Stock market development, bank credit, and renewable energy as drivers of carbon intensity using a wavelet quantile approach

This study examines the time-dependent, nonlinear, and distributional heterogeneity of stock market expansion, bank credit, trade openness, and renewable energy in their influence on carbon intensity in Vietnam, an emerging economy with developing financial markets and an ongoing energy transition. To improve temporal detail, the study modified the data to quarterly intervals using a quadratic match-sum and used a wavelet–quantile technique based on Wavelet Quantile Regression (WQR) and Wavelet Quantile Correlation (WQC) to examine heterogeneity across quantiles and time scales. Decomposing influence over time is a novel methodological contribution to the field, in contrast to traditional analyses that aggregate findings across a single scale or employ mean-level techniques. The results show that the stock market and bank credit are two consistently positive and unexpected determinants of carbon intensity. As the stock market expands and bank credit increases, carbon intensity rises in short- and medium-term cycles, with stronger effects at higher quantiles. As expected, economic expansion raises carbon intensity, with long-term effects. At upper quantiles and over medium- to long-term cycles, economic growth consistently raises carbon intensity, indicating that growth-driven industrialization amplifies emissions, particularly during high-emission regimes. Renewable energy consistently reduces carbon intensity across almost all quantiles (and time–frequency bands), with a substantial quantitative impact on decarbonization, and it also has a long-term effect by facilitating technological upgrading and greener production. These findings show that Vietnam needs green-oriented funding, energy capacity and production, and pro-green trade policies to achieve low-carbon growth.