IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v268y2018i2p653-664.html
   My bibliography  Save this article

A novel model of costly technical efficiency

Author

Listed:
  • Tsionas, Mike G.
  • Izzeldin, Marwan

Abstract

This paper presents a novel model of measuring technical inefficiency based on the notion that higher efficiency requires a certain cost. First, we apply the “rational inefficiency hypothesis” of Bogetoft and Hougaard (2003) but we fail to find that it rationalizes our data set of large U.S banks with multiple inputs and outputs. In consequence, we adopt a novel model of profit maximization which explicitly incorporates the cost of technical inefficiency. The cost of inefficiency is treated as unknown and is parametrized as a function of inputs, outputs and decision-making-unit specific fixed effects. More importantly, by showing the model to be equivalent to one in which inefficiency is an arbitrary function of inputs, outputs and the inefficiency cost, we are able to determine optimal directions in the input-output space that would reduce inefficiency. Bayesian techniques organized around Markov Chain Monte Carlo are used to perform the computations and provide statistical inferences as well as useful policy measures to reduce inefficiencies in the U.S banking sector through an examination of different realistic scenarios.

Suggested Citation

  • Tsionas, Mike G. & Izzeldin, Marwan, 2018. "A novel model of costly technical efficiency," European Journal of Operational Research, Elsevier, vol. 268(2), pages 653-664.
  • Handle: RePEc:eee:ejores:v:268:y:2018:i:2:p:653-664
    DOI: 10.1016/j.ejor.2018.01.016
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221718300341
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ejor.2018.01.016?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Simar, Léopold & Vanhems, Anne & Van Keilegom, Ingrid, 2016. "Unobserved heterogeneity and endogeneity in nonparametric frontier estimation," Journal of Econometrics, Elsevier, vol. 190(2), pages 360-373.
    2. Bădin, Luiza & Daraio, Cinzia & Simar, Léopold, 2012. "How to measure the impact of environmental factors in a nonparametric production model," European Journal of Operational Research, Elsevier, vol. 223(3), pages 818-833.
    3. Atkinson, Scott E. & Tsionas, Mike G., 2016. "Directional distance functions: Optimal endogenous directions," Journal of Econometrics, Elsevier, vol. 190(2), pages 301-314.
    4. Daraio, Cinzia & Simar, Léopold, 2014. "Directional distances and their robust versions: Computational and testing issues," European Journal of Operational Research, Elsevier, vol. 237(1), pages 358-369.
    5. Kumbhakar, Subal C. & Tsionas, Efthymios G., 2006. "Estimation of stochastic frontier production functions with input-oriented technical efficiency," Journal of Econometrics, Elsevier, vol. 133(1), pages 71-96, July.
    6. Badunenko, Oleg & Kumbhakar, Subal C., 2017. "Economies of scale, technical change and persistent and time-varying cost efficiency in Indian banking: Do ownership, regulation and heterogeneity matter?," European Journal of Operational Research, Elsevier, vol. 260(2), pages 789-803.
    7. Reifschneider, David & Stevenson, Rodney, 1991. "Systematic Departures from the Frontier: A Framework for the Analysis of Firm Inefficiency," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 32(3), pages 715-723, August.
    8. Saranga, Haritha, 2009. "The Indian auto component industry - Estimation of operational efficiency and its determinants using DEA," European Journal of Operational Research, Elsevier, vol. 196(2), pages 707-718, July.
    9. Asmild, Mette & Matthews, Kent, 2012. "Multi-directional efficiency analysis of efficiency patterns in Chinese banks 1997–2008," European Journal of Operational Research, Elsevier, vol. 219(2), pages 434-441.
    10. Dominique Deprins & Léopold Simar, 1989. "Estimation de frontières déterministes avec facteurs exogénes d'inefficacité," Annals of Economics and Statistics, GENES, issue 14, pages 117-150.
    11. Chen, Ya & Li, Yongjun & Liang, Liang & Salo, Ahti & Wu, Huaqing, 2016. "Frontier projection and efficiency decomposition in two-stage processes with slacks-based measures," European Journal of Operational Research, Elsevier, vol. 250(2), pages 543-554.
    12. Léopold Simar & Paul Wilson, 2011. "Two-stage DEA: caveat emptor," Journal of Productivity Analysis, Springer, vol. 36(2), pages 205-218, October.
    13. repec:adr:anecst:y:1989:i:14 is not listed on IDEAS
