IDEAS home Printed from https://ideas.repec.org/a/taf/apeclt/v11y2004i10p657-660.html
   My bibliography  Save this article

Aggregation bias and its bounds in measuring technical efficiency

Author

Listed:
  • Rolf Fare
  • Shawna Grosskopf
  • Valentin Zelenyuk

Abstract

The discussion about the bias due to input (or output) aggregation in efficiency measurement based on data envelopment analysis, recently revisited by Tauer (2001) and Fare and Zelenyuk (2002) is continued. Attention is focused on the direction and the bounds of the aggregation bias.

Suggested Citation

  • Rolf Fare & Shawna Grosskopf & Valentin Zelenyuk, 2004. "Aggregation bias and its bounds in measuring technical efficiency," Applied Economics Letters, Taylor & Francis Journals, vol. 11(10), pages 657-660.
    • Handle: RePEc:taf:apeclt:v:11:y:2004:i:10:p:657-660
    DOI: 10.1080/1350485042000207243
    as

    Download full text from publisher

    File URL: http://www.informaworld.com/openurl?genre=article&doi=10.1080/1350485042000207243&magic=repec&7C&7C8674ECAB8BB840C6AD35DC6213A474B5
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/1350485042000207243?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. Loren Tauer, 2001. "Input aggregation and computed technical efficiency," Applied Economics Letters, Taylor & Francis Journals, vol. 8(5), pages 295-297.
    2. Rolf Fare & Valentin Zelenyuk, 2002. "Input aggregation and technical efficiency," Applied Economics Letters, Taylor & Francis Journals, vol. 9(10), pages 635-636.
    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. Valentin Zelenyuk, 2023. "Productivity analysis: roots, foundations, trends and perspectives," Journal of Productivity Analysis, Springer, vol. 60(3), pages 229-247, December.
    2. Darold Barnum & John Gleason, 2005. "Technical efficiency bias caused by intra-input aggregation in data envelopment analysis," Applied Economics Letters, Taylor & Francis Journals, vol. 12(13), pages 785-788.
    3. Aldanondo, Ana M. & Casasnovas, Valero L., 2015. "More is better than one: the impact of different numbers of input aggregators in technical efficiency estimation," MPRA Paper 64120, University Library of Munich, Germany.
    4. A. M. Aldanondo & V. L. Casasnovas, 2015. "Input aggregation bias in technical efficiency with multiple criteria analysis," Applied Economics Letters, Taylor & Francis Journals, vol. 22(6), pages 430-435, April.
    5. Natalya Zelenyuk & Valentin Zelenyuk, 2015. "Productivity Drivers of Efficiency in Banking: Importance of Model Specifications," CEPA Working Papers Series WP082015, School of Economics, University of Queensland, Australia.
    6. Aldanondo-Ochoa, Ana M. & Casasnovas-Oliva, Valero L. & Almansa-Sáez, M. Carmen, 2017. "Cross-constrained Measuring the Cost-environment Efficiency in Material Balance Based Frontier Models," Ecological Economics, Elsevier, vol. 142(C), pages 46-55.
    7. Valentin Zelenyuk, 2022. "Aggregation of Efficiency and Productivity: From Firm to Sector and Higher Levels," Springer Books, in: Subhash C. Ray & Robert G. Chambers & Subal C. Kumbhakar (ed.), Handbook of Production Economics, chapter 25, pages 1039-1079, Springer.
    8. Darold T. Barnum & John M. Gleason, 2007. "Technical efficiency bias in data envelopment analysis caused by intra-output aggregation," Applied Economics Letters, Taylor & Francis Journals, vol. 14(9), pages 623-626.
    9. Robin Cross & Rolf Färe, 2008. "Farrell efficiency under value and quantity data," Journal of Productivity Analysis, Springer, vol. 29(3), pages 193-199, June.
    10. Heinz Ahn & Peter Bogetoft & Ana Lopes, 2019. "Measuring potential sub-unit efficiency to counter the aggregation bias in benchmarking," Journal of Business Economics, Springer, vol. 89(1), pages 53-77, February.
    11. Pavlo Demchuk & Valentin Zelenyuk, 2009. "Testing differences in efficiency of regions within a country: the case of Ukraine," Journal of Productivity Analysis, Springer, vol. 32(2), pages 81-102, October.
    12. Ali Homayoni & Reza Fallahnejad & Farhad Hosseinzadeh Lotfi, 2022. "Cross Malmquist Productivity Index in Data Envelopment Analysis," 4OR, Springer, vol. 20(4), pages 567-602, December.
    13. Darold Barnum & John Gleason, 2006. "Measuring efficiency in allocating inputs among outputs with DEA," Applied Economics Letters, Taylor & Francis Journals, vol. 13(6), pages 333-336.
    14. Colamartino, Chiara & Dipierro, Anna Rita & Toma, Pierluigi & Frittelli, Massimo, 2023. "What lies behind the success of Italian GIs products? Questioning tradition in consortia via aggregated conditional efficiency," Socio-Economic Planning Sciences, Elsevier, vol. 87(PB).
    15. Valentin Zelenyuk, 2019. "Data Envelopment Analysis and Business Analytics: The Big Data Challenges and Some Solutions," CEPA Working Papers Series WP072019, School of Economics, University of Queensland, Australia.
    16. Emil Heesche & Mette Asmild, 2022. "Implications of Aggregation Uncertainty in DEA," IFRO Working Paper 2022/02, University of Copenhagen, Department of Food and Resource Economics.
    17. Subhash C. Ray, 2022. "Choice of Inputs and Outputs for Production Analysis," Springer Books, in: Subhash C. Ray & Robert G. Chambers & Subal C. Kumbhakar (ed.), Handbook of Production Economics, chapter 26, pages 1083-1116, Springer.
