Investigating the relationship between digital trade, natural resources, energy transition, and green productivity: Moderating role of R&D investment

This study investigates the influence of the green energy transition, natural resources dependency, digital trade, and environmental regulations on green productivity in selected OECD countries from 1990 to 2019. Considering the directional distance function (DDF) approach, it constructed the green productivity index and applied the heterogeneous linear panel estimations such as D-OLS "dynamic ordinary least square" and FE-OLS "fixed effects ordinary least square" to investigate the long-run relationship between variables. Further, it determines the magnitude of the variable association by addressing the quantile-based influence of the independent variables on the dependent variable using "Method of Moments Quantile Regression" (MMQR). The study also investigates the moderating effect of domestic R&D intensity and human capital to support the nexus between digital trade and green productivity. The outcomes of the MMQR suggested that digital trade is negatively associated with green productivity at low to medium quantiles, while at the highest quantiles, the relationship became positive. In contrast, green energy transition, environmental regulation, domestic R&D intensity, and human capital are significantly and positively associated with green productivity at all quantiles. Manifestly, natural resource dependency impedes green productivity at lower, medium, and higher quantiles. The marginal effects of the above variables are substantially heterogeneous at different levels of productivity growth. It suggests the transformation of industries from resource-dependent to high-tech and R&D to facilitate higher productivity growth.