Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
In this study the non-parametric method of Data Envelopment Analysis (DEA) is applied to determine the technical efficiency (TE) index of the G7 countries, when variable returns to scale (VRS) hold for the entire period under consideration (1993–2016). As inputs labor and capital are used while we utilize GDP as output. In the second stage of our analysis the DEA bootstrap approach along the lines of Simar and Wilson (2007) is applied to deal with the disadvantages of a non-parametric DEA set up. Through this procedure we investigate the relationship between the efficiency evaluation of DMUs as calculated by the DEA method, in the first stage of our analysis, and the variables of arable land, total greenhouse gas emissions and total primary energy consumption. In addition, for these variables and through the estimated regression coefficients, elasticities and marginal effects of both TE and GDP index are calculated.