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Transitions in Poverty and Deprivations: An Analysis of Multidimensional Poverty Dynamics

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  • Nicolai Suppa

Abstract

This paper explores a novel way to analyse poverty dynamics that are specific to certain measures of multidimensional poverty, such as the "adjusted headcount ratio" proposed by Alkire and Foster (2011a). Assuming there is panel data available, I show that a simultaneous and comprehensive account of transitions in deprivations and poverty allows complex interdependencies between dimensions in a dynamic context to be handled and, at the same time, allows for several advanced types of analyses. These analyses include (i) a decomposition of changes in multidimensional poverty, which reveals why poverty decreases or increases; (ii) a framework to examine and understand the relationship between the dashboard approach and dimensional contributions and multidimensional poverty in a dynamic setting; (iii) a presentation of methods that illuminate the process of the accumulation of deprivations. The suggested types of analyses are illustrated using German panel data. The implications for monitoring, policy evaluation and strategies for analyses using repeated cross-sectional data are discussed.

Suggested Citation

  • Nicolai Suppa, 2017. "Transitions in Poverty and Deprivations: An Analysis of Multidimensional Poverty Dynamics," OPHI Working Papers 109, Queen Elizabeth House, University of Oxford.
  • Handle: RePEc:qeh:ophiwp:ophiwp109
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    2. Hoolda Kim, 2019. "Beyond Monetary Poverty Analysis: The Dynamics of Multidimensional Child Poverty in Developing Countries," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 141(3), pages 1107-1136, February.

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    More about this item

    JEL classification:

    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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