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Technical Change and Total Factor Productivity Growth for Swedish Manufacturing and Service Industries

Author

Listed:
  • Donghyun Oh

    (KTH - KTH Royal Institute of Technology [Stockholm])

  • Almas Heshmati

    (SNU - Seoul National University [Seoul])

  • Hans Lööf

    (Raoyal Institute of Technology - Economics/Centre of Excellence for Science and Innovation Studies)

Abstract

This paper presents alternative specifications of the production functions of a large panel of Swedish firms for the period 1992-2000. The period can be characterized as a transition when long-run productivity growth in the Swedish economy improved from being among the weakest to one of the strongest within the OECD. In order to present a detailed exploration of this dramatic change, the time trend and general index models are applied to estimate total factor productivity (TFP) growth, rate of technical change and returns to scale. The models are extended to allow for firm-specific as well as time-varying technical change. The parametric TFP measures are also compared with the non-parametric Solow residual, and several hypotheses are tested to explain the growth patterns in the Swedish economy. It is found that the improved growth rate, initially starting in large exporting manufacturing firms, after a deep economic crisis at the beginning of the 1990s, spilled over to the rest of the economy, both manufacturing and services.

Suggested Citation

  • Donghyun Oh & Almas Heshmati & Hans Lööf, 2011. "Technical Change and Total Factor Productivity Growth for Swedish Manufacturing and Service Industries," Post-Print hal-00693831, HAL.
    • Handle: RePEc:hal:journl:hal-00693831
    DOI: 10.1080/00036846.2011.564147
    Note: View the original document on HAL open archive server: https://hal.science/hal-00693831
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    Cited by:

    1. Donghyun Oh & Almas Heshmati & Hans Lööf, 2012. "Technical change and total factor productivity growth for Swedish manufacturing and service industries," Applied Economics, Taylor & Francis Journals, vol. 44(18), pages 2373-2391, June.
    2. Matteo Cervellati & Uwe Sunde, 2015. "The Economic and Demographic Transition, Mortality, and Comparative Development," American Economic Journal: Macroeconomics, American Economic Association, vol. 7(3), pages 189-225, July.
    3. Almas Heshmati & Masoomeh Rashidghalam, 2020. "Estimation of technical change and TFP growth based on observable technology shifters," Journal of Productivity Analysis, Springer, vol. 53(1), pages 21-36, February.
    4. Sauer, J. & Park, T. & Graversen, J., 2008. "Organic Farming in Denmark – Productivity, Technical Change and Market Exit," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 43, March.
    5. Sauer, Johannes & Graversen, Jesper T. & Park, Timothy A., 2006. "Breathtaking or Stagnating? - Productivity, Technical Change and Structural Dynamics in Danish Organic Farming," 2006 Annual meeting, July 23-26, Long Beach, CA 21481, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    6. Sun, Zhe & Zhao, Liang & Kaur, Puneet & Islam, Nazrul & Dhir, Amandeep, 2023. "Theorizing the relationship between the digital economy and firm productivity: The idiosyncrasies of firm-specific contexts," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    7. Oh, Dong-hyun, 2015. "Productivity growth, technical change and economies of scale of Korean fossil-fuel generation companies, 2001–2012: A dual approach," Energy Economics, Elsevier, vol. 49(C), pages 113-121.
    8. Triebs, T.P. & Kumbhakar, S.C., 2013. "Productivity with general indices of management and technical change," Economics Letters, Elsevier, vol. 120(1), pages 18-22.
    9. Almas Heshmati & Subal C. Kumbhakar, 2014. "A general model of technical change with an application to the OECD countries," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 23(1), pages 25-48, January.
    10. Pontus Mattsson & Jonas Månsson & William H. Greene, 2020. "TFP change and its components for Swedish manufacturing firms during the 2008–2009 financial crisis," Journal of Productivity Analysis, Springer, vol. 53(1), pages 79-93, February.
    11. Warda, Peter, 2013. "Labor Decomposition: A Firm Level Analysis on Import Quality and Labor Demand," Working Paper Series in Economics and Institutions of Innovation 322, Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies.
    12. Pontus Mattsson & Jonas Mansson & William H. Greene, 2018. "TFP Change and its Components for Swedish Manufacturing Firms During the 2008-2009 Financial Crisis," Working Papers 18-27, New York University, Leonard N. Stern School of Business, Department of Economics.
    13. Ghulam, Yaseen & Dhruva, Kamini, 2024. "Banking sector reforms in a challenging environment: An emerging financial market experience," International Review of Economics & Finance, Elsevier, vol. 92(C), pages 1074-1096.
    14. Marijn Verschelde & Michel Dumont & Bruno Merlevede & Glenn Rayp, 2014. "A constrained nonparametric regression analysis of factor-biased technical change and TFP growth at the firm level," Working Paper Research 266, National Bank of Belgium.
    15. Ma, Xuejiao & Jiang, Ping & Jiang, Qichuan, 2020. "Research and application of association rule algorithm and an optimized grey model in carbon emissions forecasting," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    16. Gugler, Klaus & Liebensteiner, Mario, 2019. "Productivity growth and incentive regulation in Austria's gas distribution," Energy Policy, Elsevier, vol. 134(C).
    17. Hou, Zheng & Roseta-Palma, Catarina & Ramalho, Joaquim José dos Santos, 2021. "Does directed technological change favor energy? Firm-level evidence from Portugal," Energy Economics, Elsevier, vol. 98(C).
    18. Alemayehu, Fikru K. & Kumbhakar, Subal C. & Landazuri Tveteraas, Sigbjørn, 2022. "Estimation of staff use efficiency: Evidence from the hospitality industry," Technological Forecasting and Social Change, Elsevier, vol. 178(C).
    19. Xinyue Lin & Lingli Qi & Haoran Pan & Basil Sharp, 2022. "COVID-19 Pandemic, Technological Progress and Food Security Based on a Dynamic CGE Model," Sustainability, MDPI, vol. 14(3), pages 1-18, February.

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    More about this item

    Keywords

    Social Sciences & Humanities;

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • 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
    • L25 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Firm Performance
    • L60 - Industrial Organization - - Industry Studies: Manufacturing - - - General
    • L80 - Industrial Organization - - Industry Studies: Services - - - General
    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General

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