IDEAS home Printed from https://ideas.repec.org/a/ksa/szemle/2244.html
   My bibliography  Save this article

A magyar feldolgozóipar technikai hatékonysági vizsgálata
[Analysing the technical efficiency of the Hungarian manufacturing industry]

Author

Listed:
  • Baráth, Lajos
  • Bareith, Tibor
  • Molnár, Dániel

Abstract

Tanulmányunk célja a magyar feldolgozóipar technikai hatékonyságának vizsgálata a 2013-2022 közötti időszakban, olyan sztochasztikushatár-modellekkel (Stochastic Frontier Analysis, SFA), amelyek lehetővé teszik a vállalatok közötti nem megfigyelt heterogenitás kezelését. Emellett az output növekedését felbontottuk az input- és a termelékenységnövekedés hatására, majd a termelékenységváltozást tovább bontottuk a technológiai változás és a technikai hatékonyság változásának hatására. Az eredmények azt mutatják, hogy a vizsgált időszakot elsősorban inputvezérelt növekedés jellemezte, és a technológiai fejlődés (évi 1,4 százalék) szintén kedvezően hatott a termelékenységre. A technikai hatékonyság javulása ugyanakkor mérsékelt, és az egyes méretkategóriák között szignifikáns különbség mutatkozott, ami arra utal, hogy jelentős tartalékok rejlenek a szektor működésének hatékonyabbá tételében, különösen a kis- és középvállalatok esetében. Mindezek mellett modellünk szerint a magasabb exportorientáltság pozitívan befolyásolja a vállalati hatékonyságot. A technológiai fejlődés és a technikai hatékonyság eltérő politikai eszközökkel támogathatók: a technológiai fejlesztést főként innovációs és K + F-ösztönzéssel lehet elősegíteni, míg a technikai hatékonyság növelésében a képzési és szaktanácsadási rendszerek fejlesztése játszhat kiemelt szerepet. Eredményeink így fontos kiindulópontot jelentenek a feldolgozóipar versenyképességét és termelékenységét előmozdító intézkedések megtervezéséhez.

Suggested Citation

  • Baráth, Lajos & Bareith, Tibor & Molnár, Dániel, 2025. "A magyar feldolgozóipar technikai hatékonysági vizsgálata [Analysing the technical efficiency of the Hungarian manufacturing industry]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(4), pages 369-387.
  • Handle: RePEc:ksa:szemle:2244
    DOI: 10.18414/KSZ.2025.4.369
    as

    Download full text from publisher

    File URL: http://www.kszemle.hu/tartalom/letoltes.php?id=2244
    Download Restriction: Registration and subscription. 3-month embargo period to non-subscribers.

