Abstract
Household consumption expenditure data is crucial for calculating important welfare measures such as poverty headcount rate. However, collecting such data is difficult and cumbersome. As an alternative, we experiment with three methods – consumption correlates model, poverty probability model, and wealth index principal components analysis (PCA) – to predict consumption expenditure and poverty using non-consumption indicators. The purpose is to use these alternatives for rapid monitoring and appraisal of social welfare as an early warning system. We test each method’s performance and find that the consumption correlates model is the best method to predict poverty quickly and relatively accurately. We find that education level, asset ownership, and consumption pattern are the best predictors of expenditure and poverty.
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Abeyasekera, S. and P. Ward: 2002, Models for Predicting Expenditure per Adult Equivalent, Tanzanian Ministry of Health, UK DFID, University of Newcastle upon Tyne, and Districts of Hai, Ilala, Morogoro, Rufiji, Temeke, Adult Morbidity and Mortality Project, mimeo
Asselin, L. M.: 2002, Composite Indicator or Multidimensional Poverty, CECI Canada, mimeo
Bibi, S.: 2004, ‘Comparing multidimensional poverty between Egypt and Tunisia’, Paper presented at conference of The Center for the Study of African Economies, University of Oxford, 21–22 March 2004
Costa, M.: 2002, ‘A multidimensional method to the measurement of poverty’, IRISS Working Paper Series No. 2002–05, CEPS/INSTEAD, Luxembourg
Costa, M.: 2003, ‘A comparison between unidimensional and multidimensional methods to the measurement of poverty’, IRISS Working Paper Series No. 2003–02, CEPS/INSTEAD, Luxembourg
Duclos, J. Y., D. Sahn and S. D. Younger: 2001, Robust Multidimensional Poverty Comparisons, Universite Laval, Canada, mimeo
Filmer D. and Pritchett L. (2001). Estimating wealth effects without expenditure data–Or tears: an application to educational enrollments in states of India. Demography 38(1): 115–132
Geda, A., N. Jong, G. Mwabu and M. S. Kimenyi: 2001, Determinants of Poverty in Kenya: A Household Level Analysis. Institute of Social Studies and Kenya Institute for Public Policy Research and Analysis, mimeo
Pradhan M., Suryahadi A., Sumarto S. and Pritchett L. (2001). Eating like which “Joneses”? An iterative solution to the choice of poverty line reference group. The Review of Income and Wealth 47(4): 473–487
Pritchett, L., A. Suryahadi and S. Sumarto: 2000, ‘Quantifying vulnerability to poverty: a proposed measure, with application to Indonesia’, SMERU Working Paper, May, SMERU Research Institute, Jakarta
Reyes, C., K. Ilarde, L. Valencia and J. Bancolita.: 2004, ‘Utilizing CBMS in monitoring and targeting the poor: The Case of Barangay Kemdeng, San Vicente, Palawan,' Paper presented at PEP Research Network Meeting, Poverty and Economic Policy Network, 16–20 June 2004
Setel, P., S. Abeyasekera, P. Ward, Y. Hemed, D. Whitting, R. Mswia, M. Antoninis and H. Kitange: 2003, ‘Development, validation, and performance of a rapid consumption expenditure proxy for measuring income poverty in Tanzania: Experience from AMMP demographic surveillance sites’, Paper prepared for the Asset Index Seminar, 26–28 March 2003, DFID’s Health Systems Resource Centre and the University of Southampton
Sumarto, S., D. Suryadarma, W. Widyanti and A. Suryahadi.: 2004, ‘Local Monitoring System During the Implementation of Indonesia's Social Safety Net Programs with Special Reference to the BKKBN System,' Paper presented at Poverty and Economic Policy (PEP) Research Network Meeting, Poverty and Economic Policy Network, 16–20 June 2004
Suryahadi A. and Sumarto S. (2003). Poverty and vulnerability in Indonesia before and after the economic crisis. Asian Economic Journal 17(1): 45–64
Tsui K. Y. (2002). Multidimensional poverty indices. Social Choice and Welfare 19(1): 69–93
Ward, P., T. Owens and G. Kahyrara: 2002, Developing Proxy Predictors for Household Expenditure and Income Poverty, Oxford Policy Management, mimeo
Zeller, M.: 2004, ‘Review of poverty assessment tools’, Accelerated Microenterprise Advancement Project Report, United States Agency for International Development, Washington, DC
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Sumarto, S., Suryadarma, D. & Suryahadi, A. Predicting Consumption Poverty using Non-Consumption Indicators: Experiments using Indonesian Data. Soc Indic Res 81, 543–578 (2007). https://doi.org/10.1007/s11205-006-0023-x
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DOI: https://doi.org/10.1007/s11205-006-0023-x