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Matching of PATSTAT applications to AIDA firms: discussion of the methodology and results

Author

Listed:
  • Francesca Lotti

    () (Bank of Italy)

  • Giovanni Marin

    () (CERIS-CNR)

Abstract

This paper is a brief methodological note on the matching of Italian firms in the AIDA database with applicants at the European Patent Office from the PATSTAT database. The need to match data on patent applications with balance-sheet information stems from the importance of patent statistics as a source of information on the innovative performance of firms. Starting from recent efforts to match applicants in PATSTAT with firms in the Bureau van Dijk databases (ORBIS, AMADEUS, FAME), we added an improved cleaning routine to maximize exact matches, followed by an approximate matching based on multiple combination of similarity scores. Starting with 272,475 firms, we matched 49,369 EPO applications in the period 1977-2009. The matching covers 68 percent of EPO applications by Italian firms for the entire period and 89 percent for 2000-2009. Finally, we describe the time, sector, size, geographical location and technology distribution of the matched applications.

Suggested Citation

  • Francesca Lotti & Giovanni Marin, 2013. "Matching of PATSTAT applications to AIDA firms: discussion of the methodology and results," Questioni di Economia e Finanza (Occasional Papers) 166, Bank of Italy, Economic Research and International Relations Area.
    • Handle: RePEc:bdi:opques:qef_166_13
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    File URL: http://www.bancaditalia.it/pubblicazioni/qef/2013-0166/QEF_166.pdf
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    Cited by:

    1. Marco Grazzi & Chiara Piccardo & Cecilia Vergari, 2019. "Concordance and complementarity in IP instruments," DISCE - Quaderni del Dipartimento di Politica Economica dipe0003, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    2. Bronzini, Raffaello & Piselli, Paolo, 2016. "The impact of R&D subsidies on firm innovation," Research Policy, Elsevier, vol. 45(2), pages 442-457.
    3. Ufuk Akcigit & Salomé Baslandze & Francesca Lotti, 2018. "Connecting to Power: Political Connections, Innovation, and Firm Dynamics," NBER Working Papers 25136, National Bureau of Economic Research, Inc.
    4. Riccardo Leoncini & Alberto Marzucchi & Sandro Montresor & Francesco Rentocchini & Ugo Rizzo, 2019. "‘Better late than never’: the interplay between green technology and age for firm growth," Small Business Economics, Springer, vol. 52(4), pages 891-904, April.
    5. Federica Bertamino & Raffaello Bronzini & Marco De Maggio & Davide Revelli, 2016. "Local policies for innovation: the case of technology districts in Italy," Questioni di Economia e Finanza (Occasional Papers) 313, Bank of Italy, Economic Research and International Relations Area.
    6. Cristiano Antonelli & Alessandra Colombelli, 2017. "The locus of knowledge externalities and the cost of knowledge," Regional Studies, Taylor & Francis Journals, vol. 51(8), pages 1151-1164, August.
    7. Danilo Liberati & Marco Marinucci & Giulia Martina Tanzi, 2016. "Science and technology parks in Italy: main features and analysis of their effects on the firms hosted," The Journal of Technology Transfer, Springer, vol. 41(4), pages 694-729, August.
    8. Roberto Antonietti & Raffaello Bronzini & Giulio Cainelli, 2015. "Inward greenfield FDI and innovation," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 42(1), pages 93-116, March.
    9. Ghisetti, Claudia & Quatraro, Francesco, 2014. "Is green Knowledge improving Environmental Productivity? Sectoral Evidence from Italian Regions," Department of Economics and Statistics Cognetti de Martiis. Working Papers 201411, University of Turin.
    10. Grinza, Elena & Quatraro, Francesco, 2019. "Workers’ replacements and firms’ innovation dynamics: New evidence from Italian matched longitudinal data," Research Policy, Elsevier, vol. 48(9), pages 1-1.
    11. Marin, Giovanni, 2014. "Do eco-innovations harm productivity growth through crowding out? Results of an extended CDM model for Italy," Research Policy, Elsevier, vol. 43(2), pages 301-317.
    12. M. Grazzi & C. Piccardo & C. Vergari, 2019. "Concordance and complementarity in Intellectual Property instruments," Working Papers wp1127, Dipartimento Scienze Economiche, Universita' di Bologna.
    13. Riccardo Leoncini & Alberto Marzucchi & Sandro Montresor & Francesco Rentocchini & Ugo Rizzo, 2016. "‘Better late than never’: a longitudinal quantile regression approach to the interplay between green technology and age for firm growth," SEEDS Working Papers 0616, SEEDS, Sustainability Environmental Economics and Dynamics Studies, revised May 2016.
    14. Giovanni Marin & Francesca Lotti, 2017. "Productivity effects of eco-innovations using data on eco-patents," Industrial and Corporate Change, Oxford University Press, vol. 26(1), pages 125-148.
    15. Michele Peruzzi & Georg Zachmann & Reinhilde Veugelers, 2014. "Remerge: regression-based record linkage with an application to PATSTAT," Working Papers 852, Bruegel.
    16. Luisa Gagliardi & Giovanni Marin & Caterina Miriello, 2014. "The Greener the Better: Job Creation and Environmentally- Friendly Technological Change," IEFE Working Papers 60, IEFE, Center for Research on Energy and Environmental Economics and Policy, Universita' Bocconi, Milano, Italy.
    17. Francesco Aiello & Giuseppe Albanese & Paolo Piselli, 2017. "Public R&D Support In Italy. Evidence From A New Firm-Level Patent Data Set," Working Papers 201702, Università della Calabria, Dipartimento di Economia, Statistica e Finanza "Giovanni Anania" - DESF.
    18. Federica Bertamino & Raffaello Bronzini & Marco De Maggio & Davide Revelli, 2017. "Regional policies for innovation: the case of technology districts in Italy," Regional Studies, Taylor & Francis Journals, vol. 51(12), pages 1826-1839, December.

    More about this item

    Keywords

    names harmonization; patents; approximate matching; PATSTAT; AIDA;

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O34 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Intellectual Property and Intellectual Capital

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