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A Note on a Unified Approach to the Frontier Production Function Models With Correlated Non-Normal Error Components: The Case of Cross Section Data

Author

Listed:
  • Manoranjan Pal

    (Economic Research Unit, Indian Statistical Institute 203 B. T. Road, Kolkata 700 108, India)

Abstract

This paper reviews the Stochastic Frontier Production Function (SFPF) Models with error components, termed as technical inefficiency error and noise variable in a cross section framework. It tries to unify all such models incorporating (i) truncation or non-normality of the technical inefficiency error term and (ii) correlation between the two error components. Allocative inefficiency error terms are also introduced and are assumed to be correlated among themselves. JEL Classification: C10

Suggested Citation

  • Manoranjan Pal, 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, Department of Economics, Delhi School of Economics, vol. 39(1), pages 7-18, January.
    • Handle: RePEc:dse:indecr:v:39:y:2004:i:1:p:7-18
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    Citations

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    Cited by:

    1. Hung-pin Lai & Cliff Huang, 2013. "Maximum likelihood estimation of seemingly unrelated stochastic frontier regressions," Journal of Productivity Analysis, Springer, vol. 40(1), pages 1-14, August.
    2. Arabinda Das, 2015. "Copula-based Stochastic Frontier Model with Autocorrelated Inefficiency," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 7(2), pages 111-126, June.
    3. Das, Arabinda, 2013. "Estimation of Inefficiency using a Firm-specific Frontier Model," MPRA Paper 46168, University Library of Munich, Germany.

    More about this item

    Keywords

    Frontier Production Function; Non - Normal Errors; Truncated Errors; Allocative Inefficiency; Technical Inefficiency;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General

    Statistics

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