IDEAS home Printed from https://ideas.repec.org/a/ris/apltrx/0036.html
   My bibliography  Save this article

Estimation of the Economic Efficiency of a Shift to the Achievable Production Potential

Author

Listed:
  • Aivazian, Sergei

    (CEMI RAS, Moscow, Russia)

  • Afanasiev, Mikhail

    (CEMI RAS, Moscow, Russia)

Abstract

Developing a concept of stochastic frontier we estimate the expected increase in the production volume achieved as a result of a shift to the achievable production potential. The expected economic effect of an activity of raising production efficiency is forecast. The distribution of the economic effect allowing analyzing risks related to an activity realization is given

Suggested Citation

  • Aivazian, Sergei & Afanasiev, Mikhail, 2009. "Estimation of the Economic Efficiency of a Shift to the Achievable Production Potential," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 15(3), pages 43-55.
  • Handle: RePEc:ris:apltrx:0036
    as

    Download full text from publisher

    File URL: http://pe.cemi.rssi.ru/pe_2009_3_43-55.pdf
    File Function: Full text
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Rafik Baccouche & Mokhtar Kouki, 2003. "Stochastic Production Frontier and Technical Inefficiency: A Sensitivity Analysis," Econometric Reviews, Taylor & Francis Journals, vol. 22(1), pages 79-91, February.
    2. Afanasiev, Mikhail, 2006. "A Model of the Production Potential with Managed Factors of Inefficiency," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 4(4), pages 74-89.
    3. Battese, George E. & Coelli, Tim J., 1988. "Prediction of firm-level technical efficiencies with a generalized frontier production function and panel data," Journal of Econometrics, Elsevier, vol. 38(3), pages 387-399, July.
    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. Aivazian, Sergei & Afanasiev, Mikhail, 2007. "Estimation of Measures Directed at Management of Factors of Production Inefficiency," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 8(4), pages 27-41.
    6. 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)

    Citations

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


    Cited by:

    1. Sergey Aivazian & Mikhail Afanasyev, 2012. "The Models For Company'S Human Capital Estimation, Based On The Stochastic Frontier Approach," Montenegrin Journal of Economics, Economic Laboratory for Transition Research (ELIT), vol. 8(1), pages 7-26.
    2. Aivazian , Sergei & Afanasiev , Mikhail & Afanasyev, Alexander, 2009. "Economic Efficiency Estimation of Banks’ Activities Directed at Loans Products Advertisement," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 16(4), pages 46-59.
    3. Айвазян С.А. & Афанасьев М.Ю., 2013. "К Оценке Стоимости Замещения Человеческого Капитала Сотрудника Компании," Журнал Экономика и математические методы (ЭММ), Центральный Экономико-Математический Институт (ЦЭМИ), vol. 49(4), pages 62-70, октябрь.
    4. Mogilat , Anastasia & Ipatova, Irina, 2016. "Technical efficiency as a factor of Russian industrial companies’ risks of financial distress," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 42, pages 05-29.
    5. Айвазян С.А. & Афанасьев М.Ю. & Руденко В.А., 2014. "Оценка Эффективности Регионов Рф На Основе Модели Производственного Потенциала С Характеристиками Готовности К Инновациям," Журнал Экономика и математические методы (ЭММ), Центральный Экономико-Математический Институт (ЦЭМИ), vol. 50(4), pages 34-70, октябрь.
    6. Айвазян С.А. & Афанасьев М.Ю., 2012. "Модели Оценки Человеческого Капитала Компании, Основанные На Концепции Стохастической Границы," Журнал Экономика и математические методы (ЭММ), Центральный Экономико-Математический Институт (ЦЭМИ), vol. 48(3), июль.
    7. Ipatova, Irina & Peresetsky, Аnatoly, 2013. "Technical efficiency of Russian plastic and rubber production firms," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 32(4), pages 71-92.

