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Likelihood ratio tests for model selection of stochastic frontier models

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  • Hung-pin Lai
  • Cliff Huang

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  • Hung-pin Lai & Cliff Huang, 2010. "Likelihood ratio tests for model selection of stochastic frontier models," Journal of Productivity Analysis, Springer, vol. 34(1), pages 3-13, August.
    • Handle: RePEc:kap:jproda:v:34:y:2010:i:1:p:3-13
    DOI: 10.1007/s11123-009-0160-8
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    References listed on IDEAS

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    1. Rafik Baccouche & Mokhtar Kouki, 2003. "Stochastic Production Frontier and Technical Inefficiency: A Sensitivity Analysis," Econometric Reviews, Taylor & Francis Journals, vol. 22(1), pages 79-91, February.
    2. White, Halbert, 1982. "Maximum Likelihood Estimation of Misspecified Models," Econometrica, Econometric Society, vol. 50(1), pages 1-25, January.
    3. Kumbhakar, Subal C & Ghosh, Soumendra & McGuckin, J Thomas, 1991. "A Generalized Production Frontier Approach for Estimating Determinants of Inefficiency in U.S. Dairy Farms," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(3), pages 279-286, July.
    4. Antonio Alvarez & Christine Amsler & Luis Orea & Peter Schmidt, 2006. "Interpreting and Testing the Scaling Property in Models where Inefficiency Depends on Firm Characteristics," Journal of Productivity Analysis, Springer, vol. 25(3), pages 201-212, June.
    5. 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.
    6. Caudill, Steven B. & Ford, Jon M., 1993. "Biases in frontier estimation due to heteroscedasticity," Economics Letters, Elsevier, vol. 41(1), pages 17-20.
    7. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Aljar Meesters, 2014. "A note on the assumed distributions in stochastic frontier models," Journal of Productivity Analysis, Springer, vol. 42(2), pages 171-173, October.
    2. Soroush, Golnoush & Cambini, Carlo & Jamasb, Tooraj & Llorca, Manuel, 2021. "Network utilities performance and institutional quality: Evidence from the Italian electricity sector," Energy Economics, Elsevier, vol. 96(C).
    3. Xu Guo & Gao-Rong Li & Michael McAleer & Wing-Keung Wong, 2018. "Specification Testing of Production in a Stochastic Frontier Model," Sustainability, MDPI, vol. 10(9), pages 1-10, August.
    4. Pablo Argüelles & Luis Orea, 2021. "Managing power supply interruptions: a bottom-up spatial (frontier) model with an application to a Spanish electricity network," Empirical Economics, Springer, vol. 60(6), pages 2867-2896, June.
    5. Sun, Lei & Chang, Tzu-Pu, 2011. "A comprehensive analysis of the effects of risk measures on bank efficiency: Evidence from emerging Asian countries," Journal of Banking & Finance, Elsevier, vol. 35(7), pages 1727-1735, July.
    6. Christopher F. Parmeter & Alan T. K. Wan & Xinyu Zhang, 2019. "Model averaging estimators for the stochastic frontier model," Journal of Productivity Analysis, Springer, vol. 51(2), pages 91-103, June.
    7. Cliff Huang & Tai-Hsin Huang & Nan-Hung Liu, 2014. "A new approach to estimating the metafrontier production function based on a stochastic frontier framework," Journal of Productivity Analysis, Springer, vol. 42(3), pages 241-254, December.
    8. Llorca, Manuel & Orea, Luis & Pollitt, Michael G., 2016. "Efficiency and environmental factors in the US electricity transmission industry," Energy Economics, Elsevier, vol. 55(C), pages 234-246.
    9. Jin-Li Hu & Tzu-Pu Chang & Ray Chou, 2014. "Market conditions and the effect of diversification on mutual fund performance: should funds be more concentrative under crisis?," Journal of Productivity Analysis, Springer, vol. 41(1), pages 141-151, February.
    10. Orea, Luis, 2019. "The Econometric Measurement of Firms’ Efficiency," Efficiency Series Papers 2019/02, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    11. C. Spulbăr & M. Niţoi, 2014. "Determinants of bank cost efficiency in transition economies: evidence for Latin America, Central and Eastern Europe and South-East Asia," Applied Economics, Taylor & Francis Journals, vol. 46(16), pages 1940-1952, June.
    12. Shamsuzzoha & Makoto Tanaka, 2021. "The role of human capital on the performance of manufacturing firms in Bangladesh," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(1), pages 21-33, January.
    13. J. Buckell & A. Smith & R. Longo & D. Holland, 2015. "Efficiency, heterogeneity and cost function analysis: empirical evidence from pathology services in the National Health Service in England," Applied Economics, Taylor & Francis Journals, vol. 47(31), pages 3311-3331, July.
    14. Nguyen, Dung Thuy Thi & Diaz-Rainey, Ivan & Roberts, Helen & Le, Minh, 2022. "The non-monotonic relationship between financial integration and cost efficiency: Evidence from East Asian commercial banks," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 418-438.
    15. Ali M. Oumer & Amin Mugera & Michael Burton & Atakelty Hailu, 2022. "Technical efficiency and firm heterogeneity in stochastic frontier models: application to smallholder maize farms in Ethiopia," Journal of Productivity Analysis, Springer, vol. 57(2), pages 213-241, April.

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    More about this item

    Keywords

    Akaike information criterion; Kullback–Leibler information criterion; Likelihood ratio test; Stochastic frontier model; Takeuchi information criterion; C12; C52; C67; D24;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

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