A note on parameterizing input distance functions: does the choice of a functional form matter?

Rolf Färe () and Michael Vardanyan

Journal of Productivity Analysis, 2016, vol. 45, issue 2, 130 pages

Abstract: We use a Monte Carlo experiment to compare the quadratic and translog functional forms in terms of their ability to approximate known frontiers that possess convex curvature. Unlike some of the existing simulation studies that have considered concave frontiers, we find that both functional forms provide a reliable approximation when a true frontier is convex. Our results lend support to existing intuitive explanations concerning the translog form’s innate propensity to yield convex, rather than concave, frontier estimates, suggesting that it should fare relatively well when modeling input isoquants. We also demonstrate that the quadratic functional form loses less of its flexibility than the translog function when shape constraints are imposed to satisfy regularity. Copyright Springer Science+Business Media New York 2016

Keywords: Distance functions; Parameterization; D24; C63 (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (6)

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Working Paper: A note on parameterizing input distance functions: does the choice of a functional form matter? (2016)
Working Paper: A Note on Parameterizing Input Distance Functions: Does the Choice of a Functional Form Matter? (2014)
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Persistent link: https://EconPapers.repec.org/RePEc:kap:jproda:v:45:y:2016:i:2:p:121-130

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DOI: 10.1007/s11123-015-0448-9

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