IDEAS home Printed from https://ideas.repec.org/b/wfo/wstudy/59303.html
   My bibliography  Save this book

Statistical Benchmarking as a Development Tool. An Introduction for Practitioners

Author

Listed:
  • Klaus Friesenbichler
  • Agnes Kügler

Abstract

This note provides an introduction to two prominent econometric benchmarking methods: Data Envelopment Analysis and Stochastic Frontier Analysis. It discusses the econometric techniques, provides a practical example using the World Bank's Enterprise Survey data, and offers conclusions for development practitioners.

Suggested Citation

  • Klaus Friesenbichler & Agnes Kügler, 2017. "Statistical Benchmarking as a Development Tool. An Introduction for Practitioners," WIFO Studies, WIFO, number 59303.
    • Handle: RePEc:wfo:wstudy:59303
    as

    Download full text from publisher

    File URL: https://www.wifo.ac.at/wwa/pubid/59303
    File Function: abstract
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chien-Ming Chen & Magali A. Delmas & Marvin B. Lieberman, 2015. "Production frontier methodologies and efficiency as a performance measure in strategic management research," Strategic Management Journal, Wiley Blackwell, vol. 36(1), pages 19-36, January.
    2. Chad Syverson, 2011. "What Determines Productivity?," Journal of Economic Literature, American Economic Association, vol. 49(2), pages 326-365, June.
    3. Edquist , Charles & Zabala-Iturriagagoitia , Jon Mikel, 2015. "The Innovation Union Scoreboard is Flawed: The case of Sweden – not being the innovation leader of the EU," Papers in Innovation Studies 2015/16, Lund University, CIRCLE - Centre for Innovation Research.
    4. 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.
    5. Pulina, Manuela & Detotto, Claudio & Paba, Antonello, 2010. "An investigation into the relationship between size and efficiency of the Italian hospitality sector: A window DEA approach," European Journal of Operational Research, Elsevier, vol. 204(3), pages 613-620, August.
    6. Azadeh, A. & Amalnick, M.S. & Ghaderi, S.F. & Asadzadeh, S.M., 2007. "An integrated DEA PCA numerical taxonomy approach for energy efficiency assessment and consumption optimization in energy intensive manufacturing sectors," Energy Policy, Elsevier, vol. 35(7), pages 3792-3806, July.
    7. Luis Orea & Subal C. Kumbhakar, 2004. "Efficiency measurement using a latent class stochastic frontier model," Empirical Economics, Springer, vol. 29(1), pages 169-183, January.
    8. Brown, Rayna, 2006. "Mismanagement or mismeasurement? Pitfalls and protocols for DEA studies in the financial services sector," European Journal of Operational Research, Elsevier, vol. 174(2), pages 1100-1116, October.
    9. 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. V. Vandenberghe, 2018. "The Contribution of Educated Workers to Firms’ Efficiency Gains: The Key Role of Proximity to the ‘Local’ Frontier," De Economist, Springer, vol. 166(3), pages 259-283, September.
    2. repec:use:tkiwps:3232 is not listed on IDEAS
    3. Ioannis Skevas, 2019. "A Hierarchical Stochastic Frontier Model for Efficiency Measurement Under Technology Heterogeneity," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 17(3), pages 513-524, September.
    4. Mike Tsionas & Marwan Izzeldin & Arne Henningsen & Evaggelos Paravalos, 2022. "Addressing endogeneity when estimating stochastic ray production frontiers: a Bayesian approach," Empirical Economics, Springer, vol. 62(3), pages 1345-1363, March.
    5. Philippe Widmer, 2015. "Does prospective payment increase hospital (in)efficiency? Evidence from the Swiss hospital sector," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 16(4), pages 407-419, May.
