An alternative probabilistic frontier analysis to the measurement of eco-efficiency

This study applies a nonparametric time dependent conditional frontier model to estimate and evaluate the convergence in eco-efficiency of a group of 51 US states over the period 1990-2017. Specifically, we utilize a mixture of global and local pollutants (carbon dioxide CO2, sulphur dioxide SO2 and nitrogen oxides NOx) to capture the environmental damage caused by the anthropogenic activities. The empirical findings indicate divergence for the whole sample, while specific groups of convergence club regions are formulated dividing the US states into worst and best performers. Moreover, Our findings reveal significant convergence patterns between the US regions over the sample period.