A1364
Title: Estimating nonparametric conditional frontiers and efficiencies: A new approach
Authors: Camilla Mastromarco - University of Calabria (Italy) [presenting]
Leopold Simar - Universite Catholique de Louvain (Belgium)
Ingrid Van Keilegom - KU Leuven (Belgium)
Abstract: Conditional frontiers measures are a flexible and appealing approach to considering the role of environmental variables in the production process. Direct approaches estimate non-parametrically conditional distribution functions requiring smoothing techniques and the use of selected bandwidths. The statistical literature produces ways to derive bandwidths of optimal order, by using, e.g., least squares cross-validation techniques. However, it has been shown that the resulting order may not be optimal when estimating the boundary of the distribution function. As a consequence, the direct approaches may suffer from some statistical instability. We suggest a fully nonparametric approach which avoids the problem of estimating these bandwidths, by eliminating, in a first step, the influence of the environmental factors on the inputs and the outputs. By doing this, we produce pure inputs and outputs, which allow estimating a pure measure of efficiency, which is more reliable for ranking the firms, since the influence of the external factors has been eliminated. This can be viewed as an extension of the use of location-scale models (semi-parametric structure) to full nonparametric models, based on nonseparable, nonparametric models. We are also able to recover the frontier and efficiencies in original units. We describe the method, its statistical properties and we show in some Monte Carlo simulations, how our new method dominates the traditional direct approach.
