IDEAS home Printed from https://ideas.repec.org/p/hhs/lunewp/1999_007.html
   My bibliography  Save this paper

Stochastic Frontier Production Function With Errors-In-Variables

Author

Listed:
  • Dhawan, Rajeev

    (Anderson Graduate School of Management)

  • Jochumzen, Peter

    (Department of Economics, Lund University)

Abstract

This paper develops a procedure for estimating parameters of a cross-sectional stochastic frontier production function when the factors of production suffer from measurement errors. Specifically, we use Fuller's (1987) reliability ratio concept to develop an estimator for the model in Aigner et al (1977). Our Monte-Carlo simulation exercise illustrates the direction and the severity of bias in the estimates of the elasticity parameters and the returns to scale feature of the production function when using the traditional maximum-likelihood estimator (MLE) in presence of measurement errors. In contrast the reliability ratio based estimator consistently estimates these parameters even under extreme degree of measurement errors. Additionally, estimates of firm level technical efficiency are severely biased for traditional MLE compared to reliability ratio estimator, rendering inter-firm efficiency comparisons infeasible. The seriousness of measurement errors in a practical setting is demonstrated by using data for a cross-section of publicly traded U.S. corporations.

Suggested Citation

  • Dhawan, Rajeev & Jochumzen, Peter, 1999. "Stochastic Frontier Production Function With Errors-In-Variables," Working Papers 1999:007, Lund University, Department of Economics.
    • Handle: RePEc:hhs:lunewp:1999_007
    as