    6. Hailu, Getu & Goddard, Ellen W. & Jeffrey, Scott R., 2005. "Measuring Efficiency in Fruit and Vegetable Marketing Co-operatives with Heterogeneous Technologies in Canada," 2005 Annual meeting, July 24-27, Providence, RI 19507, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    7. Ronald Felthoven & William Horrace & Kurt Schnier, 2009. "Estimating heterogeneous capacity and capacity utilization in a multi-species fishery," Journal of Productivity Analysis, Springer, vol. 32(3), pages 173-189, December.
    8. Orea, Luis, 2019. "The Econometric Measurement of Firms’ Efficiency," Efficiency Series Papers 2019/02, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    9. Sakouvogui Kekoura & Shaik Saleem & Doetkott Curt & Magel Rhonda, 2021. "Sensitivity analysis of stochastic frontier analysis models," Monte Carlo Methods and Applications, De Gruyter, vol. 27(1), pages 71-90, March.
    10. Amer Ait Sidhoum & K Hervé Dakpo & Laure Latruffe, 2022. "Trade-offs between economic, environmental and social sustainability on farms using a latent class frontier efficiency model: Evidence for Spanish crop farms," PLOS ONE, Public Library of Science, vol. 17(1), pages 1-17, January.
    11. Bos, J.W.B. & Economidou, C. & Koetter, M. & Kolari, J.W., 2010. "Do all countries grow alike?," Journal of Development Economics, Elsevier, vol. 91(1), pages 113-127, January.
    12. Fertő, Imre & Baráth, Lajos, 2013. "Heterogenitás és technikai hatékonyság - a magyar specializált szántóföldi növénytermesztő üzemek esete [Heterogeneity and technical efficiency - the case of Hungarys specialized arable crop produc," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(6), pages 650-669.
    13. Per J. Agrell & Mehdi Farsi & Massimo Filippini & Martin Koller, 2013. "Unobserved heterogeneous effects in the cost efficiency analysis of electricity distribution systems," Working Papers 0038, Swiss Economics.
    14. Marijn Verschelde & Michel Dumont & Glenn Rayp & Bruno Merlevede, 2016. "Semiparametric stochastic metafrontier efficiency of European manufacturing firms," Journal of Productivity Analysis, Springer, vol. 45(1), pages 53-69, February.
    15. Carlos Pestana Barros & Julio del Corral & Pedro Garcia-del-Barrio, 2008. "Identification of Segments of Soccer Clubs in the Spanish League First Division With a Latent Class Model," Journal of Sports Economics, , vol. 9(5), pages 451-469, October.
    16. Bellio, Ruggero & Grassetti, Luca, 2011. "Semiparametric stochastic frontier models for clustered data," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 71-83, January.
    17. Barros, Carlos Pestana & Chen, Zhongfei & Managi, Shunsuke & Antunes, Olinda Sequeira, 2013. "Examining the cost efficiency of Chinese hydroelectric companies using a finite mixture model," Energy Economics, Elsevier, vol. 36(C), pages 511-517.
    18. Surender Kumar & Madhu Khanna, 2019. "Temperature and production efficiency growth: empirical evidence," Climatic Change, Springer, vol. 156(1), pages 209-229, September.
    19. Maria Martinez Cillero & Fiona Thorne & Michael Wallace & James Breen & Thia Hennessy, 2018. "The Effects of Direct Payments on Technical Efficiency of Irish Beef Farms: A Stochastic Frontier Analysis," Journal of Agricultural Economics, Wiley Blackwell, vol. 69(3), pages 669-687, September.
    20. Eric J. Bartelsman & Zoltan Wolf, 2017. "Measuring Productivity Dispersion," Tinbergen Institute Discussion Papers 17-033/VI, Tinbergen Institute.
    21. Pavlos Almanidis & Mustafa U. Karakaplan & Levent Kutlu, 2019. "A dynamic stochastic frontier model with threshold effects: U.S. bank size and efficiency," Journal of Productivity Analysis, Springer, vol. 52(1), pages 69-84, December.

    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:wfo:wstudy:59303. 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: Florian Mayr (email available below). General contact details of provider: https://edirc.repec.org/data/wifooat.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.