Digital Technologies, Environmental Governance and Environmental Performance: Empirical Evidence from China

Abstract

This research conducts an empirical analysis of the relationship between digital technologies, environmental governance (assessed through environmental taxes), and China's environmental performance from 1995 to 2020. Additionally, within the framework of the STIRPAT model, the impacts of GDP and urbanization on ecological footprints are examined. This study is distinguished by its innovative approach to evaluating environmental performance via ecological footprints and the application of the Autoregressive Distributed Lag (ARDL) model along with Dynamic Ordinary Least Squares (DOLS), Canonical Cointegration Regression (CCR), and Fully Modified Ordinary Least Squares (FMOLS) as long-run estimators, methodologies not previously applied to this context in China. The findings indicate that digital technologies and environmental taxes contribute to a reduction in ecological footprints, while GDP and urbanization have an adverse effect, increasing ecological footprints. Post-estimation diagnostics confirm the absence of serial correlation and heteroskedasticity, and affirm the normal distribution of the disturbance terms. For a robustness check, the study further employs DOLS, FMOLS, and CCR methods, which corroborate the initial results regarding the beneficial impact of digital technologies and environmental governance on ecological footprints. Based on these findings, the study advises the Chinese government and policymakers to enact more effective environmental tax policies and leverage digital technologies to enhance environmental sustainability in China.