional officials and national officials. Important as it is, the payroll system has not been properly analysed for the simple reason that the unique identifier referred to in the previous chapter as the key to linking data across datasets, and in this case importantly payroll, AEC and FSD data, does not exist in the payroll data. The previous PER went to some effort to create such linkages, but this was only partly successful. Through considerable effort, this new study has managed to match most schools on the payroll to the other two main datasets, though there are still some minor unresolved issues regarding data errors.

5.2 POST PROVISIONING

The post-provisioning system is the system whereby teachers and other staff are distributed across public schools. Important aspects to consider in post provisioning relate to monitoring the system, processing enrolment data, communication work and negotiations around moving staff from one school to another, where necessary.

Although the 2001 norms for post provisioning are still officially in place, there is in effect no national policy on post provisioning, partly because it is not clear to regional officials what the national policy is – alternative norms have been proposed and received some support within the Ministry, but they have never officially been accepted as policy – and partly because officials seem to prefer devising their own approaches. This contributes to a situation where the central problem in post provisioning in Namibia is the insufficient alignment between the budgetary process and the determination of posts per school.

1 The main HRDP report is accompanied by separate reports on: (1) post provisioning; (2) the demand and supply of teachers; (3) incorporating Early Childhood Development (ECD) into the MoEAC; and (4) the fieldwork conducted for the development of the HRDP.


5.3 PERSONNEL AND PAYROLL DATA

Gustafsson (2015a) mentioned a number of problems relating to data and the payroll. He stated the following:

“Systems to prevent the fraudulent inflation of learner numbers to attract more teaching posts seem inadequate.”

Nevertheless, the distribution of teachers across schools is relatively equitable, as the fiscal incidence analysis will later confirm. Despite relatively good data systems in terms of data capturing and payment, virtually no analysis of the payroll system for monitoring takes place. Data on temporary teachers are weak, and at regional level there is too little in-year reporting on spending to date against the personnel budget. It is often difficult for a qualified teacher to know what vacant posts are available across the whole country. An undersupply of qualified teachers results in the appointment of temporary teachers, who are underqualified. Appointments of temporary teachers are often not optimal, partly, it seems, because the policies governing this are weak. Schools and regional offices often clash over who to appoint as temporary teachers.

Gustafsson (2015b) concluded that it is difficult to apply existing policies as the ideal for the distribution of teachers, because different regions apply national rules differently, and because many ad hoc decisions are taken to deal with budget constraints and demands from schools that are not well covered in the policies. He thus took the approach that the general patterns in teacher distribution seen across regions were essentially sensible and unlikely to change much in the near future. Inequities were then viewed in terms of deviations from this general pattern. The conclusion he drew was that around 6% of teachers would need to be moved in order to produce an equitable distribution. He also concluded that existing inequities are large enough to worry about. For instance, 8% of learners are in schools where the LTR is at least 5 learners too high, while for 5% of learners the LTR is too low by a margin of at least 5 learners.

Tables 18 to 23 show the number of paid staff members and payroll payments that were made in 2014 to MoEAC staff, distinguishing between teachers and non-teachers. Of the N$6.8 billion spent on salaries and allowances in that year, only N$449 million or 6.6% went to the 2 257 staff members employed within the Ministry itself (the last tables show employment numbers), mainly administrative staff. The 25 394 teaching staff were overwhelmingly appointed and paid within the regions. It is concerning to note the very small size of pre-primary education, with pre-primary teachers receiving only N$52.8 million in salaries, this being less than one percent of all salaries paid for teaching staff. Considering that the pre-primary cohort is at least as large as most older cohorts are, equal attention to pre-primary would have been expected to cost about 8% of the teacher budget. The low spending on pre-primary teachers is the result not only of just 1.1% of all teachers employed by the Ministry being pre-primary teachers, but also the fact that on average they earn just 82% of the average teacher’s salary.

Of the N$6.8 billion spent on staff salaries within the Ministry, the vast bulk (N$5.9 billion) goes to school education, mainly as salaries of teachers in primary and secondary schools (N$5.7 billion). Of the 37 612 staff members on average employed in the Ministry every month, teachers constitute 25 394.


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576

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984

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ff

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1

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990

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Reg

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2

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n

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286

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014.


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le 2

0: S

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pay

men

ts w

ith

in t

he

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EA

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each

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plu

s n

on

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cher

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5.4 COMPARING TEACHERS ON PAYROLL WITH ANNUAL SCHOOL CENSUS EMPLOYMENT IN 2014

The rising employment in the number of staff employed in the payroll as illustrated in the previous chapter raises a point that was also made in the PER of 2011, i.e. whether there are ghost teachers on the payroll, meaning persons who are not officially on the establishment but who are nevertheless receiving salaries as teachers. After a laborious process of matching paypoints to schools and illuminating discrepancies that may result from other data quality issues, it was possible to arrive at a more thorough analysis of the employed teachers according to the payroll data and those employed according to data from the AEC. However, it should be emphasised that this is a preliminary process that needs to be followed by more precise work and investigation at the national, regional and school level.

It should be remembered that there are some incentives for schools to exaggerate enrolment in the FSD Survey as well as the AEC, as this may provide them with more resources (UPE/USE, textbooks, stationery, and even additional teacher posts), but the same would not apply to the employment of teachers. Moreover, the names of the teachers have to be provided in the AEC. Figure 36 shows that there are indeed some differences between AEC and payroll employment numbers, with variations in both directions, as one would expect if the source of differences is not so much systematic bias or manipulation as it is data errors or data entry errors.

Figure 36: Comparing teacher employment according to the ACE 2014 and Payroll 2014

Source: Own calculations from Annual Education Census 2014 and Payroll 2014 (September figures).

Closer inspection shows, however, that there are indeed a number of cases where payroll numbers considerably exceed AEC numbers. In both the payroll and the AEC, teachers are listed by name, so it is possible to match individual teachers, once the paypoints have been properly linked to the schools. It was not possible to investigate all these cases, and the investigation that the research team could devote to this was by its nature superficial, but it is worrying that there are indeed almost 20 cases where as many as seven or more teachers were found on the payroll of schools but were not counted or listed by name in the AEC. This requires corrective action. It may simply be mistakes in either of the two data sources, but it is incumbent on the Ministry to ensure that such possible situations be eliminated.

Thus one of the recommendations made in this report is that a task team of the Ministry be appointed to investigate cases where payroll numbers exceed AEC numbers in particular schools, starting with those cases where there are considerable discrepancies (say six or more). Once such


discrepancies have been identified, further investigation and visits to the schools concerned should take place to determine the source of the discrepancy and to take corrective action. Should it be found that there are indeed ghost teachers on the payroll, investigation should also take place to determine how this could occur, as it would probably have required collusion at an administrative level. Following a draft of this report presented to the MoEAC, a process is already underway to institute the necessary corrective steps.

The reason for the presence of such rumoured ghost teachers not yet having been thoroughly investigated is that the data in the MoEAC are not used properly. An important aspect in this regard is the matching of paypoints to schools, and thereafter the comparison of the payroll and AEC data relating to particular schools. The ReSEP team has now matched most of these paypoints and schools, and will make this information available to the MoEAC for further investigation.

It follows that such matching and monitoring should take place on a regular basis, based on updated data. For successful planning it is essential that the three major data sources of the FSD Survey, the AEC and the payroll data be kept up to date, and that financial planning should use enrolment data from the FSD and AEC. This requires strengthening the EMIS function within the Ministry.

Furthermore, for the sake of tying educational outcomes more closely to resource inputs, the data integration process should go beyond these three data sources to also include examinations data.

Chapter 6: Fiscal Flows and School Funding: Non-Personnel Spending 55

6 FISCAL FLOWS AND SCHOOL FUNDING: NON-PERSONNEL SPENDING

55


Regional allocations of funds to schools take different forms, but the most important are the allocations for textbooks, stationery, and the universal grants for Universal Primary Education

(UPE) introduced in 2013 and Universal Secondary Education (USE) introduced in 2016. Tables 24, 25 and 26 show the allocations per region in 2016/17 for UPE, USE, textbooks and stationery.

The first thing to note is the relatively small allocations per learner to pre-primary grades for textbooks and stationery – only N$284 per child. Because such pre-primary classes are attached to primary or combined schools, they do not receive a separate allocation that is equivalent to UPE or USE. This effectively means that the UPE allocation to schools which also have pre-primary classes is more thinly spread than is the case for primary schools without pre-primary. A second thing to note is the very differentiated allocations to pre-primary education across regions, ranging between no allocation at all for Oshikoto to N$57 per learner for Erongo and even N$1 964 for Omaheke.

