IDEAS home Printed from https://ideas.repec.org/a/eee/ecolet/v190y2020ics0165176520300975.html
   My bibliography  Save this article

Directional technology distance functions through duality

Author

Listed:
  • Tsionas, Mike G.

Abstract

I provide an estimation procedure for directional technology distance functions (DTDF) through duality to avoid the unnecessarily often-used restrictive assumption that the DTDF is quadratic. I use a semi-parametric specification which avoids the imposition of restrictive functional forms on the profit function. Through the new procedure, one can obtain estimates of the distance function, its derivatives with respect to directions at observed points, as well as estimates of profit inefficiency. The dual formulation is estimated using the Bayesian version of Generalized Method of Moments of Gallant et al. (2017). An empirical application to U.S. banks reveals important aspects of technical as well as allocative inefficiency.

Suggested Citation

  • Tsionas, Mike G., 2020. "Directional technology distance functions through duality," Economics Letters, Elsevier, vol. 190(C).
  • Handle: RePEc:eee:ecolet:v:190:y:2020:i:c:s0165176520300975
    DOI: 10.1016/j.econlet.2020.109112
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165176520300975
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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, 2012. "Probabilistic characterization of directional distances and their robust versions," Journal of Econometrics, Elsevier, vol. 166(2), pages 342-354.
    2. Hannan, Timothy H., 1991. "Bank commercial loan markets and the role of market structure: evidence from surveys of commercial lending," Journal of Banking & Finance, Elsevier, vol. 15(1), pages 133-149, February.
    3. Robert M. Adams & Lars-Hendrik Röller & Robin C. Sickles, 2002. "Market Power in Outputs and Inputs: An Empirical Application to Banking," CIG Working Papers FS IV 02-33, Wissenschaftszentrum Berlin (WZB), Research Unit: Competition and Innovation (CIG).
    4. Berger, Allen N & Hannan, Timothy H, 1989. "The Price-Concentration Relationship in Banking," The Review of Economics and Statistics, MIT Press, vol. 71(2), pages 291-299, May.
    5. 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.
    6. Fare, Rolf & Grosskopf, Shawna & Noh, Dong-Woon & Weber, William, 2005. "Characteristics of a polluting technology: theory and practice," Journal of Econometrics, Elsevier, vol. 126(2), pages 469-492, June.
    7. Atkinson, Scott E. & Tsionas, Mike G., 2016. "Directional distance functions: Optimal endogenous directions," Journal of Econometrics, Elsevier, vol. 190(2), pages 301-314.
    8. Camilla Mastromarco & Léopold Simar, 2015. "Effect of FDI and Time on Catching Up: New Insights from a Conditional Nonparametric Frontier Analysis," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(5), pages 826-847, August.
    9. Gallant, A. Ronald & Giacomini, Raffaella & Ragusa, Giuseppe, 2017. "Bayesian estimation of state space models using moment conditions," Journal of Econometrics, Elsevier, vol. 201(2), pages 198-211.
    10. Rüdiger Fahlenbrach & Robert Prilmeier & René M. Stulz, 2012. "This Time Is the Same: Using Bank Performance in 1998 to Explain Bank Performance during the Recent Financial Crisis," Journal of Finance, American Finance Association, vol. 67(6), pages 2139-2185, December.
    11. Färe, Rolf & Pasurka, Carl & Vardanyan, Michael, 2017. "On endogenizing direction vectors in parametric directional distance function-based models," European Journal of Operational Research, Elsevier, vol. 262(1), pages 361-369.
    12. 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.
    13. Daouia, Abdelaati & Simar, Leopold, 2007. "Nonparametric efficiency analysis: A multivariate conditional quantile approach," Journal of Econometrics, Elsevier, vol. 140(2), pages 375-400, October.
    14. 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.
    15. R. G. Chambers & Y. Chung & R. Färe, 1998. "Profit, Directional Distance Functions, and Nerlovian Efficiency," Journal of Optimization Theory and Applications, Springer, vol. 98(2), pages 351-364, August.
    Full references (including those not matched with items on IDEAS)

