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Measuring Risk by Looking at Changes in Inequality: vulnerability in Ecuador

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  • Ligon, Ethan A.

Abstract

We describe a measure of welfare, "vulnerability", which measures the difference between the highest feasible average level of utility in a population given aggregate resources, and the actual average level of utility. This measure can be decomposed into two components, related to inequality and to risk. We provide methods for computing vulnerability, inequality, and risk using only data on expenditures from repeated cross-sections of household data, and relate these to Atkinson's family of inequality measures. Using methods developed here and household-level Ecuadorean data from 1995 and 2006, we estimate the vulnerability and risk of �different population groups. Taking the population altogether, we find that the crisis of the late nineties was not only a large shock for the country as a whole, but also greatly increased the risk faced by individual households in the Sierra, risk which was subsequently translated into greater inequality. After 1999, overall risk borne by the average household fell dramatically, with the consequence that inequality remained nearly constant from 1999-2006. Levels of rural risk are considerably greater than are urban; further, rural risks tend to be the consequence of spatial shocks, while urban risks are much more idiosyncratic in nature.

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Bibliographic Info

Paper provided by Department of Agricultural & Resource Economics, UC Berkeley in its series Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series with number qt8vj75725.

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Date of creation: 25 Jan 2010
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Handle: RePEc:cdl:agrebk:qt8vj75725

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Keywords: Social and Behavioral Sciences;

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References

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  1. Chris Elbers & Jan Willem Gunning, 2003. "Vulnerability in a Stochastic Dynamic Model," Tinbergen Institute Discussion Papers 03-070/2, Tinbergen Institute.
  2. Christiaensen, Luc J.M. & Boisvert, Richard N., 2000. "On Measuring Household Food Vulnerability: Case Evidence from Northern Mali," Working Papers 127676, Cornell University, Department of Applied Economics and Management.
  3. Hoddinott, John & Quisumbing, Agnes, 2003. "Methods for microeconometric risk and vulnerability assessments," Social Protection Discussion Papers 29138, The World Bank.
  4. Glewwe, Paul & Hall, Gillette, 1998. "Are some groups more vulnerable to macroeconomic shocks than others? Hypothesis tests based on panel data from Peru," Journal of Development Economics, Elsevier, vol. 56(1), pages 181-206, June.
  5. Jalan, Jyotsna & Ravallion, Martin, 1999. "Are the poor less well insured? Evidence on vulnerability to income risk in rural China," Journal of Development Economics, Elsevier, vol. 58(1), pages 61-81, February.
  6. Kocherlakota, Narayana R. & Pistaferri, Luigi, 2005. "Asset pricing implications of Pareto optimality with private information," Discussion Paper Series 1: Economic Studies 2005,29, Deutsche Bundesbank, Research Centre.
  7. Ligon, Ethan & Laura Schechter, 2002. "Measuring Vulnerability," Royal Economic Society Annual Conference 2002 128, Royal Economic Society.
  8. Martin Biewen, 2006. "Variance estimation for generalized entropy and Atkinson inequality indices: The complex survey data case," German Stata Users' Group Meetings 2006 04, Stata Users Group.
  9. Townsend, R.M., 1991. "Risk and Insurance in Village India," University of Chicago - Economics Research Center 91-3, Chicago - Economics Research Center.
  10. Shubham Chaudhuri & Jyotsna Jalan & Asep Suryahadi, 2002. "Assessing household vulnerability to poverty from cross-sectional data: A methodology and estimates from Indonesia," Discussion Papers 0102-52, Columbia University, Department of Economics.
  11. Stefan Dercon & Pramila Krishnan, 2000. "Vulnerability, seasonality and poverty in Ethiopia," Journal of Development Studies, Taylor & Francis Journals, vol. 36(6), pages 25-53.
  12. Atkinson, Anthony B., 1970. "On the measurement of inequality," Journal of Economic Theory, Elsevier, vol. 2(3), pages 244-263, September.
  13. Sajeda Amin & Ashok S. Rai & Giorgio Topa, 1999. "Does Microcredit Reach the Poor and Vulnerable? Evidence from Northern Bangladesh," CID Working Papers 28, Center for International Development at Harvard University.
  14. Deaton, Angus, 1985. "Panel data from time series of cross-sections," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 109-126.
  15. Deaton, A. & Paxson, C., 1993. "Intertemporal Choice and Inequality," Papers 168, Princeton, Woodrow Wilson School - Development Studies.
  16. Mace, Barbara J, 1991. "Full Insurance in the Presence of Aggregate Uncertainty," Journal of Political Economy, University of Chicago Press, vol. 99(5), pages 928-56, October.
  17. Bewley, Truman, 1977. "The permanent income hypothesis: A theoretical formulation," Journal of Economic Theory, Elsevier, vol. 16(2), pages 252-292, December.
  18. Pritchett, Lant & Suryahadi, Asep & Sumarto, Sudarno, 2000. "Quantifying vulnerability to poverty - a proposed measure, applied to Indonesia," Policy Research Working Paper Series 2437, The World Bank.
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Cited by:
  1. Naudé, Wim, 2011. "Entrepreneurship is Not a Binding Constraint on Growth and Development in the Poorest Countries," World Development, Elsevier, vol. 39(1), pages 33-44, January.

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