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Matching Household Surveys with DHS Data to Create Nationally Representative Time Series of Poverty: An Application to Bolivia

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  • Melanie Grosse

    (University of Göttingen)

  • Stephan Klasen

    (University of Göttingen)

  • Julius Spatz

    (University of Göttingen)

Abstract

In many developing countries, there does not exist a time series of nationally repre- sentative household budget or income surveys, while there often are urban household surveys as well as nationally representative Demographic and Health Surveys (DHS) which lack information on incomes. This makes an analysis of trends and determinants of poverty and inequality over a longer time period impossible. This is also the situation in Bolivia where there exist urban household surveys and nationally representative DHS since 1989, while nationally representative household income surveys only exist since 1997. In this paper, we adjust a technique developed for poverty mapping exercises to link urban household income surveys with DHS data to generate a nationally representative time series of household income data from 1989 to 1999. Our technique performs well on validation tests, is superior to proxying welfare with asset ownership in the DHS, and is able to generate new information on poverty and inequality in Bolivia.

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Bibliographic Info

Paper provided by Courant Research Centre PEG in its series Courant Research Centre: Poverty, Equity and Growth - Discussion Papers with number 21.

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Date of creation: 22 Dec 2009
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Handle: RePEc:got:gotcrc:021

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Related research

Keywords: Microsimulation; survey matching; poverty; inequality; pro-poor growth; poverty profile; growth incidence curve; Bolivia;

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References

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  1. Angus Deaton & Salman Zaidi, 2002. "Guidelines for Constructing Consumption Aggregates for Welfare Analysis," World Bank Publications, The World Bank, number 14101, August.
  2. David Stifel & Luc Christiaensen, 2007. "Tracking Poverty Over Time in the Absence of Comparable Consumption Data," World Bank Economic Review, World Bank Group, World Bank Group, vol. 21(2), pages 317-341, June.
  3. Hentschel, Jesko, et al, 2000. "Combining Census and Survey Data to Trace the Spatial Dimensions of Poverty: A Case Study of Ecuador," World Bank Economic Review, World Bank Group, World Bank Group, vol. 14(1), pages 147-65, January.
  4. Sahn, David E. & Stifel, David C., 2000. "Poverty Comparisons Over Time and Across Countries in Africa," World Development, Elsevier, Elsevier, vol. 28(12), pages 2123-2155, December.
  5. de la Grandville,Olivier, 2009. "Economic Growth," Cambridge Books, Cambridge University Press, Cambridge University Press, number 9780521898010.
  6. Adriana Cardozo & Melanie Grosse, 2009. "Pro-Poor Growth Using Non-Income Indicators: An Empirical Illustration for Colombia," Ibero America Institute for Econ. Research (IAI) Discussion Papers, Ibero-America Institute for Economic Research 192, Ibero-America Institute for Economic Research.
  7. Ravallion, Martin & Shaohua Chen, 2001. "Measuring pro-poor growth," Policy Research Working Paper Series 2666, The World Bank.
  8. Melanie Grosse & Stephan Klasen & Julius Spatz, 2005. "Creating National Poverty Profiles and Growth Incidence Curves with Incomplete Income or Consumption Expenditure Data: An Application to Bolivia," Ibero America Institute for Econ. Research (IAI) Discussion Papers, Ibero-America Institute for Economic Research 129, Ibero-America Institute for Economic Research.
  9. Datt, Gaurav & Ravallion, Martin, 1992. "Growth and redistribution components of changes in poverty measures : A decomposition with applications to Brazil and India in the 1980s," Journal of Development Economics, Elsevier, Elsevier, vol. 38(2), pages 275-295, April.
  10. David E. Sahn & David Stifel, 2003. "Exploring Alternative Measures of Welfare in the Absence of Expenditure Data," Review of Income and Wealth, International Association for Research in Income and Wealth, International Association for Research in Income and Wealth, vol. 49(4), pages 463-489, December.
  11. Stanislav Kolenikov & Gustavo Angeles, 2009. "Socioeconomic Status Measurement With Discrete Proxy Variables: Is Principal Component Analysis A Reliable Answer?," Review of Income and Wealth, International Association for Research in Income and Wealth, International Association for Research in Income and Wealth, vol. 55(1), pages 128-165, 03.
  12. Klasen, Stephan, 2007. "Determinants of pro-poor growth:," 2020 vision briefs, International Food Policy Research Institute (IFPRI) BB09 Special Edition, International Food Policy Research Institute (IFPRI).
  13. Chris Elbers & Jean O. Lanjouw & Peter Lanjouw, 2003. "Micro--Level Estimation of Poverty and Inequality," Econometrica, Econometric Society, Econometric Society, vol. 71(1), pages 355-364, January.
  14. de la Grandville,Olivier, 2009. "Economic Growth," Cambridge Books, Cambridge University Press, Cambridge University Press, number 9780521725200.
  15. Filmer, Deon & Pritchett, Lant, 1998. "Estimating wealth effects without expenditure data - or tears : with an application to educational enrollments in states of India," Policy Research Working Paper Series 1994, The World Bank.
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Cited by:
  1. Adriana Cardozo & Melanie Grosse, 2009. "Pro-Poor Growth Using Non-Income Indicators: An Empirical Illustration for Colombia," Courant Research Centre: Poverty, Equity and Growth - Discussion Papers, Courant Research Centre PEG 9, Courant Research Centre PEG.

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