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The mode-based poverty decomposition into the growth and distribution effects

Takahiro Yamada

Journal of Income Distribution2024https://doi.org/10.25071/1874-6322.40554article
AJG 1ABDC B
Weight
0.51

Abstract

This study proposes the mode-based decomposition approach to better examine the change of the wealth of more impoverished populations into growth and distribution effects. Given Gibrat’s law, the decomposition first approximates the income distribution to lognormal distribution using the maximum likelihood estimation and household sample surveys. Then, it performs the residual-free and the time-reversion consistent poverty decomposition into growth and distribution effects. The case study uses the post-Doi Moi Vietnam, 1993-2014, where significant poverty reduction has taken place. The results indicate that the distribution effect adversely affects the bottom 10 and 20 percent of the population, unlike the growth effect that mostly induced the poverty decrease. Growth enhancing policies targeting the mean or per-capita increase of income is generally good for the poor, but it could fail to capture the sensitive welfare change of the poorest of the poor, which is particularly vulnerable to shocks.

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https://doi.org/https://doi.org/10.25071/1874-6322.40554

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@article{takahiro2024,
  title        = {{The mode-based poverty decomposition into the growth and distribution effects}},
  author       = {Takahiro Yamada},
  journal      = {Journal of Income Distribution},
  year         = {2024},
  doi          = {https://doi.org/https://doi.org/10.25071/1874-6322.40554},
}

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The mode-based poverty decomposition into the growth and distribution effects

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Evidence weight

0.51

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.52 × 0.4 = 0.21
M · momentum0.55 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.