IDEAS home Printed from https://ideas.repec.org/a/mup/actaun/actaun_2020068040765.html
   My bibliography  Save this article

Efficiency Comparison and Efficiency Development of the Metallurgical Industry in the EU: Parametric and Non-parametric Approaches

Author

Listed:
  • Michaela Staňková

    (Department of Statistics and Operation Analysis, Faculty of Business and Economics, Mendel University in Brno, Zemědělská 1, 613 00 Brno, Czech Republic)

Abstract

This article deals with the development of technical (production) efficiency in the metallurgical industry in EU countries with an emphasis on the situation in the Czech Republic. The efficiency of individual countries was estimated for the period from 1995 to 2015. The parametric stochastic frontier analysis method with different settings was chosen to estimate efficiency and the results were verified using a competitive non-parametric data envelopment analysis method. It was found that during the period under review, there was an average increase in efficiency in the metallurgical industry. The largest increase in efficiency (confirmed by all types of models) was observed in the Czech Republic. A visible positive efficiency shift was also recorded in Spain and Greece. Surprisingly, there has been a decline in efficiency in Sweden and Italy.

Suggested Citation

  • Michaela Staňková, 2020. "Efficiency Comparison and Efficiency Development of the Metallurgical Industry in the EU: Parametric and Non-parametric Approaches," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 68(4), pages 765-774.
  • Handle: RePEc:mup:actaun:actaun_2020068040765
    DOI: 10.11118/actaun202068040765
    as

    Download full text from publisher

    File URL: http://acta.mendelu.cz/doi/10.11118/actaun202068040765.html
    Download Restriction: free of charge

    File URL: http://acta.mendelu.cz/doi/10.11118/actaun202068040765.pdf
    Download Restriction: free of charge

    File URL: https://libkey.io/10.11118/actaun202068040765?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. Hosseinzadeh, Ahmad & Smyth, Russell & Valadkhani, Abbas & Le, Viet, 2016. "Analyzing the efficiency performance of major Australian mining companies using bootstrap data envelopment analysis," Economic Modelling, Elsevier, vol. 57(C), pages 26-35.
    2. Li, Ying & Chiu, Yung-ho & Lin, Tai-Yu, 2019. "Coal production efficiency and land destruction in China's coal mining industry," Resources Policy, Elsevier, vol. 63(C), pages 1-1.
    3. Federico Belotti & Silvio Daidone & Giuseppe Ilardi & Vincenzo Atella, 2013. "Stochastic frontier analysis using Stata," Stata Journal, StataCorp LP, vol. 13(4), pages 718-758, December.
    4. 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.
    5. Wu, Ya & Su, JingRong & Li, Ke & Sun, Chuanwang, 2019. "Comparative study on power efficiency of China's provincial steel industry and its influencing factors," Energy, Elsevier, vol. 175(C), pages 1009-1020.
    6. Kumbhakar,Subal C. & Wang,Hung-Jen & Horncastle,Alan P., 2015. "A Practitioner's Guide to Stochastic Frontier Analysis Using Stata," Cambridge Books, Cambridge University Press, number 9781107029514.
    7. Silva, Thiago Christiano & Tabak, Benjamin Miranda & Cajueiro, Daniel Oliveira & Dias, Marina Villas Boas, 2017. "A comparison of DEA and SFA using micro- and macro-level perspectives: Efficiency of Chinese local banks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 216-223.
    8. Charoenrat, Teerawat & Harvie, Charles, 2014. "The efficiency of SMEs in Thai manufacturing: A stochastic frontier analysis," Economic Modelling, Elsevier, vol. 43(C), pages 372-393.
    9. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    10. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2007. "Data Envelopment Analysis," Springer Books, Springer, edition 0, number 978-0-387-45283-8, November.
    11. 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.
    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. Veronika Varvařovská & Michaela Staňková, 2021. "Does the Involvement of "Green Energy" Increase the Productivity of Companies in the Production of the Electricity Sector?," European Journal of Business Science and Technology, Mendel University in Brno, Faculty of Business and Economics, vol. 7(2), pages 152-164.

