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The Individual Poverty Incidence of Growth

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  • Maria C. Lo Bue
  • Flaviana Palmisano

Abstract

The canonical approach to analyse the poverty impact of growth is based on the comparison of poverty before and after growth. Measurement tools endorsing this approach fail to capture the different experiences of poverty dynamic in the population: there can be groups of the population made poorer or non‐poor made poor by growth. We propose an approach that allows measuring this individual poverty incidence of growth and show how it is related with existing models. We apply our framework to evaluate the poverty impact of growth in Indonesia, by comparing the 1993–2000 with the 2000–07 and 2007–14 growth spells.

Suggested Citation

  • Maria C. Lo Bue & Flaviana Palmisano, 2020. "The Individual Poverty Incidence of Growth," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(6), pages 1295-1321, December.
    • Handle: RePEc:bla:obuest:v:82:y:2020:i:6:p:1295-1321
    DOI: 10.1111/obes.12362
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    Cited by:

    1. Fourrier-Nicolaï Edwin & Lubrano Michel, 2024. "Bayesian inference for non-anonymous growth incidence curves using Bernstein polynomials: an application to academic wage dynamics," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 28(2), pages 319-336, April.
    2. Olivier Bargain & Maria Lo Bue & Francesco Palmisano, 2022. "Dynastic Measures of Intergenerational Mobility," Working Papers hal-03896551, HAL.
    3. Stephan Klasen & Maria C. Lo Bue & Vincenzo Prete, 2020. "What's behind pro-poor growth?: The role of shocks and measurement error," WIDER Working Paper Series wp-2020-16, World Institute for Development Economic Research (UNU-WIDER).
    4. Flaviana Palmisano & Ida Petrillo, 2021. "A general rank-dependent approach for distributional comparisons," Working Papers 567, ECINEQ, Society for the Study of Economic Inequality.
    5. Flaviana Palmisano & Ida Petrillo, 2022. "A general rank‐dependent approach for distributional comparisons," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 24(2), pages 380-409, April.
    6. Tang, Kai & Li, Zhenshan & He, Chun, 2023. "Spatial distribution pattern and influencing factors of relative poverty in rural China," Innovation and Green Development, Elsevier, vol. 2(1).
    7. Edwin Fourrier-Nicolai & Michel Lubrano, 2022. "Bayesian inference for non-anonymous Growth Incidence Curves using Bernstein polynomials: an application to academic wage dynamics," Working Papers hal-03880243, HAL.

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