    14. Sickles, Robin C. & Good, David & Johnson, Richard L., 1986. "Allocative distortions and the regulatory transition of the U.S. airline industry," Journal of Econometrics, Elsevier, vol. 33(1-2), pages 143-163.
    15. Biener, Christian & Eling, Martin & Wirfs, Jan Hendrik, 2016. "The determinants of efficiency and productivity in the Swiss insurance industry," European Journal of Operational Research, Elsevier, vol. 248(2), pages 703-714.
    16. Peter Bogetoft & Jens Hougaard, 2003. "Rational Inefficiencies," Journal of Productivity Analysis, Springer, vol. 20(3), pages 243-271, November.
    17. Sun, Kai & Kumbhakar, Subal C. & Tveterås, Ragnar, 2015. "Productivity and efficiency estimation: A semiparametric stochastic cost frontier approach," European Journal of Operational Research, Elsevier, vol. 245(1), pages 194-202.
    18. Reyes, Pedro M. & Li, Suhong & Visich, John K., 2016. "Determinants of RFID adoption stage and perceived benefits," European Journal of Operational Research, Elsevier, vol. 254(3), pages 801-812.
    19. Tecles, Patricia Langsch & Tabak, Benjamin M., 2010. "Determinants of bank efficiency: The case of Brazil," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1587-1598, December.
    20. Kutlu, Levent & Sickles, Robin C., 2012. "Estimation of market power in the presence of firm level inefficiencies," Journal of Econometrics, Elsevier, vol. 168(1), pages 141-155.
    21. Asmild, Mette & Bogetoft, Peter & Leth Hougaard, Jens, 2013. "Rationalising inefficiency: Staff utilisation in branches of a large Canadian bank," Omega, Elsevier, vol. 41(1), pages 80-87.
    22. 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.
    23. Kumbhakar, Subal C. & Tsionas, Efthymios G., 2016. "The good, the bad and the technology: Endogeneity in environmental production models," Journal of Econometrics, Elsevier, vol. 190(2), pages 315-327.
    24. Sena, Vania, 2006. "The determinants of firms' performance: Can finance constraints improve technical efficiency?," European Journal of Operational Research, Elsevier, vol. 172(1), pages 311-325, July.
    25. repec:adr:anecst:y:1989:i:14:p:06 is not listed on IDEAS
    26. 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.
    27. Dominique DEPRINS & Léopold SIMAR, 1989. "Estimating Technical Inefficiencies With Correction For Environmental Conditions," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 60(1), pages 81-102, January.
    28. Annaert, Jan & van den Broeck, Julien & Vander Vennet, Rudi, 2003. "Determinants of mutual fund underperformance: A Bayesian stochastic frontier approach," European Journal of Operational Research, Elsevier, vol. 151(3), pages 617-632, December.
    29. Cornwell, Christopher & Schmidt, Peter & Sickles, Robin C., 1990. "Production frontiers with cross-sectional and time-series variation in efficiency levels," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 185-200.
    30. Tsionas, Euthimios G. & Mamatzakis, Emmanuel C., 2017. "Adjustment costs in the technical efficiency: An application to global banking," European Journal of Operational Research, Elsevier, vol. 256(2), pages 640-649.
    31. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    32. 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.
    33. Mark Girolami & Ben Calderhead, 2011. "Riemann manifold Langevin and Hamiltonian Monte Carlo methods," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 73(2), pages 123-214, March.
    34. Sickles, Robin C., 2005. "Panel estimators and the identification of firm-specific efficiency levels in parametric, semiparametric and nonparametric settings," Journal of Econometrics, Elsevier, vol. 126(2), pages 305-334, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Tsionas, Mike G. & Malikov, Emir & Kumbhakar, Subal C., 2020. "Endogenous dynamic efficiency in the intertemporal optimization models of firm behavior," European Journal of Operational Research, Elsevier, vol. 284(1), pages 313-324.
    2. Tsionas, Mike G. & Andrikopoulos, Athanasios, 2020. "On a High-Dimensional Model Representation method based on Copulas," European Journal of Operational Research, Elsevier, vol. 284(3), pages 967-979.
    3. Tsionas, Mike G. & Polemis, Michael L., 2019. "On the estimation of total factor productivity: A novel Bayesian non-parametric approach," European Journal of Operational Research, Elsevier, vol. 277(3), pages 886-902.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tsionas, Mike G. & Andrikopoulos, Athanasios, 2020. "On a High-Dimensional Model Representation method based on Copulas," European Journal of Operational Research, Elsevier, vol. 284(3), pages 967-979.