In primary education, the per learner allocations for UPE, textbooks and stationery together amount to N$879, of which N$511 is for UPE alone. The range of allocations per primary child for UPE is somewhat smaller, ranging from N$447 in the two Kavango regions (combined) to N$605 in Otjozondjupa. Considering all three of these transfers to the regions, Khomas is the main beneficiary, with N$1 087 per enrolled primary learner.

Table 24: Part of regional operational budget allocations for 2016/17: Pre-primary

Regions Textbooks StationeryTotal

allocationEnrolment

Total per learner

//Kharas 263 160 310 340 573 500 1 514 379

Erongo - 107 295 107 295 1 882 57

Hardap - 386 405 386 405 1 477 262

Kavango East & West - 461 020 461 020 4 854 95

Khomas 404 250 958 420 1 362 670 4 353 313

Kunene 255 750 170 750 426 500 1 912 223

Ohangwena 529 650 888 100 1 417 750 4 537 312

Omaheke - 2 281 800 2 281 800 1 162 1 964

Omusati 501 000 435 200 936 200 3 791 247

Oshana 345 600 280 144 625 744 2 780 225

Oshikoto - - - 3 944 -

Otjozondjupa 326 100 697 400 1 023 500 2 393 428

Zambezi 447 938 547 580 995 518 2 699 369

Total 3 073 448 7 524 454 10 597 902 37 298 284Source: Data obtained from MoEAC.


Table 25: Part of regional operational budget allocations for 2016/17: Primary

Regions UPE Textbooks StationeryTotal

allocationEnrolment

Total per learner

//Kharas 5 521 481 2 069 400 1 438 468 9 029 349 11 761 768

Erongo 8 571 850 3 790 650 156 650 12 519 150 18 638 672

Hardap 6 357 710 3 436 600 3 537 000 13 331 310 13 896 959

Kavango East & West 24 776 850 9 289 950 4 601 415 38 668 215 55 417 698

Khomas 15 799 100 9 992 800 5 512 800 31 304 700 28 787 1 087

Kunene 7 759 500 3 032 250 2 043 500 12 835 250 15 917 806

Ohangwena 28 436 335 9 293 400 7 004 100 44 733 835 52 002 860

Omaheke 6 058 500 2 452 200 - 8 510 700 12 151 700

Omusati 24 841 600 5 814 450 3 926 300 34 582 350 51 190 676

Oshana 13 133 705 5 803 650 3 869 100 22 806 455 24 460 932

Oshikoto 18 963 200 6 870 750 6 870 750 32 704 700 32 177 1 016

Otjozondjupa 11 273 150 4 473 300 3 182 200 18 928 650 18 631 1 016

Zambezi 9 058 751 4 317 450 2 951 500 16 327 701 18 577 879

Total 180 551 732 70 636 850 45 093 783 296 282 365 353 604 838Source: Data obtained from MoEAC.

For secondary education, the picture is a little more complex due to the addition of funds to purchase the revised textbooks for the new Junior Secondary curriculum. About N$97 million was allocated for this, half of which had been allocated to regions and the other half still having to be allocated. If one excludes this part of the expenditure, secondary children were subsidised on average N$1 011, this being substantially more than for either pre-primary and primary education.

Table 26: Part of regional operational budget allocations for 2016/17: Secondary

Regions USE Textbooks

Textbooks for new

Junior Sec. curriculum

Stationery Total allocation

Enrol-ment

Total per learner

All Excl. new curriculum

//Kharas 3 234 375 1 940 700 1 664 000 662 000 7 501 075 4 920 1 525 1 186

Erongo 5 818 253 2 529 000 2 249 000 641 585 11 237 838 9 116 1 233 986

Hardap 3 277 328 1 593 750 356 240 637 500 5 864 818 5 808 1 010 948

Kavango E&W 11 759 670 2 750 250 5 203 165 1 100 100 20 813 185 19 816 1 050 788

Khomas 13 454 483 5 479 250 6 706 320 5 479 250 31 119 303 15 586 1 997 1 566

Kunene 2 493 833 1 234 750 1 150 000 509 650 5 388 233 4 156 1 296 1 020

Ohangwena 15 873 795 7 668 500 7 854 960 3 503 318 34 900 573 28 144 1 240 961

Omaheke 2 562660 1 167 500 1 024 000 - 4 754 160 5 028 946 742

Omusati 14 843 970 6 343 500 7 537 200 2 766 400 31 491 070 27 142 1 160 883

Oshana 9 810 765 2 150 750 5 710 320 860 300 18 532 135 11 279 1 643 1 137

Oshikoto 10 510 943 5 077 750 6 209 440 3 581 100 25 379 233 18 633 1 362 1 029

Otjozondjupa 5 531 558 2 612 750 2 113 200 1 645 100 11 902 608 6 022 1 977 1 626

Zambezi 5 928 998 1 522 500 2 024 640 682 200 10 158 338 11 734 866 693

Total 105 100 628 42 070 950 49 802 485 22 068 503 219 042 566 167 384 1 309 1 011

HQ: Revised Curriculum 47 059 000 47 059 000

Total (incl. unallocated) 96 861 485 266 101 566 167 384 1 590 1 011

Note: Funds at HQ for Revised Curriculum textbooks redistributed to Regional Councils in August 2016.Source: Data obtained from MoEAC.


The uncertainty about enrolment numbers and the different data sources used leads to considerable anomalies. The allocations of resources to regions in 2016/17 for USE, calculated at N$500 per child in secondary education, implies a secondary school enrolment of 210 000, this being more than a quarter higher than the 167 000 obtained from the FSD Survey of 2016. Moreover, different regions are differently affected by this, as the discrepancies between the enrolment numbers used at the level of the Ministry and the FSD enrolment differ widely across regions.

Table 27 shows enrolment by region according to the AEC of 2012, which is often used within the Ministry (because of its ready availability, it appears, rather than its superior quality) to allocate funds to regions, and according to the 2016 FSD data, which regions use to allocate funds to schools. Given enrolment growth, the actual allocation per learner by the regions would thus be expected to be lower than that calculated at the national level. However, differential regional growth leads to anomalies. As can be seen, there are some large discrepancies between these numbers. Consequently, the allocation per learner in Kavango East would be only 79% and in Zambezi only 84% of the average allocation per learner calculated at the national level, while it would be 100% of the average in Oshana. The differentiated growth rates across regions in the interim period thus implies that the use of two different datasets for allocating funds at national level and regional level would be quite inequitable, with those regions experiencing the fastest enrolment growth according to these numbers being disadvantaged.

Table 27: Enrolment by region according to the Annual Education Census of 2012 relative to the Fifteenth School Day Survey of 2016

Regions Enrolment AEC 2012 Enrolment FSD 2016 Ratio AEC 2012: FSD 2016

//Kharas 15 890 16 750 95%

Erongo 24 803 28 344 88%

Hardap 19 934 21 923 91%

Kavango East 39 268 49 444 79%

Kavango West 27 425 33 619 82%

Khomas 46 503 47 229 98%

Kunene 14 804 17 963 82%

Ohangwena 84 073 88 525 95%

Omaheke 15 265 18 121 84%

Omusati 82 162 86 235 95%

Oshana 39 574 39 568 100%

Oshikoto 51 003 54 361 94%

Otjozondjupa 23 628 27 109 87%

Zambezi 27 118 32 145 84%

Total 511 450 561 336 91%

Source: Calculations from Annual Education Census 2012 and FSD Survey 2016.

It is useful to place the allocations to regions for distribution to schools in some perspective. Even if one includes the funds allocated to accommodate the introduction of the new Junior Secondary curriculum, the 2016/17 allocations for UPE/USE, textbooks and stationery combined amount to only N$526 million, of which half is allocated to secondary education (which constitutes only 30% of enrolment across pre-primary, primary and secondary levels). This should be considered against the N$5 621 million that teachers in these three school levels are paid. (This latter figure relates to the 2014 calendar year, obtained from paypoint data.)

Thus non-personnel spending is relatively low compared to spending on personnel, an issue that often arises in developing countries, despite the fact that most studies show that the marginal


returns to spending on textbooks and other learning material tend to exceed those on personnel (see Pritchett and Filmer, 1997). It is crucial that the tightening fiscal situation does not lead to further pressure on non-personnel spending. The previous PER already indicated that spending on goods and services had been suffering from crowding out by personnel spending (Ecorys, 2011: 117).

It is therefore desirable that spending on textbooks and learning materials should be given precedence in the budget. An appropriate way of doing this would be to draw up a five-year Learning and Teaching Support Materials (LTSM) plan whereby the real spending on these materials is set to grow by 8-10% per year. This will allow for both ensuring that more children have textbooks and increasing the number of textbooks available.

To accommodate this, it would be necessary to curtail personnel spending a little – something that is given more importance by the fiscal cutbacks that would have to occur. Given that learner-teacher ratios are comparatively low in Namibia, this should be possible. Also, teacher salaries for qualified teachers are relatively high (Ecorys, 2011: 139), so real increases in salaries should be avoided as far as possible. It is also important that the modest reduction in teacher numbers that this would entail should not take place by reducing teacher numbers in small schools.

