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Measuring Vulnerability to Poverty Using Long-Term Panel Data

Author

Listed:
  • Katja Landau

    (Georg-August-University Göttingen)

  • Stephan Klasen

    (Georg-August-University Göttingen)

  • Walter Zucchini

    (Georg-August-University Göttingen)

Abstract

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.

Suggested Citation

  • Katja Landau & Stephan Klasen & Walter Zucchini, 2012. "Measuring Vulnerability to Poverty Using Long-Term Panel Data," Courant Research Centre: Poverty, Equity and Growth - Discussion Papers 118, Courant Research Centre PEG.
    • Handle: RePEc:got:gotcrc:118
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    Cited by:

    1. is not listed on IDEAS
    2. Stephan Klasen & Simon Lange, 2015. "Targeting Performance and Poverty Effects of Proxy Means-Tested Transfers: Trade-offs and Challenges," Ibero America Institute for Econ. Research (IAI) Discussion Papers 231, Ibero-America Institute for Economic Research.
    3. Zhang Huafeng, 2016. "Household vulnerability and economic status during disaster recovery and its determinants: a case study after the Wenchuan earthquake," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 83(3), pages 1505-1526, September.
    4. Klasen, Stephan & Meyer, Katrin M. & Dislich, Claudia & Euler, Michael & Faust, Heiko & Gatto, Marcel & Hettig, Elisabeth & Melati, Dian N. & Jaya, I. Nengah Surati & Otten, Fenna & Pérez-Cruzado, Cés, 2016. "Economic and ecological trade-offs of agricultural specialization at different spatial scales," Ecological Economics, Elsevier, vol. 122(C), pages 111-120.
    5. Jehane Simona-Moussa, 2020. "The Subjective Well-Being of Those Vulnerable to Poverty in Switzerland," Journal of Happiness Studies, Springer, vol. 21(5), pages 1561-1580, June.
    6. Martina Celidoni, 2015. "Decomposing Vulnerability to Poverty," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 61(1), pages 59-74, March.

    More about this item

    Keywords

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    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • O29 - Economic Development, Innovation, Technological Change, and Growth - - Development Planning and Policy - - - Other

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