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What drives productivity growth in the new EU member states? The case of Poland

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  • Kolasa, Marcin

Abstract

This paper considers productivity developments in the new EU member states and provides evidence on factors driving productivity growth in these countries, focusing on a panel of Polish manufacturing industries. Companies in Poland seem to benefit significantly from transfer of technologies that have been accumulated in more developed economies. By contrast, no strong evidence is found on immediate technology transfer. Another result is a significant effect of domestic innovation activity. There are signs that market reforms also boosted efficiency, whereas the role of reallocation of production factors towards more productive activities was marginal. Bearing in mind all methodological and data-related caveats, as well as cross-country diversity, caution is required while interpreting the findings and extrapolating them to other new member states. However, the results obtained provide some policy implications and make the case for taking into account domestic innovation activity while constructing endogenous growth models for the EU catching-up economies. JEL Classification: C23, O31, O47

Suggested Citation

  • Kolasa, Marcin, 2005. "What drives productivity growth in the new EU member states? The case of Poland," Working Paper Series 486, European Central Bank.
    • Handle: RePEc:ecb:ecbwps:2005486
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    File URL: https://www.ecb.europa.eu//pub/pdf/scpwps/ecbwp486.pdf
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    References listed on IDEAS

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    1. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
    2. Nelson, Charles R & Startz, Richard, 1990. "The Distribution of the Instrumental Variables Estimator and Its t-Ratio When the Instrument Is a Poor One," The Journal of Business, University of Chicago Press, vol. 63(1), pages 125-140, January.
    3. Stephen M. Miller & Mukti P. Upadhyay, 2002. "Total Factor Productivity, Human Capital and Outward Orientation: Differences by Stage of Ddevelopment and Geographic Regions," Working papers 2002-33, University of Connecticut, Department of Economics.
    4. Susanto Basu & John Fernald, 2001. "Why Is Productivity Procyclical? Why Do We Care?," NBER Chapters, in: New Developments in Productivity Analysis, pages 225-302, National Bureau of Economic Research, Inc.
    5. Bernard, Andrew B & Jones, Charles I, 1996. "Comparing Apples to Oranges: Productivity Convergence and Measurement across Industries and Countries," American Economic Review, American Economic Association, vol. 86(5), pages 1216-1238, December.
    6. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
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    Cited by:

    1. Matthias Mohr, 2005. "A Trend-Cycle(-Season) Filter," Econometrics 0508004, University Library of Munich, Germany.
    2. K. Skorik, 2020. "Structural transformations of the EU industrial sector," Economy and Forecasting, Valeriy Heyets, issue 3, pages 115-145.
    3. Kolasa Marcin, 2008. "How does FDI inflow affect productivity of domestic firms? The role of horizontal and vertical spillovers, absorptive capacity and competition," The Journal of International Trade & Economic Development, Taylor & Francis Journals, vol. 17(1), pages 155-173.
    4. Jan Hagemejer & Joanna Tyrowicz, 2012. "Is the effect really so large? Firm‐level evidence on the role of FDI in a transition economy-super-1," The Economics of Transition, The European Bank for Reconstruction and Development, vol. 20(2), pages 195-233, April.
    5. Jan Hagemejer & Michal Gradzewicz & Zbigniew Zolkiewski, 2007. "Globalization and the Polish Economy: Some Stylized Facts and CGE Model Simulations," EcoMod2007 23900033, EcoMod.
    6. V. Namazov, 2020. "Structured Financial Products Trading And Its Implementation Perspectives In Emerging Economies," Economy and Forecasting, Valeriy Heyets, issue 4, pages 122-136.
    7. Camilleri, Silvio John & Falzon, Joseph, 2013. "The Challenges of Productivity Growth in the Small Island States of Europe: A Critical Look of Malta and Cyprus," MPRA Paper 62489, University Library of Munich, Germany.
    8. International Monetary Fund, 2006. "Republic of Poland: Selected Issues," IMF Staff Country Reports 2006/392, International Monetary Fund.

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    More about this item

    Keywords

    convergence; innovation; manufacturing; multi-factor productivity; new Member States;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence

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