Analysing Economic Growth and Environmental Quality: A Classical and Bayesian Approach

This empirical study investigates the intricate relationship between the ecological environment and economic growth within the context of Zhejiang Province, China - a region characterised by its rapid urbanisation and significant economic development. By analysing data spanning from 2011 to 2020, the research applies the Environmental Kuznets Curve (EKC) model, which hypothesises an inverted U-shaped relationship between environmental degradation and economic growth, within both classical and Bayesian statistical frameworks to examine the province’s per capita GDP. Findings from both statistical approaches reveal a distinct correlation between economic progression and environmental conditions, underscoring the Environmental Kuznets Curve hypothesis. Additionally, this study conducts a comparative analysis between Vector Autoregression (VAR) and Bayesian Vector Autoregression (BVAR) models to evaluate their predictive capabilities concerning the interplay between ecological health and economic advancement in Zhejiang. The BVAR model, with its incorporation of Bayesian statistics, demonstrates superior forecasting precision, providing valuable insights into the dynamics governing the relationship between economic growth and the ecological environment in Zhejiang Province.