Faculty Publications
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Item Nexus between climate policy uncertainty and economic policy uncertainty among BRIC nations: evidence from ARDL and NARDL approach(Emerald Publishing, 2025) Akshaya, A.; Gopalakrishna, B.V.Purpose – Climate policy is a collective name for the set of initiatives and legal frameworks that nations and international organizations have put in place to address the challenges of climate change. In this empirical analysis, we have studied the symmetric and asymmetric association between climate policy uncertainty (CPU) and economic policy uncertainty (EPU) among the BRIC nations. Design/methodology/approach – In the present analysis, the authors have used the autoregressive distributed lag (ARDL) and nonlinear autoregressive distributed lag (NARDL) models, which help explain the linear and nonlinear relationships among the variables. Descriptive statistics, stationarity tests and BDM statistics for nonlinearity are applied in the study to determine the data characteristics. Findings – Our model results demonstrate that the CPU has a significant impact on the EPU of the BRIC nations, except for India and the association is symmetric. India’s economic policies are more stable than those of other BRIC countries. Research limitations/implications – Due to the growing issue of climate change and its impact on economic policies, emerging nations must develop stable climate action plans to mitigate the effects on their economic policies. This empirical investigation will help economic policymakers and businesses to adopt appropriate growth and development policies. Originality/value – This study makes a novel contribution by being the first to examine how CPU influences EPU in emerging economies. The research question and methodological approach not only enrich the academic discourse but also provide valuable insights for the formulation of economic policy. © 2025 Emerald Publishing LimitedItem Impact of climate and economic policy uncertainties on inflation in India: using the vector error correction model approach(Springer Science and Business Media B.V., 2025) Akshaya, A.; Gopalakrishna, B.V.Economic policies are designed to address challenges in the economic environment and mitigate future associated risks and uncertainties. The present study addressed the impact of policy uncertainties such as climate policy uncertainty (CPU) and economic policy uncertainty (EPU) on price inflation in India. The data were sourced from the Reserve Bank of India and Policy Uncertainty databases from April 2004 to March 2024. Descriptive statistics and stationarity tests were conducted to analyze the characteristics of the variables. Johansen’s cointegration test assessed the long-term relationships among the regressors. The vector error correction model (VECM) and impulse response function (IRF) were used to evaluate long-run equilibrium dynamics and the responsiveness of inflation to policy uncertainties. The empirical outcomes specified a significant relationship between inflation and economic policy uncertainty, while climate policy uncertainty exhibited an insignificant positive effect on inflation. These findings suggest that policy uncertainties influence inflation and broader economic stability. The study emphasizes the importance of formulating coherent and stable economic policies to mitigate inflationary pressures and foster economic resilience. © The Japan Section of the Regional Science Association International 2025.Item Climate anomalies and stock market dynamics: Evidence from empirical analysis(Academic Press, 2025) Akshaya, A.; Gopalakrishna, B.V.The longstanding variation in average climate parameters, typically occurring over decades or longer, is known as climate change. The authors examine the impact of climate change anomalies, specifically the changes in temperature and precipitation, on the equity market. This empirical approach utilized monthly long-term time-series data from 1996 to 2024, comprising 348 observations. To test the empirical association between the variables, the study employed the autoregressive distributed lag (ARDL) and Nonlinear ARDL (NARDL) models. The findings of this analysis reveal a significant short-run symmetric effect of temperature changes on market volatility (? = 0.0004, p = 0.010). Increasing temperatures intensify market instability, suggesting that short-term climatic shocks amplify investor uncertainty and risk perception, and heighten market momentum. In contrast, increasing precipitation exhibits a long-term stabilizing effect (? = ?8.91e-06, p = 0.032), indicating that higher rainfall helps mitigate market instability over time. The alternative explanatory data from the World Bank and the GARCH model results are robust to the primary outcome. The study's outcomes provide valuable insights for regulatory bodies' climate disclosure policies and highlight the importance of proactive hazard management, particularly for investors in emerging markets and vulnerable sectors that are more susceptible to climate-driven volatility. © 2025 Elsevier Ltd