IDEAS home Printed from https://ideas.repec.org/p/ags/aaea05/19402.html
   My bibliography  Save this paper

Feasible Estimation of Firm-Specific Allocative Inefficiency through Bayesian Numerical Methods

Author

Listed:
  • Atkinson, Scott E.
  • Dorfman, Jeffrey H.

Abstract

The estimation of allocative and technical inefficiency has grown to an enormous body of literature, both theoretical and empirical. Ideally, one would estimate time-varying firm and input-specific parameters describing allocative inefficiency in order to minimize aggregation bias. However, this has never been previously accomplished. Typically, only industry-wide allocative efficiency parameters have been empirically identified. Our proposed solution is to employ Gibbs sampling to approximate posterior distributions from a Bayesian limited information model, embedding GMM moment conditions imposed via an instrumental variables step to obtain plant-specific parameters estimates that vary flexibly over time. For a panel of Chilean hydroelectric power plants, posterior distributions of these estimates display substantial differences in location and precision. By contrast, the standard GMM approach which produces industry-wide, time-varying allocative inefficiency parameters, not only fails to reveal the inter-plant differences by construction, but does not even produce posterior medians that approximate a weighted average of the plant-specific posterior medians.

Suggested Citation

  • Atkinson, Scott E. & Dorfman, Jeffrey H., 2005. "Feasible Estimation of Firm-Specific Allocative Inefficiency through Bayesian Numerical Methods," 2005 Annual meeting, July 24-27, Providence, RI 19402, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
  • Handle: RePEc:ags:aaea05:19402
    DOI: 10.22004/ag.econ.19402
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/19402/files/sp05at01.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.19402?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
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Koop, Gary & Tobias, Justin L., 2006. "Semiparametric Bayesian inference in smooth coefficient models," Journal of Econometrics, Elsevier, vol. 134(1), pages 283-315, September.
    2. Koop, Gary & Poirier, Dale J., 2004. "Bayesian variants of some classical semiparametric regression techniques," Journal of Econometrics, Elsevier, vol. 123(2), pages 259-282, December.
    3. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    4. Griffin, J. E. & Steel, M. F. J., 2004. "Semiparametric Bayesian inference for stochastic frontier models," Journal of Econometrics, Elsevier, vol. 123(1), pages 121-152, November.
    5. Kim, Jae-Young, 2002. "Limited information likelihood and Bayesian analysis," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 175-193, March.
    6. Jeffrey T. LaFrance, 1999. "Inferring the Nutrient Content of Food With Prior Information," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 81(3), pages 728-734.
    7. 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.
    8. Lim, Hongil & Shumway, C Richard, 1992. "Profit Maximization, Returns to Scale, and Measurement Error," The Review of Economics and Statistics, MIT Press, vol. 74(3), pages 430-438, August.
    9. Zellner, Arnold & Tobias, Justin, 2001. "Further Results on Bayesian Method of Moments Analysis of the Multiple Regression Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 42(1), pages 121-140, February.
    10. Atkinson, Scott E & Cornwell, Christopher, 1994. "Parametric Estimation of Technical and Allocative Inefficiency with Panel Data," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 35(1), pages 231-243, February.
    11. Atkinson, Scott E. & Primont, Daniel, 2002. "Stochastic estimation of firm technology, inefficiency, and productivity growth using shadow cost and distance functions," Journal of Econometrics, Elsevier, vol. 108(2), pages 203-225, June.
    12. repec:bla:obuest:v:61:y:1999:i:4:p:455-87 is not listed on IDEAS
    13. Zellner, Arnold & Highfield, Richard A., 1988. "Calculation of maximum entropy distributions and approximation of marginalposterior distributions," Journal of Econometrics, Elsevier, vol. 37(2), pages 195-209, February.
    14. Atkinson, Scott E & Halvorsen, Robert, 1980. "A Test of Relative and Absolute Price Efficiency in Regulated Utilities," The Review of Economics and Statistics, MIT Press, vol. 62(1), pages 81-88, February.
    15. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    16. Zellner, Arnold, 1998. "The finite sample properties of simultaneous equations' estimates and estimators Bayesian and non-Bayesian approaches," Journal of Econometrics, Elsevier, vol. 83(1-2), pages 185-212.
    17. Zellner, Arnold & Bauwens, Luc & Van Dijk, Herman K., 1988. "Bayesian specification analysis and estimation of simultaneous equation models using Monte Carlo methods," Journal of Econometrics, Elsevier, vol. 38(1-2), pages 39-72.