    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. Song, Malin & Wang, Jianlin, 2018. "Environmental efficiency evaluation of thermal power generation in China based on a slack-based endogenous directional distance function model," Energy, Elsevier, vol. 161(C), pages 325-336.
    2. Mastromarco, Camilla & Simar, Léopold, 2018. "Globalization and productivity: A robust nonparametric world frontier analysis," Economic Modelling, Elsevier, vol. 69(C), pages 134-149.
    3. Wei, Xiao & Zhang, Ning, 2020. "The shadow prices of CO2 and SO2 for Chinese Coal-fired Power Plants: A partial frontier approach," Energy Economics, Elsevier, vol. 85(C).
    4. Cinzia Daraio & Léopold Simar & Paul W. Wilson, 2020. "Fast and efficient computation of directional distance estimators," Annals of Operations Research, Springer, vol. 288(2), pages 805-835, May.
    5. 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.
    6. Mallick, Sushanta & Matousek, Roman & Tzeremes, Nickolaos G., 2016. "Financial development and productive inefficiency: A robust conditional directional distance function approach," Economics Letters, Elsevier, vol. 145(C), pages 196-201.
    7. Ferrier, Gary D. & Johnson, Andrew L. & Layer, Kevin & Sickles, Robin C., 2018. "Direction Selection in Stochastic Directional Distance Functions," Working Papers 18-010, Rice University, Department of Economics.
    8. Jean Pierre Huiban & Camille Mastromarco & Antonio Musolesi & Michel Simioni, 2016. "The impact of pollution abatement investments on production technology: new insights from frontier analysis," Working Papers hal-01512154, HAL.
    9. Pierluigi Toma, 2020. "Size and productivity: a conditional approach for Italian pharmaceutical sector," Journal of Productivity Analysis, Springer, vol. 54(1), pages 1-12, August.
    10. Safiullah, Md, 2020. "Bank governance and crisis-period efficiency: A multinational study on Islamic and conventional banks," Pacific-Basin Finance Journal, Elsevier, vol. 62(C).
    11. Daraio, Cinzia & Simar, Leopold & Wilson, Paul, 2019. "Quality and its impact on efficiency," LIDAM Discussion Papers ISBA 2019004, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    12. Yaryna Kolomiytseva, 2018. "Revisiting Transformation and Directional Technology Distance Functions," Papers 1812.10108, arXiv.org.
    13. Deng, Zhongqi & Jiang, Nan & Pang, Ruizhi, 2021. "Factor-analysis-based directional distance function: The case of New Zealand hospitals," Omega, Elsevier, vol. 98(C).
    14. Cordero, José Manuel & Pedraja-Chaparro, Francisco & Pisaflores, Elsa C. & Polo, Cristina, 2016. "Efficiency assessment of Portuguese municipalities using a conditional nonparametric approach," MPRA Paper 70674, University Library of Munich, Germany.
    15. Polemis, Michael L. & Tzeremes, Nickolaos G., 2019. "Competitive conditions and sectors’ productive efficiency: A conditional non-parametric frontier analysis," European Journal of Operational Research, Elsevier, vol. 276(3), pages 1104-1118.
    16. Juan Aparicio & Jose Manuel Cordero & Carlos Díaz-Caro, 2020. "Efficiency and productivity change of regional tax offices in Spain: an empirical study using Malmquist–Luenberger and Luenberger indices," Empirical Economics, Springer, vol. 59(3), pages 1403-1434, September.
    17. Camilla Mastromarco & Léopold Simar, 2015. "Effect of FDI and Time on Catching Up: New Insights from a Conditional Nonparametric Frontier Analysis," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(5), pages 826-847, August.
    18. Mastromarco, Camilla & Simar, Leopold & Wilson, Paul, 2019. "Predicting Recessions: A New Measure of Output Gap as Predictor," LIDAM Discussion Papers ISBA 2019023, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    19. Orea, Luis, 2019. "The Econometric Measurement of Firms’ Efficiency," Efficiency Series Papers 2019/02, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    20. Mastromarco, Camilla & Simar, Leopold, 2017. "Cross-Section Dependence and Latent Heterogeneity to Evaluate the Impact of Human Capital on Country Performance," LIDAM Discussion Papers ISBA 2017030, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

    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:ecolet:v:190:y:2020:i:c:s0165176520300975. 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: (Nithya Sathishkumar). General contact details of provider: http://www.elsevier.com/locate/ecolet .

    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 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.

    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.