IDEAS home Printed from https://ideas.repec.org/a/kap/jproda/v18y2002i3p241-253.html
   My bibliography  Save this article

Heteroscedasticity and Non-Monotonic Efficiency Effects of a Stochastic Frontier Model

Author

Listed:
  • Hung-Jen Wang

Abstract

We consider a model that provides flexible parameterizations of the exogenous influences on inefficiency. In particular, we demonstrate the model's unique property of accommodating non-monotonic efficiency effect. With this non-monotonicity, production efficiency no longer increases or decreases monotonically with the exogenous influence; instead, the relationship can shifts within the sample. Our empirical example shows that variables can indeed have non-monotonic effects on efficiency. Furthermore, ignoring non-monotonicity is shown to yield an inferior estimation of the model, which sometimes results in opposite predictions concerning the data. Copyright Kluwer Academic Publishers 2002

Suggested Citation

  • Hung-Jen Wang, 2002. "Heteroscedasticity and Non-Monotonic Efficiency Effects of a Stochastic Frontier Model," Journal of Productivity Analysis, Springer, vol. 18(3), pages 241-253, November.
  • Handle: RePEc:kap:jproda:v:18:y:2002:i:3:p:241-253
    DOI: 10.1023/A:1020638827640
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1023/A:1020638827640
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1023/A:1020638827640?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 look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Anil Bera & Subhash Sharma, 1999. "Estimating Production Uncertainty in Stochastic Frontier Production Function Models," Journal of Productivity Analysis, Springer, vol. 12(3), pages 187-210, November.
    2. Coelli, Tim J. & Battese, George E., 1996. "Identification Of Factors Which Influence The Technical Inefficiency Of Indian Farmers," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 40(2), pages 1-26, August.
    3. Caudill, Steven B. & Ford, Jon M., 1993. "Biases in frontier estimation due to heteroscedasticity," Economics Letters, Elsevier, vol. 41(1), pages 17-20.
    4. Hadri, Kaddour, 1999. "Estimation of a Doubly Heteroscedastic Stochastic Frontier Cost Function," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(3), pages 359-363, July.
    5. Meeusen, Wim & van den Broeck, J, 1977. "Technical Efficiency and Dimension of the Firm: Some Results on the Use of Frontier Production Functions," Empirical Economics, Springer, vol. 2(2), pages 109-122.
    6. Hung-jen Wang & Peter Schmidt, 2002. "One-Step and Two-Step Estimation of the Effects of Exogenous Variables on Technical Efficiency Levels," Journal of Productivity Analysis, Springer, vol. 18(2), pages 129-144, September.
    7. 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.
    8. 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.
    9. Bauer, Paul W., 1990. "Recent developments in the econometric estimation of frontiers," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 39-56.
    10. Caudill, Steven B & Ford, Jon M & Gropper, Daniel M, 1995. "Frontier Estimation and Firm-Specific Inefficiency Measures in the Presence of Heteroscedasticity," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(1), pages 105-111, January.
    11. 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.
    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. Paul, Satya & Shankar, Sriram, 2018. "Modelling Efficiency Effects in a True Fixed Effects Stochastic Frontier," MPRA Paper 87437, University Library of Munich, Germany.
    2. 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.
    3. Efecan, Volkan & Temiz, İzzettin, 2023. "Assessing the technical efficiency of container ports based on a non-monotonic inefficiency effects model," Utilities Policy, Elsevier, vol. 81(C).
    4. Antti Saastamoinen, 2015. "Heteroscedasticity Or Production Risk? A Synthetic View," Journal of Economic Surveys, Wiley Blackwell, vol. 29(3), pages 459-478, July.
    5. Mäkinen, Mikko, 2007. "Do Stock Opiton Schemes Affect Technical Inefficiency? Evidence from Finland," Discussion Papers 1085, The Research Institute of the Finnish Economy.
