On the generation of a regular multi-input multi-output technology using parametric output distance functions

Sergio Perelman and Daniel Santín

CREPP Working Papers from Centre de Recherche en Economie Publique et de la Population (CREPP) (Research Center on Public and Population Economics) HEC-Management School, University of Liège

Abstract: Monte-Carlo experimentation is a well-known approach to test the performance of alternative methodologies under different hypothesis. In the frontier analysis framework, whatever parametric or non-parametric methods tested, most experiments have been developed up to now assuming single output multi-input production functions and data generated using a Cobb- Douglas technology. The aim of this paper is to show how reliable multi-output multi-input production data can be generated using a parametric output distance function approach. A flexible translog technology is used for this purpose that satisfies regularity conditions. Two meaningful outcomes of this analysis are the identification of a valid range of parameters values satisfying monotonicity and curvature restrictions and of a rule of thumb to be applied in empirical studies.

Keywords: Output distance function; technical efficiency, Monte-Carlo experiments. (search for similar items in EconPapers)
JEL-codes: C14 C15 C24 (search for similar items in EconPapers)
Date: 2005
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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