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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. Hai-Anh H. Dang & Peter F. Lanjouw, 2018. "Poverty Dynamics in India between 2004 and 2012: Insights from Longitudinal Analysis Using Synthetic Panel Data," Economic Development and Cultural Change, University of Chicago Press, vol. 67(1), pages 131-170.
    2. Hai‐Anh H. Dang & Elena Ianchovichina, 2018. "Welfare Dynamics With Synthetic Panels: The Case of the Arab World In Transition," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 64(s1), pages 114-144, October.
    3. Dang, Hai-Anh H. & Lanjouw, Peter F., 2020. "Welfare Dynamics in India over a Quarter Century: Poverty, Vulnerability, and Mobility during 1987-2012," GLO Discussion Paper Series 535, Global Labor Organization (GLO).
    4. Dang,Hai-Anh H. & Lokshin,Michael M. & Abanokova,Ksenia & Bussolo,Maurizio, 2018. "Inequality and Welfare Dynamics in the Russian Federation during 1994-2015," Policy Research Working Paper Series 8629, The World Bank.
    5. Peter Lanjouw & Hai-Anh Dang, 2018. "Welfare dynamics in India over a quarter-century: Poverty, vulnerability, and mobility, 1987–2012," WIDER Working Paper Series 175, World Institute for Development Economic Research (UNU-WIDER).
    6. 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.
    7. Nicolas Hérault & Stephen P. Jenkins, 2019. "How valid are synthetic panel estimates of poverty dynamics?," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 17(1), pages 51-76, March.
    8. 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.
    9. Dang, Hai-Anh H. & Raju, Dhushyanth & Tanaka, Tomomi & Abanokova, Kseniya, 2024. "Poverty dynamics for Ghana during 2005/06–2016/17: an investigation using synthetic panels," LSE Research Online Documents on Economics 124105, London School of Economics and Political Science, LSE Library.
    10. Ines A. Ferreira & Vincenzo Salvucci & Finn Tarp, 2021. "Poverty and vulnerability transitions in Myanmar: An analysis using synthetic panels," Review of Development Economics, Wiley Blackwell, vol. 25(4), pages 1919-1944, November.
    11. Hai‐Anh Dang & Dean Jolliffe & Calogero Carletto, 2019. "Data Gaps, Data Incomparability, And Data Imputation: A Review Of Poverty Measurement Methods For Data‐Scarce Environments," Journal of Economic Surveys, Wiley Blackwell, vol. 33(3), pages 757-797, July.
    12. Bellemare, Marc F. & Fajardo-Gonzalez, Johanna & Gitter, Seth R., 2018. "Foods and fads: The welfare impacts of rising quinoa prices in Peru," World Development, Elsevier, vol. 112(C), pages 163-179.
    13. Brian Colgan, 2023. "EU-SILC and the potential for synthetic panel estimates," Empirical Economics, Springer, vol. 64(3), pages 1247-1280, March.
    14. F. Clementi & A. L. Dabalen & V. Molini & F. Schettino, 2020. "We forgot the middle class! Inequality underestimation in a changing Sub-Saharan Africa," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 18(1), pages 45-70, March.
    15. Vincenzo Salvucci & Finn Tarp, 2021. "Poverty and vulnerability in Mozambique: An analysis of dynamics and correlates in light of the Covid‐19 crisis using synthetic panels," Review of Development Economics, Wiley Blackwell, vol. 25(4), pages 1895-1918, November.
    16. Hai‐Anh H. Dang & Peter Lanjouw, 2018. "Welfare dynamics in India over a quarter-century: Poverty, vulnerability, and mobility, 1987-2012," WIDER Working Paper Series wp-2018-175, World Institute for Development Economic Research (UNU-WIDER).

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