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Risk-adjusted poverty in Argentina: measurement and determinants

Author

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  • Cruces, Guillermo
  • Wodon, Quentin

Abstract

Relying on a Constant Relative Risk Aversion utility function, we use panel data for Argentina to compute risk-adjusted income and poverty measures and to analyze their determinants. Taking risk into account increases poverty. The regression analysis suggests that many household characteristics are correlated not only with the average income of the household over time, but also with income variability.

Suggested Citation

  • Cruces, Guillermo & Wodon, Quentin, 2003. "Risk-adjusted poverty in Argentina: measurement and determinants," LSE Research Online Documents on Economics 6550, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:6550
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    References listed on IDEAS

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    2. Mussa, Richard, 2015. "A regression based model of average exit time from poverty with application to Malawi," MPRA Paper 65204, University Library of Munich, Germany.
    3. Fields, Gary S. & Sánchez Puerta, María Laura, 2010. "Earnings Mobility in Times of Growth and Decline: Argentina from 1996 to 2003," World Development, Elsevier, vol. 38(6), pages 870-880, June.
    4. Ana Iturriza & Arjun S. Bedi & Robert Sparrow, 2011. "Unemployment Assistance and Transition to Employment in Argentina," Economic Development and Cultural Change, University of Chicago Press, vol. 59(4), pages 811-837.
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    6. Mussa, Richard, 2017. "Poverty in Malawi: Policy Analysis with Distributional Changes," MPRA Paper 75980, University Library of Munich, Germany.
    7. Nouve, Kofi & Bambio, Yiriyibin & Kabore, Samuel & Wodon, Quentin, 2010. "Risque et mesures de la pauvreté rurale au Burkina Faso [Risk and Measures of Rural Poverty in Burkina Faso]," MPRA Paper 34374, University Library of Munich, Germany.
    8. World Bank, 2006. "Managing Risks in Rural Senegal : A Multi-Sectoral Review of Efforts to Reduce Vulnerability," World Bank Publications - Reports 19467, The World Bank Group.
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    10. Mussa, Richard, 2015. "A joint analysis of correlates of poverty intensity, incidence, and gap with application to Malawi," MPRA Paper 65205, University Library of Munich, Germany.
    11. Philippe Van Kerm, 2013. "Generalized measures of wage differentials," Empirical Economics, Springer, vol. 45(1), pages 465-482, August.
    12. Guillermo Cruces & Quentin Wodon, 2003. "Argentina’s crises and the Poor, 1995-2002," Económica, Instituto de Investigaciones Económicas, Facultad de Ciencias Económicas, Universidad Nacional de La Plata, vol. 0(1-2), pages 55-96, January-D.
    13. Stefan Dercon & Joseph S. Shapiro, 2007. "Moving On, Staying Behind, Getting Lost: Lessons on poverty mobility from longitudinal data," Economics Series Working Papers GPRG-WPS-075, University of Oxford, Department of Economics.
    14. repec:qeh:ophiwp:ophiwp052 is not listed on IDEAS
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    17. Groisman, Fernando & Beccaría, Luis Alberto, 2006. "Income instability, mobility and distribution in Argentina," Revista CEPAL, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL), August.
    18. Guillermo Cruces & Quentin T. Wodon, 2003. "Transient and chronic poverty in turbulent times: Argentina 1995-2002," Economics Bulletin, AccessEcon, vol. 9(3), pages 1-12.
    19. Mussa, Richard, 2017. "Contextual Effects of Education on Poverty in Malawi," MPRA Paper 75976, University Library of Munich, Germany.
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    Keywords

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    JEL classification:

    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement

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