In the light of the above, it is worrying to note that the provisional budget allocations for 2017/18 show large reductions for UPE and USE, even without considering inflation (see Table 28). The allocation for UPE has been reduced from N$188.6 million in the previous year to N$114.1 million, and that for USE from N$105.1 million to N$53.4 million. The latter in particular is a very sharp reduction, by more than half if expressed in real (inflation-adjusted) terms. While the initial budgets for UPE and USE were drawn up to allocate N$400 per primary learner and N$600 per secondary learner, these amounts were revised downwards to N$250 per learner in both primary and secondary schools. This will affect schools substantially. It appears that non-personnel spending may be reduced especially sharply in reaction to the stricter fiscal constraints, with personnel spending perhaps crowding out non-personnel spending even more. Textbook provision was provisionally cut back from more than N$115 million (excluding the provision of N$97 for textbooks for the new curriculum) to only N$72 million. Similarly, spending allocated for school stationery was reduced from N$75 million to N$48 million. More details on the provisional regional allocations for 2017/18 are contained in the Tables 28, 29 and 30.

Table 28: Provisional operational budget allocations to regions, 2017/18

Description Pre-primary Primary Secondary Library Adult Total

Textbooks 4 074 000 22 566 000 44 873 000 498 000 354 000 72 365 000

Hostel catering - 59 538 000 191 689 000 - - 251 227 000

School feeding - 130 917 000 - - - 130 917 000

Universal Primary grant (UPE) - 114 412 000 - - - 114 412 000

Universal Secondary grant (USE) - - 53 400 000 - - 53 400 000

Security contract - 9 995 000 7 273 000 1 492 000 624 000 19 384 000

Utilities 1 272 000 53 877 000 54 236 000 1 752 000 867 000 112 004 000

Daily Subsistence Allowance (DSA) - 1 596 000 2 506 000 504 000 434 000 5 040 000

School stationery 5 523 000 17 749 000 22 068 000 1 202 000 999 000 47 541 000

Community hostel - 39 974 000 20 030 000 - - 60 004 000

Private school/hostel - 16 771 000 12 734 000 - - 29 505 000

Total 10 869 000 467 395 000 408 809 000 5 448 000 3 278 000 895 799 000

Source: Data obtained from MoEAC.


Table 29: Provisional regional allocations of full operational budget, 2017/18

Regions Pre-Primary Primary Secondary LibraryAdult

EducationTotal

//Kharas 558 000 22 069 000 17 002 000 784 000 171 000 40 584 000

Erongo 82 000 20 738 000 17 023 000 715 000 502 000 39 060 000

Hardap 474 000 20 702 000 19 442 000 367 000 237 000 41 222 000

Kavango East 852 000 37 112 000 32 379 000 304 000 237 000 70 884 000

Kavango West 567 000 31 312 000 15 194 000 140 000 179 000 47 392 000

Khomas 1 450 000 39 339 000 43 615 000 592 000 277 000 85 273 000

Kunene 375 000 33 550 000 22 487 000 247 000 167 000 56 826 000

Ohangwena 921 000 51 942 000 50 063 000 610 000 355 000 103 891 000

Omusati 1 461 000 53 671 000 47 068 000 310 000 94 000 102 604 000

Oshana 696 000 31 530 000 33 709 000 474 000 96 000 66 505 000

Oshikoto 691 000 40 691 000 35 129 000 152 000 193 000 76 856 000

Otjozondjupa 965 000 31 149 000 30 012 000 258 000 292 000 62 676 000

Omaheke 1 081 000 30 722 000 27 062 000 324 000 235 000 59 424 000

Zambezi 696 000 22 868 000 18 624 000 171 000 243 000 42 602 000

Total 10 869 000 467 395 000 408 809 000 5 448 000 3 278 000 895 799 000


Table 30: Provisional regional allocations of development (capital) budget, 2017/18

Regions Primary Secondary Total

//Kharas 3 646 000 2 871 000 6 517 000

Erongo 3 218 000 3 090 000 6 308 000

Hardap 3 057 000 2 678 000 5 735 000

Kavango East 8 019 000 3 024 000 11 043 000

Kavango West 5 973 000 1 942 000 7 915 000

Khomas 5 126 000 6 020 000 11 146 000

Kunene 6 398 000 3 274 000 9 672 000

Ohangwena 22 601 000 5 768 000 28 369 000

Omaheke 4 379 000 3 220 000 7 599 000

Omusati 18 907 000 6 363 000 25 270 000

Oshana 6 835 000 4 010 000 10 845 000

Oshikoto 15 832 000 4 543 000 20 375 000

Otjozondjupa 11 541 000 3 889 000 15 430 000

Zambezi 6 968 000 2 335 000 9 303 000

Total 122 500 000 53 027 000 175 527 000


Chapter 7: Fiscal Incidence and Equity 61

7 FISCAL INCIDENCE AND EQUITY

61


7.1 FISCAL INCIDENCE: COST PER LEARNER

The fiscal incidence of government spending relates to how equitably it is spread across groups, particularly the extent to which it reaches the poor. In the Namibian case, one pertinent issue would be to determine how equitably spending is distributed across regions, considering that two regions (Khomas and Erongo) have far wealthier populations than the other regions. A second possibility is to consider the distribution of fiscal resources across groups of schools according to the categorisation of the remoteness of schools – a categorisation that is used for determining which teachers qualify for the remoteness incentive. A third possibility requires use of census data and data from the Namibia Household Income and Expenditure Survey. These data were used to calculate an asset index based on households’ possessions within each enumerator area. These enumerator areas were then classified into 10 deciles with equal numbers of children of the core school-age group 7 to 18 in each decile. Decile 1 then contains schools in the poorest enumerator areas, and Decile 10 schools located in the richest enumerator areas.

The first level of analysis was simply applied to the cost per teacher. Despite fairly large differences in the salaries and allowances of teachers by qualification level as well as substantial differences in the mix of teachers in different schools and regions, no evidence was found that teacher salaries and allowances were systematically higher in more affluent regions, remoteness categories or deciles. Multivariate regression analysis also did not show any statistically significant association between per teacher costs across the three types of classifications, or where there were differences, these were small and not systematically favouring the more affluent. This also applied when teacher-learner ratios were analysed, as well as when the teacher salary costs per learner were analysed. The latter is of course a function of the teacher-learner ratio and the cost per teacher. Tables 31, 32, 33 and 34 illustrate the findings that there are no systematic biases in the main spending category, teacher salaries, across regions, remoteness categories or school decile, where schools are arranged from those located in the poorest to those located in the richest enumerator areas in the country. This conclusion does not change if non-teacher salaries at school level are included.

Thus it is warranted to make the assumption made in virtually all fiscal incidence studies inter-nationally, that costs do not widely or systematically differ across beneficiaries. This is important, as Namibia’s history makes it important to test whether such systematic favouring of certain learners may have remained, as was true in apartheid South Africa. (See Lustig et al., 2013; Gustafsson & Patel, 2006; Van der Berg, 2006; Van der Berg & Moses, 2012).


Table 31: Enrolment, teacher and non-teacher salaries, and spending per learner per month by school type, 2014

Spending Category

Agricultural School

Primary School

Combined School

Secondary School

Special School

Technical/ Vocational

SchoolTotal

Schools 1 792 436 145 5 7 1 386

Enrolled 2014 191 245 362 213 110 79 142 1 169 4 201 543 175

Teachers 13 9 799 9 132 3 637 151 184 22 916

Teacher salaries 234 761 186 120 114 179 962 274 75 318 719 3 273 055 3 791 649 448 700 573

Salaries per teacher 18 059 18 994 19 707 20 709 21 676 20 607 19 580

Salaries per learner 1 229 759 844 952 2 800 903 826

Learner-teacher ratio 15 25 23 22 8 23 24

Non-teachers 12 1 882 1 485 1 091 72 77 4 619

Non-teacher salaries 60 181 10 914 557 9 075 451 6 384 417 425 638 423 922 27 284 166

Non-teacher salaries per learner

315 44 43 81 364 101 50

Teacher + non-teacher salaries per learner

1 544 803 887 1 032 3 164 1 003 876



Tab

le 3

2: E

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lmen

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each

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176

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1 28

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826

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970

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Tab

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Tab

le 3

4: E

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917

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310

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183

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681

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rolle

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5561

319

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2 65

02

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2 38

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1 85

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902

1 94

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2323

2322

2323

2626

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No

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291

447

436

432

418

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488

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4 61

9

No

n-t

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ies

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2 48

7 48

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363

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3 18

92

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800

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84 1

66

No

n-t

each

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alar

ies

per

lear

ner

3643

4247

5156

6658

5847

50

Teac

her

+ n

on

-tea

cher

sa

lari

es p

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arn

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587

988

792

394

792

593

081

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383

787

6

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tain

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Mo

EA

C.


