Conditional nonparametric frontier models for convex and nonconvex technologies: a unifying approach |
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Authors: | Cinzia Daraio Léopold Simar |
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Institution: | (1) Department of Electrical Systems and Automation, University of Pisa, Pisa, Italy;(2) Institut de Statistique, Université Catholique de Louvain, Louvain-la-Neuve, Belgium |
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Abstract: | The explanation of productivity differentials is very important to identify the economic conditions that create inefficiency
and to improve managerial performance. In the literature two main approaches have been developed: one-stage approaches and
two-stage approaches. Daraio and Simar (2005, J Prod Anal 24(1):93–121) propose a fully nonparametric methodology based on
conditional FDH and conditional order-m frontiers without any convexity assumption on the technology. However, convexity has always been assumed in mainstream production
theory and general equilibrium. In addition, in many empirical applications, the convexity assumption can be reasonable and
sometimes natural. Lead by these considerations, in this paper we propose a unifying approach to introduce external-environmental
variables in nonparametric frontier models for convex and nonconvex technologies. Extending earlier contributions by Daraio
and Simar (2005, J Prod Anal 24(1):93–121) as well as Cazals et al. (2002, J Econometrics 106:1–25), we introduce a conditional
DEA estimator, i.e., an estimator of production frontier of DEA type conditioned to some external-environmental variables
which are neither inputs nor outputs under the control of the producer. A robust version of this conditional estimator is
proposed too. These various measures of efficiency provide also indicators of convexity which we illustrate using simulated
and real data.
Cinzia Daraio received Research support from the Italian Ministry of Education Research on Innovation Systems Project (iRis)
“The reorganization of the public system of research for the technological transfer: governance, tools and interventions”
and from the Italian Ministry of Educational Research Project (MIUR 40% 2004) “System spillovers on the competitiveness of
Italian economy: quantitative analysis for sectoral policies” which are acknowledged.
Léopold Simar received Research support from the “Interuniversity Attraction Pole”, Phase V (No. P5/24) from the Belgian Government
(Belgian Science Policy) is acknowledged. |
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Keywords: | Convexity External-environmental factors Production frontier Nonparametric estimation Robust estimation |
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