The herein presented study estimates cross-country environmental efficiency using a novel Bayesian data envelopment analysis (DEA) approach and regresses it on formal institutional factors such as control of corruption and government effectiveness. It has been proven that the Bayesian DEA approach used in this study yields valid estimates that outperform other extant bias-correction DEA techniques (e.g., lower mean square error and mean absolute error). The regression analysis draws on a two-step generalized method of moments (GMM) for linear dynamic panel data. The study uses a balanced panel of 144 countries from 2002 to 2019, classified into developed and developing. In line with the economic growth and some of the environmental efficiency literature, the study identified an inverse relationship between control of corruption and developing countries' environmental efficiency. This effect is statistically significant but marginal, while it is not statistically significant for developed countries. This finding expands the “grease the wheel” theory to environmental efficiency. Additionally, the effect of lagged environmental efficiencies on current environmental performance is strong and statistically significant, signifying the need for countries’ commitment further to regulate energy consumption and its by-product, CO2 emissions.