IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2201.09878.html
   My bibliography  Save this paper

Has EU accession boosted patents performance in the EU-13? -- A critical evaluation using causal impact analysis with Bayesian structural time-series models

Author

Listed:
  • Agnieszka Kleszcz
  • Krzysztof Rusek

Abstract

Nowadays innovation is one of the main determinants of economic development. Patents are a key measure of innovation output, as patent indicators reflect the inventive performance of countries, technologies and firms. This paper provides new insights on the causal effects of the enlargement of the European Union (EU) by investigating the patents performance within the new EU member states (EU-13). The empirical results based on data collected from the OECD database from 1985-2017 and causal impact using a Bayesian structural time-series model (proposed by Google) point towards a conclusion that joining the EU has had a significant impact on patents performance in Romania, Estonia, Poland, 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 patents performance in the EU-13? -- A critical evaluation using causal impact analysis with Bayesian structural time-series models," Papers 2201.09878, arXiv.org.
  • Handle: RePEc:arx:papers:2201.09878
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2201.09878
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. Heidi L. Williams, 2017. "How Do Patents Affect Research Investments?," Annual Review of Economics, Annual Reviews, vol. 9(1), pages 441-469, September.
    5. 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.
    6. Michele Boldrin & David K. Levine, 2013. "The Case against Patents," Journal of Economic Perspectives, American Economic Association, vol. 27(1), pages 3-22, Winter.
    7. repec:fth:harver:1473 is not listed on IDEAS
    8. Alison Abbott & Quirin Schiermeier, 2019. "How European scientists will spend €100 billion," Nature, Nature, vol. 569(7757), pages 472-475, May.
    9. 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.
    10. Harvey,Andrew C., 1991. "Forecasting, Structural Time Series Models and the Kalman Filter," Cambridge Books, Cambridge University Press, number 9780521405737, January.
    11. 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.
    12. Gabriel Felbermayr & Jasmin Katrin Gröschl & Inga Heiland, 2018. "Undoing Europe in a New Quantitative Trade Model," ifo Working Paper Series 250, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    13. 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.
    14. 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.
    15. Ramesh Chandra Das, 2020. "Interplays among R&D spending, patent and income growth: new empirical evidence from the panel of countries and groups," Journal of Innovation and Entrepreneurship, Springer, vol. 9(1), pages 1-22, December.
    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. 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.
    2. Ramesh Chandra Das, 2020. "Interplays among R&D spending, patent and income growth: new empirical evidence from the panel of countries and groups," Journal of Innovation and Entrepreneurship, Springer, vol. 9(1), pages 1-22, December.
    3. van der Waal, Mark B. & Feddema, Jelle J. & van de Burgwal, Linda H.M., 2023. "Mapping the broad societal impact of patents," Technovation, Elsevier, vol. 128(C).
    4. Xiangfei Ma & Inna Gryshova & Viktoriia Khaustova & Olena Reshetnyak & Maryna Shcherbata & Denys Bobrovnyk & Mykyta Khaustov, 2022. "Assessment of the Impact of Scientific and Technical Activities on the Economic Growth of World Countries," Sustainability, MDPI, vol. 14(21), pages 1-35, November.
    5. Avanzi, Benjamin & Taylor, Greg & Vu, Phuong Anh & Wong, Bernard, 2020. "A multivariate evolutionary generalised linear model framework with adaptive estimation for claims reserving," Insurance: Mathematics and Economics, Elsevier, vol. 93(C), pages 50-71.
    6. Yuo-Hsien Shiau & Su-Fen Yang & Rishan Adha & Syamsiyatul Muzayyanah, 2022. "Modeling Industrial Energy Demand in Relation to Subsector Manufacturing Output and Climate Change: Artificial Neural Network Insights," Sustainability, MDPI, vol. 14(5), pages 1-18, March.
    7. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    8. Nicholas Bloom & John Van Reenen & Heidi Williams, 2019. "A toolkit of policies to promote innovation," Voprosy Ekonomiki, NP Voprosy Ekonomiki, issue 10.
    9. Krist'of N'emeth & D'aniel Hadh'azi, 2023. "GDP nowcasting with artificial neural networks: How much does long-term memory matter?," Papers 2304.05805, arXiv.org, revised Feb 2024.
    10. de Rassenfosse, Gaétan & Pellegrino, Gabriele & Raiteri, Emilio, 2024. "Do patents enable disclosure? Evidence from the invention secrecy act," International Journal of Industrial Organization, Elsevier, vol. 92(C).
    11. Bhaven N. Sampat, 2018. "A Survey of Empirical Evidence on Patents and Innovation," NBER Working Papers 25383, National Bureau of Economic Research, Inc.
    12. Di Giorgio, Giorgio & Traficante, Guido, 2013. "The loss from uncertainty on policy targets," Economic Modelling, Elsevier, vol. 30(C), pages 175-182.
    13. Ying Shu & Chengfu Ding & Lingbing Tao & Chentao Hu & Zhixin Tie, 2023. "Air Pollution Prediction Based on Discrete Wavelets and Deep Learning," Sustainability, MDPI, vol. 15(9), pages 1-19, April.
    14. S. Sriram & Pradeep K. Chintagunta & Ramya Neelamegham, 2006. "Effects of Brand Preference, Product Attributes, and Marketing Mix Variables in Technology Product Markets," Marketing Science, INFORMS, vol. 25(5), pages 440-456, September.
    15. Azumah Karim & Ananda Omotukoh Kube & Bashiru Imoro Ibn Saeed, 2020. "Modeling of Monthly Meteorological Time Series," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 9(4), pages 1-8.
    16. Peilun He & Karol Binkowski & Nino Kordzakhia & Pavel Shevchenko, 2021. "On Modelling of Crude Oil Futures in a Bivariate State-Space Framework," Papers 2108.01886, arXiv.org.
    17. Gupta, Apoorva & Stiebale, Joel, 2024. "Gains from patent protection: Innovation, market power and cost savings in India," DICE Discussion Papers 414, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    18. Bronwyn H. Hall & Christian Helmers & Mark Rogers & Vania Sena, 2012. "The Choice between Formal and Informal Intellectual Property: A Literature Review," NBER Working Papers 17983, National Bureau of Economic Research, Inc.
    19. Valentina Bosetti & Elena Verdolini, 2013. "Clean and Dirty International Technology Diffusion," Working Papers 2013.43, Fondazione Eni Enrico Mattei.
    20. Djuranovik, Leslie, 2014. "The Indonesian macroeconomy and the yield curve: A dynamic latent factor approach," Journal of Asian Economics, Elsevier, vol. 34(C), pages 1-15.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:arx:papers:2201.09878. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.