7.2 FISCAL INCIDENCE: WHO GAINS ACCESS TO EDUCATION?

The question that then remains is one that most international fiscal incidence studies focus on: whether access systematically favours the wealthier parts of the population. This cannot be determined from school data or financial data; it requires an analysis using census data.

Table 35 shows the distribution of the core school-age group aged 7 to 18 by school enrolment, distinguishing also between primary and secondary attainment. There are systematic differences across deciles. In the poorest deciles of enumerator areas, 52% of children attend primary school and 11% secondary school; in the richest decile it is 54% and 32%. Thus 37% of Decile 1 children do not attend school at all, as against 13% of Decile 10 children.1

Table 35: School enrolment of core school-age group 7-18 according to deciles of enumerator area wealth status, 2011

Deciles Not attendingAttending primary

Attending secondary

Completed Grade 12

Total

Decile 1 20 607 29 387 6 124 38 56 156

Decile 2 13 791 32 981 8 603 67 55 442

Decile 3 12 248 32 943 9 795 72 55 058

Decile 4 10 741 33 564 10 657 83 55 045

Decile 5 11 507 32 372 10 669 91 54 639

Decile 6 11 763 31 146 11 391 123 54 423

Decile 7 14 003 30 155 10 387 149 54 694

Decile 8 12 260 30 006 12 036 201 54 503

Decile 9 9 713 30 365 13 868 280 54 226

Decile 10 6 781 29 196 17 287 483 53 747

Total 123 414 312 115 110 817 1 587 547 933

% of each decile

Decile 1 37% 52% 11% 0% 100%

Decile 2 25% 59% 16% 0% 100%

Decile 3 22% 60% 18% 0% 100%

Decile 4 20% 61% 19% 0% 100%

Decile 5 21% 59% 20% 0% 100%

Decile 6 22% 57% 21% 0% 100%

Decile 7 26% 55% 19% 0% 100%

Decile 8 22% 55% 22% 0% 100%

Decile 9 18% 56% 26% 1% 100%

Decile 10 13% 54% 32% 1% 100%

Total 23% 57% 20% 0% 100%

Source: Own calculations from Namibia Population and Housing Census 2011.

1 Note that in Decile 10 a small percentage, almost 1%, do not attend school as they have already passed Grade 12. This seems anomalous, and may in some cases simply reflect small inaccuracies in age reporting.


Figure 37: School attendance by enumerator area wealth decile, 2011


The same phenomenon can also be illustrated by another figure based on the census. Figure 38 shows enrolment status of the same age group 7 to 18 by main home language grouping as shown in the census. The columns have been arranged in ascending order of the percentage not attending school, which is as low as 14% among English and 16% among Afrikaans speakers, to as high as 35% among Otjiherero and an astonishing 58% among speakers of San languages.

Figure 38: School attendance by home language grouping, 2011


7.3 INEQUALITY IN EDUCATIONAL OUTCOMES

So, although the allocation of fiscal resources follows the patterns of enrolment in schools, with no biases favouring richer households, there are clear inequities in school access and educational outcomes. This relates to school access, which favours the more affluent groups in society, but even more so in terms of school outcomes. One way of illustrating this is to look at a graph of so-called pseudo-survival rates. This shows the number of children in various higher grades as a percentage of those in Grade 1. This is thus different from a cohort analysis, where the same children are tracked over time, but it shows a very similar phenomenon, that some children drop out without completing higher grades, thus leading to a sharply declining survival rate even when the numbers of children in the population of different year groups are quite similar.


Figure 39 shows such pseudo-survival rates. The most dramatic difference is between the San, whose numbers in Grade 12 are only 1% of the numbers in Grade 1, and English and Afrikaans speakers, whose Grade 12s are more than 40% of their Grade 1 numbers. For the San, most of the dropout occurs early.

Figure 39: Pseudo-survival rates by home language, 2015

Note: These data refer to enrolment in each grade relative to enrolment in Grade 1. It is thus not a real cohort of indi-viduals that are tracked over time, but simply a cross-section of enrolment in 2015. However, as enrolment in different grades is relatively stable over time, this can be interpreted very similarly to cohort survival rates.

Source: Own calculations from Annual Education Census 2015 (preliminary data).

The poor survival rates to higher grades, and especially to Grade 12, are clearly related to the quality of education. Though the distribution of educational resources within the education system is relatively equitable, the skewed access to and progression in schools imply that the education system is not performing optimally in providing skills to the poor and in reducing inequality.

This important equity aspect of the Namibian education system needs continued attention. Though it is not principally a matter of finances and thus seemingly not central to a Public Expenditure Review, there are some important questions stemming from this that have implications for how resources need to be applied in Namibia. Especially important is the question of access, which is related to the distribution of schools and hostels and the provision of transport, and quality, which is a much deeper and intractable problem that needs continued attention.

7.4 OTHER EQUITY ISSUES

Besides the above, there are also some other important equity issues that Namibia has set out to address, but with respect to which it still has a long road ahead. These relate to, inter alia, ECD and pre-primary education, and education for children with special needs.

7.4.1 Pre-primary education

Although Namibia has only really started to pursue pre-primary education aggressively quite recently, and facilities are in many instances still inadequate, the enrolment growth rate of almost 25% per year between 2011 and 2015 shows that there is no lack of demand. As with the case of the rapid expansion of school enrolment after more schools were built in Kunene, the expansion of pre-primary education points to pent-up demand in many communities. It is important that good quality pre-primary education is provided, in order for it to make its potential contribution for raising cognitive outcomes at lower levels and thereby provide a stimulus to the whole education system.


From this perspective it is important that spending on pre-primary education keeps up with the needs, and also that every effort is made to enrol children in hard-to-reach rural areas. It is amongst such communities where school access, progression and eventually outcomes still lag far behind.

Namibian children qualify to enter pre-primary education if they have turned 5 before the end of the previous calendar year. The census was taken in August 2011, thus most of those who entered at the correct age would have turned 6. Therefore children aged 6 who are out of school are those not attending either pre-primary or primary school. Altogether 13 082 (28%) fell into this category in the census, as against 33 195 6-year-olds who were attending pre-primary or primary school (almost equally divided between these two school types). Kunene (61%), Zambezi (49%) and Omaheke (45%) were the regions with the highest proportion of 6-year-olds out of school, while the large Kavango Region (before it was divided into Kavango East and West) contained 20% of all such out-of-school pre-primary-aged children. There appears to be almost no gender differences in access to pre-primary schools.

According to the census, there were altogether 38 102 children in pre-primary schools, some of them older than 6 years at the time of the census. This number is much higher than the 13 459 enrolled according to the EMIS data. The difference can be accounted for by the fact that most day centres, nursery schools and kindergartens also offer pre-primary or early childhood education, and census respondents may have included these. Such non-public pre-primary school offerings make the issue of the quality of pre-primary education offered even more intractable.

Table 36: Pre-primary-aged children (6 years) out of school, in pre-primary and in primary schools by region, and younger children in pre-primary schools, 2011

RegionsOut of

school

In pre-

primary

In primary school

Total%

out of school

% of out

of school

Pre-primary younger than 6

//Kharas 293 523 468 1 284 23% 2% 118

Erongo 392 1 165 847 2 404 16% 3% 102

Hardap 512 646 477 1 635 31% 4% 276

Kavango 2 576 1 579 1 922 6 077 42% 20% 114

Khomas 984 2 351 2 179 5 514 18% 8% 632

Kunene 1 407 490 395 2 292 61% 11% 542

Ohangwena 1 492 2 787 2 231 6 510 23% 11% 171

Omaheke 726 571 322 1 619 45% 6% 1 016

Omusati 990 2 073 2 476 5 539 18% 8% 143

Oshana 406 1 352 1 640 3 398 12% 3% 693

Oshikoto 978 1 690 1 729 4 397 22% 7% 387

Otjozondjupa 1 203 1 070 962 3 235 37% 9% 502

Zambezi 1 123 558 588 2 269 49% 9% 285

Total 13 082 16 855 16 236 46 173 28% 100% 4 981

Girls 6 355 8 550 8 313 23 218 27% 49% 2 526

Boys 6 727 8 305 7 923 22 955 29% 51% 2 455Source: Derived from Namibia Population and Housing Census 2011.