    Download full text from publisher

    File URL: https://swopec.hhs.se/lunewp/papers/lunewp1999_007.ps.zip
    File Function: Complete Rendering
    Download Restriction: no
    File URL: https://swopec.hhs.se/lunewp/papers/lunewp1999_007.ps
    File Function: Complete Rendering
    Download Restriction: no
    File URL: https://swopec.hhs.se/lunewp/papers/lunewp1999_007.pdf.zip
    File Function: Complete Rendering
    Download Restriction: no
    File URL: https://swopec.hhs.se/lunewp/papers/lunewp1999_007.pdf
    File Function: Complete Rendering
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mark Gertler & R. Glenn Hubbard, 1988. "Financial factors in business fluctuations," Proceedings - Economic Policy Symposium - Jackson Hole, Federal Reserve Bank of Kansas City, pages 33-78.
    2. Kumbhakar, Subal C, 1987. "Production Frontiers and Panel Data: An Application to U.S. Class 1 Railroads," Journal of Business & Economic Statistics, American Statistical Association, vol. 5(2), pages 249-255, April.
    3. Klepper, Steven & Leamer, Edward E, 1984. "Consistent Sets of Estimates for Regressions with Errors in All Variables," Econometrica, Econometric Society, vol. 52(1), pages 163-183, January.
    4. Rajeev Dhawan, 1997. "Asymmetric Information and Debt Financing: Hie Empirical Importance of Size and Balance Sheet Factors," International Journal of the Economics of Business, Taylor & Francis Journals, vol. 4(2), pages 189-202.
    5. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    6. Fried, Harold O. & Lovell, C. A. Knox & Schmidt, Shelton S. (ed.), 1993. "The Measurement of Productive Efficiency: Techniques and Applications," OUP Catalogue, Oxford University Press, number 9780195072181.
    7. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    8. Kumbhakar, Subal C & Hjalmarsson, Lennart, 1995. "Labour-Use Efficiency in Swedish Social Insurance Offices," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(1), pages 33-47, Jan.-Marc.
    9. Murphy, Kevin M & Topel, Robert H, 2002. "Estimation and Inference in Two-Step Econometric Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 88-97, January.
    10. Edgerton, David & Jochumzen, Peter, 2003. "Estimation in Binary Choice Models with Measurement Errors," Working Papers 2003:4, Lund University, Department of Economics, revised 07 Jul 2003.
    11. Stevenson, Rodney E., 1980. "Likelihood functions for generalized stochastic frontier estimation," Journal of Econometrics, Elsevier, vol. 13(1), pages 57-66, May.
    12. Battese, George E. & Coelli, Tim J., 1988. "Prediction of firm-level technical efficiencies with a generalized frontier production function and panel data," Journal of Econometrics, Elsevier, vol. 38(3), pages 387-399, July.
    13. Rajeev Dhawan & Geoffrey Gerdes, 1997. "Estimating Technological Change Using a Stochastic Frontier Production Function Framework: Evidence from U.S. Firm-Level Data," Journal of Productivity Analysis, Springer, vol. 8(4), pages 431-446, November.
    14. Paul W. Bauer, 1988. "Decomposing TFP growth in the presence of cost inefficiency, nonconstant returns to scale, and technological progress," Working Papers (Old Series) 8813, Federal Reserve Bank of Cleveland.
    15. Bauer, Paul W., 1990. "Recent developments in the econometric estimation of frontiers," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 39-56.
    16. 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.
    17. Beckers, Dominique E. & Hammond, Christopher J., 1987. "A tractable likelihood function for the normal-gamma stochastic frontier model," Economics Letters, Elsevier, vol. 24(1), pages 33-38.
    18. Kumbhakar, Subal C, 1988. "On the Estimation of Technical and Allocative Inefficiency Using Stochastic Frontier Functions: The Case of U.S. Class 1 Railroads," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 29(4), pages 727-743, November.
    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. Luis R. Murillo‐Zamorano, 2004. "Economic Efficiency and Frontier Techniques," Journal of Economic Surveys, Wiley Blackwell, vol. 18(1), pages 33-77, February.
    2. Tsionas, Efthymios G., 2012. "Maximum likelihood estimation of stochastic frontier models by the Fourier transform," Journal of Econometrics, Elsevier, vol. 170(1), pages 234-248.
    3. Dairo Estrada & Poldy Osorio, 2004. "Effects of Financial Capital on Colombian Banking Efficiency," Revista ESPE - Ensayos sobre Política Económica, Banco de la Republica de Colombia, vol. 22(47), pages 162-201, December.
    4. Gian Carlo Scarsi, 1999. "Local Electricity Distribution in Italy: Comparative Efficiency Analysis and Methodological Cross-Checking," Working Papers 1999.16, Fondazione Eni Enrico Mattei.
    5. Joaquín Maudos Villarroya, 1996. "Market structure and performance in Spanish banking using a direct measure of efficiency," Working Papers. Serie EC 1996-12, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    6. Althaler, Karl S. & Slavova, Tatjana, 2000. "DEA Problems under Geometrical or Probability Uncertainties of Sample Data," Economics Series 89, Institute for Advanced Studies.
    7. Belegri-Roboli, Athena & Michaelides, Panayotis G., 2005. "Measuring Technical Efficiency in the Greek Public Power Corporation by means of Stochastic Frontier Analysis (1970-1997)," MPRA Paper 74425, University Library of Munich, Germany.
    8. Dong, Xiao-yuan & Putterman, Louis, 1997. "Productivity and Organization in China's Rural Industries: A Stochastic Frontier Analysis," Journal of Comparative Economics, Elsevier, vol. 24(2), pages 181-201, April.
    9. Abdelaziz Rouabah, 2002. "Economies d?échelle, économies de diversification et efficacité productive des banques luxembourgeoises : une analyse comparative des frontières stochastiques sur données en panel," BCL working papers 3, Central Bank of Luxembourg.
    10. Kevin Cullinane & Dong-Wook Song, 2003. "A stochastic frontier model of the productive efficiency of Korean container terminals," Applied Economics, Taylor & Francis Journals, vol. 35(3), pages 251-267.
    11. Coelli, Tim J., 1995. "Recent Developments In Frontier Modelling And Efficiency Measurement," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 39(3), pages 1-27, December.
    12. Ali M. Oumer & Amin Mugera & Michael Burton & Atakelty Hailu, 2022. "Technical efficiency and firm heterogeneity in stochastic frontier models: application to smallholder maize farms in Ethiopia," Journal of Productivity Analysis, Springer, vol. 57(2), pages 213-241, April.
    13. Cullinane, Kevin & Song, Dong-Wook, 2006. "Estimating the Relative Efficiency of European Container Ports: A Stochastic Frontier Analysis," Research in Transportation Economics, Elsevier, vol. 16(1), pages 85-115, January.
    14. Cullinane, Kevin & Song, Dong-Wook & Gray, Richard, 2002. "A stochastic frontier model of the efficiency of major container terminals in Asia: assessing the influence of administrative and ownership structures," Transportation Research Part A: Policy and Practice, Elsevier, vol. 36(8), pages 743-762, October.
    15. Lokina, Razack B., 2008. "Technical Efficiency and the Role of Skipper Skill in Artisanal Lake Victoria Fisheries," RFF Working Paper Series dp-08-13-efd, Resources for the Future.
    16. Roberto Colombi & Subal Kumbhakar & Gianmaria Martini & Giorgio Vittadini, 2014. "Closed-skew normality in stochastic frontiers with individual effects and long/short-run efficiency," Journal of Productivity Analysis, Springer, vol. 42(2), pages 123-136, October.
    17. Schalk Hans Joachim & Untiedt Gerhard & Lüschow Jörg, 1995. "Technische Effizienz, Wachstum und Konvergenz in den Arbeitsmarktregionen der Bundesrepublik Deutschland (West). Eine ökonometrische Analyse für die Verarbeitende Industrie mit einem „Frontier Product," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 214(1), pages 25-49, February.
    18. van den Broeck, Julien & Koop, Gary & Osiewalski, Jacek & Steel, Mark F. J., 1994. "Stochastic frontier models : A Bayesian perspective," Journal of Econometrics, Elsevier, vol. 61(2), pages 273-303, April.
    19. Maira Caño- Guiral, 1995. "Competitividad y eficiencia técnica. Un modelo de datos panel para la industria láctea uruguaya," Documentos de Trabajo (working papers) 0795, Department of Economics - dECON.
    20. Satya Paul & Sriram Shankar, 2020. "Estimating efficiency effects in a panel data stochastic frontier model," Journal of Productivity Analysis, Springer, vol. 53(2), pages 163-180, April.

    More about this item

    Keywords

    Errors-In-Variables; Stochastic Frontier; Technical Efficiency; Reliability Ratio;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:hhs:lunewp:1999_007. 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: Iker Arregui Alegria (email available below). General contact details of provider: https://edirc.repec.org/data/delunse.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.