英文摘要 |
This article uses two types of the DEA (data envelopment analysis)method to estimate the production efficiency of countries: one does notconsider undesirable output, and the other one considers carbon dioxideas an undesirable output. By comparing the results from these two typesof efficiency estimation, we find that the efforts by European countries inrecent years have paid off, which is different from results in the pastliterature. This study employs a spatial quantile regression model toanalyze the factors affecting the efficiency of national production. Themodel solves the problem of data exhibiting spatial correlation andheterogeneity and therefore avoids biased estimations. We show that thedegree of corruption affecting high production efficiency countries ismore significant, that foreign direct investment has a significant effectfor less efficient countries, and that trade might have a negative impactfor highly productive countries. By considering undesirable output, whenspatial correlation does exist, the least efficient countries do not get thebenefits through technology spillover from adjacent countries. The extentof corruption influences highly productive countries more negativelythan inefficient countries, because the high degree of corruption in higherproductive countries allows for an increase in carbon dioxide emissions.In addition, the least productive countries no longer benefit from foreigndirect investment. Finally, we note that an increase in trade likely leads tolower production efficiency in less efficient countries. |