Pre-primary education has grown rapidly after a late start. Table 37 shows that there was a tenfold increase in enrolment from 2008 to 2015, though from a very low base. If it is considered that there are about 55 000 children in the 6-year-old cohort, then the enrolment of almost 32 000 in 2015 is about 58% of the cohort. It is important that such growth is not at the cost of quality, as pre-primary education has to lay the foundation for the important primary phases, where quality


is already seriously deficient. Moreover, both access and quality of pre-primary education should be equitable from the start, for “early inequitable provision will exacerbate inequalities in later phases of education” (UNICEF and UIS, 2014a: 21).

Table 37: Enrolment in pre-primary education by region, 2008 to 2015

Regions 2008 2009 2010 2011 2012 2013 2014 2015Growth 2011-15

//Kharas 322 457 620 872 931 1 169 1 190 1 442 65%

Erongo 135 477 527 758 932 1 247 1 458 1 693 123%

Hardap 139 360 552 841 1 050 1 312 1 401 1 392 66%

Kavango 235 623 910 1 466 1 931 2 710 3 438 3 845 162%

Kavango East 1 806 1 920 –

Kavango West 1 632 1 925 –

Khomas 472 746 873 1 599 2 055 2 965 3 560 3 798 138%

Kunene 124 292 419 661 902 1 209 1 155 1 591 141%

Ohangwena 211 408 601 1 163 1 562 2 254 2 857 3 537 204%

Omaheke 213 365 524 747 927 1 089 691 735 -2%

Omusati 264 482 700 1 100 1 584 2 234 2 798 3 371 206%

Oshana 436 586 802 1 169 1 569 2 446 2 369 2 582 121%

Oshikoto 220 513 675 1 211 1 624 2 419 2 914 3 422 183%

Otjozondjupa 308 505 745 1 088 1 351 1 904 2 018 2 240 106%

Zambezi 67 302 527 784 1 154 1 787 2 164 2 284 191%

Total: Namibia 3 146 6 116 8 475 13 459 17 572 24 745 28 013 31 932 137%Sources: Own calculations from Annual Education Censuses 2008-2015.

Considering the growth of enrolment since the census, it is worrying that Omaheke has shown no growth despite the fact that it was one of the worst-off regions in terms of attendance of pre-primary education in 2011. The growth in the Kavango regions and especially Zambezi was higher than average, and reduced the out-of-school problem in this age group.

7.4.2 Special schools and schools for learners with special needs

In the 2016 AEC, 5 special schools were enu-merated (there are some others that are not included in the AEC), with a total enrolment of 1 249, including 731 primary and 146 secondary learners. There were 151 teachers and 72 non-teachers on the payroll for these schools in 2014, indicating a very favourable ratio of learners to teachers: in each of these schools the 2016 enrol-ment and the 2014 payroll numbers imply that there are fewer than 10 learners per teacher. The need for low learner-teacher ratios is especially acute in special schools, so this is an important achievement.

The 2001 post-provisioning norm implies that a school qualifies for one additional teacher if primary learners increase by 35, secondary learners by 30 and learners in special classes by 15. However, that presumes that such learners are separately accommodated within classrooms.


Table 38: Special schools listed on Payroll 2014

RE

GIO

NS

SCHOOL

ENROLMENT TEACHERSN

ON

-T

EA

CH

ER

S

ON

PAYR

OLL

IN 2014

Total 2015

Prim

ary

Seco

nd

ary

On

payro

ll in

2014

In FS

D 2016

Hardap Klein-Aub Special School 105 91 0 13 12 14

Oshana Eluwa Special School 347 203 109 47 94 34

Khomas Eros Girls’ School 273 0 0 28 32 5

Khomas Pioneer Boys’ School 398 358 0 42 40 13

Khomas School for the Visually Impaired 126 79 37 21 22 6

Total 1 249 731 146 151 200 72

Note: Enrolment data across primary and secondary schools do not add up.Source: Own calculations from Payroll data.

As the policy of the MoEAC is to mainstream disability as much as is possible, it is to be expected that there would be many cases of children with disabilities and/or special need in ordinary schools. Indeed, that is confirmed by Table 39, drawn from the AEC of 2015. According to this table, almost 31 000 learners in Namibian ordinary schools have physical disabilities of one sort or another.2 However, this data is based only on teacher observations, and teachers are not always in a position to identify the nature of such disabilities. A good example in point is autism. Nevertheless, the data do give some indication of the prevalence of different disabilities amongst learners in schools. According to this data, the disability that is most common – or at least most noted by teachers – is partial blindness (5 833), followed by children being hard of hearing (5 511) and children having learning disabilities (5 173).

Much still needs to be done to ensure that children with special needs get the attention they should be getting, both before entering school and in the school system, and ensuring that those who need to be placed in special schools do get placed there. Issues of distance again make this a difficult problem, as it is always optimal for children to attend schools near their homes. With only five special schools in Namibia, this is clearly not always possible.

7.4.3 School feeding

According to the 2015 implementation report (MoEAC, 2015), the Namibian School Feeding Programme (NSFP) provides mid-morning meals to over 330 000 learners in 1 428 pre-primary and primary schools. It is stated that “The meal is a hot porridge made from fortified maize blend. The main objectives for giving the meal are to increase the concentration of learners, improve attendance and ultimately learning performance as well as progression through grades.” (MoEAC, 2015: 3; see also Ellis, 2012: 6-7.) Participation varies across schools, but is around 80% in participating schools, with much higher rates in rural areas. In 2012 the cost was N$60 million for the food, i.e. about N$1 per child per day. Non-food costs are borne by the schools and the Ministry, but these are difficult to quantify.

2 It is of course possible that some children have multiple disabilities and may have been counted more than once in this data.


According to the 2015 Term 2 Implementation report, only one-third of participating schools provide meals every day, and altogether 78% either have meals every day or most days. Due to, inter alia, problems with procurement, late delivery of maize to schools remains a challenge. There are plans to extend the feeding scheme to secondary schools, which may assist progression to these levels in poor communities, and to provide a more enriched diet and a diversified meal.

Table 39: Children with physical disabilities as reported by teachers by grade and nature of disability as captured in the Annual Education Census, 2015

Disabilities Gender

Pre-Primary

Grade 1

Grade 2

Grade 3

Grade 4

Grade 5

Grade 6

Grade 7

Grade 8

Grade 9

Grade 10

Grade 11

Grade 12

Other Total

Visual and Hearing

Total 3 5 21 65 58 100 67 86 116 160 107 73 10 2 873

Female 0 1 17 31 34 53 42 48 59 78 68 38 6 1 476

Male 3 4 4 34 24 47 25 38 57 82 39 35 4 1 397

Partially Blind

Total 36 139 191 259 359 529 575 477 928 786 556 578 371 49 5 833

Female 14 63 78 114 172 277 306 252 538 470 318 370 218 23 3 213

Male 22 76 113 145 187 252 269 225 390 316 238 208 153 26 2 620

Totally Blind

Total 3 15 7 8 26 25 14 15 35 39 24 3 3 0 217

Female 0 4 4 4 9 16 6 9 22 25 16 1 0 0 116

Male 3 11 3 4 17 9 8 6 13 14 8 2 3 0 101

Hard of Hearing

Total 48 306 344 515 567 707 556 450 767 527 316 227 153 28 5 511

Female 23 140 165 261 295 367 310 258 439 315 173 143 91 17 2 997

Male 25 166 179 254 272 340 246 192 328 212 143 84 62 11 2 514

Deaf

Total 44 49 48 54 53 47 54 41 50 41 50 3 8 102 644

Female 21 20 25 30 21 22 25 23 29 16 22 3 4 40 301

Male 23 29 23 24 32 25 29 18 21 25 28 0 4 62 343

Physical

Total 51 195 145 109 119 131 105 86 139 93 46 31 31 42 1 323

Female 21 90 48 43 52 58 47 36 69 40 22 17 13 25 581

Male 30 105 97 66 67 73 58 50 70 53 24 14 18 17 742

Epileptic

Total 22 65 73 82 89 134 114 92 123 114 51 33 22 40 1 054

Female 5 29 30 39 52 83 78 68 89 81 45 24 14 15 652

Male 17 36 43 43 37 51 36 24 34 33 6 9 8 25 402

Behavioural

Total 198 692 525 490 385 485 391 280 658 412 274 103 130 115 5 138

Female 77 228 154 164 118 124 123 66 247 147 115 38 50 39 1 690

Male 121 464 371 326 267 361 268 214 411 265 159 65 80 76 3 448

Mild Intellectual

Total 53 309 223 218 294 399 236 199 470 237 119 38 35 218 3 048

Female 30 111 72 75 113 151 89 86 220 120 74 19 17 96 1 273

Male 23 198 151 143 181 248 147 113 250 117 45 19 18 122 1 775

Severe Intellectual

Total 31 97 55 103 83 135 48 51 92 60 18 1 9 103 886

Female 9 42 18 45 33 55 18 25 46 30 8 1 3 42 375

Male 22 55 37 58 50 80 30 26 46 30 10 0 6 61 511

Learning

Total 102 688 601 594 480 562 436 290 392 359 127 126 67 349 5 173

Female 39 282 235 220 164 219 196 156 186 171 59 69 36 166 2 198

Male 63 406 366 374 316 343 240 134 206 188 68 57 31 183 2 975

Autistic

Total 8 34 34 22 25 11 25 7 10 12 5 9 17 219

Female 3 12 10 8 7 2 11 0 5 6 1 1 7 73

Male 5 22 24 14 18 9 14 7 5 6 4 8 10 146

Other

Total 31 121 86 76 51 77 61 47 124 73 22 55 26 99 949

Female 13 37 31 18 20 27 24 20 80 37 8 37 14 47 413

Male 18 84 55 58 31 50 37 27 44 36 14 18 12 52 536

Total 630 2 715 2 353 2 595 2 589 3 342 2 682 2 121 3 904 2 913 1 715 1 280 865 1 164 30 868

Note: The data in the tables were compiled by teachers based on their observations at times, and are not necessarily validated by medical professionals. It is therefore possible that teachers’ interpretations are not always valid.

