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Has EU Accession Boosted Patent Performance in the EU-13? A Critical Evaluation Using Causal Impact Analysis with Bayesian Structural Time-Series Models

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  • Agnieszka Kleszcz

    (Faculty of Natural Sciences, Jan Kochanowski University, 25-369 Kielce, Poland
    Institute of Telecommunications, AGH University of Science and Technology, 30-059 Krakow, Poland)

  • Krzysztof Rusek

    (Institute of Telecommunications, AGH University of Science and Technology, 30-059 Krakow, Poland)

Abstract

This paper provides new insights into the causal effects of the enlargement of the European Union (EU) on patent performance. The study focuses on the new EU member states (EU-13) and accession is considered as an intervention whose causal effect is estimated by the causal impact method using a Bayesian structural time-series model (proposed by Google). The empirical results based on data collected from the OECD database from 1985–2017 point towards a conclusion that joining the EU has had a significant impact on patent performance in Romania, Estonia, Poland, the Czech Republic, Croatia and Lithuania, although in the latter two countries, the impact was negative. For the rest of the EU-13 countries, there is no significant effect on patent performance. Whether the EU accession effect is significant or not, the EU-13 are far behind the EU-15 (countries which entered the EU before 2004) in terms of patent performance. The majority of patents (98.66%) are assigned to the EU-15, with just 1.34% of assignees belonging to the EU-13.

Suggested Citation

  • Agnieszka Kleszcz & Krzysztof Rusek, 2022. "Has EU Accession Boosted Patent Performance in the EU-13? A Critical Evaluation Using Causal Impact Analysis with Bayesian Structural Time-Series Models," Forecasting, MDPI, vol. 4(4), pages 1-16, October.
    • Handle: RePEc:gam:jforec:v:4:y:2022:i:4:p:47-881:d:957135
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    References listed on IDEAS

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    1. Klaus S. Friesenbichler, 2020. "Does EU-accession affect domestic market structures and firm level productivity?," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 47(2), pages 343-364, May.
    2. Heidi L. Williams, 2017. "How Do Patents Affect Research Investments?," Annual Review of Economics, Annual Reviews, vol. 9(1), pages 441-469, September.
    3. Michele Boldrin & David K. Levine, 2013. "The Case against Patents," Journal of Economic Perspectives, American Economic Association, vol. 27(1), pages 3-22, Winter.
    4. repec:fth:harver:1473 is not listed on IDEAS
    5. Ivana Rukavina, 2022. "Evaluation of macroeconomic outcomes and the seven-year membership of Croatia in the European Union," Public Sector Economics, Institute of Public Finance, vol. 46(1), pages 1-42.
    6. Harvey,Andrew C., 1991. "Forecasting, Structural Time Series Models and the Kalman Filter," Cambridge Books, Cambridge University Press, number 9780521405737, November.
    7. Maresch, Daniela & Fink, Matthias & Harms, Rainer, 2016. "When patents matter: The impact of competition and patent age on the performance contribution of intellectual property rights protection," Technovation, Elsevier, vol. 57, pages 14-20.
    8. Zvi Griliches, 1998. "Patent Statistics as Economic Indicators: A Survey," NBER Chapters, in: R&D and Productivity: The Econometric Evidence, pages 287-343, National Bureau of Economic Research, Inc.
    9. Andrea Filippetti & Antonio Peyrache, 2013. "Is the Convergence Party Over? Labour Productivity and the Technology Gap in Europe," Journal of Common Market Studies, Wiley Blackwell, vol. 51(6), pages 1006-1022, November.
    10. Szopik-Depczyńska, Katarzyna & Kędzierska-Szczepaniak, Angelika & Szczepaniak, Krzysztof & Cheba, Katarzyna & Gajda, Waldemar & Ioppolo, Giuseppe, 2018. "Innovation in sustainable development: an investigation of the EU context using 2030 agenda indicators," Land Use Policy, Elsevier, vol. 79(C), pages 251-262.
    11. Appio, Francesco Paolo & Baglieri, Daniela & Cesaroni, Fabrizio & Spicuzza, Lucia & Donato, Alessia, 2022. "Patent design strategies: Empirical evidence from European patents," Technological Forecasting and Social Change, Elsevier, vol. 181(C).
    12. Keun Lee & Jongho Lee, 2020. "National innovation systems, economic complexity, and economic growth: country panel analysis using the US patent data," Journal of Evolutionary Economics, Springer, vol. 30(4), pages 897-928, September.
    13. Harvey, Andrew & Snyder, Ralph D., 1990. "Structural time series models in inventory control," International Journal of Forecasting, Elsevier, vol. 6(2), pages 187-198, July.
    14. Michael Fritsch & Martin Obschonka & Michael Wyrwich, 2019. "Historical roots of entrepreneurship-facilitating culture and innovation activity: an analysis for German regions," Regional Studies, Taylor & Francis Journals, vol. 53(9), pages 1296-1307, September.
    15. Yee Kyoung Kim & Keun Lee, 2015. "Different Impacts of Scientific and Technological Knowledge on Economic Growth: Contrasting Science and Technology Policy in East Asia and Latin America," Asian Economic Policy Review, Japan Center for Economic Research, vol. 10(1), pages 43-66, January.
    16. Alison Abbott & Quirin Schiermeier, 2019. "How European scientists will spend €100 billion," Nature, Nature, vol. 569(7757), pages 472-475, May.
    17. Alexandre Almeida & Aurora A.C. Teixeira, 2007. "Does Patenting negatively impact on R&D investment?An international panel data assessment," FEP Working Papers 255, Universidade do Porto, Faculdade de Economia do Porto.
    18. Teemu Makkonen & Timo Mitze, 2016. "Scientific collaboration between ‘old’ and ‘new’ member states: Did joining the European Union make a difference?," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(3), pages 1193-1215, March.
    19. Amaia Altuzarra, 2019. "R&D and patents: is it a two way street?," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 28(2), pages 180-196, February.
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