Measuring Vulnerability to Poverty Using Long-Term Panel Data
We investigate the accuracy of ex ante assessments of vulnerability to income poverty using cross-sectional data and panel data. We use long-term panel data from Germany and apply di fferent regression models, based on household covariates and previous-year equivalence income, to classify a household as vulnerable or not. Predictive performance is assessed using the Receiver Operating Characteristics (ROC), which takes account of false positive as well as true positive rates. Estimates based on cross-sectional data are much less accurate than those based on panel data, but for Germany, the accuracy of vulnerability predictions is limited even when panel data are used. In part this low accuracy is due to low poverty incidence and high mobility in and out of poverty.
|Date of creation:||06 Jul 2012|
|Contact details of provider:|| Postal: Platz der Goettinger Sieben 3; D-37073 Goettingen, GERMANY|
Phone: +49 551 39 14066
Fax: + 49 551 39 14059
Web page: http://www.uni-goettingen.de/en/82144.html
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Cesar Calvo & Stefan Dercon, 2005. "Measuring Individual Vulnerability," Economics Series Working Papers 229, University of Oxford, Department of Economics.
- Ligon, Ethan & Schechter, Laura, 2004. "Evaluating different approaches to estimating vulnerability," Social Protection and Labor Policy and Technical Notes 30159, The World Bank.
- Luc J. Christiaensen & Kalanidhi Subbarao, 2005.
"Towards an Understanding of Household Vulnerability in Rural Kenya,"
Journal of African Economies,
Centre for the Study of African Economies (CSAE), vol. 14(4), pages 520-558, December.
- Christiaensen, Luc. J. & Subbarao, Kalanidhi, 2004. "Toward an understanding of household vulnerability in rural Kenya," Policy Research Working Paper Series 3326, The World Bank.
- Selten, Reinhard, 1991. "Properties of a measure of predictive success," Mathematical Social Sciences, Elsevier, vol. 21(2), pages 153-167, April.
- Selten,Reinhard, "undated". "Properties of a measure of predictive succes," Discussion Paper Serie B 130, University of Bonn, Germany.
- Ethan Ligon & Laura Schechter, 2003. "Measuring Vulnerability," Economic Journal, Royal Economic Society, vol. 113(486), pages 95-102, March.
- Ligon, Ethan & Schechter, Laura, 2002. "Measuring Vulnerability," 2002 Annual meeting, July 28-31, Long Beach, CA 19899, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
- Ligon, Ethan & Laura Schechter, 2002. "Measuring Vulnerability," Royal Economic Society Annual Conference 2002 128, Royal Economic Society.
- Joon-Ho Hahm & Douglas G. Steigerwald, 1999. "Consumption Adjustment under Time-Varying Income Uncertainty," The Review of Economics and Statistics, MIT Press, vol. 81(1), pages 32-40, February.
- 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.
- Frick, Joachim R. & Grabka, Markus M., 2007. "Item Non-Response and Imputation of Annual Labor Income in Panel Surveys from a Cross-National Perspective," IZA Discussion Papers 3043, Institute for the Study of Labor (IZA).
- Joachim R. Frick & Markus M. Grabka, 2007. "Item Non-response and Imputation of Annual Labor Income in Panel Surveys from a Cross-National Perspective," Discussion Papers of DIW Berlin 736, DIW Berlin, German Institute for Economic Research.
- Joachim R. Frick & Markus M. Grabka, 2007. "Item Non-response and Imputation of Annual Labor Income in Panel Surveys from a Cross-National Perspective," SOEPpapers on Multidisciplinary Panel Data Research 49, DIW Berlin, The German Socio-Economic Panel (SOEP).
- Hoddinott, John & Quisumbing, Agnes, 2003. "Methods for microeconometric risk and vulnerability assessments," Social Protection and Labor Policy and Technical Notes 29138, The World Bank.
- Joachim R. Frick & Markus M. Grabka, 2003. "Missing Income Data in the German SOEP: Incidence, Imputation and its Impact on the Income Distribution," Discussion Papers of DIW Berlin 376, DIW Berlin, German Institute for Economic Research.
- Günther, Isabel & Harttgen, Kenneth, 2009. "Estimating Households Vulnerability to Idiosyncratic and Covariate Shocks: A Novel Method Applied in Madagascar," World Development, Elsevier, vol. 37(7), pages 1222-1234, July.
- Annelies Debels & Leen Vandecasteele, 2008. "The Time Lag In Annual Household-Based Income Measures: Assessing And Correcting The Bias," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 54(1), pages 71-88, March.
- Yuan Zhang & Guanghua Wan, 2009. "How Precisely Can We Estimate Vulnerability to Poverty?," Oxford Development Studies, Taylor & Francis Journals, vol. 37(3), pages 277-287.
- Raghbendra Jha & Tu Dang, 2008. "Vulnerability to poverty in Papua New Guinea," Departmental Working Papers 2008-08, The Australian National University, Arndt-Corden Department of Economics.
- Asep Suryahadi & Sudarno Sumarto, 2003. "Poverty and Vulnerability in Indonesia Before and After the Economic Crisis," Asian Economic Journal, East Asian Economic Association, vol. 17(1), pages 45-64, March.
- Lusardi, Annamaria, 1996. "Permanent Income, Current Income, and Consumption: Evidence from Two Panel Data Sets," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(1), pages 81-90, January. Full references (including those not matched with items on IDEAS)