Demographic Transition and the Dynamics of Income Distribution in Japan: A Bayesian State-Space Approach

TL;DR

This paper introduces a Bayesian state-space model to analyze how demographic changes like aging influence income inequality in Japan, using only grouped income data.

Contribution

It develops a novel Bayesian framework combining GB2 distribution with latent parameters to track income distribution dynamics over time.

Findings

Demographic factors significantly impact income inequality.

Aging affects lower income distribution tails.

Household size decline influences upper income distribution tails.

Abstract

We develop a Bayesian state-space model for analyzing the dynamic evolution of income distributions using grouped income data. The model combines the generalized beta distribution of the second kind (GB2) with latent time-varying parameters to capture changes in the entire income distribution over time. Using Japanese household income data, we examine how demographic factors, particularly population aging and declining household size, affect inequality dynamics. The results show that demographic changes have heterogeneous effects across different parts of the income distribution and contribute substantially to the evolution of inequality. Counterfactual analyses indicate that aging and household size changes affect the lower and upper tails of the distribution differently. Because the proposed framework requires only grouped income data, it can be applied to countries where micro-level income data are unavailable.