Ricerc@Sapienza

In this paper, we demonstrate that standard central limit theorem (CLT) results do not hold for means of non-parametric, conditional efficiency estimators, and we provide new CLTs that permit applied researchers to make valid inference about mean conditional efficiency or to compare mean efficiency across groups of producers. The new CLTs are used to develop a test of the restrictive ‘separability’ condition that is necessary for second-stage regressions of efficiency estimates on environmental variables.

Directional distances provide useful, flexible measures of technical efficiency of production units relative to the efficient frontier of the attainable set in input-output space. In addition, the additive nature of directional distances permits negative input or outputs quantities. The choice of the direction allows analysis of different strategies for the units attempting to reach the efficient frontier. Simar et al.

Conditional efficiency measures are needed when the production process does not depend only on the inputs and outputs, but may be influenced by external factors and/or environmental variables (Z). They are estimated by means of a nonparametric estimator of the conditional distribution function of the inputs and outputs, conditionally on values of Z. For doing this, smoothing procedures and smoothing parameters, the bandwidths, are involved.