    18. Aldanondo, Ana M. & Casasnovas, Valero L. & Almansa, M. Carmen, 2016. "Cost-constrained measures of environmental efficiency: a material balance approach," MPRA Paper 72490, University Library of Munich, Germany.
    19. Zelenyuk, Valentin, 2020. "Aggregation of inputs and outputs prior to Data Envelopment Analysis under big data," European Journal of Operational Research, Elsevier, vol. 282(1), pages 172-187.
    20. Aldanondo, Ana M. & Casasnovas, Valero L., 2016. "A note on the impact of multiple input aggregators in technical efficiency estimation," MPRA Paper 75290, 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. Heinz Ahn & Peter Bogetoft & Ana Lopes, 2019. "Measuring potential sub-unit efficiency to counter the aggregation bias in benchmarking," Journal of Business Economics, Springer, vol. 89(1), pages 53-77, February.
    2. Valentin Zelenyuk, 2022. "Aggregation of Efficiency and Productivity: From Firm to Sector and Higher Levels," Springer Books, in: Subhash C. Ray & Robert G. Chambers & Subal C. Kumbhakar (ed.), Handbook of Production Economics, chapter 25, pages 1039-1079, Springer.
    3. Monchuk, Daniel C. & Chen, Zhuo & Bonaparte, Yosef, 2010. "Explaining production inefficiency in China's agriculture using data envelopment analysis and semi-parametric bootstrapping," China Economic Review, Elsevier, vol. 21(2), pages 346-354, June.
    4. Aldanondo, Ana M. & Casasnovas, Valero L., 2016. "A note on the impact of multiple input aggregators in technical efficiency estimation," MPRA Paper 75290, University Library of Munich, Germany.
    5. Ali Homayoni & Reza Fallahnejad & Farhad Hosseinzadeh Lotfi, 2022. "Cross Malmquist Productivity Index in Data Envelopment Analysis," 4OR, Springer, vol. 20(4), pages 567-602, December.
    6. A. M. Aldanondo & V. L. Casasnovas, 2015. "Input aggregation bias in technical efficiency with multiple criteria analysis," Applied Economics Letters, Taylor & Francis Journals, vol. 22(6), pages 430-435, April.
    7. Zelenyuk, Valentin, 2020. "Aggregation of inputs and outputs prior to Data Envelopment Analysis under big data," European Journal of Operational Research, Elsevier, vol. 282(1), pages 172-187.
    8. Darold T. Barnum & John M. Gleason, 2007. "Technical efficiency bias in data envelopment analysis caused by intra-output aggregation," Applied Economics Letters, Taylor & Francis Journals, vol. 14(9), pages 623-626.
    9. Aldanondo, Ana M. & Casasnovas, Valero L., 2015. "More is better than one: the impact of different numbers of input aggregators in technical efficiency estimation," MPRA Paper 64120, University Library of Munich, Germany.
    10. Valentin Zelenyuk, 2019. "Data Envelopment Analysis and Business Analytics: The Big Data Challenges and Some Solutions," CEPA Working Papers Series WP072019, School of Economics, University of Queensland, Australia.
    11. Darold Barnum & John Gleason, 2005. "Technical efficiency bias caused by intra-input aggregation in data envelopment analysis," Applied Economics Letters, Taylor & Francis Journals, vol. 12(13), pages 785-788.
    12. Darold Barnum & John Gleason, 2006. "Measuring efficiency in allocating inputs among outputs with DEA," Applied Economics Letters, Taylor & Francis Journals, vol. 13(6), pages 333-336.
    13. Silva Portela, Maria Conceição A., 2014. "Value and quantity data in economic and technical efficiency measurement," Economics Letters, Elsevier, vol. 124(1), pages 108-112.
    14. Kim-Huong Nguyen & Tim Coelli, 2009. "Quantifying the effects of modelling choices on hospital efficiency measures: A meta-regression analysis," CEPA Working Papers Series WP072009, School of Economics, University of Queensland, Australia.
    15. Byma, Justin P. & Tauer, Loren W., 2007. "Farm Inefficiency Resulting from the Missing Management Input," Working Papers 127008, Cornell University, Department of Applied Economics and Management.
    16. Wenjun Liu & Tomokazu Nomura & Shoji Nishijima, 2011. "Gender Discrimination and Firm Profit Efficiency:Evidence from Brazil," Discussion Papers 1019, Graduate School of Economics, Kobe University.
    17. Antonio Peyrache, 2014. "Cost Constrained Industry Inefficiency," CEPA Working Papers Series WP042014, School of Economics, University of Queensland, Australia.
    18. Christine E Whitt & Loren W Tauer & Heather Huson, 2019. "Bull efficiency using dairy genetic traits," PLOS ONE, Public Library of Science, vol. 14(11), pages 1-14, November.
    19. Ma, Shuzhong & Feng, Han, 2013. "Will the decline of efficiency in China's agriculture come to an end? An analysis based on opening and convergence," China Economic Review, Elsevier, vol. 27(C), pages 179-190.
    20. Ma, Hengyun & Rae, Allan N. & Huang, Jikun, 2004. "Livestock Productivity In China: Data Revision And Total Factor Productivity Decomposition," China Agriculture Project Working Papers 23691, Massey University, Centre for Applied Economics and Policy Studies.

    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:apeclt:v:11:y:2004:i:10:p:657-660. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RAEL20 .

    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.