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Estimating quarterly poverty rates using labor force surveys : a primer

Author

Listed:
  • Douidich, Mohamed
  • Ezzrari, Abdeljaouad
  • Van der Weide, Roy
  • Verme, Paolo

Abstract

The paper shows how Labor Force Surveys can be used effectively to estimate poverty rates using Household Expenditure Surveys and cross-survey imputation methods. With only two rounds of Household Expenditure Survey data for Morocco (2001 and 2007), the paper estimates quarterly poverty rates for the period 2001-2010 by imputing household expenditures into the Labor Force Surveys. The results are encouraging. The methodology is able to accurately reproduce official poverty statistics by combining current Labor Force Surveys with previous period Household Expenditure Surveys, and vice versa. Although the focus is on head-count poverty, the method can be applied to any welfare indicator that is a function of household income or expenditure, such as the poverty gap or the Gini index of inequality. The newly produced time-series of poverty rates can help researchers and policy makers to: (a) study the determinants of poverty reduction or use poverty as an explanatory factor in cross-section and panel models; (b) forecast poverty rates based on a time-series model fitted to the data; and (c) explore the linkages between labor market conditions and poverty and simulate the effects of policy reforms or economic shocks. This is a promising research agenda that can expand significantly the tool-kit of the welfare economist.

Suggested Citation

  • Douidich, Mohamed & Ezzrari, Abdeljaouad & Van der Weide, Roy & Verme, Paolo, 2013. "Estimating quarterly poverty rates using labor force surveys : a primer," Policy Research Working Paper Series 6466, The World Bank.
    • Handle: RePEc:wbk:wbrwps:6466
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    References listed on IDEAS

    as
    1. Natalia Evgenevna Antonova, 2007. "The international scientific conference «Economic Cooperation between the Russian Far East and the Asia-Pacific Region Countries»," Spatial Economics=Prostranstvennaya Ekonomika, Economic Research Institute, Far Eastern Branch, Russian Academy of Sciences (Khabarovsk, Russia), issue 2, pages 177-182.
    2. Luc Christiaensen & Peter Lanjouw & Jill Luoto & David Stifel, 2012. "Small area estimation-based prediction methods to track poverty: validation and applications," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 10(2), pages 267-297, June.
    3. repec:pri:rpdevs:deaton_price_trends_in_india_version_3_jan_08_all.pdf is not listed on IDEAS
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    More about this item

    Keywords

    Rural Poverty Reduction; Regional Economic Development; Achieving Shared Growth; Poverty Monitoring&Analysis;
    All these keywords.

    JEL classification:

    • D6 - Microeconomics - - Welfare Economics
    • H53 - Public Economics - - National Government Expenditures and Related Policies - - - Government Expenditures and Welfare Programs
    • I3 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty
    • R13 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - General Equilibrium and Welfare Economic Analysis of Regional Economies

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