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Neoclassical versus Frontier Production Models? Testing for the Skewness of Regression Residuals

  • Timo Kuosmanen
  • Mogens Fosgerau

The empirical literature on production and cost functions is divided into two strands. The neoclassical approach concentrates on model parameters, while the frontier approach decomposes the disturbance term to a symmetric noise term and a positively skewed inefficiency term. We propose a theoretical justification for the skewness of the inefficiency term, arguing that this skewness is the key testable hypothesis of the frontier approach. We propose to test the regression residuals for skewness in order to distinguish the two competing approaches. Our test builds directly upon the asymmetry of regression residuals and does not require any prior distributional assumptions. Copyright � The editors of the "Scandinavian Journal of Economics" 2009. .

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Article provided by Wiley Blackwell in its journal Scandinavian Journal of Economics.

Volume (Year): 111 (2009)
Issue (Month): 2 (06)
Pages: 351-367

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Handle: RePEc:bla:scandj:v:111:y:2009:i:2:p:351-367
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  1. Godfrey, L. G. & Orme, C. D., 1991. "Testing for skewness of regression disturbances," Economics Letters, Elsevier, vol. 37(1), pages 31-34, September.
  2. Alicia Pérez Alonso, 2006. "A Bootstrap Approach To Test The Conditional Symmetry In Time Series Models," Working Papers. Serie AD 2006-18, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
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  9. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
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  11. Fan, Yanqin & Li, Qi & Weersink, Alfons, 1996. "Semiparametric Estimation of Stochastic Production Frontier Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(4), pages 460-68, October.
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  15. Ondrich, Jan & Ruggiero, John, 2001. "Efficiency measurement in the stochastic frontier model," European Journal of Operational Research, Elsevier, vol. 129(2), pages 434-442, March.
  16. Timo Kuosmanen, 2008. "Representation theorem for convex nonparametric least squares," Econometrics Journal, Royal Economic Society, vol. 11(2), pages 308-325, 07.
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