Estimation of Inefficiency using a Firm-specific Frontier Model

Das, Arabinda (2013): Estimation of Inefficiency using a Firm-specific Frontier Model.

Abstract

It has been argued that the deterministic frontier approach in inefficiency measurement has a major limitation as inefficiency is mixed with measurement error (statistical noise) in this approach. The result is that inefficiency is contaminated with noise. Later stochastic frontier approach improves the situation with allowing a statistical noise in the model which captures all other factors other than inefficiency. The stochastic frontier model has been used for inefficiency analysis despite its complicated form and estimation procedure. This paper introduced an extra parameter which estimates the amount of proportion that an error component shares in the observational error. An EM estimation approach is used for estimation of the model and a test procedure is developed to test the significance of presence of the error component in the observational error.

• Item Type: MPRA Paper
• Language: English
• Keywords: stochastic frontier model, skew-normal distribution, identification, EM algorithm, Monte Carlo simulation.
• Subjects: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C15 - Statistical Simulation Methods: General; C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C21 - Cross-Sectional Models ; Spatial Models ; Treatment Effect Models ; Quantile Regressions; C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C51 - Model Construction and Estimation

References

Aigner, D. C. and S. F. Chu (1968) On Estimating the Industry Production Function. American Economic Review, 58:4, 826-839.

Aigner, D., K. Lovell and P. Schmidt (1977) Formulation and Estimation of Stochastic Frontier Production Function Models, Journal of Econometrics, 6, 21-37.

Azzalini A. (1985) A Class of Distributions which includes the Normal Ones, Scand. J. Statistics, 12, 171-178.

Battese, G. and G. Corra (1977) Estimation of a Production Frontier Model with Application to the Pastoral Zone off Eastern Australia. Australian Journal of Agricultural Economics, 21, 169-179.

Cobb, C. and P. H. Douglas (1928) A Theory of Production. American Economic Review, Supplement, 18, 139-165.

Greene, W. H. (1980) On the Estimation of a Flexible Frontier Production Model. Journal of Econometrics, 13:1, 101-115.

Greene, W. H. (1990) A Gamma Distributed Stochastic Frontier Model. Journal of Econometrics, 46, 141-164.

Jondrow, J., I. Materov, K. Lovell and P. Schmidt (1982) On the Estimation of Technical Inefficiency in the Stochastic Frontier Production Function Model, Journal of Econometrics, 19, 233-238.

Kumbhakar, S., and K. Lovell (2000) Stochastic Frontier Analysis, Cambridge University Press, Cambridge.

Meeusen, W. and J. van den Broeck (1977) Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error, International Economic Review, 18, 435-444.

Pal, M. (2004) A note on a unified approach to the frontier production function models with correlated non-normal error components: the case of cross-section data, Indian Economic Review, 39, 7–18.

Pal, M. and A. Sengupta (1999) A model of FPF with correlated error components: an application to Indian agriculture, Sankhya B, 61, 337–50.

Richmond, J. (1974) Estimating the Efficiency of Production, International Economic Review, 15:2, 515-521.

Ruggiero, J. (1999) Efficiency Estimation and Error Decomposition in the Stochastic Frontier Model: A Monte Carlo Analysis. European Journal of Operational Research, 115:3, 555-563.

Schmidt, P. (1976) On the Statistical Estimation of Parametric Frontier Production Functions. Review of Economics and Statistics, 58:2, 238-239.

Stevenson, R. (1980) Likelihood Functions for Generalized Stochastic Frontier Estimation. Journal of Econometrics, 13, 57-66.

Timmer, C. P. (1971) Using a Probabilistic Frontier Production Function to Measure Technical Efficiency. Journal of Political Economy, 79:4, 776-794.

Winsten, C. B. (1957) Discussion on Mr. Farrell’s Paper. Journal of the Royal Statistical Society, Series A, 120:3, 282-284.

Wu, C. F. J. (1983) On the convergence properties of the EM algorithm, The Annals of Statistics, 11, 95–103.