Nexus between climate policy uncertainty and economic policy uncertainty among BRIC nations: evidence from ARDL and NARDL approach
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Date
2025
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Publisher
Emerald Publishing
Abstract
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 Limited
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Keywords
Asymmetric, BRIC, Climate change, E63, Economic policy, F68, Q52, Q54, Symmetric, Uncertainty
Citation
Journal of Economic and Administrative Sciences, 2025, , , pp. 1-18