    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. Aivazian , Sergei & Afanasiev , Mikhail & Afanasyev, Alexander, 2009. "Economic Efficiency Estimation of Banks’ Activities Directed at Loans Products Advertisement," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 16(4), pages 46-59.
    2. Aivazian, Sergei & Afanasiev, Mikhail, 2007. "Estimation of Measures Directed at Management of Factors of Production Inefficiency," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 8(4), pages 27-41.
    3. Mogilat , Anastasia & Ipatova, Irina, 2016. "Technical efficiency as a factor of Russian industrial companies’ risks of financial distress," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 42, pages 05-29.
    4. Quang Nguyen & Sean Pascoe & Louisa Coglan & Son Nghiem, 2021. "The sensitivity of efficiency scores to input and other choices in stochastic frontier analysis: an empirical investigation," Journal of Productivity Analysis, Springer, vol. 55(1), pages 31-40, February.
    5. Christopher F. Parmeter & Alan T. K. Wan & Xinyu Zhang, 2019. "Model averaging estimators for the stochastic frontier model," Journal of Productivity Analysis, Springer, vol. 51(2), pages 91-103, June.
    6. Rosen Azad Chowdhury & Dilshad Jahan & Tapas Mishra & Mamata Parhi, 2023. "A Quality Dimension? A Re-appraisal of Financial Development and Economic Growth Nexus in a Quality-Quantity Setting," Working Papers 2023-02, Swansea University, School of Management.
    7. B. E. Bravo‐Ureta & L. Rieger, 1990. "Alternative Production Frontier Methodologies And Dairy Farm Efficiency," Journal of Agricultural Economics, Wiley Blackwell, vol. 41(2), pages 215-226, May.
    8. Tai-Hsin Huang & Yi-Huang Chiu & Chih-Ying Mao, 2021. "Imposing Regularity Conditions to Measure Banks’ Productivity Changes in Taiwan Using a Stochastic Approach," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 28(2), pages 273-303, June.
    9. Alfonso Flores-Lagunes & William C. Horrace & Kurt E. Schnier, 2007. "Identifying technically efficient fishing vessels: a non-empty, minimal subset approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(4), pages 729-745.
    10. Sabrina Auci & Laura Castellucci & Manuela Coromaldi, 2021. "How does public spending affect technical efficiency? Some evidence from 15 European countries," Bulletin of Economic Research, Wiley Blackwell, vol. 73(1), pages 108-130, January.
    11. I. Fraser & W. Horrace, 2003. "Technical Efficiency of Australian Wool Production: Point and Confidence Interval Estimates," Journal of Productivity Analysis, Springer, vol. 20(2), pages 169-190, September.
    12. Forgione, Antonio Fabio & Migliardo, Carlo, 2023. "Mafia risk perception: Evaluating the effect of organized crime on firm technical efficiency and investment proclivity," Socio-Economic Planning Sciences, Elsevier, vol. 88(C).
    13. Pantzios, Christos J. & Rozakis, Stelios & Tzouvelekas, Vangelis, 2006. "Evading Farm Support Reduction via Efficient Input Use: The Case of Greek Cotton Growers," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 38(3), pages 555-574, December.
    14. Muhamad Zahid Muhamad & Mad Nasir Shamsudin & Nitty Hirawaty Kamarulzaman & Nolila Mohd Nawi & Jamaliah Laham, 2022. "Investigating Yield Variability and Technical Efficiency of Smallholders Pineapple Production in Johor," Sustainability, MDPI, vol. 14(22), pages 1-18, November.
    15. Mark Andor & Frederik Hesse, "undated". "The StoNED age: The Departure Into a New Era of Efficiency Analysis? An MC study Comparing StoNED and the "Oldies" (SFA and DEA)," Working Papers 201285, Institute of Spatial and Housing Economics, Munster Universitary.
    16. Nazir Muhammad Abdullahi & Xuexi Huo & Qiangqiang Zhang & Aminah Bolanle Azeez, 2021. "Determinants and Potential of Agri-Food Trade Using the Stochastic Frontier Gravity Model: Empirical Evidence From Nigeria," SAGE Open, , vol. 11(4), pages 21582440211, December.
    17. MAIMOUNA DIAKITE & Jean-François BRUN, 2016. "Tax Potential and Tax Effort: An Empirical Estimation for Non-Resource Tax Revenue and VAT’s Revenue," EcoMod2016 9537, EcoMod.
    18. Martin, Sheila Ann, 1992. "The effectiveness of state technology incentives: evidence from the machine tool industry," ISU General Staff Papers 1992010108000011381, Iowa State University, Department of Economics.
    19. Farsi, Mehdi & Filippini, Massimo, 2009. "An analysis of cost efficiency in Swiss multi-utilities," Energy Economics, Elsevier, vol. 31(2), pages 306-315, March.
    20. Glass, Anthony J. & Kenjegalieva, Karligash & Sickles, Robin C. & Weyman-Jones, Thomas, 2018. "The Spatial Efficiency Multiplier and Common Correlated Effects in a Spatial Autoregressive Stochastic Frontier Model," Working Papers 18-003, Rice University, Department of Economics.

    More about this item

    Keywords

    Production potential; stochastic frontier; production function; technical efficiency; achievable production potential;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

    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:ris:apltrx:0036. 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: Anatoly Peresetsky (email available below). General contact details of provider: http://appliedeconometrics.cemi.rssi.ru/ .

    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.