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Finding the Best Indicators to Identify the Poor

  • Adama BAH

    ()

    (Centre d'Etudes et de Recherches sur le Développement International)

Proxy-means testing (PMT) is a method used to assess household or individual welfare level based on a set of observable indicators. The accuracy, and therefore usefulness of PMT relies on the selection of indicators that produce accurate predictions of household welfare. In this paper I propose a method to identify indicators that are robustly and strongly correlated with household welfare, measured by per capita consumption. From an initial set of 340 candidate variables drawn from the Indonesian Family Life Survey, I identify the variables that contribute most significantly to model predictive performance and that are therefore desirable to be included in a PMT formula. These variables span the categories of household private asset holdings, access to basic domestic energy, education level, sanitation and housing. A comparison of the predictive performance of PMT formulas including 10, 20 and 30 of the best predictors of welfare shows that leads to recommending formulas with 20 predictors. Such parsimonious models have similar predictive performance as the PMT formulas currently used in Indonesia, although these latter are based on models of 32 variables on average.

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Paper provided by CERDI in its series Working Papers with number 201324.

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Length: 40
Date of creation: 2013
Date of revision:
Handle: RePEc:cdi:wpaper:1509
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  1. David Coady & Margaret Grosh & John Hoddinott, 2004. "Targeting of Transfers in Developing Countries : Review of Lessons and Experience," World Bank Publications, The World Bank, number 14902.
  2. Pradhan, Menno, et al, 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 473-87, December.
  3. Sudarno Sumarto & Daniel Suryadarma & Asep Suryahadi, 2007. "Predicting Consumption Poverty using Non-Consumption Indicators: Experiments using Indonesian Data," Social Indicators Research, Springer, vol. 81(3), pages 543-578, May.
  4. Edward E. Leamer, 2010. "Tantalus on the Road to Asymptopia," Journal of Economic Perspectives, American Economic Association, vol. 24(2), pages 31-46, Spring.
  5. Temple, Jonathan, 2000. "Growth Regressions and What the Textbooks Don't Tell You," Bulletin of Economic Research, Wiley Blackwell, vol. 52(3), pages 181-205, July.
  6. Leamer, Edward E, 1985. "Sensitivity Analyses Would Help," American Economic Review, American Economic Association, vol. 75(3), pages 308-13, June.
  7. Levine, Ross & Renelt, David, 1991. "A sensitivity analysis of cross-country growth regressions," Policy Research Working Paper Series 609, The World Bank.
  8. Edward E. Leamer, 1982. "Let's Take the Con Out of Econometrics," UCLA Economics Working Papers 239, UCLA Department of Economics.
  9. Ahmed, Akhter U. & Bouis, Howarth E., 2002. "Weighing what's practical: proxy means tests for targeting food subsidies in Egypt," Food Policy, Elsevier, vol. 27(5-6), pages 519-540.
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