Does climate policy uncertainty affect carbon emissions in China? A novel dynamic ARDL simulation perspective

Abstract

Abstract This study provides new insights into the impact of climate policy uncertainty, energy consumption, and economic development on China’s carbon emissions. In doing so, we develop a novel index of China’s climate policy uncertainty (CCPU). We then use the newly constructed dynamic autoregressive distributed lag (ARDL) simulation model, the frequency-domain causality (FDC) test, and the fully modified OLS (FMOLS) estimation to investigate these potential relationships from 2005 to 2021. The empirical results suggest that increasing CCPU reduces carbon emissions in most parts of China, which improves environmental degradation. Furthermore, the effects of energy consumption and economic growth on carbon emissions are confirmed to be positive in each location. Finally, the results of the FDC and FMOLS confirm the robustness of the model. Our findings suggest that information from the CCPU can be used to forecast CO2 emissions in China. Furthermore, the government should strike a balance between economic growth and environmental regulation and promote the use of renewable energy to reduce carbon emissions. Proactively developing climate policy is important to achieve the goal of carbon neutrality.