Does national governance shape the effects of economic policy uncertainty on capital allocation efficiency?

Purpose This study aims to examine how economic policy uncertainty (EPU) affects firms’ capital allocation efficiency (CAE) and whether national governance (NGI) reduces uncertainty-driven investment inefficiencies. Design/methodology/approach This study uses unbalanced panel data of non-financial firms listed on the Bombay Stock Exchange 500 index over the period 2016–2024. CAE is measured as the inverse of investment inefficiency, estimated through investment inefficiency residuals. Panel data quantile regression (PDQR) is used to capture the heterogeneous effects of EPU, and NGI is included as a moderating factor. The PDQR models control for firm-level characteristics, as well as year and sector fixed effects. The results remain robust under system generalized method of moments estimation, addressing potential endogeneity concerns. Findings EPU significantly improves firms, with stronger effects observed at the higher quantiles (Q50 and Q75). NGI significantly moderates the relationship between EPU and CAE, although it does not have a direct effect on CAE. The findings indicate that the impact of EPU on firms’ CAE varies with the quality of national governance. Practical implications The findings highlight that EPU exerts a disciplining effect on CAE, particularly for moderately and highly inefficient firms. While NGI does not reduce inefficiency directly, a stronger institutional framework plays a moderating role by influencing how firms respond to uncertainty. These results suggest that policy should focus on strengthening governance to enhance firms’ adaptive capacity during uncertainty periods. Originality/value This study provides novel distributional evidence by using PDQR to capture heterogeneity across firms. Furthermore, the study contributes by including NGI as a moderating factor in an emerging market context. This study highlights the role of institutional quality in influencing firm responses to uncertainty.