IDEAS home Printed from https://ideas.repec.org/a/rnp/ecopol/ep1922.html
   My bibliography  Save this article

Analysis of Impact of New Technologies in Metallurgy on the Industry Production Function and Total Factor Productivity
[Совокупная Факторная Производительность В Черной Металлургии: Влияние Новых Технологий]

Author

Listed:
  • Malein, Viktor (Малеин, Виктор)

    (Russian Presidential Academy of National Economy and Public Administration)

  • Ponomarev, Yuriy (Пономарев, Юрий)

    (Russian Presidential Academy of National Economy and Public Administration; Gaidar Institute for Economic Policy)

Abstract

Identification of positive conditions for structural transformation of industries in the Russian economy and also formation of a scientific base for development of practical recommendations for industrial policy are extremely important for the fulfillment of national goals set forth in the Presidential Decree No. 204 dated May 7, 2018. From the early 2000s up till now, development of the Russian metal industry has been characterized by gradual abandonment of the traditional method of steelmaking in open-hearth furnaces as well as transition to a more progressive electric melting technology. The article assesses the impact of this technology change on total factor productivity (TFP) of metallurgical enterprises and on the functional form of the production function in the industry for the period 2008–2017, as well as the factors of transition to the new technology for metallurgical companies. The results show that the transition to the new technology was accompanied by a 24–28% increase in TFP as well as changes in the parameters of the production function, in particular, a decrease in labor and material intensity of production. An analysis of the factors influencing the likelihood of transition to the new technology has confirmed our hypotheses: the process of assets consolidation in the metallurgical industry under the control of several holdings in the 2000s was accompanied by technological re-equipment of production and construction of new facilities. Enterprises that are part of a single financial and industrial group with higher productivity and access to the world market are characterized by a higher probability of transition to the new technology. In addition, estimates of the likelihood of transition to the new technology are higher for enterprises with higher levels of productivity.

Suggested Citation

  • Malein, Viktor (Малеин, Виктор) & Ponomarev, Yuriy (Пономарев, Юрий), 2019. "Analysis of Impact of New Technologies in Metallurgy on the Industry Production Function and Total Factor Productivity [Совокупная Факторная Производительность В Черной Металлургии: Влияние Новых Т," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 3, June.
    • Handle: RePEc:rnp:ecopol:ep1922
    as

