The mode-based decomposition into the growth and distribution effects for segments of poor
DOI:
https://doi.org/10.25071/1874-6322.40554Keywords:
Socialist institutions and their transitions, Business cycles, Shocks and vulnerability, Historic reduction of poor, Patterns of development, Shapley value decomposition, Lognormal distribution, Gibrat’s law, Mode-based decomposition method, Growth and distribution effects of the lower income segmentsAbstract
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 the lognormal distribution from the household sample surveys applying the maximum likelihood estimation. Then, it performs the residual-free and the time-reversion consistent decomposition into growth and distribution effects for the segments of poor. The case study focuses the post Doi Moi, 1993-2014, where historical reduction of poverty happened. The results indicate that the distribution effect adversely affects the bottom 10 and 20 per cent of the population, unlike the growth effect that mostly induced the decrease of poor. Inducing growth that targets the mean or per capita income increase are good for the poor on average. Still, it could fail to capture the sensitive change of the lower segments, which is particularly vulnerable to shocks and fluctuations of business cycle.
