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How Well Can Method Substitute for Data? Five Experiments in Poverty Analysis

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  • Ravallion, Martin

Abstract

No one doubts the good data are essential to sound policymaking. Alas, data are invariably faulty. Methodological solutions to data inadequacies have often been proposed and implemented, but they have been tested only rarely. Yet the methods that are used may well determine the direction of policy. For example, the particular survey method used--and the way nonsurvey data are interpreted--may be critical in assessing whether a country's strategy for reducing poverty is working. This article shows how counterfactual experiments can help test the reliability of various methods of dealing with common data problems. Well-designed methods--and they need not be very complicated--can help get around the problem, although it appears that substituting method for data is a long way from being perfect. Copyright 1996 by Oxford University Press.

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Bibliographic Info

Article provided by World Bank Group in its journal World Bank Research Observer.

Volume (Year): 11 (1996)
Issue (Month): 2 (August)
Pages: 199-221

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Handle: RePEc:oup:wbrobs:v:11:y:1996:i:2:p:199-221

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Cited by:
  1. Haughton, Jonathan & Khandker, Shahidur R., 2014. "The Surprising Effects of the Great Recession: Losers and Winners in Thailand in 2008–09," World Development, Elsevier, vol. 56(C), pages 77-92.
  2. World Bank, 2011. "Georgia - Poverty dynamics, 2003-2010," World Bank Other Operational Studies 2806, The World Bank.
  3. Tilman Bruck, . "Determinants of Rural Poverty in Post-War Mozambique: Evidence from a Household Survey and Implications for Government and Donor Policy," QEH Working Papers qehwps67, Queen Elizabeth House, University of Oxford.
  4. Carlo Azzarri & Gero Carletto & Benjamin Davis & Alberto Zezza, 2006. "Monitoring Poverty Without Consumption Data : An Application Using the Albania Panel Survey," Eastern European Economics, M.E. Sharpe, Inc., vol. 44(1), pages 59-82, February.
  5. Stefan Dercon & Pramila Krishnan, 1998. "Changes in poverty in rural Ethiopia 1989-1995: measurement, robustness tests and decomposition," CSAE Working Paper Series 1998-07, Centre for the Study of African Economies, University of Oxford.
  6. Bidani, Benu & Ravallion, Martin, 1995. "Decomposing social indicators using distributional data," Policy Research Working Paper Series 1487, The World Bank.
  7. Gaurav Datt & Martin Ravallion, 2002. "Is India's Economic Growth Leaving the Poor Behind?," Journal of Economic Perspectives, American Economic Association, vol. 16(3), pages 89-108, Summer.
  8. Sanjeev Gupta & Marijn Verhoeven & Erwin R. Tiongson, 2003. "Public spending on health care and the poor," Health Economics, John Wiley & Sons, Ltd., vol. 12(8), pages 685-696.
  9. Howard White, 2005. "Combining the Quantitative and Qualitative Approaches to Poverty Measurement and Analysis," Development and Comp Systems 0505003, EconWPA.
  10. Ahmed, Faizuddin & Dorji, Cheku & Takamatsu, Shinya & Yoshida, Nobuo, 2014. "Hybrid survey to improve the reliability of poverty statistics in a cost-effective manner," Policy Research Working Paper Series 6909, The World Bank.
  11. Newhouse, D. & Shivakumaran, S. & Takamatsu, S. & Yoshida, N., 2014. "How survey-to-survey imputation can fail," Policy Research Working Paper Series 6961, The World Bank.

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