    2. Minviel, Jean Joseph & De Witte, Kristof, 2017. "The influence of public subsidies on farm technical efficiency: A robust conditional nonparametric approach," European Journal of Operational Research, Elsevier, vol. 259(3), pages 1112-1120.
    3. Antonio Alvarez & Carlos Arias, 2014. "A selection of relevant issues in applied stochastic frontier analysis," Economics and Business Letters, Oviedo University Press, vol. 3(1), pages 3-11.
    4. Orea, Luis, 2019. "The Econometric Measurement of Firms’ Efficiency," Efficiency Series Papers 2019/02, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    5. Julio Peña & Julio Aguirre & René Cerca D'amico, 2004. "Pesca demersal en Chile: eficiencia técnica y escalas de operación," Revista de Analisis Economico – Economic Analysis Review, Universidad Alberto Hurtado/School of Economics and Business, vol. 19(1), pages 119-160, June.
    6. Gralka, Sabine, 2018. "Stochastic frontier analysis in higher education: A systematic review," CEPIE Working Papers 05/18, Technische Universität Dresden, Center of Public and International Economics (CEPIE).
    7. Paul, Satya & Shankar, Sriram, 2018. "Modelling Efficiency Effects in a True Fixed Effects Stochastic Frontier," MPRA Paper 87437, University Library of Munich, Germany.
    8. Tim Coelli & Sergio Perelman & Elliot Romano, 1999. "Accounting for Environmental Influences in Stochastic Frontier Models: With Application to International Airlines," Journal of Productivity Analysis, Springer, vol. 11(3), pages 251-273, June.
    9. Sherlund, Shane M. & Barrett, Christopher B. & Adesina, Akinwumi A., 2002. "Smallholder technical efficiency controlling for environmental production conditions," Journal of Development Economics, Elsevier, vol. 69(1), pages 85-101, October.
    10. Subal C. Kumbhakar & Christopher F. Parmeter & Valentin Zelenyuk, 2017. "Stochastic Frontier Analysis: Foundations and Advances," Working Papers 2017-10, University of Miami, Department of Economics.
    11. Meryem Duygun & Levent Kutlu & Robin C. Sickles, 2016. "Measuring productivity and efficiency: a Kalman filter approach," Journal of Productivity Analysis, Springer, vol. 46(2), pages 155-167, December.
    12. Giannis Karagiannis & Vangelis Tzouvelekas, 1999. "Measuring Technical Efficiency with Panel Data: Results from Competing Models," Working Papers 9914, University of Crete, Department of Economics.
    13. Giannis Karagiannis, 2005. "Explaining output growth with a heteroscedastic non-neutral production frontier: the case of sheep farms in Greece," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 32(1), pages 51-74, March.
    14. Francesco Aiello & Camilla Mastromarco & Angelo Zago, 2011. "Be productive or face decline. On the sources and determinants of output growth in Italian manufacturing firms," Empirical Economics, Springer, vol. 41(3), pages 787-815, December.
    15. Martín Rossi, 2015. "The Econometrics Approach to the Measurement of Efficiency: A Survey," Working Papers 117, Universidad de San Andres, Departamento de Economia, revised Feb 2015.
    16. Karagiannis, Giannis & Tzouvelekas, Vangelis, 2009. "Parametric Measurement of Time-Varying Technical Inefficiency: Results from Competing Models," Agricultural Economics Review, Greek Association of Agricultural Economists, vol. 10(1), pages 1-30.
    17. Sickles, Robin C. & Hao, Jiaqi & Shang, Chenjun, 2015. "Panel Data and Productivity Measurement," Working Papers 15-018, Rice University, Department of Economics.
    18. Jose M. Cordero & Cristina Polo & Daniel Santín, 2020. "Assessment of new methods for incorporating contextual variables into efficiency measures: a Monte Carlo simulation," Operational Research, Springer, vol. 20(4), pages 2245-2265, December.
    19. Kashiwagi, Kenichi & Mtimet, Nadhem & Zaibet, Lokman & Nagaki, Masakazu, 2010. "Technical efficiency of olive oil manufacturing and efficacy of modernization programme in Tunisia," 2010 AAAE Third Conference/AEASA 48th Conference, September 19-23, 2010, Cape Town, South Africa 96195, African Association of Agricultural Economists (AAAE).
    20. Arazmuradov, Annageldy & Martini, Gianmaria & Scotti, Davide, 2014. "Determinants of total factor productivity in former Soviet Union economies: A stochastic frontier approach," Economic Systems, Elsevier, vol. 38(1), pages 115-135.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:268:y:2018:i:2:p:653-664. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: http://www.elsevier.com/locate/eor .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.