Decomposing Poverty Change: A New Four-Dimensional Decomposition Method

In this study, we propose a new method for poverty decomposition that offers advantages such as time-reversion consistency. Our decomposition is based on the Shapley decomposition method from cooperative game theory. It separates changes in mean income into changes in total income and in total population. These two factors, combined with changes in inequality and the poverty line, generate four effects: growth, distribution, population, and poverty line effects. Our decomposition includes twenty-four possible ways, and we take the mean of these to compute the four effects. However, considering the practical significance of the poverty line effect, we compute this effect using the final period as the reference period. By excluding the eighteen decomposition ways that do not meet the conditions, we average the remaining six ways to obtain the constrained four-dimensional poverty decomposition method. Applying this method to China for the period 2001–2022 demonstrates its feasibility under different poverty lines. We believe that the poverty decomposition method presented in this study has broad applicability and can help identify the sources of changes in poverty, thereby providing policymakers with valuable information to implement more effective antipoverty policies.