    18. Atkinson, Scott E & Halvorsen, Robert, 1984. "Parametric Efficiency Tests, Economies of Scale, and Input Demand in U.S. Electric Power Generation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 25(3), pages 647-662, October.
    19. Zellner, Arnold, 1988. "Bayesian analysis in econometrics," Journal of Econometrics, Elsevier, vol. 37(1), pages 27-50, January.
    20. Greene, William H., 1980. "On the estimation of a flexible frontier production model," Journal of Econometrics, Elsevier, vol. 13(1), pages 101-115, May.
    21. Gary Koop & Jacek Osiewalski & Mark F. J. Steel, 1999. "The Components of Output Growth: A Stochastic Frontier Analysis," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(4), pages 455-487, November.
    22. Atkinson, Scott E. & Halvorsen, Robert, 1998. "Parametric tests for static and dynamic equilibrium," Journal of Econometrics, Elsevier, vol. 85(1), pages 33-50, July.
    23. 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.
    24. Bauer, Paul W., 1990. "Recent developments in the econometric estimation of frontiers," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 39-56.
    25. Rombouts, Jeroen V. K. & Bauwens, Luc, 2004. "Econometrics," Papers 2004,33, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).
      • BAUWENS, Luc & ROMBOUTS, Jeroen V.K., 2004. "Econometrics," LIDAM Reprints CORE 1713, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    26. Kumbhakar, Subal C. & Tsionas, Efthymios G., 2005. "The Joint Measurement of Technical and Allocative Inefficiencies: An Application of Bayesian Inference in Nonlinear Random-Effects Models," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 736-747, September.
    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. Bruno De Borger & Kristiaan Kerstens & Diego Prior & Ignace Van de Woestyne, 2013. "Static efficiency decompositions and capacity utilization: integrating economic and technical capacity notions," Applied Economics, Taylor & Francis Journals, vol. 45(24), pages 3529-3529, August.
    2. Jin, Qianying & Kerstens, Kristiaan & Van de Woestyne, Ignace, 2020. "Metafrontier productivity indices: Questioning the common convexification strategy," European Journal of Operational Research, Elsevier, vol. 283(2), pages 737-747.
    3. Oum, Tae H. & Yan, Jia & Yu, Chunyan, 2008. "Ownership forms matter for airport efficiency: A stochastic frontier investigation of worldwide airports," Journal of Urban Economics, Elsevier, vol. 64(2), pages 422-435, September.
    4. Kristiaan Kerstens & Ignace Van de Woestyne, 2021. "Cost functions are nonconvex in the outputs when the technology is nonconvex: convexification is not harmless," Annals of Operations Research, Springer, vol. 305(1), pages 81-106, October.
    5. Cesaroni, Giovanni & Kerstens, Kristiaan & Van de Woestyne, Ignace, 2019. "Short- and long-run plant capacity notions: Definitions and comparison," European Journal of Operational Research, Elsevier, vol. 275(1), pages 387-397.
    6. Kristiaan Kerstens & Jafar Sadeghi & Ignace Van de Woestyne, 2019. "Plant Capacity and Attainability: Exploration and Remedies," Operations Research, INFORMS, vol. 67(4), pages 1135-1149, July.
    7. Briec, Walter & Kerstens, Kristiaan & Prior, Diego & Van de Woestyne, Ignace, 2010. "Tangency capacity notions based upon the profit and cost functions: A non-parametric approach and a general comparison," Economic Modelling, Elsevier, vol. 27(5), pages 1156-1166, September.
    8. Tao, Xiangyang & An, Qingxian & Goh, Mark, 2024. "Plant capacity utilization with piecewise Cobb-Douglas technology: Definition and interpretation," European Journal of Operational Research, Elsevier, vol. 316(3), pages 1034-1043.
    9. Walter Briec & Kristiaan Kerstens & Ignace Van de Woestyne, 2013. "Nonparametric cost and revenue functions under constant economies of scale: An enumeration approach for the single output or input case," Working Papers 2013-ECO-22, IESEG School of Management.
    10. Kerstens, Kristiaan & Van de Woestyne, Ignace, 2014. "Comparing Malmquist and Hicks–Moorsteen productivity indices: Exploring the impact of unbalanced vs. balanced panel data," European Journal of Operational Research, Elsevier, vol. 233(3), pages 749-758.
    11. Briec, Walter & Kerstens, Kristiaan & Van de Woestyne, Ignace, 2011. "Nonparametric cost and revenue functions under constant economies of scale: A simplification for the single output or input case," Working Papers 2011/12, Hogeschool-Universiteit Brussel, Faculteit Economie en Management.
    12. Kerstens, Kristiaan & O’Donnell, Christopher & Van de Woestyne, Ignace, 2019. "Metatechnology frontier and convexity: A restatement," European Journal of Operational Research, Elsevier, vol. 275(2), pages 780-792.
    13. Tsionas, Efthymios & Assaf, A. George & Gillen, David & Mattila, Anna S., 2017. "Modeling technical and service efficiency," Transportation Research Part B: Methodological, Elsevier, vol. 96(C), pages 113-125.
    14. Assaf, A. George & Tsionas, Mike & Kock, Florian & Josiassen, Alexander, 2021. "A Bayesian non-parametric stochastic frontier model," Annals of Tourism Research, Elsevier, vol. 87(C).

