Estimation of Local Poverty in the Philippines
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Estimation of Local Poverty in the Philippines November 2005 Republika ng Pilipinas PAMBANSANG LUPON SA UGNAYANG PANG-ESTADISTIKA (NATIONAL STATISTICAL COORDINATION BOARD) http://www.nscb.gov.ph in cooperation with The WORLD BANK Estimation of Local Poverty in the Philippines FOREWORD This report is part of the output of the Poverty Mapping Project implemented by the National Statistical Coordination Board (NSCB) with funding assistance from the World Bank ASEM Trust Fund. The methodology employed in the project combined the 2000 Family Income and Expenditure Survey (FIES), 2000 Labor Force Survey (LFS) and 2000 Census of Population and Housing (CPH) to estimate poverty incidence, poverty gap, and poverty severity for the provincial and municipal levels. We acknowledge with thanks the valuable assistance provided by the Project Consultants, Dr. Stephen Haslett and Dr. Geoffrey Jones of the Statistics Research and Consulting Centre, Massey University, New Zealand. Ms. Caridad Araujo, for the assistance in the preliminary preparations for the project; and Dr. Peter Lanjouw of the World Bank for the continued support. The Project Consultants prepared Chapters 1 to 8 of the report with Mr. Joseph M. Addawe, Rey Angelo Millendez, and Amando Patio, Jr. of the NSCB Poverty Team, assisting in the data preparation and modeling. Chapters 9 to 11 were prepared mainly by the NSCB Project Staff after conducting validation workshops in selected provinces of the country and the project’s national dissemination forum. It is hoped that the results of this project will help local communities and policy makers in the formulation of appropriate programs and improvements in the targeting schemes aimed at reducing poverty. CHORCHING GOH ROMULO A. VIROLA Task Manager Secretary General The World Bank National Statistical Coordination Board Estimation of Local Poverty in the Philippines SUMMARY We produce small-area estimates of poverty in the Philippines at provincial and municipal levels by combining survey data with auxiliary data derived from the 2000 census. Estimates of poverty are produced for both expenditure-based and income-based measures. We explore the use of a single predictive model for the whole country in comparison with the fitting of separate models within each region. A single overall model also containing urban / rural and regional effects is found to be adequate for predicting log average per capita household income and log per capita household expenditure, and the poverty measures derived from it at municipality level have on the whole acceptably small standard errors. Maps of all the small-area estimates are given in an Appendix. ii Estimation of Local Poverty in the Philippines Contents 1. Introduction .................................................................................................................... 1 2. Methodology .................................................................................................................. 5 3. Data Sources ................................................................................................................ 11 4. Implementation ............................................................................................................ 14 5. The ELL Methodology as Applied to Philippine Data ................................................. 20 6. Results for Income-based Measures ............................................................................ 23 7. Results for Expenditure-based Measures ..................................................................... 28 8. The Poorest Forty Provinces ........................................................................................ 31 9. Project Validation Exercises......................................................................................... 34 10. National Dissemination Forum .................................................................................. 37 11. Conclusions ................................................................................................................ 40 References ........................................................................................................................ 41 Appendices A. Auxiliary variables .......................................................................................... 43 B. Regression results ............................................................................................ 48 C. Summary of income based small-area estimates ............................................. 51 D. Summary of expenditure based small-area estimates ...................................... 55 iii Estimation of Local Poverty in the Philippines E. Poverty maps ................................................................................................... 58 F. Validation Form................................................................................................ 65 H. Municipal level small-area estimates............................................................... 69 iv Estimation of Local Poverty in the Philippines 1. Introduction 1.1 Background The Millennium Declaration adopted by the member countries of the United Nations in 2000 called for the halving of world poverty by the year 2015. The measurement of poverty by national statistical systems as well as by international agencies makes a key contribution to the Millennium Development Indicators being used to monitor progress towards these goals. Whilst the Philippines, with an official poverty incidence of 27 percent, is not one of the poorest countries, there exists within this ecologically and culturally diverse country a wide spatial disparity in poverty rates. Alleviation of the effects of poverty in these pockets of high incidence is an important and much-discussed government policy. The Kapit-Bisig Laban sa Kahirapan (KALAHI) Project aims to improve the poverty reduction efforts of the government, but the resources allocated to it need to be targeted towards the geographic and administrative areas where the need is greatest in order to have maximum effect. The National Statistical Coordination Board (NSCB) of the Philippines has for some years been producing estimates of the incidence of poverty at regional level. There has been however an increasing demand from policy makers and planners for a more disaggregated set of poverty statistics so that aid programs could be more effectively targeted to the areas in most need. In response to this the NSCB released in 2003 estimates of poverty at provincial level, based on the 2000 Family Income and Expenditure Survey (FIES)1. Because of the small sample sizes at this level, the standard errors of these estimates were sometimes quite large. The statistical methodology of small-area estimation allows the possibility of improving on the precision of these estimates, and even for allowing a finer level of disaggregation to municipality level, by combining the survey data with information from a recent census. 1.2 Geographic and administrative units The Philippines in 2000 was composed of 79 provinces and 4 districts in the National Capital Region (NCR), which were grouped into 16 regions including the NCR. Provinces are composed of municipalities, which are themselves divided into smaller units called barangays. Each barangay can be designated as urban or rural, with rural barangays corresponding to villages. Approximately 50 percent of the population live in rural barangays. Most municipalities contain both urban and rural barangays, but the NCR region is entirely urban. Table 1.1 shows the hierarchy of geographic and administrative units in the Philippines, and their approximate size in terms of number of households and number of barangay, based on the 2000 census. 1 The 2000 provincial poverty thresholds used as basis in coming up with the SAE estimates are the old/unrevised 2000 estimates since the revised 2000 provincial poverty thresholds were not yet released at the time when the SAE estimates were being generated. 1 Estimation of Local Poverty in the Philippines Table 1.1 The number and size of administrative units at different levels Region Province Municipality Barangay Household Census contains 16 83 1623 41926 15275046 Mean no. households 954690 184037 9412 364 1 Min no. households 263851 3489 24 1 Mean no. barangays 2620 505 26 Min no. barangays 1172 29 1 These figures play an important role in determining the level of disaggregation possible. The precision of a small-area estimate for a municipality depends on the number of barangay and the number of households. We can see from the table that municipalities contain on average about 9400 households and 26 barangays, but there are some small municipalities comprising, for example, a single barangay and only 24 households. This suggests that while municipal-level estimation may be achievable in general, there will be some municipalities where the estimates are very imprecise, with large standard errors. 1.3 Poverty maps The statistical technique of small-area estimation (Rao, 1999; Ghosh and Rao, 1994) provides a way of improving survey estimates at small levels of aggregation, by combining the survey data with information derived from other sources, typically a population census. A variant of this methodology has been developed by a research team at the World Bank specifically for the small-area estimation of poverty measures (Elbers, Lanjouw and Lanjouw, 2001, 2003). The ELL method has been implemented in several countries including Thailand (Healy,