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Estimating poverty transitions using repeated cross-sections: a three-country validation exercise

Author

Listed:
  • Guillermo Cruces

    ()

  • Peter Lanjouw

    ()

  • Leonardo Lucchetti

    ()

  • Elizaveta Perova

    ()

  • Renos Vakis

    ()

  • Mariana Viollaz

    ()

Abstract

This paper validates a recently proposed method to estimate intra-generational poverty transitions through repeated cross-sectional surveys. The technique allows the creation of a “synthetic panel” – done by predicting future or past household income or consumption using a set of simple modeling and error structure assumptions – and thus permits the estimation of lower and upper bounds of the joint distribution of poverty and non-poverty transitions. We validate the approach in three different settings where good panel data exist (Chile, Nicaragua, and Peru). In doing so, we also carry out a number of refinements to the validation procedure and expand the set of tests undertaken. The results are broadly encouraging in estimating the joint probabilities of poverty and non-poverty transitions between two periods in all three contexts. The approach is also robust to a broad set of additional “stress” and sensitivity tests, especially in cases where richer model specifications can be estimated. Finally, we test whether the scope of synthetic panels can be expanded in three new directions, namely comparing between income and consumption welfare measures; the robustness to longer intervals (the approach does especially well in predicting long-term poverty transition patterns); and the robustness to two transition lines instead of one. Overall, the results lend support to the application of this approach to settings where panel data are absent. Copyright Springer Science+Business Media New York 2015

Suggested Citation

  • Guillermo Cruces & Peter Lanjouw & Leonardo Lucchetti & Elizaveta Perova & Renos Vakis & Mariana Viollaz, 2015. "Estimating poverty transitions using repeated cross-sections: a three-country validation exercise," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 13(2), pages 161-179, June.
  • Handle: RePEc:kap:jecinq:v:13:y:2015:i:2:p:161-179
    DOI: 10.1007/s10888-014-9284-9
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    Citations

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    Cited by:

    1. Marc F. Bellemare & Johanna Fajardo-Gonzalez & Seth R. Gitter, 2016. "Foods and Fads - The Welfare Impacts of Rising Quinoa Prices in Peru," Working Papers 2016-06, Towson University, Department of Economics, revised Mar 2016.
    2. Dang,Hai-Anh H., 2018. "To impute or not to impute ? a review of alternative poverty estimation methods in the context of unavailable consumption data," Policy Research Working Paper Series 8403, The World Bank.
    3. Dang,Hai-Anh H. & Lanjouw,Peter F. & Dang,Hai-Anh H. & Lanjouw,Peter F., 2015. "Poverty dynamics in India between 2004 and 2012 : insights from longitudinal analysis using synthetic panel data," Policy Research Working Paper Series 7270, The World Bank.
    4. Jolliffe,Dean Mitchell & Dang,Hai-Anh H. & Carletto,Calogero & Dang,Hai-Anh H. & Jolliffe,Dean Mitchell & Carletto,Calogero, 2017. "Data gaps, data incomparability, and data imputation : a review of poverty measurement methods for data-scarce environments," Policy Research Working Paper Series 8282, The World Bank.
    5. Dang,Hai-Anh H. & Lanjouw,Peter F. & Swinkels,Robertus A & Dang,Hai-Anh H. & Lanjouw,Peter F. & Swinkels,Robertus A, 2014. "Who remained in poverty, who moved up, and who fell down ? an investigation of poverty dynamics in Senegal in the late 2000s," Policy Research Working Paper Series 7141, The World Bank.
    6. Herault, Nicolas & Jenkins, Stephen P., 2018. "How Valid Are Synthetic Panel Estimates of Poverty Dynamics?," IZA Discussion Papers 11484, Institute for the Study of Labor (IZA).
    7. Dang,Hai-Anh H. & Ianchovichina,Elena & Dang,Hai-Anh H. & Ianchovichina,Elena, 2016. "Welfare dynamics with synthetic panels : the case of the Arab world in transition," Policy Research Working Paper Series 7595, The World Bank.

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