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How valid are synthetic panel estimates of poverty dynamics?

Author

Listed:
  • Nicolas Hérault

    (University of Melbourne
    ARC Centre of Excellence for Children and Families over the Life Course)

  • Stephen P. Jenkins

    (University of Melbourne
    London School of Economics
    University of Essex
    IZA)

Abstract

A growing literature uses repeated cross-section surveys to derive ‘synthetic panel’ data estimates of poverty dynamics statistics. It builds on the pioneering study by Dang et al. (‘DLLM’, Journal of Development Economics, 2014) providing bounds estimates and the innovative refinement proposed by Dang and Lanjouw (‘DL’, World Bank Policy Research Working Paper 6504, 2013) providing point estimates of the statistics of interest. We provide new evidence about the accuracy of synthetic panel estimates relative to benchmarks based on estimates derived from genuine household panel data, employing high quality data from Australia and Britain, while also examining the sensitivity of results to a number of analytical choices. For these two high-income countries we show that DL-method point estimates are distinctly less accurate than estimates derived in earlier validity studies, all of which focus on low- and middle-income countries. We also demonstrate that estimate validity depends on choices such as the age of the household head (defining the sample), the poverty line level, and the years analyzed. DLLM parametric bounds estimates virtually always include the true panel estimates, though the bounds can be wide.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:joecin:v:17:y:2019:i:1:d:10.1007_s10888-019-09408-8
    DOI: 10.1007/s10888-019-09408-8
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    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. Mary Jo Bane & David T. Ellwood, 1986. "Slipping into and out of Poverty: The Dynamics of Spells," Journal of Human Resources, University of Wisconsin Press, vol. 21(1), pages 1-23.
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    6. Patrick Sevestre & Laszlo Matyas, 2008. "The Econometrics of Panel Data," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00279977, HAL.
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    11. Jenkins, Stephen P., 2011. "Changing Fortunes: Income Mobility and Poverty Dynamics in Britain," OUP Catalogue, Oxford University Press, number 9780199226436.
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    13. Hai-Anh H. Dang & Andrew L. Dabalen, 2019. "Is Poverty in Africa Mostly Chronic or Transient? Evidence from Synthetic Panel Data," Journal of Development Studies, Taylor & Francis Journals, vol. 55(7), pages 1527-1547, July.
    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. repec:ese:ukhlsp:2015-16 is not listed on IDEAS
    16. Perez, Victor, 2015. "Moving in and out of poverty in Mexico: What can we learn from pseudo-panel methods?," ISER Working Paper Series 2015-16, Institute for Social and Economic Research.
    17. Frick, Joachim R. & Jenkings, Stephen P. & Lillard, Dean R. & Lipps, Oliver & Wooden, Mark, 2007. "The Cross-National Equivalent File (CNEF) and Its Member Country Household Panel Studies," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 127(4), pages 627-654.
    18. 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.
    19. László Mátyás & Patrick Sevestre (ed.), 2008. "The Econometrics of Panel Data," Advanced Studies in Theoretical and Applied Econometrics, Springer, number 978-3-540-75892-1.
    20. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Blog mentions

    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. How Valid are Synthetic Panel Estimates of Poverty Dynamics?
      by maximorossi in NEP-LTV blog on 2019-04-29 14:02:10

    Citations

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    Cited by:

    1. Rongen,Gerton & Binti Ali Ahmad,Zainab & Lanjouw,Peter F. & Simler,Kenneth, 2022. "The Interplay of Regional and Ethnic Inequalities in Malaysian Poverty Dynamics," Policy Research Working Paper Series 9898, The World Bank.
    2. Federica Alfani & Fabio Clementi & Michele Fabiani & Vasco Molini & Enzo Valentini, 2023. "Once NEET, always NEET? A synthetic panel approach to analyze the Moroccan labor market," Review of Development Economics, Wiley Blackwell, vol. 27(4), pages 2401-2437, November.
    3. Hai-Anh H. Dang & Peter F. Lanjouw, 2023. "Regression-based imputation for poverty measurement in data-scarce settings," Chapters, in: Jacques Silber (ed.), Research Handbook on Measuring Poverty and Deprivation, chapter 13, pages 141-150, Edward Elgar Publishing.
    4. Dang, Hai-Anh H. & Lanjouw, Peter F., 2021. "Data Scarcity and Poverty Measurement," GLO Discussion Paper Series 904, Global Labor Organization (GLO).
    5. 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.
    6. Lanjouw Peter, 2020. "Income mobility in the developing world: Recent approaches and evidence," WIDER Working Paper Series wp2020-7, World Institute for Development Economic Research (UNU-WIDER).
    7. Ayesha Tantriana, 2024. "Poverty and vulnerability transitions in Indonesia before and during the COVID-19: insights from synthetic panels," Quality & Quantity: International Journal of Methodology, Springer, vol. 58(4), pages 3215-3249, August.
    8. Alessio Fusco & Philippe Van Kerm, 2023. "Measuring poverty persistence," Chapters, in: Jacques Silber (ed.), Research Handbook on Measuring Poverty and Deprivation, chapter 18, pages 192-200, Edward Elgar Publishing.
    9. Hai‐Anh Dang & Peter Lanjouw & Elise Vrijburg, 2021. "Poverty in India in the face of Covid‐19: Diagnosis and prospects," Review of Development Economics, Wiley Blackwell, vol. 25(4), pages 1816-1837, November.
    10. 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.
    11. Himanshu & Peter Lanjouw, 2020. "Income mobility in the developing world: Recent approaches and evidence," WIDER Working Paper Series wp-2020-7, World Institute for Development Economic Research (UNU-WIDER).
    12. Roger Wilkins, 2021. "Economic Wellbeing," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 54(4), pages 469-481, December.
    13. Jehovaness Aikaeli & David Garcés‐Urzainqui & Kenneth Mdadila, 2021. "Understanding poverty dynamics and vulnerability in Tanzania: 2012–2018," Review of Development Economics, Wiley Blackwell, vol. 25(4), pages 1869-1894, November.
    14. Kimberly Bolch & Luis F. Lopez‐Calva & Eduardo Ortiz‐Juarez, 2023. "“When Life Gives You Lemons”: Using Cross‐Sectional Surveys to Identify Chronic Poverty in the Absence of Panel Data," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 69(2), pages 474-503, June.
    15. 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.
    16. Brian Colgan, 2023. "EU-SILC and the potential for synthetic panel estimates," Empirical Economics, Springer, vol. 64(3), pages 1247-1280, March.

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    More about this item

    Keywords

    Synthetic panel; Pseudo panel; Poverty dynamics; Poverty entry; Poverty exit; BHPS; HILDA;
    All these keywords.

    JEL classification:

    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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