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Building a firm level dataset for the analysis of industrial dynamics and demography

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Listed:
  • M. Grazzi
  • C. Piccardo
  • C. Vergari

Abstract

This paper illustrates the building procedure of a firm-level panel dataset that merges several sources of information concerning the various activities of business firms. The aim of this work is to achieve a detailed dataset able to shed light on firm demographics, in terms of survival, entry and exit processes, distinguishing between voluntary" and involuntary" exits. Moreover, the derived dataset allows to monitor the innovation activities of the firms and also to capture complementarities between two instruments of intellectual property rights (IPRs), namely granted patents and registered trademarks. We assess the validity of the proposed procedures resorting to the virtual universe of Italian limited liability companies as provided by Bureau van Dijk (BvD). The dataset covers more than 1 million companies operating in both manufacturing and service sectors and contain financial and economic information, as well as, among the others, the ownership structure and administrative procedures undergone by the firms, which may lead to firm exit. The main purpose of the paper is to provide a unified set of procedures to help the researcher dealing with the vast amount of information available on corporate firms and of ever increasing size. This will also facilitate the replication of empirical analyses, across researchers working on dataset with similar characteristics, although from different countries or data providers.

Suggested Citation

  • M. Grazzi & C. Piccardo & C. Vergari, 2017. "Building a firm level dataset for the analysis of industrial dynamics and demography," Working Papers wp2003, Dipartimento Scienze Economiche, Universita' di Bologna.
  • Handle: RePEc:bol:bodewp:wp2003
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    References listed on IDEAS

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    6. Grazzi, Marco & Sanzo, Roberto & Secchi, Angelo & Zeli, Alessandro, 2013. "The building process of a new integrated system of business micro-data 1989–2004," Journal of Economic and Social Measurement, IOS Press, issue 4, pages 291-324.
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    10. Travis J. Lybbert & Nikolas J. Zolas & Prantik Bhattacharyya, 2014. "An "Algorithmic Links with Probabilities" Concordance for Trademarks For Disaggregated Analysis of Trademark and Economic Data," WIPO Economic Research Working Papers 14, World Intellectual Property Organization - Economics and Statistics Division.
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    Cited by:

    1. Marco Grazzi & Chiara Piccardo & Cecilia Vergari, 2020. "Concordance and complementarity in IP instruments," Industry and Innovation, Taylor & Francis Journals, vol. 27(7), pages 756-788, August.
    2. Jochen Hundsdoerfer & Julia Wagner, 2020. "How accurately does the CCCTB apportionment formula allocate profits? An evaluation of the European Commission proposal," Journal of Business Economics, Springer, vol. 90(4), pages 495-536, May.

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    More about this item

    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
    • L60 - Industrial Organization - - Industry Studies: Manufacturing - - - General
    • L80 - Industrial Organization - - Industry Studies: Services - - - General
    • O14 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Industrialization; Manufacturing and Service Industries; Choice of Technology
    • 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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