    6. Narangerel Ganbold & Shah Fahad & Hua Li & Tumendemberel Gungaa, 2022. "An evaluation of subsidy policy impacts, transient and persistent technical efficiency: A case of Mongolia," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(7), pages 9223-9242, July.
    7. Subal C. Kumbhakar & Christopher F. Parmeter & Valentin Zelenyuk, 2022. "Stochastic Frontier Analysis: Foundations and Advances I," Springer Books, in: Subhash C. Ray & Robert G. Chambers & Subal C. Kumbhakar (ed.), Handbook of Production Economics, chapter 8, pages 331-370, Springer.
    8. Giovanni Marin & Alessandro Palma, 2015. "Technology invention and diffusion in residential energy consumption. A stochastic frontier approach," IEFE Working Papers 81, IEFE, Center for Research on Energy and Environmental Economics and Policy, Universita' Bocconi, Milano, Italy.
    9. Jorge Galán & Helena Veiga & Michael Wiper, 2014. "Bayesian estimation of inefficiency heterogeneity in stochastic frontier models," Journal of Productivity Analysis, Springer, vol. 42(1), pages 85-101, August.
    10. Christine Amsler & Peter Schmidt & Wen-Jen Tsay, 2015. "A post-truncation parameterization of truncated normal technical inefficiency," Journal of Productivity Analysis, Springer, vol. 44(2), pages 209-220, October.
    11. Dipanwita Sarkar & Trevor C. Collier, 2019. "Does host-country education mitigate immigrant inefficiency? Evidence from earnings of Australian university graduates," Empirical Economics, Springer, vol. 56(1), pages 81-106, January.
    12. Paul, Satya & Shankar, Sriram, 2018. "On estimating efficiency effects in a stochastic frontier model," European Journal of Operational Research, Elsevier, vol. 271(2), pages 769-774.
    13. Ajayi, Victor & Weyman-Jones, Tom, 2021. "State-level electricity generation efficiency: Do restructuring and regulatory institutions matter in the US?," Energy Economics, Elsevier, vol. 104(C).
    14. Markose Chekol Zewdie & Michele Moretti & Daregot Berihun Tenessa & Zemen Ayalew Ayele & Jan Nyssen & Enyew Adgo Tsegaye & Amare Sewnet Minale & Steven Van Passel, 2021. "Agricultural Technical Efficiency of Smallholder Farmers in Ethiopia: A Stochastic Frontier Approach," Land, MDPI, vol. 10(3), pages 1-17, March.
    15. Christopher F. Parmeter & Hung-Jen Wang & Subal C. Kumbhakar, 2017. "Nonparametric estimation of the determinants of inefficiency," Journal of Productivity Analysis, Springer, vol. 47(3), pages 205-221, June.
    16. Getu Hailu & B. James Deaton, 2016. "Agglomeration Effects in Ontario’s Dairy Farming," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 98(4), pages 1055-1073.
    17. Fabio Pieri & Enrico Zaninotto, 2010. "The Impact of Vertical Integration and Outsourcing on Firm Efficiency: Evidence from the Italian Machine Tool Industry," DISA Working Papers 1001, Department of Computer and Management Sciences, University of Trento, Italy, revised 11 Mar 2010.
    18. repec:kap:iaecre:v:14:y:2008:i:1:p:76-89 is not listed on IDEAS
    19. Mohanty, Sunil K. & Lin, Winston T. & Lin, Hong-Jen, 2013. "Measuring cost efficiency in presence of heteroskedasticity: The case of the banking industry in Taiwan," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 26(C), pages 77-90.
    20. Mussa, Richard, 2014. "Externalities of Education on Efficiency and Production Uncertainty of Maize in Rural Malawi," MPRA Paper 54628, University Library of Munich, Germany.
    21. Holtkamp, A.M. & Brummer, B., 2018. "Environmental efficiency of smallholder rubber production," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277518, International Association of Agricultural Economists.

    More about this item

    Keywords

    stochastic frontiers; heteroscedasticity; non-monotonic effects;
    All these keywords.

    JEL classification:

    • C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Econometric and Statistical Methods; Specific Distributions
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets

    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:kap:jproda:v:18:y:2002:i:3:p:241-253. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.