    Download full text from publisher

    File URL: https://repec.ranepa.ru/rnp/ecopol/ep1922.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Allan Collard-Wexler & Jan De Loecker, 2015. "Reallocation and Technology: Evidence from the US Steel Industry," American Economic Review, American Economic Association, vol. 105(1), pages 131-171, January.
    2. Paul Schrimpf & Michio Suzuki & Hiroyuki Kasahara, 2015. "Identification and Estimation of Production Function with Unobserved Heterogeneity," 2015 Meeting Papers 924, Society for Economic Dynamics.
    3. Olley, G Steven & Pakes, Ariel, 1996. "The Dynamics of Productivity in the Telecommunications Equipment Industry," Econometrica, Econometric Society, vol. 64(6), pages 1263-1297, November.
    4. Tsuyoshi Nakamura & Hiroshi Ohashi, 2008. "Effects Of Technology Adoption On Productivity And Industry Growth: A Study Of Steel Refining Furnaces," Journal of Industrial Economics, Wiley Blackwell, vol. 56(3), pages 470-499, September.
    5. Vincenzo Mollisi & Gabriele Rovigatti, 2017. "Theory and Practice of TFP Estimation: the Control Function Approach Using Stata," CEIS Research Paper 399, Tor Vergata University, CEIS, revised 14 Feb 2017.
    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. Ryuki Kobayashi, 2023. "The effects of new technology on productivity: technological improvement and reallocation efficiency in the Japanese steelmaking industry," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 12(1), pages 1-24, December.
    2. Amitabh Chandra & Amy Finkelstein & Adam Sacarny & Chad Syverson, 2016. "Health Care Exceptionalism? Performance and Allocation in the US Health Care Sector," American Economic Review, American Economic Association, vol. 106(8), pages 2110-2144, August.
    3. Catherine Fuss & Angelos Theodorakopoulos, 2018. "Compositional Changes in Aggregate Productivity in an Era of Globalisation and Financial Crisis," Working Papers of VIVES - Research Centre for Regional Economics 627696, KU Leuven, Faculty of Economics and Business (FEB), VIVES - Research Centre for Regional Economics.
    4. David Van Dijcke, 2022. "On the Non-Identification of Revenue Production Functions," Papers 2212.04620, arXiv.org, revised May 2024.
    5. Mauro Caselli & Arpita Chatterjee & Shengyu Li, 2023. "Productivity and Quality of Multi-product Firms," Discussion Papers 2023-10, School of Economics, The University of New South Wales.
    6. Bos, J.W.B. & van Santen, P.C. & Schilp, P., 2013. "The importance of reallocation for productivity growth: Evidence from European and US banking," Research Memorandum 056, Maastricht University, Graduate School of Business and Economics (GSBE).
    7. Lucia Foster & Cheryl Grim & John Haltiwanger, 2016. "Reallocation in the Great Recession: Cleansing or Not?," Journal of Labor Economics, University of Chicago Press, vol. 34(S1), pages 293-331.
    8. Geoffrey Barrows & Helene Ollivier, 2016. "Emission intensity and firm dynamics: reallocation, product mix, and technology in India," GRI Working Papers 245, Grantham Research Institute on Climate Change and the Environment.
    9. Nhan Buu Phany & Shino Takayamaz, 2020. "Analyses of Corruption and Productivity with Empirical Study in Vietnam," Discussion Papers Series 628, School of Economics, University of Queensland, Australia.
    10. Caroline Stiel, 2017. "Modern Public Enterprises: Organisational Innovation and Productivity," Discussion Papers of DIW Berlin 1713, DIW Berlin, German Institute for Economic Research.
    11. Chun‐Yu Ho & Yue Sheng, 2022. "Productivity advantage of large cities for creative industries," Papers in Regional Science, Wiley Blackwell, vol. 101(6), pages 1289-1306, December.
    12. Tetsushi Murao, 2017. "Aggregate Productivity Growth Decomposition: an Overview," Public Policy Review, Policy Research Institute, Ministry of Finance Japan, vol. 13(3), pages 269-286, November.
    13. Caselli, Mauro & Schiavo, Stefano & Nesta, Lionel, 2018. "Markups and markdowns," Economics Letters, Elsevier, vol. 173(C), pages 104-107.
    14. Alpysbayeva, Dinara & Vanormelingen, Stijn, 2022. "Labor market rigidities and misallocation: Evidence from a natural experiment," Labour Economics, Elsevier, vol. 78(C).
    15. Santiago Caicedo & Miguel Espinosa & Arthur Seibold, 2022. "Unwilling to Train?—Firm Responses to the Colombian Apprenticeship Regulation," Econometrica, Econometric Society, vol. 90(2), pages 507-550, March.
    16. Matthew Backus, 2020. "Why Is Productivity Correlated With Competition?," Econometrica, Econometric Society, vol. 88(6), pages 2415-2444, November.
    17. Kritikos, Alexander S. & Schiersch, Alexander & Stiel, Caroline, 2021. "The Productivity Puzzle in Business Services," IZA Discussion Papers 14610, Institute of Labor Economics (IZA).
    18. Michele Fioretti & Junnan He & Jorge Tamayo, 2024. "Prices and Concentration: A U-Shape? Theory and Evidence from Renewables," Working Papers hal-04631762, HAL.
    19. Xie, Mengmeng & Ding, Lin & Xia, Yan & Guo, Jianfeng & Pan, Jiaofeng & Wang, Huijuan, 2021. "Does artificial intelligence affect the pattern of skill demand? Evidence from Chinese manufacturing firms," Economic Modelling, Elsevier, vol. 96(C), pages 295-309.
    20. Konings, Jozef & Dhyne, Emmanuel & Van den bosch, Jeroen & ,, 2018. "The Return on Information Technology: Who Benefits Most?," CEPR Discussion Papers 13246, C.E.P.R. Discussion Papers.

    More about this item

    Keywords

    metallurgy; total factor productivity; technological changes;
    All these keywords.

    JEL classification:

    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • L23 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Organization of Production
    • M11 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - Production Management
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

    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:rnp:ecopol:ep1922. 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: RANEPA maintainer (email available below). General contact details of provider: https://edirc.repec.org/data/aneeeru.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.