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On the choice of functional form in stochastic frontier modeling

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Abstract.

This paper examines the effect of functional form specification on the estimation of technical efficiency using a panel data set of 125 olive-growing farms in Greece for the period 1987–93. The generalized quadratic Box-Cox transformation is used to test the relative performance of alternative, widely used, functional forms and to examine the effect of prior choice on final efficiency estimates. Other than the functional specifications nested within the Box-Cox transformation, the comparative analysis includes the minflex Laurent translog and generalized Leontief that possess desirable approximation properties. The results indicate that technical efficiency measures are very sensitive to the choice of functional specification. Perhaps most importantly, the choice of functional form affects the identification of the factors affecting individual performance – the sources of technical inefficiency. The analysis also shows that while specification searches do narrow down the set of feasible alternatives, the identification of the most appropriate functional specification might not always be (statistically) feasible.

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First version received: November 1999/Final version received: July 2001

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ID="*"  The authors wish to thank Almas Heshmati, Robert Romain, and an anonymous referee for insightful comments and suggestions. Special thanks go to the associate editor who handled the paper, and whose careful reading and suggestions have improved the paper substantially. The second author wishes to acknowledge the financial support from “President SSHRC” from the University of Saskatchewan. The usual caveats with respect to opinions expressed in the paper apply. Senior authorship is shared. This is University of Nebraska-Lincoln Agricultural Research Division Article No. 13270.

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Giannakas, K., Tran, K. & Tzouvelekas, V. On the choice of functional form in stochastic frontier modeling. Empirical Economics 28, 75–100 (2003). https://doi.org/10.1007/s001810100120

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  • DOI: https://doi.org/10.1007/s001810100120

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