IDEAS home Printed from https://ideas.repec.org/a/spr/empeco/v60y2021i1d10.1007_s00181-020-01929-w.html
   My bibliography  Save this article

A hierarchical panel data stochastic frontier model for the estimation of stochastic metafrontiers

Author

Listed:
  • Christine Amsler

    (Michigan State University)

  • Yi Yi Chen

    (Tamkang University)

  • Peter Schmidt

    (Michigan State University)

  • Hung Jen Wang

    (National Taiwan University)

Abstract

This paper proposes a stochastic frontier model with three composed errors, and therefore six error components. As in the metafrontier literature, firms belong to groups with a group-specific frontier. A firm has a level of short-run and long-run inefficiency relative to its group-specific frontier, as in existing models with two composed errors and four error components. But now there is also a group-specific inefficiency, that is, a shortfall of the group-specific frontier from the best practice metafrontier. The paper shows how to estimate this model and how to extract predictions of the various inefficiencies.

Suggested Citation

  • Christine Amsler & Yi Yi Chen & Peter Schmidt & Hung Jen Wang, 2021. "A hierarchical panel data stochastic frontier model for the estimation of stochastic metafrontiers," Empirical Economics, Springer, vol. 60(1), pages 353-363, January.
    • Handle: RePEc:spr:empeco:v:60:y:2021:i:1:d:10.1007_s00181-020-01929-w
    DOI: 10.1007/s00181-020-01929-w
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00181-020-01929-w
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s00181-020-01929-w?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.

    References listed on IDEAS

    as
    1. 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.
    2. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, December.
    3. Laszlo Matyas (ed.), 2017. "The Econometrics of Multi-dimensional Panels," Advanced Studies in Theoretical and Applied Econometrics, Springer, number 978-3-319-60783-2, July-Dece.
    4. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
    5. Roberto Colombi & Gianmaria Martini & Giorgio Vittadini, 2011. "A Stochastic Frontier Model with short-run and long-run inefficiency random effects," Working Papers 1101, Department of Management, Information and Production Engineering, University of Bergamo.
    6. Qi Li & Jeffrey Scott Racine, 2006. "Density Estimation, from Nonparametric Econometrics: Theory and Practice," Introductory Chapters, in: Nonparametric Econometrics: Theory and Practice, Princeton University Press.
    7. Lau, Lawrence J. & Yotopoulos, Pan A., 1989. "The meta-production function approach to technological change in world agriculture," Journal of Development Economics, Elsevier, vol. 31(2), pages 241-269, October.
    8. Mark M. Pitt, 1983. "Farm-Level Fertilizer Demand in Java: A Meta-Production Function Approach," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 65(3), pages 502-508.
    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. Qi Li & Vasilis Sarafidis & Joakim Westerlund, 2021. "Essays in honor of Professor Badi H Baltagi," Empirical Economics, Springer, vol. 60(1), pages 1-11, January.
    2. Li, Qi & Sarafidis, Vasilis & Westerlund, Joakim, 2020. "Essays in Honor of Professor Badi H Baltagi: Editorial," MPRA Paper 104751, University Library of Munich, Germany.

