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GMM estimation of stochastic frontier model with endogenous regressors

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  • Tran, Kien C.
  • Tsionas, Efthymios G.

Abstract

A convenient and simple GMM procedure for estimating stochastic frontier models in the presence of endogenous regressors is proposed. Monte Carlo simulations show that the proposed estimator works very well in finite samples. We apply the proposed method to panel data of Norwegian dairy farms to illustrate the usefulness of the proposed approach.

Suggested Citation

  • Tran, Kien C. & Tsionas, Efthymios G., 2013. "GMM estimation of stochastic frontier model with endogenous regressors," Economics Letters, Elsevier, vol. 118(1), pages 233-236.
    • Handle: RePEc:eee:ecolet:v:118:y:2013:i:1:p:233-236
    DOI: 10.1016/j.econlet.2012.10.028
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    References listed on IDEAS

    as
    1. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    2. Newey, Whitney K., 1984. "A method of moments interpretation of sequential estimators," Economics Letters, Elsevier, vol. 14(2-3), pages 201-206.
    3. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    4. Kutlu, Levent, 2010. "Battese-coelli estimator with endogenous regressors," Economics Letters, Elsevier, vol. 109(2), pages 79-81, November.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Endogeneity; Generalized method of moments; Maximum likelihood; Technical efficiency;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General

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