The Mode-Based Poverty Decomposition into the Growth and Distribution Effects

Abstract

This study proposes the mode-based decomposition approach to better examine the change of the more impoverished population s wealth 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 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.