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Bounded rationality and thick frontiers in stochastic frontier analysis

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  • Tsionas, Mike G.

Abstract

Recent research has proposed a statistical test based on the notion that agents have bounded rationality, if and only if more attractive states are chosen with larger probability. We propose and implement a statistical test for bounded rationality in the context of stochastic cost frontiers. Bounded rationality is related to probabilistically cost-efficient distributions. The test is based on comparing a discrete set of probabilities with the theoretical distribution under bounded rationality. Implementation is shown to be quite easy in a Bayesian framework using the Bayes factor for model comparison between estimated and theoretical probabilities. The bounded-rationality model introduces only an extra parameter in frontier models and, therefore, it is quite practical to use in applications as a general semi-parametric model for inefficiency.

Suggested Citation

  • Tsionas, Mike G., 2020. "Bounded rationality and thick frontiers in stochastic frontier analysis," European Journal of Operational Research, Elsevier, vol. 284(2), pages 762-768.
  • Handle: RePEc:eee:ejores:v:284:y:2020:i:2:p:762-768
    DOI: 10.1016/j.ejor.2019.12.010
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    1. Tsionas, Mike G. & Izzeldin, Marwan, 2018. "Smooth approximations to monotone concave functions in production analysis: An alternative to nonparametric concave least squares," European Journal of Operational Research, Elsevier, vol. 271(3), pages 797-807.
    2. Atkinson, Scott E. & Dorfman, Jeffrey H., 2005. "Bayesian measurement of productivity and efficiency in the presence of undesirable outputs: crediting electric utilities for reducing air pollution," Journal of Econometrics, Elsevier, vol. 126(2), pages 445-468, June.
    3. Michaelides, Panayotis G. & Vouldis, Angelos T. & Tsionas, Efthymios G., 2010. "Globally flexible functional forms: The neural distance function," European Journal of Operational Research, Elsevier, vol. 206(2), pages 456-469, October.
    4. Filip Matêjka & Alisdair McKay, 2015. "Rational Inattention to Discrete Choices: A New Foundation for the Multinomial Logit Model," American Economic Review, American Economic Association, vol. 105(1), pages 272-298, January.
    5. Fernandez, Carmen & Osiewalski, Jacek & Steel, Mark F. J., 1997. "On the use of panel data in stochastic frontier models with improper priors," Journal of Econometrics, Elsevier, vol. 79(1), pages 169-193, July.
    6. Michaelides, Panayotis G. & Tsionas, Efthymios G. & Vouldis, Angelos T. & Konstantakis, Konstantinos N., 2015. "Global approximation to arbitrary cost functions: A Bayesian approach with application to US banking," European Journal of Operational Research, Elsevier, vol. 241(1), pages 148-160.
    7. Perrakis, Konstantinos & Ntzoufras, Ioannis & Tsionas, Efthymios G., 2014. "On the use of marginal posteriors in marginal likelihood estimation via importance sampling," Computational Statistics & Data Analysis, Elsevier, vol. 77(C), pages 54-69.
    8. Kneip, Alois & Simar, Léopold & Van Keilegom, Ingrid, 2015. "Frontier estimation in the presence of measurement error with unknown variance," Journal of Econometrics, Elsevier, vol. 184(2), pages 379-393.
    9. Lv, Wei & Li, Hongyi & Tang, Jiafu, 2017. "Bargaining model of labor disputes considering social mediation and bounded rationalityAuthor-Name: Liu, Dehai," European Journal of Operational Research, Elsevier, vol. 262(3), pages 1064-1071.
    10. Anas, Alex, 1983. "Discrete choice theory, information theory and the multinomial logit and gravity models," Transportation Research Part B: Methodological, Elsevier, vol. 17(1), pages 13-23, February.
    11. Hampf, Benjamin, 2017. "Rational Inefficiency. Adjustment Costs and Sequential Technologies," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 92488, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    12. Barucci, Emilio & Landi, Leonardo, 1996. "Speculative dynamics with bounded rationality learning," European Journal of Operational Research, Elsevier, vol. 91(2), pages 284-300, June.
    13. Hampf, Benjamin, 2017. "Rational inefficiency, adjustment costs and sequential technologies," European Journal of Operational Research, Elsevier, vol. 263(3), pages 1095-1108.
    14. Emir Malikov & Subal C. Kumbhakar & Mike G. Tsionas, 2016. "A Cost System Approach to the Stochastic Directional Technology Distance Function with Undesirable Outputs: The Case of us Banks in 2001–2010," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1407-1429, November.
    15. Mattsson, Lars-Goran & Weibull, Jorgen W., 2002. "Probabilistic choice and procedurally bounded rationality," Games and Economic Behavior, Elsevier, vol. 41(1), pages 61-78, October.
    16. Kumbhakar, Subal C. & Parmeter, Christopher F. & Tsionas, Efthymios G., 2013. "A zero inefficiency stochastic frontier model," Journal of Econometrics, Elsevier, vol. 172(1), pages 66-76.
    17. Mike G. Tsionas, 2017. "“When, Where, and How” of Efficiency Estimation: Improved Procedures for Stochastic Frontier Modeling," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(519), pages 948-965, July.
    18. Allen N. Berger & David B. Humphrey, 1992. "Measurement and Efficiency Issues in Commercial Banking," NBER Chapters, in: Output Measurement in the Service Sectors, pages 245-300, National Bureau of Economic Research, Inc.
    19. Stigler, George J, 1976. "The Xistence of X-Efficiency," American Economic Review, American Economic Association, vol. 66(1), pages 213-216, March.
    20. Chia -Yen Lee & Andrew L. Johnson, 2015. "Measuring Efficiency in Imperfectly Competitive Markets: An Example of Rational Inefficiency," Journal of Optimization Theory and Applications, Springer, vol. 164(2), pages 702-722, February.
    21. Ubøe, Jan & Andersson, Jonas & Jörnsten, Kurt & Lillestøl, Jostein & Sandal, Leif, 2017. "Statistical testing of bounded rationality with applications to the newsvendor model," European Journal of Operational Research, Elsevier, vol. 259(1), pages 251-261.
    22. Jiang, Zhong-Zhong & Fang, Shu-Cherng & Fan, Zhi-Ping & Wang, Dingwei, 2013. "Selecting optimal selling format of a product in B2C online auctions with boundedly rational customers," European Journal of Operational Research, Elsevier, vol. 226(1), pages 139-153.
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