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On measures of technical inefficiency and production uncertainty in stochastic frontier production model with correlated error components

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  • Debdas Bandyopadhyay
  • Arabinda Das

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  • Debdas Bandyopadhyay & Arabinda Das, 2006. "On measures of technical inefficiency and production uncertainty in stochastic frontier production model with correlated error components," Journal of Productivity Analysis, Springer, vol. 26(2), pages 165-180, October.
    • Handle: RePEc:kap:jproda:v:26:y:2006:i:2:p:165-180
    DOI: 10.1007/s11123-006-0011-9
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    References listed on IDEAS

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    1. Anil Bera & Subhash Sharma, 1999. "Estimating Production Uncertainty in Stochastic Frontier Production Function Models," Journal of Productivity Analysis, Springer, vol. 12(3), pages 187-210, November.
    2. Schmidt, Peter & Lin, Tsai-Fen, 1984. "Simple tests of alternative specifications in stochastic frontier models," Journal of Econometrics, Elsevier, vol. 24(3), pages 349-361, March.
    3. Kumbhakar, Sabul C., 1993. "Production risk, technical efficiency, and panel data," Economics Letters, Elsevier, vol. 41(1), pages 11-16.
    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. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    6. Murray D Smith, 2004. "Stochastic Frontier Models With Correlated Error Components," Econometric Society 2004 Australasian Meetings 121, Econometric Society.
    7. Greene, William H., 1990. "A Gamma-distributed stochastic frontier model," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 141-163.
    8. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
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    Citations

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    Cited by:

    1. Huang, Tai-Hsin & Chen, Kuan-Chen & Lin, Chung-I, 2018. "An extension from network DEA to copula-based network SFA: Evidence from the U.S. commercial banks in 2009," The Quarterly Review of Economics and Finance, Elsevier, vol. 67(C), pages 51-62.
    2. George Furstenberg, 2008. "Assessing the Competitiveness of International Financial Services in Particular Locations: A Survey of Methods and Perspectives," Open Economies Review, Springer, vol. 19(4), pages 539-556, September.
    3. Tsionas, Mike G., 2022. "Convex non-parametric least squares, causal structures and productivity," European Journal of Operational Research, Elsevier, vol. 303(1), pages 370-387.
    4. 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.
    5. Jianxu Liu & Mengjiao Wang & Ji Ma & Sanzidur Rahman & Songsak Sriboonchitta, 2020. "A Simultaneous Stochastic Frontier Model with Dependent Error Components and Dependent Composite Errors: An Application to Chinese Banking Industry," Mathematics, MDPI, vol. 8(2), pages 1-23, February.

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    More about this item

    Keywords

    Stochastic frontier model; Efficiency measurement; Hazard function; Skew normal distribution; C11; C14; C23;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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