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On Synthetic Income Panels

Author

Listed:
  • Moreno, Héctor

    (University of Oxford)

  • Bourguignon, Francois

    (Paris School of Economics)

  • Dang, Hai-Anh H

    (World Bank)

Abstract
In many developing countries, the increasing public interest in monitoring economic inequality and mobility is hindered by the scarce availability of longitudinal data. Synthetic panels based on matching individuals with the same time-invariant characteristics in consecutive cross-sections have been recently proposed as a substitute to such data. We extend the methodology to construct such synthetic panels in several directions by: a) explicitly assuming the unobserved or time variant determinants of (log) income are AR(1) and relying on pseudo-panel procedures to estimate the corresponding auto-regressive coefficient; b) abstracting from (log) normality assumptions; c) generating a close to perfect match of the terminal year income distribution and d) considering the whole income mobility matrix rather than mobility in and out of poverty. We exploit the cross-sectional dimension of a national-representative Mexican panel survey to evaluate the validity of this approach. With the median estimate of the AR coefficient, the income mobility matrix in the synthetic panel closely approximates that of the genuine matrix observed in the actual panel, except for out-lying values of the AR coefficient.

Suggested Citation

  • Moreno, Héctor & Bourguignon, Francois & Dang, Hai-Anh H, 2021. "On Synthetic Income Panels," IZA Discussion Papers 14236, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp14236
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    1. Fatih Guvenen & Fatih Karahan & Serdar Ozkan & Jae Song, 2015. "What Do Data on Millions of U.S. Workers Reveal about Life-Cycle Earnings Risk?," NBER Working Papers 20913, National Bureau of Economic Research, Inc.
    2. Deepankar Basu, 2020. "Bias of OLS Estimators due to Exclusion of Relevant Variables and Inclusion of Irrelevant Variables," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(1), pages 209-234, February.
    3. François Bourguignon, 2011. "Non-anonymous growth incidence curves, income mobility and social welfare dominance," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 9(4), pages 605-627, December.
    4. Francisca Antman & David McKenzie, 2007. "Poverty traps and nonlinear income dynamics with measurement error and individual heterogeneity," Journal of Development Studies, Taylor & Francis Journals, vol. 43(6), pages 1057-1083.
    5. 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.
    6. McKenzie, D.J.David J., 2004. "Asymptotic theory for heterogeneous dynamic pseudo-panels," Journal of Econometrics, Elsevier, vol. 120(2), pages 235-262, June.
    7. 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.
    8. Dang,Hai-Anh H. & Lanjouw,Peter F., 2013. "Measuring poverty dynamics with synthetic panels based on cross-sections," Policy Research Working Paper Series 6504, The World Bank.
    9. Deaton, Angus, 1985. "Panel data from time series of cross-sections," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 109-126.
    10. Kathleen Beegle & Luc Christiaensen & Andrew Dabalen & Isis Gaddis, 2016. "Poverty in a Rising Africa," World Bank Publications - Books, The World Bank Group, number 22575.
    11. Dang, Hai-Anh & Lanjouw, Peter & Luoto, Jill & McKenzie, David, 2014. "Using repeated cross-sections to explore movements into and out of poverty," Journal of Development Economics, Elsevier, vol. 107(C), pages 112-128.
    12. Browning, Martin & Deaton, Angus & Irish, Margaret, 1985. "A Profitable Approach to Labor Supply and Commodity Demands over the Life-Cycle," Econometrica, Econometric Society, vol. 53(3), pages 503-543, May.
    13. Bourguignon, Francois & Goh, Chor-ching & Kim, Dae Il, 2004. "Estimating individual vulnerability to poverty with pseudo-panel data," Policy Research Working Paper Series 3375, The World Bank.
    14. Francisco H.G. Ferreira & Julian Messina & Jamele Rigolini & Luis-Felipe López-Calva & Maria Ana Lugo & Renos Vakis, 2013. "Economic Mobility and the Rise of the Latin American Middle Class [La movilidad económica y el crecimiento de la clase media en América Latina]," World Bank Publications - Books, The World Bank Group, number 11858.
    15. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
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    Cited by:

    1. Hai‐Anh H. Dang & Peter F. Lanjouw, 2023. "Measuring Poverty Dynamics with Synthetic Panels Based on Repeated Cross Sections," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(3), pages 599-622, June.
    2. Bertschek Irene & Müller David F., 2023. "Political Ignorance and the Internet," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 243(1), pages 3-28, February.
    3. David Garcés‐Urzainqui & Peter Lanjouw & Gerton Rongen, 2021. "Constructing synthetic panels for the purpose of studying poverty dynamics: A primer," Review of Development Economics, Wiley Blackwell, vol. 25(4), pages 1803-1815, November.

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    More about this item

    Keywords

    income mobility; synthetic panel; Mexico;
    All these keywords.

    JEL classification:

    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty

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