    File URL: https://libkey.io/10.18414/KSZ.2025.4.369?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. Robert J. Gordon, 2016. "The Rise and Fall of American Growth: The U.S. Standard of Living since the Civil War," Economics Books, Princeton University Press, edition 1, number 10544.
    2. Chad Syverson, 2011. "What Determines Productivity?," Journal of Economic Literature, American Economic Association, vol. 49(2), pages 326-365, June.
    3. Xi Wan & Shehla Anjum Ajaz Kazmi & Chun Yee Wong, 2022. "Manufacturing, Exports, and Sustainable Growth: Evidence from Developing Countries," Sustainability, MDPI, vol. 14(3), pages 1-22, January.
    4. Fried, Harold O. & Lovell, C. A. Knox & Schmidt, Shelton S. (ed.), 2008. "The Measurement of Productive Efficiency and Productivity Growth," OUP Catalogue, Oxford University Press, number 9780195183528, Decembrie.
    5. John G. Fernald, 2015. "Productivity and Potential Output before, during, and after the Great Recession," NBER Macroeconomics Annual, University of Chicago Press, vol. 29(1), pages 1-51.
    6. Mehdi Farsi & Massimo Filippini & William Greene, 2005. "Efficiency Measurement in Network Industries: Application to the Swiss Railway Companies," Journal of Regulatory Economics, Springer, vol. 28(1), pages 69-90, July.
    7. 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.
    8. Seog-Chan Oh & Alfred J. Hildreth, 2014. "Estimating the Technical Improvement of Energy Efficiency in the Automotive Industry—Stochastic and Deterministic Frontier Benchmarking Approaches," Energies, MDPI, vol. 7(9), pages 1-27, September.
    9. Schmidt, Peter & Sickles, Robin C, 1984. "Production Frontiers and Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 367-374, October.
    10. Greene, William, 2005. "Reconsidering heterogeneity in panel data estimators of the stochastic frontier model," Journal of Econometrics, Elsevier, vol. 126(2), pages 269-303, June.
    11. Willam Greene, 2005. "Fixed and Random Effects in Stochastic Frontier Models," Journal of Productivity Analysis, Springer, vol. 23(1), pages 7-32, January.
    12. Awudu Abdulai & Hendrik Tietje, 2007. "Estimating technical efficiency under unobserved heterogeneity with stochastic frontier models: application to northern German dairy farms," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 34(3), pages 393-416, September.
    13. Xiaobing Wang & Heinrich Hockmann & Junfei Bai, 2012. "Technical Efficiency and Producers’ Individual Technology: Accounting for Within and Between Regional Farm Heterogeneity," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 60(4), pages 561-576, December.
    14. 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.
    15. Pitt, Mark M. & Lee, Lung-Fei, 1981. "The measurement and sources of technical inefficiency in the Indonesian weaving industry," Journal of Development Economics, Elsevier, vol. 9(1), pages 43-64, August.
    16. Mehdi Farsi & Massimo Filippini & Michael Kuenzle, 2005. "Unobserved heterogeneity in stochastic cost frontier models: an application to Swiss nursing homes," Applied Economics, Taylor & Francis Journals, vol. 37(18), pages 2127-2141.
    17. Norayati Hashim & Mohd Fahmy-Abdullah, 2024. "Technical efficiency in the Malaysian electric and electronic manufacturing industry: A stochastic frontier analysis approach," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 14(2), pages 88-104.
    18. 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. Farsi, Mehdi & Filippini, Massimo, 2009. "An analysis of cost efficiency in Swiss multi-utilities," Energy Economics, Elsevier, vol. 31(2), pages 306-315, March.
    2. Massimo Filippini & William Greene, 2016. "Persistent and transient productive inefficiency: a maximum simulated likelihood approach," Journal of Productivity Analysis, Springer, vol. 45(2), pages 187-196, April.
    3. Lajos Barath & Heinrich Hockmann, 2016. "Technological differences, theoretically consistent frontiers and technical efficiency: a Random parameter application in the Hungarian crop producing farms," IEHAS Discussion Papers 1636, Institute of Economics, Centre for Economic and Regional Studies.
    4. Mehdi Farsi & Aurelio Fetz & Massimo Filippini, 2007. "Benchmarking and Regulation in the Electricity Distribution Sector," CEPE Working paper series 07-54, CEPE Center for Energy Policy and Economics, ETH Zurich.
    5. Mehdi Farsi & Massimo Filippini & William Greene, 2006. "Application Of Panel Data Models In Benchmarking Analysis Of The Electricity Distribution Sector," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 77(3), pages 271-290, September.
    6. Hailu, Kidanemariam Berhe & Tanaka, Makoto, 2015. "A “true” random effects stochastic frontier analysis for technical efficiency and heterogeneity: Evidence from manufacturing firms in Ethiopia," Economic Modelling, Elsevier, vol. 50(C), pages 179-192.
    7. Filippini, Massimo & Hunt, Lester C., 2012. "US residential energy demand and energy efficiency: A stochastic demand frontier approach," Energy Economics, Elsevier, vol. 34(5), pages 1484-1491.
    8. Sickles, Robin C. & Hao, Jiaqi & Shang, Chenjun, 2015. "Panel Data and Productivity Measurement," Working Papers 15-018, Rice University, Department of Economics.
    9. Filippini, Massimo & Hunt, Lester C., 2015. "Measurement of energy efficiency based on economic foundations," Energy Economics, Elsevier, vol. 52(S1), pages 5-16.
    10. Liu, Fengqin & Sim, Jae-yeon & Sun, Huaping & Edziah, Bless Kofi & Adom, Philip Kofi & Song, Shunfeng, 2023. "Assessing the role of economic globalization on energy efficiency: Evidence from a global perspective," China Economic Review, Elsevier, vol. 77(C).
    11. Lundgren, Tommy & Marklund, Per-Olov & Zhang, Shanshan, 2016. "Industrial energy demand and energy efficiency – Evidence from Sweden," Resource and Energy Economics, Elsevier, vol. 43(C), pages 130-152.
    12. Cazals Catherine & Dudley Paul & Florens Jean-Pierre & Jones Michael, 2011. "The Effect of Unobserved Heterogeneity in Stochastic Frontier Estimation: Comparison of Cross Section and Panel with Simulated Data for the Postal Sector," Review of Network Economics, De Gruyter, vol. 10(3), pages 1-22, September.
    13. Massimo Filippini & Lester C. Hunt, 2013. "'Underlying Energy Efficiency' in the US," CER-ETH Economics working paper series 13/181, CER-ETH - Center of Economic Research (CER-ETH) at ETH Zurich.
    14. Cullmann, Astrid & Farsi, Mehdi & Filippini Massimo, 2009. "Unobserved Heterogeneity and International Benchmarking in Public Trasport," Quaderni della facoltà di Scienze economiche dell'Università di Lugano 0904, USI Università della Svizzera italiana.
    15. Keller, Michael, 2020. "Wasted windfalls: Inefficiencies in health care spending in oil rich countries," Resources Policy, Elsevier, vol. 66(C).
    16. 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.
    17. Lajos Baráth & Imre Fertő & Heinrich Hockmann, 2020. "Technological Differences, Theoretical Consistency, and Technical Efficiency: The Case of Hungarian Crop-Producing Farms," Sustainability, MDPI, vol. 12(3), pages 1-18, February.
    18. Ayadi, Ahmed & Hammami, Sami, 2015. "An analysis of the performance of public bus transport in Tunisian cities," Transportation Research Part A: Policy and Practice, Elsevier, vol. 75(C), pages 51-60.
    19. Martini, Gianmaria & Scotti, Davide & Viola, Domenico & Vittadini, Giorgio, 2020. "Persistent and temporary inefficiency in airport cost function: An application to Italy," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 999-1019.
    20. Meryem Duygun & Jiaqi Hao & Anders Isaksson & Robin C. Sickles, 2017. "World Productivity Growth: A Model Averaging Approach," Pacific Economic Review, Wiley Blackwell, vol. 22(4), pages 587-619, October.

    More about this item

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • L60 - Industrial Organization - - Industry Studies: Manufacturing - - - General

    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:ksa:szemle:2244. 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: Odon Sok The email address of this maintainer does not seem to be valid anymore. Please ask Odon Sok to update the entry or send us the correct address (email available below). General contact details of provider: http://www.kszemle.hu .

    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.