A Homothetic Data Generated Technology

Antonio Peyrache ()
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Antonio Peyrache: School of Economics and Centre for Efficiency and Productivity Analysis (CEPA) at The University of Queensland, Australia

No WP042022, CEPA Working Papers Series from University of Queensland, School of Economics

Abstract: In this paper I propose a method for constructing an enlargement of a variable returns to scale (VRS) data generated production technology that will satisfy homotheticity. The method can be used both with convex and non-convex technologies and both in the single output and multiple output setting. The method is computationally fast, therefore it provides a tool that can be used on large datasets. An empirical illustration is provided based on a dataset of Italian courts of justice

Keywords: Input Homotheticity; Output Homotheticity; DEA; FDH; Efficiency (search for similar items in EconPapers)
JEL-codes: Q54 Q56 (search for similar items in EconPapers)
Date: 2022-04
New Economics Papers: this item is included in nep-eff
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:qld:uqcepa:176

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