    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. Agee, Mark D. & Atkinson, Scott E. & Crocker, Thomas D. & Williams, Jonathan W., 2014. "Non-separable pollution control: Implications for a CO2 emissions cap and trade system," Resource and Energy Economics, Elsevier, vol. 36(1), pages 64-82.
    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. Rungsuriyawiboon, Supawat & Stefanou, Spiro E., 2007. "Dynamic Efficiency Estimation: An Application to U.S. Electric Utilities," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 226-238, April.
    4. Scott E. Atkinson & Rolf Färe & Daniel Primont, 2003. "Stochastic Estimation of Firm Inefficiency Using Distance Functions," Southern Economic Journal, John Wiley & Sons, vol. 69(3), pages 596-611, January.
    5. Scott Atkinson & Jeffrey Dorfman, 2005. "Multiple Comparisons with the Best: Bayesian Precision Measures of Efficiency Rankings," Journal of Productivity Analysis, Springer, vol. 23(3), pages 359-382, July.
    6. Supawat Rungsuriyawiboon, 2004. "A Dynamic Approach to Estimate the Efficiency of U.S. Electric Utilities," Econometric Society 2004 Australasian Meetings 91, Econometric Society.
    7. Atkinson, Scott E. & Primont, Daniel, 2002. "Stochastic estimation of firm technology, inefficiency, and productivity growth using shadow cost and distance functions," Journal of Econometrics, Elsevier, vol. 108(2), pages 203-225, June.
    8. Kleibergen, Frank & Zivot, Eric, 2003. "Bayesian and classical approaches to instrumental variable regression," Journal of Econometrics, Elsevier, vol. 114(1), pages 29-72, May.
    9. Shenggen Fan, 2000. "Technological change, technical and allocative efficiency in Chinese agriculture: the case of rice production in Jiangsu," Journal of International Development, John Wiley & Sons, Ltd., vol. 12(1), pages 1-12.
    10. Rolf Färe & Daniel Primont, 2012. "Dual allocative efficiency parameters," Journal of Productivity Analysis, Springer, vol. 37(3), pages 233-238, June.
    11. Heckelei, Thomas & Mittelhammer, Ron C., 2003. "Bayesian bootstrap multivariate regression," Journal of Econometrics, Elsevier, vol. 112(2), pages 241-264, February.
    12. Zellner, Arnold, 2007. "Some aspects of the history of Bayesian information processing," Journal of Econometrics, Elsevier, vol. 138(2), pages 388-404, June.
    13. Kim, Jae-Young, 2002. "Limited information likelihood and Bayesian analysis," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 175-193, March.
    14. David H. Good & M. Ishaq Nadiri & Robin C. Sickles, 1996. "Index Number and Factor Demand Approaches to the Estimation of Productivity," NBER Working Papers 5790, National Bureau of Economic Research, Inc.
    15. Tai-Hsin Huang, 2000. "Estimating X-Efficiency in Taiwanese Banking Using a Translog Shadow Profit Function," Journal of Productivity Analysis, Springer, vol. 14(3), pages 225-245, November.
    16. Liu, Tung, 2021. "Measuring cost inefficiency: A dual approach," Economic Modelling, Elsevier, vol. 99(C).
    17. Luis R. Murillo‐Zamorano, 2004. "Economic Efficiency and Frontier Techniques," Journal of Economic Surveys, Wiley Blackwell, vol. 18(1), pages 33-77, February.
    18. Juan José Díaz-Hernández, "undated". "Exact Allocative and Technical Inefficiency Using the Normalized Quadratic Cost System," Studies on the Spanish Economy 210, FEDEA.
    19. Tim Coelli & Gholamreza Hajargasht & C.A. Knox Lovell, 2008. "Econometric Estimation of an Input Distance Function in a System of Equations," CEPA Working Papers Series WP012008, School of Economics, University of Queensland, Australia.
    20. Zellner, Arnold & Ando, Tomohiro, 2010. "Bayesian and non-Bayesian analysis of the seemingly unrelated regression model with Student-t errors, and its application for forecasting," International Journal of Forecasting, Elsevier, vol. 26(2), pages 413-434, April.

    More about this item

    Keywords

    Research Methods/ Statistical Methods;

    Statistics

    Access and download statistics

    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:ags:aaea05:19402. See general information about how to correct material in RePEc.

    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: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/aaeaaea.html .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.