    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. 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.
    2. Eduardo Fé & Bruce Hollingsworth, 2016. "Short- and long-run estimates of the local effects of retirement on health," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 179(4), pages 1051-1067, October.
    3. Elia Lapenta, 2022. "A Bootstrap Specification Test for Semiparametric Models with Generated Regressors," Papers 2212.11112, arXiv.org, revised Oct 2023.
    4. Hernandez, Manuel A. & Torero, Maximo, 2018. "A poverty-sensitive scorecard to prioritize lending and grant allocation: Evidence from Central America," Food Policy, Elsevier, vol. 77(C), pages 81-90.
    5. Xiaolin Sun, 2022. "Estimation of Heterogeneous Treatment Effects Using a Conditional Moment Based Approach," Papers 2210.15829, arXiv.org, revised Dec 2022.
    6. Chen, Yi-Yi & Schmidt, Peter & Wang, Hung-Jen, 2014. "Consistent estimation of the fixed effects stochastic frontier model," Journal of Econometrics, Elsevier, vol. 181(2), pages 65-76.
    7. Chaohua Dong & Jiti Gao & Oliver Linton & Bin peng, 2020. "On Time Trend of COVID-19: A Panel Data Study," Monash Econometrics and Business Statistics Working Papers 22/20, Monash University, Department of Econometrics and Business Statistics.
    8. Walter Sosa-Escudero & Sergio Petralia, 2011. "Anatomy of Distributive Changes in Argentina," Chapters, in: Werner Baer & David Fleischer (ed.), The Economies of Argentina and Brazil, chapter 10, Edward Elgar Publishing.
    9. Luis Alvarez & Cristine Pinto & Vladimir Ponczek, 2022. "Homophily in preferences or meetings? Identifying and estimating an iterative network formation model," Papers 2201.06694, arXiv.org, revised Mar 2024.
    10. Castiglione, Concetta & Infante, Davide & Zieba, Marta, 2023. "Public support for performing arts. Efficiency and productivity gains in eleven European countries," Socio-Economic Planning Sciences, Elsevier, vol. 85(C).
    11. Camelia Minoiu & Sanjay Reddy, 2014. "Kernel density estimation on grouped data: the case of poverty assessment," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 12(2), pages 163-189, June.
    12. Vittadini, Giorgio & Sturaro, Caterina & Folloni, Giuseppe, 2022. "Non-Cognitive Skills and Cognitive Skills to measure school efficiency," Socio-Economic Planning Sciences, Elsevier, vol. 81(C).
    13. repec:hal:spmain:info:hdl:2441/4hgajj9cf48dladkd9pn9jcj4p is not listed on IDEAS
    14. Cornelius Christian & Lukas Hensel & Christopher Roth, 2019. "Income Shocks and Suicides: Causal Evidence From Indonesia," The Review of Economics and Statistics, MIT Press, vol. 101(5), pages 905-920, December.
    15. Quoc-Anh Do & Kieu-Trang Nguyen & Anh N. Tran, 2017. "One Mandarin Benefits the Whole Clan: Hometown Favoritism in an Authoritarian Regime," American Economic Journal: Applied Economics, American Economic Association, vol. 9(4), pages 1-29, October.
    16. Campante, Filipe R. & Do, Quoc-Anh & Guimaraes, Bernardo, 2012. "Isolated Capital Cities and Misgovernance: Theory and Evidence," Working Paper Series rwp12-058, Harvard University, John F. Kennedy School of Government.
    17. Hugo Bodory & Martin Huber & Michael Lechner, 2022. "The finite sample performance of instrumental variable-based estimators of the Local Average Treatment Effect when controlling for covariates," Papers 2212.07379, arXiv.org.
    18. Manuel Hernandez & Maximo Torero, 2014. "Parametric versus nonparametric methods in risk scoring: an application to microcredit," Empirical Economics, Springer, vol. 46(3), pages 1057-1079, May.
    19. Filipe Campante & Quoc-Anh Do & Bernardo Guimaraes, 2014. "Capital Cities, Conflict, and Misgovernance: Theory and Evidence," Sciences Po Economics Discussion Papers 2014-13, Sciences Po Departement of Economics.
    20. Damian Kozbur, 2013. "Inference in additively separable models with a high-dimensional set of conditioning variables," ECON - Working Papers 284, Department of Economics - University of Zurich, revised Apr 2018.
    21. Sickles, Robin C. & Song, Wonho & Zelenyuk, Valentin, 2018. "Econometric Analysis of Productivity: Theory and Implementation in R," Working Papers 18-008, Rice University, Department of Economics.

    More about this item

    Keywords

    Stochastic frontier; Panel data; Hierarchical model; Metafrontier; Inefficiency;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation

    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:spr:empeco:v:60:y:2021:i:1:d:10.1007_s00181-020-01929-w. 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.