Climate Transition Risk and Stock Market Dynamics in Emerging Economies: A Panel ARDL ApproachBrazil, China, India and South Africa, 2015-2025

Abstract

This study examines the relationship between climate transition risk and stock-market dynamics in four major emerging economies - Brazil, China, India and South Africa - using monthly data from January 2015 to December 2025. Climate transition risk is proxied primarily by country-specific climate policy uncertainty (CPU), while inflation, the bilateral exchange rate against the US dollar, the CBOE Volatility Index (VIX), Brent crude oil prices and geopolitical risk are incorporated as macro-financial controls. The master panel contains 528 country-month observations. Because the South African national CPU series begins in July 2018, the principal country-CPU Panel ARDL analysis uses a balanced July 2018-December 2025 sample of 360 observations; the unavailable pre-July-2018 South African CPU observations are not imputed. Cross-sectional-dependence diagnostics indicate substantial common shocks, while unit-root diagnostics support a mixture of I(0) and I(1) variables and no evidence that the core variables are I(2). The preferred baseline specification is approximately ARDL(2,1). Pooled Mean Group (PMG) estimates show that country-specific CPU is statistically insignificant in both the long run (0.0590, p=0.271) and short run (0.0012, p=0.535). In contrast, short-run inflation, exchange-rate changes and VIX changes are statistically significant. Error-correction behaviour is heterogeneous, with significant convergence for Brazil but weak or absent adjustment in the other markets. An extended model including Brent and geopolitical risk preserves the null CPU result. A robustness model using global CPU over the complete 2015-2025 panel yields only marginal long-run evidence (p=0.059). The findings suggest that emerging equity markets are more consistently associated with conventional macro-financial shocks than with country-specific climate-policy uncertainty, while global transition-policy signals may have a limited longer-run role. Residual cross-sectional dependence and heterogeneous adjustment imply that the PMG estimates should be complemented by cross-sectionally augmented estimators before strong long-run generalizations are made.