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Predicting Consumption Poverty Using Non-consumption Indicators : Experiments Using Indonesian Data

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  • Sudarno Sumarto

    (SMERU)

  • Daniel Suryadarma
  • Asep Suryahadi

Abstract

Although consumption expenditure data is crucial for assessing the level of peoples welfare and calculating important welfare measures such as the poverty headcount rate, collecting such data requires significant time and effort. In this study, we experiment with three approaches to predict consumption expenditure and poverty at household and aggregate level as simpler alternatives to using consumption expenditure. The idea is not to use these alternatives as a substitute for consumption expenditure data, rather to use it for the purposes of rapid monitoring and appraisal of welfare. The three approaches are i) consumption correlates model, ii) poverty probability model, and iii) the wealth index Principal Components Analysis (PCA). We test each approachs performance and found that the consumption correlates model is the best approach to predict poverty quickly and relatively accurately. We found that education level, asset ownership, and consumption pattern are the best predictors of expenditure and poverty.

Suggested Citation

  • Sudarno Sumarto & Daniel Suryadarma & Asep Suryahadi, 2006. "Predicting Consumption Poverty Using Non-consumption Indicators : Experiments Using Indonesian Data," Development Economics Working Papers 22542, East Asian Bureau of Economic Research.
  • Handle: RePEc:eab:develo:22542
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    7. Menno Pradhan & Asep Suryahadi & Sudarno Sumarto & Lant Pritchett, 2001. "Eating like which “Joneses?” an Iterative Solution to the Choice of a Poverty Line “Reference Group”," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 47(4), pages 473-487, December.
    8. COSTA Michele, 2002. "A multidimensional approach to the measurement of poverty," IRISS Working Paper Series 2002-05, IRISS at CEPS/INSTEAD.
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    10. Sami Bibi, 2004. "Comparing Multidimensional Poverty between Egypt and Tunisia," Cahiers de recherche 0416, CIRPEE.
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    6. Adama Bah & Samuel Bazzi & Sudarno Sumarto & Julia Tobias, 2019. "Finding the Poor vs. Measuring Their Poverty: Exploring the Drivers of Targeting Effectiveness in Indonesia," The World Bank Economic Review, World Bank Group, vol. 33(3), pages 573-597.
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    8. Adama Bah, 2015. "Finding the Best Indicators to Identify the Poor," CERDI Working papers halshs-00936201, HAL.
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    10. Andy Sumner, 2014. "Who are likely to be the future poor in Indonesia? Evidence on primary school non-completion from six rounds of the Demographic and Health Survey, 1991-2012," Working Papers in Economics and Development Studies (WoPEDS) 201406, Department of Economics, Padjadjaran University, revised May 2014.
    11. Andy Sumner & Peter Edward, 2013. "From Low Income, High Poverty to High-Income, No Poverty? An Optimistic View of the Long-Run Evolution of Poverty in Indonesia By International Poverty Lines, 1984–2030," Working Papers in Economics and Development Studies (WoPEDS) 201310, Department of Economics, Padjadjaran University, revised Jun 2013.
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    13. Dossou, Smith A.R. & Aoudji, Augustin K. N. & Vissoh, Pierre & Zannou, Afio, 2021. "Effect of Social Networks and Performance of Young Women Agribusiness Owners in a Developing Country: The Moderating Effect of Business Environment," 2021 Conference, August 17-31, 2021, Virtual 315361, International Association of Agricultural Economists.
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    15. Yanfeng Chen & Qingjie Xia & Xiaolin Wang, 2021. "Consumption and Income Poverty in Rural China: 1995–2018," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 29(4), pages 63-88, July.
    16. Gemini Mtei & Josephine Borghi & Kara Hanson, 2015. "Predicting Consumption Expenditure for the Analysis of Health Care Financing Equity in Low Income Countries: a Comparison of Approaches," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 124(2), pages 339-355, November.
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    More about this item

    Keywords

    consumption; poverty; predictor; data; Indonesia;
    All these keywords.

    JEL classification:

    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • I31 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General Welfare, Well-Being
    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth

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