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Coverage and representativeness of Orbis data

Author

Listed:
  • Matej Bajgar

    (OECD)

  • Giuseppe Berlingieri

    (OECD)

  • Sara Calligaris

    (OECD)

  • Chiara Criscuolo

    (OECD)

  • Jonathan Timmis

    (OECD)

Abstract

This paper describes the coverage and representativeness of Orbis, a commercial database of firm-level records across many countries. Such databases can provide key insights into global economic trends and shed light on how policies affect firms within and across countries. As a benchmark, the paper uses industry-level data from the OECD STAN dataset as well as micro-aggregated data from the OECD MultiProd and DynEmp projects, which draw on official microdata representative of the entire firm population. Results indicate that Orbis is more suitable for studies that: i) take a global perspective rather than make comparisons across countries; ii) analyse top performers and multinationals rather than underperforming firms; and iii) focus on mean performance or changes within firms rather than the entire firm distribution or entry and exit.

Suggested Citation

  • Matej Bajgar & Giuseppe Berlingieri & Sara Calligaris & Chiara Criscuolo & Jonathan Timmis, 2020. "Coverage and representativeness of Orbis data," OECD Science, Technology and Industry Working Papers 2020/06, OECD Publishing.
  • Handle: RePEc:oec:stiaaa:2020/06-en
    DOI: 10.1787/c7bdaa03-en
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    Citations

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    Cited by:

    1. Vaziri, M., 2022. "Antitrust Law and Business Dynamism," Janeway Institute Working Papers 2219, Faculty of Economics, University of Cambridge.
    2. Matteo Borrotti & Michele Rabasco & Alessandro Santoro, 2022. "Using Accounting Information to Predict Aggressive Tax Placement Decisions by European Groups," Working Papers 488, University of Milano-Bicocca, Department of Economics, revised Feb 2022.
    3. Kris De Jaegher & Michal Soltes & Vitezslav Titl, 2023. "Easing Renegotiation Rules in Public Procurement: Evidence from a Policy Reform," CERGE-EI Working Papers wp757, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    4. Tommaso Bighelli & Filippo di Mauro & Marc J Melitz & Matthias Mertens, 2023. "European Firm Concentration and Aggregate Productivity," Journal of the European Economic Association, European Economic Association, vol. 21(2), pages 455-483.
    5. Nakatani, Ryota, 2023. "Debt maturity and firm productivity—The role of intangibles," Research in Economics, Elsevier, vol. 77(1), pages 116-121.
    6. Borrotti, Matteo & Rabasco, Michele & Santoro, Alessandro, 2023. "Using accounting information to predict aggressive tax location decisions by European groups," Economic Systems, Elsevier, vol. 47(3).
    7. Brutscher, Philipp-Bastian & Coali, Andrea & Delanote, Julie & Harasztosi, Peter, 2020. "EIB Group Survey on Investment and Investment Finance: A technical note on data quality," EIB Working Papers 2020/08, European Investment Bank (EIB).
    8. Vera Santomartino & Barbara Bratta & Paolo Acciari, 2020. "Country-by-Country Reports statistics – a new perspective to multinational enterprises Descriptive analysis of national and foreign MNEs with a local presence in Italy," Working Papers wp2020-9, Ministry of Economy and Finance, Department of Finance.
    9. Vaziri, M., 2022. "Antitrust Law and Business Dynamism," Cambridge Working Papers in Economics 2243, Faculty of Economics, University of Cambridge.
    10. Kerstin Hotte & Angelos Theodorakopoulos & Pantelis Koutroumpis, 2021. "Automation and Taxation," Papers 2103.04111, arXiv.org, revised Apr 2022.
    11. Benatti, Nicola & Groiss, Martin & Kelly, Petra & Lopez-Garcia, Paloma, 2023. "Environmental regulation and productivity growth in the euro area: testing the Porter hypothesis," Working Paper Series 2820, European Central Bank.
    12. Archanskaia, Elizaveta & Canton, Erik & Hobza, Alexandr & Nikolov, Plamen & Simons, Wouter, 2023. "The asymmetric impact of COVID-19: A novel approach to quantifying financial distress across industries," European Economic Review, Elsevier, vol. 158(C).
    13. Pietro Santoleri & Andrea Mina & Alberto Di Minin & Irene Martelli, 2020. "The causal effects of R&D grants: evidence from a regression discontinuity," LEM Papers Series 2020/18, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.

    More about this item

    Keywords

    cross-country analysis; distributed microdata analysis; firm-level data;
    All these keywords.

    JEL classification:

    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
    • Y1 - Miscellaneous Categories - - Data: Tables and Charts

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