Source: Own calculations from Annual Education Census 2015 (preliminary data).

Chapter 8: Summary and Recommendations 73

8 SUMMARY AND RECOMMENDATIONS

73


The foregoing analysis has shown a number of important aspects of Namibia’s school education sector, with a particular focus on a review of the expenditure of this sector. This chapter provides

a brief summary of issues that were found in the preceding chapters of this report, before turning to some important policy recommendations.

8.1 SUMMARY OF ISSUES

8.1.1 Fiscal management and expenditure management

Generally, Namibian fiscal management has been disciplined and the fiscal situation is relatively healthy.

However, the fiscal situation has tightened due to lower economic growth, a difficult international economic situation, and lower income from the South African Customs Union. Prospects for growth of educational expenditure have thus deteriorated.

Within education, expenditure management has been relatively good, though budget overruns are relatively common. This is largely the result of personnel spending over-runs, while other items sometimes experience underspending, perhaps due to some capacity constraints, e.g. relating to the planning of capital expenditure.

Expenditure on teacher salaries dominates the budget and tends to crowd out other spending.

8.1.2 Post provisioning and teacher salaries

The post-provisioning system is relatively favourable and leads to quite low learner-teacher ratios in both primary and secondary education.

Salaries of qualified teachers are quite high for a middle-income country.

As a consequence of the low learner-teacher ratio, spending per learner is quite high (a little above levels in South Africa, a higher-income country).

In many cases, temporary teachers are appointed because of the shortage of qualified teachers. This applies especially in primary education, in remote regions and for specific subjects where there are too few qualified teachers.


The post-provisioning norms of 2001 still officially apply, though some regions appear to apply alternative norms. Deviation from the post-provisioning norms occurs in all regions. The patterns of such deviation seem to suggest that regions apply their own notions of equity when deviating from the norms. The main deviations seem to be the appointment of additional teachers for small schools and for schools that have too few teachers to provide the necessary subject specialisation at higher primary grades and in secondary school.

Fiscal pressure and the need to create more fiscal space for non-personnel (particularly for textbooks and other learning materials) require that the overly favourable learner-teacher ratios be reduced somewhat, i.e. that the number of posts relative to existing learner numbers be reduced a little.

It appears best to codify the ongoing deviations from the post-provisioning norms in a slightly revised set of norms, that would also allow some reduction in the total number of posts as referred to above and to meet the need for more non-personnel spending.

8.1.3 Fiscal incidence, spending equity and the need to target rural areas

Distribution of teachers and their cost per learner across regions, remoteness catego-ries and poverty deciles of the location of the schools shows no systematic bias against the poor.

Non-teacher spending is also relatively equitably divided across schools (though there are issues of regional differences, discussed elsewhere). It is thus warranted simply to assume equal spending per learner across schools, as is done in most international studies.

Analysis of fiscal incidence across deciles show systematically higher spending on children from richer deciles, not because of spending bias, but because patterns of enrolment and progression to secondary schools favour the rich, i.e. fiscal incidence is influenced by dropout and repetition.

This inequity in the system is pervasive and is unlikely to change without focused efforts to improve access and quality of schooling for the poor. It also spills over into inequities between language groups.

Reaching poor children in remote areas and providing them with quality education that can overcome their home background deficits is difficult.

Important policy choices would need to be made, e.g. between more schools or schools continuing to higher grades in some isolated rural areas, as against more funding for transport and hostels.

Providing schools in isolated areas is expensive and a large part of such expenses are front-loaded, in terms of school buildings and teacher accommodation (an issue discussed further elsewhere).

There is currently little indication that progression through the school system is improving. For instance, the number of learners in the highest grades has stagnated in the last five years. Progression needs to be improved. Placing greater focus on reaching deep into rural areas may be one aspect of such improvement. Improved


flows to higher grades in isolated rural areas would over time also reduce the unit cost of providing such education at higher grade levels in such areas.

Housing construction for teachers in remote areas needs priority to maintain and even improve the quality of education to learners in such locations.

8.1.4 Non-personnel spending

Schools complain about uncertainty and that they have little discretion in using UPE and USE resources, as well as about the timing of these payments, as the payments are poorly aligned to their spending needs.

Allocation of non-personnel spending to regions is not based on recent or consistent national data on enrolment, e.g. from the Fifteenth School Day (FSD) Survey and the Annual Education Census (AEC). Within regions, their own (revised) version of the FSD data is usually used. The discrepancy between the enrolment data used at national and at regional levels leads to inequities in spending per child across regions, and increases uncertainty about future allocation, though there appear to be fewer differences within regions.

Due to high personnel spending, non-personnel spending tends to be crowded out. The international literature shows that textbooks and learning materials at school level are usually underfunded relative to personnel, given the important contribution good texts can make to learning. Thus it is worth considering fixing the total amount allocated for textbooks as a percentage of personnel spending, to ensure that this percentage is maintained over time, especially as fiscal resources are becoming tighter.

Non-personnel subsidies for pre-primary children are much lower than for primary and secondary learners, and must be increased to ensure quality provision of pre-primary education.

Textbook availability and costs for small languages remain problematic. Dealing with this through unit subsidies to schools alone is inadequate: the MoEAC, in cooperation with the National Institute for Educational Development (NIED), should have a programme of support for the writing and production of textbooks in indigenous Namibian languages that are at a disadvantage compared to European languages regarding the availability, cost and quality of textbooks.

8.1.5 Data consistency and the use of data for management

Data from the Fifteenth School Day (FSD) Survey and the Annual Education Census (AEC) are not well used for planning purposes. Financial management makes poor use of these data sources, perhaps in part because such data are not made available to everyone and not soon enough.

A comparison of payroll data with the FSD Survey and AEC of 2014 shows worrying discrepancies that in some cases could point to the presence of “ghost teachers” on the payroll. This requires immediate attention, using the FSD and AEC to compare data with the current payroll at the level of teacher names, to be followed by inspection on the ground where required and remedial steps against such individuals and officials who may have assisted them.


8.2 SPECIFIC RECOMMENDATIONS

This section contains recommendations. In cases where the case for such recommendations has not yet been made in the preceding chapters, some motivation will also be provided. In other instances readers are referred to the preceding chapters for motivation.

8.2.1 Managing the salary bill

Given the budgetary pressures that the MoEAC is likely to face in the next few years, some spending cutbacks may be inevitable. Yet it is likely that the demand for education will continue to rise. An analysis of the demand for education in the five countries of the South African Customs Union was recently undertaken. Table 40 contains some historical data and enrolment projections. The average projected enrolment growth rate of 2.1% for Namibia in the period 2015-2030 is somewhat faster than the expected growth of 1.6% of the school-age population, implying some progress with retention in the school system to higher grades. Note that Namibia has the highest projected growth rate of both the population and enrolment of the five countries covered.

Table 40: School enrolment and projections, 1950 to 2050 (in thousands)

Botswana Lesotho NamibiaSouth Africa

SwazilandSACU Total

School-age population (,000)

1950 123 203 127 3 648 78 4 179

2000 525 578 561 12 051 368 14 084

2015 540 591 663 12 585 362 14 742

2030 633 663 844 12 454 407 15 001

2050 597 648 911 11 411 396 13 963

Growth rate 2015-2030 per annum 1.1% 0.8% 1.6% -0.1% 0.8% 0.1%

Growth rate 2015-2050 per annum 0.3% 0.3% 0.9% -0.3% 0.3% -0.2%

School enrolment (assuming 12% repetition rate) (,000)

1950 27 75 42 1 990 24 2 159

2000 486 425 475 11 720 317 13 423

2015 532 492 602 12 574 330 14 530

2030 643 614 818 12 761 395 15 231

2050 623 643 926 11 941 402 14 535

Growth rate 2015-2030 per annum 1.3% 1.5% 2.1% 0.1% 1.2% 0.3%

Growth rate 2015-2050 per annum 0.4% 0.8% 1.2% -0.1% 0.6% 0.0%

Source: Van der Berg & Knoesen, 2015: Table 5.

