Testing load capacity and environmental Kuznets curve hypothesis for China: Evidence from novel dynamic autoregressive distributed lags model

Abstract

Climate changes are occurring faster than expected and affecting human lives through increasing carbon emissions, food scarcity and changes in global temperatures. Following this trend, China is one of the top contributors to global pollution, and at the same time, it is a leading producer of electricity production from renewable sources (ELREC). The current research examines the relationship between ELREC, research and development (REDEV), and economic growth and their impact on three environmental quality indicators: carbon dioxide emissions, ecological footprint, and load capacity factor in China from 1985 to 2018. This research is significant because it helps to identify factors contributing to the environmental deterioration in China and how they can be addressed. Using the autoregressive distributed lag and dynamic autoregressive distributed lag model, the research suggests a load capacity curve (LCC) and simultaneously tests the LCC and environmental Kuznets curve (EKC) hypotheses. The findings indicate that the LCC and EKC hypotheses are viable in China and that ELREC favorably influences environmental quality. Additionally, REDEV has a significant impact on environmental indicators. The findings of this research reveal, in general, that sustainable REDEV, prioritizing environmental protection, and transitioning towards renewable energy sources are crucial elements of China's green development strategy. This study's findings provide valuable insights for policymakers and stakeholders working to improve environmental quality in China.