Does economic policy uncertainty affect public pension spending? Evidence from Japan

Abstract We study the impact of economic policy uncertainty (EPU) on public pension spending (PPS) in Japan from 1997 to 2024, employing the autoregressive distributed lag (ARDL) approach alongside kernel-based regularized least squares (KRLS), a machine learning method that does not require a predefined functional form. The results show that higher EPU is negatively associated with PPS in the long run, while short-run estimates indicate a significant positive association. The KRLS results show a somewhat larger negative association compared to the ARDL model, and estimates across EPU quantiles indicate that the negative association varies across the EPU distribution. Heterogeneity analysis further shows that the negative association differs between the pre- and post-Abenomics periods and strengthens during major global shocks, particularly the 2008 global financial crisis and the COVID-19 pandemic. Based on these findings, we discuss the policy implications and identify directions for future research.