How can the MoEAC deal with rising enrolment numbers while operating in a situation of fiscal stress? Given the facts that personnel spending completely dominates education spending, that capital spending is getting inadequate attention, and that there is little scope for reducing spending on UPE and USE and on textbooks, only two options present themselves. The first of these is to allow teacher salary levels to grow less than inflation, thus reducing real spending on teachers. This may occur, but will only occur if the Government as a whole cuts back on salary rises to below inflation; it is probably, realistically speaking, outside the control of the Ministry.

Thus a second option should be considered, namely reducing the number of teaching positions. Since schools in Namibia generally have a very favourable staffing situation, this may well be a feasible option. However, this cannot be done easily either. The first necessary step would be to ensure that no new


qualified teachers are appointed without a thorough reconsideration of the post establishment of the school. This is a policy initiative that the MoEAC has already started investigating, working in conjunction with regions.

Recommendation 1: Determine the appropriate post establishment for each school by applying the 2001 post-provisioning norms. This should be done at a central level with inputs from the regions, to ensure that the norms are uniformly applied across regions. These norms are quite favourable in the context of a developing country, but it may be necessary to allow some leniency for small schools and to ensure that schools obtain the necessary subject specialists. Then ensure that no qualified teacher is appointed to any school that goes beyond the establishment. Unqualified teachers, holding temporary positions, should then not be reappointed to schools where they exceed the establishment.

Recommendation 2: If further staff reductions cannot be avoided, the 2001 post-provisioning norms would have to be adjusted and made a little less favourable, i.e. the learner-teacher ratios should rise somewhat. As current ratios are quite favourable in an international perspective and also compared to most countries in the Southern African region, this is a viable option. With this adjustment in the norms it would be good to also incorporate the equity issues that the regions have de facto included in their post provisioning, i.e. a slightly more favourable dispensation for small schools and also some provision of personnel to allow schools to offer all subjects that they need to offer. Once these new post-provisioning norms have been decided on, the same procedure as in the previous recommendation should then be implemented in order to move actual post provisioning closer to what Namibia can afford.

8.2.2 Data consistency and ensuring there are no ‘ghost teachers’

The following recommendations are made regarding school data (see Section 4.4 above):

Recommendation 3: Improve data consistency as set out in Section 4.4 above by ensuring all data collection processes within the EMIS follow the EMIS life cycle; simplifying the FSD form; developing official forms for hostels and the school feeding programme; and developing an EMIS policy that sets out data collection processes and data dissemination procedures.

Recommendation 4: Verify and improve data collection, eliminate errors, expedite the availability of such data and use the FSD and AEC data consistently and widely in the school system at all levels, particularly for allocation of funds.

Recommendation 5: Ensure consistency between payroll data, the Fifteenth School Day (FSD) Survey and the Annual Education Census (AEC). Match payroll data closely with the AEC to ensure that the payroll data do not contain anomalies. Then appoint a task team to investigate any sources of discrepancies to eliminate any “ghost teachers” there may be in the system (see Section 5.4). (Investigating this issue of managing payroll data is already underway in the MoEAC at the time of writing.)

8.2.3 Private schools

Two major forms of subsidies to private schools currently co-exist in Namibia. The form that was initially less common, where teachers in schools serving the low- and middle-income segments of the population are paid full salaries by the State, is now rapidly expanding in number. The second, and hitherto more common form, is a category of schools catering for relatively high-income groups and offering relatively high-fee education. Such schools receive subsidies based on operational costs in public schools. Following is a discussion of these two forms.


Teacher salary payment for low-fee private schools

In 2014 there were 29 low-fee private schools whose teachers received salaries through the public payroll, with the same remuneration levels as for public school teachers. Altogether 11 883 children attended these schools, and the State paid annual salaries totalling N$7.6 million plus allowances of teachers in these schools, so almost N$6 400 per child. This is far more per child than the state subsidy to the second category of private schools discussed below, i.e. those that receive only a subsidy based on operational costs (regional transfers to schools). These schools were in many cases relatively poor schools: only nine were located in the richest two deciles.

These subsidies are warranted as such schools offer education largely to children from low- or middle-income groups. The fact that such schools do not receive other operational costs (including UPE or USE from the State) means that it costs the State somewhat less to educate these children than is the case for children in public schools. Presumably these costs are made up for by parental contributions or donations. Moreover, such education is to be encouraged in situations where the State cannot meet particular needs, e.g. needs of specific religious communities, education in specific languages, or education serving very remote areas. However, given the extent of the subsidisation of such schools, it is imperative to exercise proper control over the quality of education in such schools through the regional offices and inspectors.

Recommendation 6: Teacher salary payment subsidies to low-fee private schools should continue in their current form, subject to such schools being registered and closely monitored to ensure that they provide good-quality education. The registration process should ensure that such schools offer something to parents and children that public schools do not offer, rather than that they simply provide employment to unemployed teachers. It is also imperative that such teachers meet the same criteria as teachers in public schools. Also, to avoid the proliferation of such schools, it may be necessary at a national level to cap the number of new schools that will be allowed to register in any particular region in a year. In addition, teachers in such schools should not be placed on the public payroll or paid by the MoEAC until six months after the school has been registered at a national level.

Operational-cost subsidies to high-fee private schools

In the 2014 AEC, 88 schools classified as private schools received no salaries support but only operational-cost subsidies from the State. The formula for such subsidies has the effect that a school receives the average operational cost per learner for a region for 90% of learners. The school could also receive the same subsidy for the other 10% of learners, but only if they are from disadvantaged backgrounds and receive full scholarships. Thus, if a private school has no learners on such scholarships, they would nevertheless receive 90% of the operational-cost subsidies that a public school in the same region would usually receive, and if they do have 10% or more of their learners on scholarships, they would receive the same operational-cost subsidy per learner that applies to public schools. There were 21 537 learners in these schools in 2014 and the total subsidy was around N$39 million, thus the average subsidy per learner amounted to N$1 816, this being far less than the subsidy per child for the category of private schools whose teachers are paid through the public payroll. However, instead of the 2 153 students who should have been receiving scholarships according to the rules for such private schools, the actual number was estimated to be only 326, which is 1.5% of the enrolment of these private schools.1 (Ministry of Education, 2014b). The Ministry has been quite critical of these public schools for not taking the scholarships seriously enough, and a greater penalty than the current one for offering enough scholarship

1 The report mentions that “Figures in some regions are not the actual but they are purely for illustrative purposes”, thus the calculations done here should also be read in that light.


positions has been suggested. Some officials were also sceptical about subsidising such schools at all, based on the argument that parents in such schools are rich enough to pay for the education of their children. Against that should be seen the fact that the N$39 million that the State pays to such schools is far less than the additional N$250 million that would have been required for paying teacher and non-teacher salaries if such children had had to be accommodated in public schools. Also, from the perspective of the public schools, the current subsidy formula implies that a private school would be compensated an additional N$1 816 for each scholarship that it provides, which is a very small portion of the actual costs to the schools of such scholarships.

An alternative way of looking at the subsidies paid to such schools is to consider the total cost of such subsidies per disadvantaged learner. If all these schools had met the scholarship requirement, the cost would have been N$18 160 per scholarship learner. In effect the current cost to the State is N$120 000 per scholarship learner, because there are so few such learners.

Recommendation 7: It is recommended that the future subsidy should be 20 times the per capita operational cost (national average) for each disadvantaged learner on a scholarship, calculated for up to 10% of the actual enrolment in such private schools, and that non-scholarship learners not be subsidised. This would mean that the subsidy per disadvantaged learner would be approximately N$36 320, which would in some cases make up for the full cost of providing a scholarship. Schools where the scholarship may be even more costly may then still not find it financially attractive to offer such scholarships, thus discussions with such schools may be required to convince them that it is in their long-term interest to cross-subsidise the difference from their school fees.

Thus the formula would read S = 20 x D, where D is the number of disadvantaged learners on scholarships, but D should not exceed 10% of the enrolment in the private school concerned.

The current cost of such a subsidy would thus be only N$11.8 million. Based on current figures, if schools were to take in the 10% disadvantaged children on scholarships, this would rise to N$78.2 million – double its current value. Though this would raise overall costs of such subsidies, it is likely to be implemented slowly, yet it should have the desired effect of ensuring that more Namibians from disadvantaged backgrounds benefit from the quality of education that such private schools can offer. It should also be noted that subsidies to private schools of this type have been cut back considerably in the provisional allocations to regions for 2017/18.

