Dynamic relationship between carbon emissions and climate policy uncertainty: a dynamic symmetric and asymmetric fourier causality analysis

Abstract

This paper tests the causal link between climate policy uncertainty (CPU) and carbon dioxide (CO2) emissions in the United States from April 1987 to February 2022. In this paper, we use a novel CPU index recently developed and employ a novel econometric methodology, dynamic symmetric and asymmetric Fourier causality tests. The findings of the causality tests show a symmetric causality relationship from CO2to CPU, and a unidirectional causality runs from positive shocks of CO2to positive shocks of CPU. We also run the causality test in a dynamic framework to test the instabilities in the causality relationship. The dynamic symmetric causality test results show a significant unidirectional causality from CO2(CPU) to CPU (CO2) for specific periods. Since different shocks may affect the causality relationship, we test the causality relationship by considering positive and negative shocks. The asymmetric causality test results show a significant unidirectional asymmetric causality from positive shocks of CO2(CPU) to positive shocks of CPU (CO2) for certain periods. Finally, the asymmetric causality test results also show a unidirectional asymmetric causality from negative shocks of CO2(CPU) to negative shocks of CPU (CO2) for certain periods. Based on our results indicating a significant causal link between CPU and CO2, governments and policymakers should avoid policies and decisions that may lead to such uncertainties.