2005/12 | LEM Working Paper Series | |
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Conditional Nonparametric Frontier Models for Convex and Non Convex Technologies: a Unifying Approach |
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Cinzia Daraio, Léopold Simar |
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Keywords | ||
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Convexity, External-Environmental Factors, Production Frontier, Nonparametric Estimation, Robust Estimation.
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JEL Classifications | ||
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C13, C14, D20.
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Abstract | ||
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The explanation of productivity differentials is very important to identify the economic conditions
that create inefficiency and to improve managerial performance. In literature two main approaches have
been developed: one-stage approaches and two-stage approaches. Daraio and Simar (2003) propose a full
nonparametric methodology based on conditional FDH and conditional order-m frontiers without any convexity
assumption on the technology. On the one hand, convexity has always been assumed
in mainstream production theory and general equilibrium. On the other hand, in many empirical applications,
the convexity assumption can be reasonable and sometimes natural. Leading by these considerations, in this paper
we propose a unifying approach to
introduce external-environmental variables in nonparametric frontier models for convex
and non convex technologies. Developing further the work done in Daraio and Simar
(2003) 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 also proposed. These various measures of efficiency provide
also indicators of convexity. Illustrations through simulated and real data (mutual
funds) examples are reported.
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