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Consistent method of moments estimation of the true fixed effects model

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  • Wikström, Daniel

Abstract

About a decade ago William H. Greene introduced the so-called ‘True fixed effects’ (TFE) model, which is intended to discriminate between heterogeneity and efficiency in stochastic frontier analysis. We would say that the TFE model has had a huge impact on applied stochastic frontier analysis. One problem with the original TFE estimator, is its inconsistency in cases with finite time observations, at least for the variance components. For the normal-half-normal model, this problem was solved by Chen et al. (2014) based on maximum likelihood estimation of the within-transformed model. In this study, we illustrate the possibilities offered by method of moments estimation. This approach is more flexible than the MLE proposed by Chen et al. (2014), since the method of moments estimators are not so closely dependent on the distributional assumptions and do not hinge on an explicit distribution of the random error. We only assume symmetry, as well as a fixed fourth-order cumulant for more complicated models. Greene’s methodology can, and has been, generalized to other models than the normal-half-normal model. However, the method of moments estimators proposed here are consistent.

Suggested Citation

  • Wikström, Daniel, 2015. "Consistent method of moments estimation of the true fixed effects model," Economics Letters, Elsevier, vol. 137(C), pages 62-69.
    • Handle: RePEc:eee:ecolet:v:137:y:2015:i:c:p:62-69
    DOI: 10.1016/j.econlet.2015.08.036
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    References listed on IDEAS

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    1. Greene, William H., 1990. "A Gamma-distributed stochastic frontier model," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 141-163.
    2. Willam Greene, 2005. "Fixed and Random Effects in Stochastic Frontier Models," Journal of Productivity Analysis, Springer, vol. 23(1), pages 7-32, January.
    3. Chen, Yi-Yi & Schmidt, Peter & Wang, Hung-Jen, 2014. "Consistent estimation of the fixed effects stochastic frontier model," Journal of Econometrics, Elsevier, vol. 181(2), pages 65-76.
    4. 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.
    5. Wang, Hung-Jen & Ho, Chia-Wen, 2010. "Estimating fixed-effect panel stochastic frontier models by model transformation," Journal of Econometrics, Elsevier, vol. 157(2), pages 286-296, August.
    6. Greene, William, 2005. "Reconsidering heterogeneity in panel data estimators of the stochastic frontier model," Journal of Econometrics, Elsevier, vol. 126(2), pages 269-303, June.
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    Cited by:

    1. Satya Paul & Sriram Shankar, 2020. "Estimating efficiency effects in a panel data stochastic frontier model," Journal of Productivity Analysis, Springer, vol. 53(2), pages 163-180, April.
    2. Paul, Satya & Shankar, Sriram, 2018. "Modelling Efficiency Effects in a True Fixed Effects Stochastic Frontier," MPRA Paper 87437, University Library of Munich, Germany.

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    More about this item

    Keywords

    Stochastic frontier; Fixed effects; Panel data; Method of moments;
    All these keywords.

    JEL classification:

    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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