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On the Measurement of Poverty Dynamics

Author

Listed:
  • Hojman, Daniel

    (Harvard University)

  • Kast, Felipe

    (Universidad Catolica de Chile)

Abstract

This paper introduces a family of multi-period poverty measures derived from commonly used static poverty measures. Our measures trade-off poverty levels and changes (gains and losses) over time, and are consistent with loss aversion. We characterize the partial ranking over income dynamics induced by these measures and use it in two empirical applications with longitudinal household level data. Comparing two decades of income dynamics in the United States we find that the income dynamics of the 1990s -post Welfare reform- dominates the income dynamics of the 1980s -pre Welfare reform. Next, we compare the contemporary income dynamics of three industrialized countries and conclude that United Kingdom dominates Germany and United States, and Germany dominates the United States if poverty stocks are given more importance than poverty flows. The differences between our ranking and those obtained using other welfare criteria such as social mobility suggest that our measures capture critical information about the evolution of poverty.

Suggested Citation

  • Hojman, Daniel & Kast, Felipe, 2009. "On the Measurement of Poverty Dynamics," Working Paper Series rwp09-035, Harvard University, John F. Kennedy School of Government.
    • Handle: RePEc:ecl:harjfk:rwp09-035
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    File URL: https://research.hks.harvard.edu/publications/workingpapers/citation.aspx?PubId=6882&type=WPN
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    Cited by:

    1. Hendrik Thiel & Stephan L. Thomsen, 2015. "Individual Poverty Paths and the Stability of Control-Perception," SOEPpapers on Multidisciplinary Panel Data Research 794, DIW Berlin, The German Socio-Economic Panel (SOEP).
    2. BOSSERT, Walter & CERIANI, Lidia & CHAKRAVARTY, Satya R. & D'AMBROSIO, Conchita, 2012. "Intertemporal Material Deprivation," Cahiers de recherche 2012-06, Universite de Montreal, Departement de sciences economiques.
    3. Antonio Acconcia & Maria Carannante & Michelangelo Misuraca & Germana Scepi, 2020. "Measuring Vulnerability to Poverty with Latent Transition Analysis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 151(1), pages 1-31, August.
    4. Carlos Gradín & Coral Del Río & Olga Cantó, 2012. "Measuring Poverty Accounting For Time," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 58(2), pages 330-354, June.
    5. Hai‐Anh H. Dang & Peter F. Lanjouw, 2017. "Welfare Dynamics Measurement: Two Definitions of a Vulnerability Line and Their Empirical Application," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 63(4), pages 633-660, December.
    6. Isabel Günther & Johannes K. Maier, 2014. "Poverty, Vulnerability, and Reference-Dependent Utility," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 60(1), pages 155-181, March.
    7. Dang, Hai-Anh & Lanjouw, Peter & Luoto, Jill & McKenzie, David, 2014. "Using repeated cross-sections to explore movements into and out of poverty," Journal of Development Economics, Elsevier, vol. 107(C), pages 112-128.

    More about this item

    JEL classification:

    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty

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