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.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
References
Bane, M., Ellwood, D.: Slipping into and out of poverty: the dynamics of spells. J. Hum. Resour. 21, 1–23 (1986)
Bourguignon, F., Moreno, H.: On the construction of synthetic panels. Paper presented at the North East Universities Development Conference, Brown University, Providence RI (2015)
Canberra Group: Handbook on Household Income Statistics, 2nd. United Nations Economic Commission for Europe, Geneva (2011)
Cruces, G., Lanjouw, P., Lucchetti, L., Perova, E., Vakis, R., Viollaz, M.: Estimating poverty transitions using repeated cross-sections: a three-country validation exercise. J. Econ. Inequal. 13, 161–179 (2015)
Dang, H.-A., Dabalen, A.L.: Is poverty in Africa mostly chronic or transient? Evidence from synthetic panel data. Journal of Development Studies, online (2018)
Dang, H.-A., Ianchovichina, E.: Welfare dynamics with synthetic panels: the case of the Arab world in transition. Rev. Income Wealth 64(S1), S114–S144 (2018)
Dang, H.-A., Lanjouw, P.: Measuring poverty dynamics with synthetic panels based on cross-sections. Policy Research Working Paper 6504, The World Bank (2013)
Dang, H.-A., Lanjouw, P.: Poverty dynamics in India between 2004 and 2012: Insights from longitudinal analysis using synthetic panel data. Econ. Dev. Cult. Chang. 67(1), 131–170 (2018)
Dang, H.-A., Lanjouw, P., Luoto, L., McKenzie, D.: Using repeated cross-sections to explore movements into and out of poverty. J. Dev. Econ. 107, 112–128 (2014)
Dang, H.-A., Lanjouw, P., Swinkels, R: Who remained in poverty, who moved up, and who fell down? An investigation of poverty dynamics in Senegal in the 2000s. In: Nissanke, M., Ndulo, M. (eds.) Poverty Reduction in the Course of African Development. Oxford University Press, Oxford (2017)
Deaton, A.: Panel data from time series of cross-sections. J. Econ. 30, 109–126 (1985)
Ferreira, F.H.G., Messina, J., Rigolini, J., López-Calva, L.-F., Lugo, M.A., Vakis, R.: Economic Mobility and the Rise of the Latin American Middle Class. The World Bank, Washington DC (2013)
Fields, G., Viollaz, M.: Can the limitations of panel datasets be overcome by using pseudo-panels to estimate income mobility? Paper presented at the ECINEQ Conference, Bari, Italy (2013)
Frick, J.R., Jenkins, S.P., Lillard, D.R., Lipps, O., Wooden, M.: The Cross-National Equivalent File (CNEF) and its member country household panel studies. Schmollers Jahrbuch J. Appl. Soc. Sci. Stud. 127(4), 627–654 (2007)
Garcés Urzainqui, D.: Poverty transitions without panel data? An appraisal of synthetic panel methods. Paper presented at the ECINEQ Conference, New York City (2017)
Jenkins, S.P.: Changing Fortunes. Income Mobility and Poverty Dynamics in Britain. Oxford University Press, Oxford (2011)
Jenkins, S.P., Van Kerm, P.: How does attrition affect estimates of persistent poverty rates? The case of EU-SILC. In: Atkinson, A.B., Guio, A., Marlier, E. (eds.) Monitoring Social Europe, 2017 Edition. Luxembourg: Eurostat, pp 401–417 (2017)
Moffitt, R.: Identification and estimation of dynamic models with a time series of repeated cross sections. J. Econ. 59, 99–123 (1993)
OECD: Employment Outlook, 2015. OECD Publishing, Paris (2015)
OECD: A Broken Elevator? How to Promote Social Mobility. OECD Publishing, Paris (2018)
Perez, V.: Moving in and out of poverty in Mexico: what can we learn from pseudo-panel methods? ISER Working Paper 2015-16, University of Essex (2015)
Rama, M., Béteille, T., Li, Y., Mitra, P.K., Newman, J.L.: Addressing Inequality in South Asia. The World Bank, Washington DC (2014)
Rigolini, J., Vakis, R., Lucchetti, L.: Left behind Chronic Poverty in Latin America and the Caribbean. The World Bank, Washington DC (2016)
Rosenzweig, M.R.: Payoffs from panels in low-income countries: economic development and economic mobility. Am. Econ. Rev. Pap. Proc. 93(2), 112–117 (2003)
Summerfield, M., Freidin, S., Hahn, M., La, N., Li, N., Macalalad, N., O’Shea, M., Watson, N., Wilkins, R., Wooden, M.: HILDA user Manual – Release, 15. Melbourne Institute for Applied Social and Economic Research, Melbourne (2016)
Verbeek, M.: Synthetic panels and repeated cross-sections. In: Matyas, L., Sevestre, P. (eds.) The Econometrics of Panel Data, pp 369–383. Springer-Verlag, Berlin (2008)
Watson, N., Wooden, M.: Re-engaging with survey non-respondents: the BHPS, SOEP and HILDA survey experience, HILDA Project Discussion Paper 1/11 (2011)
Wilkins, R.: The Household, Income and Labour Dynamics in Australia Survey: Selected Findings from Waves 1 to 15. Melbourne Institute of Applied Social and Economic Research, Melbourne (2017)
Acknowledgements
We dedicate this paper to the memory of Tony Atkinson. This paper uses unit record data from the Household, Income and Labour Dynamics in Australia (HILDA) Survey. The HILDA Project was initiated and is funded by the Australian Government Department of Social Services (DSS) and is managed by the Melbourne Institute of Applied Economic and Social Research (Melbourne Institute). The findings and views reported in this paper, however, are those of the authors and should not be attributed to either DSS or the Melbourne Institute. Our research is supported by an Australian Research Council Discovery Grant (award DP150102409). Jenkins’s research is also partially supported by core funding of the Research Centre on Micro-Social Change at the Institute for Social and Economic Research by the University of Essex and the UK Economic and Social Research Council (award ES/L009153/1). For helpful discussions, we thank Hai-Anh Dang, Peter Lanjouw, David Garcés Urzainqui, the handling editor (Markus Jäntti), and an anonymous referee. We thank DLLM for making their Stata code freely downloadable. Our Stata code, which builds on theirs, is available on request. Helpful comments from audiences in Bristol, Dublin, Essex, Melbourne, and Oslo are also acknowledged.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
About this article
Cite this article
Hérault, N., Jenkins, S.P. How valid are synthetic panel estimates of poverty dynamics?. J Econ Inequal 17, 51–76 (2019). https://doi.org/10.1007/s10888-019-09408-8
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10888-019-09408-8