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Finite Mixture Estimation of Multiproduct Cost Functions

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  • Beard, T Randolph
  • Caudill, Steven B
  • Gropper, Daniel M

Abstract

This paper presents a technique of cost-function estimation, based on the theory of finite mixture distributions, which allows for the simultaneous existence of multiple technologies of production when the researcher does not know which observations correspond to which technologies. The finite mixture technique provides estimates of the proportions of firms using the various technologies, facilitates comparisons between technologies, and preserves the traditional interpretations of cost estimation. After describing the mixture procedure, the technique is illustrated on a large sample of savings and loan associations, and it is concluded that this industry exhibits multiple technologies of production. Copyright 1991 by MIT Press.

Suggested Citation

  • Beard, T Randolph & Caudill, Steven B & Gropper, Daniel M, 1991. "Finite Mixture Estimation of Multiproduct Cost Functions," The Review of Economics and Statistics, MIT Press, vol. 73(4), pages 654-664, November.
    • Handle: RePEc:tpr:restat:v:73:y:1991:i:4:p:654-64
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    Cited by:

    1. Beard, T. Randolph & Caudill, Steven B. & Gropper, Daniel M., 1997. "The diffusion of production processes in the U.S. banking industry: A finite mixture approach," Journal of Banking & Finance, Elsevier, vol. 21(5), pages 721-740, May.
    2. Mei-Hui Wang & Tai-Hsin Huang, 2009. "Threshold effects of financial status on the cost frontiers of financial institutions in nondynamic panels," Applied Economics, Taylor & Francis Journals, vol. 41(26), pages 3389-3401.
    3. Odejar, Maria Ana E & McNulty, Mark S, 2001. "Bayesian Analysis of the Stochastic Switching Regression Model Using Markov Chain Monte Carlo Methods," Computational Economics, Springer;Society for Computational Economics, vol. 17(2-3), pages 265-284, June.
    4. Acharya, Ram N., 2000. "Market Power And Asymmetry In Farm-Retail Price Transmission," 2000 Annual meeting, July 30-August 2, Tampa, FL 21768, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    5. Marine Carrasco & Jean-Pierre Florens, 2000. "Efficient GMM Estimation Using the Empirical Characteristic Function," Working Papers 2000-33, Center for Research in Economics and Statistics.
    6. Juan Prieto Rodríguez & Juan Gabriel Rodríguez & Rafael Salas, 2006. "On The Measurement Of Illegal Wage Discrimination: The Michael Jordan Paradox," Working Papers 38, ECINEQ, Society for the Study of Economic Inequality.
    7. Steven Caudill & Claudio Detotto & Dominique Prunetti, 2020. "Bargaining power in apartment sales in Corsica: A latent class approach," Urban Studies, Urban Studies Journal Limited, vol. 57(13), pages 2754-2772, October.
    8. Antti Saastamoinen, 2015. "Heteroscedasticity Or Production Risk? A Synthetic View," Journal of Economic Surveys, Wiley Blackwell, vol. 29(3), pages 459-478, July.
    9. Orea, Luis & Pérez, Jose A. & Roibás, David, 2013. "Evaluating the double effect of land fragmentation on technology choice and dairy farm productivity: A latent class model approach," Efficiency Series Papers 2013/08, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    10. Ram Acharya & Henry Kinnucan & Steven Caudill, 2011. "Asymmetric farm-retail price transmission and market power: a new test," Applied Economics, Taylor & Francis Journals, vol. 43(30), pages 4759-4768.
    11. Orea, Luis & Jamasb, Tooraj, 2014. "Identifying efficient regulated firms with unobserved technological heterogeneity: A nested latent class approach to Norwegian electricity distribution networks," Efficiency Series Papers 2014/03, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    12. Katherine G. Yewell & Steven B. Caudill & Franklin G. Mixon, Jr., 2014. "Referee Bias and Stoppage Time in Major League Soccer: A Partially Adaptive Approach," Econometrics, MDPI, vol. 2(1), pages 1-19, February.
    13. Goldbaum, David & Zwinkels, Remco C.J., 2014. "An empirical examination of heterogeneity and switching in foreign exchange markets," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PB), pages 667-684.
    14. Schottmüller, Christoph, 2015. "Adverse selection without single crossing: Monotone solutions," Journal of Economic Theory, Elsevier, vol. 158(PA), pages 127-164.
    15. Subal Kumbhakar & Efthymios Tsionas, "undated". "Does Deregulation Change Economic Behavior of Firms?," Working Papers 0303, University of Crete, Department of Economics.
    16. Marine H. Carrasco & Jean-Pierre Florens, 2000. "Estimation of a Mixture via the Empirical Characteristic Function," Econometric Society World Congress 2000 Contributed Papers 0514, Econometric Society.
    17. Llorca, Manuel & Orea, Luis & Pollitt, Michael G., 2014. "Using the latent class approach to cluster firms in benchmarking: An application to the US electricity transmission industry," Operations Research Perspectives, Elsevier, vol. 1(1), pages 6-17.
    18. Hilger, James & Hanemann, W. Michael, 2008. "The Impact of Water Quality on Southern California Beach Recreation: A Finite Mixture Model Approach," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt9v17r715, Department of Agricultural & Resource Economics, UC Berkeley.

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