    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. Keller, Michael, 2020. "Wasted windfalls: Inefficiencies in health care spending in oil rich countries," Resources Policy, Elsevier, vol. 66(C).
    2. Wanglin Ma & Kathryn Bicknell & Alan Renwick, 2019. "Feed use intensification and technical efficiency of dairy farms in New Zealand," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 63(1), pages 20-38, January.
    3. Gralka, Sabine, 2018. "Stochastic frontier analysis in higher education: A systematic review," CEPIE Working Papers 05/18, Technische Universität Dresden, Center of Public and International Economics (CEPIE).
    4. 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.
    5. Pal, Debdatta & Mitra, Subrata K. & Chatterjee, Somdeep, 2022. "Does “investment climate” affect GDP? Panel data evidence using reduced-form and stochastic frontier analysis," Journal of Business Research, Elsevier, vol. 138(C), pages 301-310.
    6. Albalate, Daniel & Rosell, Jordi, 2019. "On the efficiency of toll motorway companies in Spain," Research in Transportation Economics, Elsevier, vol. 76(C).
    7. Luis Antonio Galiano Bastarrica & Eva M. Buitrago Esquinas & María Ángeles Caraballo Pou & Rocío Yñiguez Ovando, 2023. "Environmental adjustment of the EU27 GDP: an econometric quantitative model," Environment Systems and Decisions, Springer, vol. 43(1), pages 115-128, March.
    8. Lien, Gudbrand & Kumbhakar, Subal C. & Alem, Habtamu, 2018. "Endogeneity, heterogeneity, and determinants of inefficiency in Norwegian crop-producing farms," International Journal of Production Economics, Elsevier, vol. 201(C), pages 53-61.
    9. Zarkovic, Maja, 2020. "Cap-and-trade and produce at least cost? Investigating firm behaviour in the EU ETS," Working papers 2020/12, Faculty of Business and Economics - University of Basel.
    10. Ather Hassan Dar & Somesh Kumar Mathur & Sila Mishra, 2021. "The Efficiency of Indian Banks: A DEA, Malmquist and SFA Analysis with Bad Output," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(4), pages 653-701, December.
    11. Christian Stetter & Johannes Sauer, 2022. "Greenhouse Gas Emissions and Eco-Performance at Farm Level: A Parametric Approach," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 81(3), pages 617-647, March.
    12. Victor Moutinho & Mara Madaleno, 2021. "Assessing Eco-Efficiency in Asian and African Countries Using Stochastic Frontier Analysis," Energies, MDPI, vol. 14(4), pages 1-17, February.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. Massimiliano Piacenza & Gilberto Turati, 2014. "Does Fiscal Discipline Towards Subnational Governments Affect Citizens' Well‐Being? Evidence On Health," Health Economics, John Wiley & Sons, Ltd., vol. 23(2), pages 199-224, February.
    18. Farsi, Mehdi & Filippini, Massimo, 2009. "An analysis of cost efficiency in Swiss multi-utilities," Energy Economics, Elsevier, vol. 31(2), pages 306-315, March.
    19. Yuichi Watanabe & Haruko Noguchi & Yoshinori Nakata, 2020. "How efficient are surgical treatments in Japan? The case of a high-volume Japanese hospital," Health Care Management Science, Springer, vol. 23(3), pages 401-413, September.
    20. Federico Belotti & Giuseppe Ilardi & Andrea Piano Mortari, 2019. "Estimation of Stochastic Frontier Panel Data Models with Spatial Inefficiency," CEIS Research Paper 459, Tor Vergata University, CEIS, revised 30 May 2019.

    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:mup:actaun:actaun_2020068040765. 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: Ivo Andrle (email available below). General contact details of provider: https://mendelu.cz/en/ .

    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.