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Vulnerability to poverty revisited: Flexible modeling and better predictive performance

Author

Listed:
  • Maike Hohberg

    () (University of Goettingen)

  • Katja Landau

    (University of Goettingen)

  • Thomas Kneib

    (University of Goettingen)

  • Stephan Klasen

    (University of Goettingen)

  • Walter Zucchini

    (University of Goettingen)

Abstract

This paper analyzes several modifications to improve a simple measure of vulnerability as expected poverty. Firstly, in order to model income, we apply distributional regression relating potentially each parameter of the conditional income distribution to the covariates. Secondly, we determine the vulnerability cutoff endogenously instead of defining a household as vulnerable if its probability of being poor in the next period is larger than 0.5. For this purpose, we employ the receiver operating characteristic curve that is able to consider prerequisites according to a particular targeting mechanism. Using long-term panel data from Germany, we build both mean and distributional regression models with the established 0.5 probability cutoff and our vulnerability cutoff. We find that our new cutoff considerably increases predictive performance. Placing the income regression model into the distributional regression framework does not improve predictions further but has the advantage of a coherent model where parameters are estimated simultaneously replacing the original three step estimation approach.

Suggested Citation

  • Maike Hohberg & Katja Landau & Thomas Kneib & Stephan Klasen & Walter Zucchini, 2018. "Vulnerability to poverty revisited: Flexible modeling and better predictive performance," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 16(3), pages 439-454, September.
  • Handle: RePEc:spr:joecin:v:16:y:2018:i:3:d:10.1007_s10888-017-9374-6
    DOI: 10.1007/s10888-017-9374-6
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    References listed on IDEAS

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    Cited by:

    1. Mauricio Gallardo, 2020. "Measuring Vulnerability to Multidimensional Poverty," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 148(1), pages 67-103, February.
    2. Kakungulu, Moses & Akoyi, Kevin Teopista & Van Hoyweghen, Kaat & Vranken, Liesbet & Isabirye, Moses & Maertens, Miet, 2018. "Who should diversify and move out of agriculture? Income portfolios and household welfare in rural Uganda," Working Papers 276469, Katholieke Universiteit Leuven, Centre for Agricultural and Food Economics.

    More about this item

    Keywords

    Vulnerability to poverty; Distributional regression; Generalized additive model for location; Scale and shape; Receiver operating characteristic curve;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • 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

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