Such a change could initially be quite destabilising for schools that currently receive large subsidies. Moreover, it would be fair to give them an opportunity to adjust to the new formula. Thus it is suggested that in the first year of implementation, the subsidy to such private schools should be two-thirds of the old subsidy plus one-third of the new subsidy, in the second year one-third of the old subsidy plus two-thirds of the new subsidy, and only in the third year would the new subsidy fully apply.

8.2.4 School maintenance

School principals who were interviewed were unhappy with both the extent of the funds available for undertaking maintenance and their discretion in doing so. This remains a difficult area, because of the unpredictability of maintenance needs as well as the difficulty of ensuring that funds allocated for maintenance are well spent. It does not appear as if much improvement can be expected in this regard, irrespective of whatever procedures are put in place to deal with this, and while funds are so scarce there is a need for proper accounting on how such funds are spent. Maintenance costs should also be seen along with capital spending to add to or renovate physical facilities.


Recommendation 8: It is recommended that the allocation of the funds for maintenance use the current per capita formula, whereby fund allocations are largely based on enrolments. The level of funding should be similar across all schools nationally, though it would be sensible to also allocate a certain share (perhaps 10%) to regions for assisting schools that may be experiencing particularly great needs with respect to maintenance. However, care should be taken that schools not be allowed to benefit from spending too little on maintenance themselves.

8.2.5 Textbooks

School principals appeared relatively satisfied with the funds allocated to schools for purchasing or topping up textbooks. It appears that the system whereby the same textbooks are used for a number of years by successive cohorts of children works quite well, and that topping up to make provision for books that are damaged or for rises in enrolment can be well funded in this manner. Related aspects did disturb principals, though, these being the uncertainty about the amounts of funds they will receive, and the timing of the arrival of those funds. These are issues that can be dealt with by greater clarity on the amounts that schools will receive, by good planning and by discussions about the timing of fund transfers.

Recommendation 9: The UPE, USE and all other funds allocated to schools on the basis of enrolment should be centrally announced, and these funds should not differ between regions. This would enable schools to plan better, while leaving less leeway for regions that overspend on their personnel budgets to make up for that by reducing allocations to schools.

Recommendation 10: To make up for the small percentage of funds currently allocated for school textbooks compared to personnel, this amount should grow by 8% per year above the inflation rate for the next five years, so that, in real terms, there is a considerable increase in textbook spending per child.

Pre-primary learners’ need for books, stationery and other learning materials is as great if not greater than that of older children, and the emphasis placed on early learning is precisely to introduce these children to a print-rich environment where their development could be stimulated. The current N$284 per learner allocated in pre-primary grades as against N$879 in primary grades is not in line with the emphasis on early learning that forms part of the Ministry’s vision (see Chapter 6).

Recommendation 11: The amounts allocated per pre-primary learner should be the same as for primary learners, and schools should report on how they allocate these funds, to ensure that they do not use the funds to cross-subsidise other grades.

Recommendation 12: Because of the high costs of producing textbooks in small indigenous languages, schools that offer education in these languages will always be at a disadvantage. It would not be sensible to allocate additional amounts to such schools. It is rather recommended that the MoEAC negotiate with publishers of such books and compensate them adequately to reduce the cost of buying such books for schools and parents. In this way the MoEAC would also carry out its function as promoter of the culture of Namibia’s indigenous languages.

8.2.6 Cost of hostels and transport versus cost of providing education to higher grades

A pressing issue affecting resource allocation in the school education system is how much provision to make for learner hostel accommodation. This is particularly relevant in Namibia, where the school-going population is spread over vast distances, and many rural learners experience


difficulties attending school as the majority of schools are situated in urban areas. The relative benefit of making hostel facilities available then becomes a pertinent consideration. This section provides a brief overview of factors that would influence the decision on whether to offer hostel accommodation, as opposed to building more schools or expanding existing schools (to offer more grades) in closer proximity of learners.

From a budgetary perspective, the costs associated with hostel accommodation include additional personnel that would otherwise not be required, such as hostel management and support staff, as well as non-personnel expenditures such as maintenance expenses and transport. These costs can escalate over time if facilities are poorly managed or not maintained regularly, for example dilapidated hostels require increased maintenance expenses, and in some instances capital renewal projects are needed. Transport of learners to and from hostels is another cost that would not necessarily exist if schools are in proximity of learners. All these costs must be compared to the cost of building and financially sustaining additional schools, or expanding the capacity of existing ones. The relative benefits of having a school nearby (especially for younger learners) include ensuring the learners’ safety and security as well as their liberty to experience their home environment. As indicated earlier in the report, Namibia has several schools offering only the lower grades, which compels learners to travel long distances to schools to further their education. Learners can be in school hostels where available, and can apply for accommodation if they reside 5 km outside the radius of the hostel. However, this policy is not strictly enforced – see the Auditor-General report on the administration of hostels (Republic of Namibia, 2014) for more details as to why this policy is not strictly enforced. Other problems include inefficient management of facilities, overcrowded hostels and the degradation of facilities because of inadequate maintenance.

Spending on school hostels as a percentage of total education expenditure has declined in recent years. According to the Auditor-General’s report of 2009/10, the cost to the State of providing hostel accommodation was almost N$330 million or 6% of education spending. In the next financial year this figure fell dramatically (see Figure 40), because the goods and other services spending for hostels were reclassified and no longer fell under hostels. However, this is simply a bookkeeping change and does not affect the underlying cost of providing hostel accommodation. Statistics in the Estimates of Revenue, Income and Expenditure reveal that in 2013/14 the majority of the total budget was allocated to personnel expenditure, leaving little room for maintenance or capital expenditure. Given current fiscal constraints, it is questionable whether increased funds will be available to address the pressing concerns highlighted above.

Figure 40: Expenditure on school hostels (% of total education expenditure), 2007/08-2014/15

Sources: Office of the Auditor General (various years).


If the 6% of the total education budget devoted to hostels in 2009/10 is applied to 2014/15, it amounts to almost N$800 million that the hostels probably cost the State. This is a considerable sum but may even be an underestimate, as many hostel costs are hidden costs in that teachers and principals often have to deal with hostel issues. To that must be added the costs to parents of their children being in hostels. In addition, there are large social and psychological costs attached to staying in hostels that affect the poorest children and families in remote areas the most, and which put them at a disadvantage in their education compared to students who can stay at home. This equity issue requires attention. The proliferation of informal hostels in some areas is also a response to the limited capacity of the State to provide enough hostel accommodation. Community hostels are subsidised directly from regional budgets; in 2017/18 the provisional amount set aside for this was N$12 per learner or around N$60 million (budgetary figures on this item are somewhat contradictory), while private hostels and private schools were allocated N$30 million. The mushrooming of community hostels implies that the supply of education in remote areas does not match the demand, thereby forcing many parents and children either to discontinue children’s education early, or to accept the high social and economic costs that entering hostels hold.

This is particularly problematic in the primary grades. One-fifth of the schools that offer education up to Grade 4 do not offer Grade 7, implying that children from these schools who wish to continue their primary education either have to travel longer distances to schools or become boarders.

Recommendation 13: Where possible all schools offering education up to Grade 4 should be extended to offer such education up to Grade 7. As Grade 4 will now be in the same school phase as Grade 7 after the introduction of the new curriculum, having Grade 4 and Grade 7 in the same school would also ease the process of introducing subject specialisation. Extending the highest grade that schools offer should start in those schools that go up to only Grade 4 or less, and where the number of children in the highest grade is large enough to make it likely that the subsequent grade (usually Grade 5) would have enough children to warrant a teacher.

Such a policy step would have implications for the budget, though not so much for additional teachers, as this would largely imply a shifting of teacher positions across schools. The main fiscal cost, though, lies with the additional classrooms that would have to be provided and furnished. These costs per annum would be relatively small, as it is likely that such a policy can only be implemented over a period of time. On the other hand, some costs currently borne by households, including travel costs and hostel costs, would be reduced, while it would also reduce the costs to the State of providing hostels.


8.3 IN CONCLUSION

This report was compiled by a team of researchers from ReSEP (Research on Socio-Economic Policy) in the Department of Economics at the University of Stellenbosch for the Ministry of Education, Arts and Culture and with the financial support of UNICEF Namibia. The team was given access to a wide array of data by the Ministry and could draw on public finance data and reports of the Auditor General. This allowed the team to provide a far more detailed picture of public expenditure on education in Namibia than has been possible in the past. For this the authors wish to thank the officials of the Ministry in Windhoek, and the regional officials and principals for sharing their insights and data.

This review was undertaken at a time when the fiscal situation in Namibia was tightening, after a period of rapid growth made possible by strong economic growth. The fiscal environment within which the education sector has to operate has thus become far more stringent.

Chapter 9: Bibliography 85

9 BIBLIOGRAPHY

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