IDEAS home Printed from https://ideas.repec.org/a/taf/regstd/v53y2019i11p1565-1574.html
   My bibliography  Save this article

Agglomeration effects and spatial spillovers in efficiency analysis: a distribution-free methodology

Author

Listed:
  • Levent Kutlu
  • Usha Nair-Reichert

Abstract

Technical efficiency estimates using standard stochastic frontier models do not include spillover effects, although the existence of such spillovers is well documented in the productivity literature. This paper proposes a regression-based, distribution-free estimation method applicable to both time-varying efficiency spatial stochastic frontier and fixed effects spatial autoregressive models, which is relatively easy to estimate. The empirical results from the Indian chemical industry illustrate that ignoring spatial dependence may seriously distort estimates for efficiency rankings. The average overall spillover effect on a firm’s efficiency is 7.20 percentage points, or an average positive spillover effect of US$4.9 million in sales revenue.

Suggested Citation

  • Levent Kutlu & Usha Nair-Reichert, 2019. "Agglomeration effects and spatial spillovers in efficiency analysis: a distribution-free methodology," Regional Studies, Taylor & Francis Journals, vol. 53(11), pages 1565-1574, November.
    • Handle: RePEc:taf:regstd:v:53:y:2019:i:11:p:1565-1574
    DOI: 10.1080/00343404.2019.1590543
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00343404.2019.1590543
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00343404.2019.1590543?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.

    Citations

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


    Cited by:

    1. Levent Kutlu, 2022. "Spatial stochastic frontier model with endogenous weighting matrix," Empirical Economics, Springer, vol. 63(4), pages 1947-1968, October.
    2. Samuel Faria & Sofia Gouveia & Alexandre Guedes & João Rebelo, 2021. "Transient and Persistent Efficiency and Spatial Spillovers: Evidence from the Portuguese Wine Industry," Economies, MDPI, vol. 9(3), pages 1-20, August.
    3. Carmelo Algeri & Antonio F. Forgione & Carlo Migliardo, 2022. "Do spatial dependence and market power matter in the diversification of cooperative banks?," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 51(3), November.
    4. Elisa Fusco & Giuseppe Arbia & Francesco Vidoli & Vincenzo Nardelli, 2024. "On Spatio-Temporal Stochastic Frontier Models," Econometrics Working Papers Archive 2024_09, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    5. Kutlu, Levent & Tran, Kien C. & Tsionas, Mike G., 2020. "A spatial stochastic frontier model with endogenous frontier and environmental variables," European Journal of Operational Research, Elsevier, vol. 286(1), pages 389-399.
    6. Kassoum Ayouba, 2023. "Spatial dependence in production frontier models," Journal of Productivity Analysis, Springer, vol. 60(1), pages 21-36, August.
    7. Yuanxin Peng & Zhuo Chen & Jay Lee, 2020. "Dynamic Convergence of Green Total Factor Productivity in Chinese Cities," Sustainability, MDPI, vol. 12(12), pages 1-18, June.
    8. Carmelo Algeri & Luc Anselin & Antonio Fabio Forgione & Carlo Migliardo, 2022. "Spatial dependence in the technical efficiency of local banks," Papers in Regional Science, Wiley Blackwell, vol. 101(3), pages 685-716, June.

    More about this item

    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:taf:regstd:v:53:y:2019:i:11:p:1565-1574. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/CRES20 .

    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.