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Big Data Analytics and Exports—Evidence for Manufacturing Firms from 27 EU Countries

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  • Joachim Wagner

    (Leuphana University Lueneburg and Kiel Centre for Globalization)

Abstract

The use of big data analytics (including data mining and predictive analytics) by firms can be expected to increase productivity and reduce trade costs, which should be positively related to export activities. This paper uses firm level data from the Flash Eurobarometer 486 survey conducted in February – May 2020 to investigate the link between the use of big data analytics and export activities in manufacturing enterprises from the 27 member countries of the European Union. We find that firms which use big data analytics do more often export, do more often export to various destinations all over the world, and do export to more different destinations. The estimated big data analytics premia for exports are statistically highly significant after controlling for firm size, firm age, patents, and country. Furthermore, the size of these premia can be considered to be large. Successful exporters tend to use big data analytics.

Suggested Citation

  • Joachim Wagner, 2025. "Big Data Analytics and Exports—Evidence for Manufacturing Firms from 27 EU Countries," Open Economies Review, Springer, vol. 36(3), pages 825-834, July.
    • Handle: RePEc:kap:openec:v:36:y:2025:i:3:d:10.1007_s11079-024-09777-2
    DOI: 10.1007/s11079-024-09777-2
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    1. Bernard, Andrew B. & Bradford Jensen, J., 1999. "Exceptional exporter performance: cause, effect, or both?," Journal of International Economics, Elsevier, vol. 47(1), pages 1-25, February.
    2. Joachim Wagner, 2016. "Exports and Productivity: A Survey of the Evidence from Firm Level Data," World Scientific Book Chapters, in: Microeconometrics of International Trade, chapter 1, pages 3-41, World Scientific Publishing Co. Pte. Ltd..
    3. Janos Ferencz & Javier López González & Irene Oliván García, 2022. "Artificial Intelligence and international trade: Some preliminary implications," OECD Trade Policy Papers 260, OECD Publishing.
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    Cited by:

    1. Joachim Wagner, 2024. "Cloud Computing and Extensive Margins of Exports: Evidence for Manufacturing Firms from 27 EU Countries," Journal of Information Economics, Anser Press, vol. 2(1), pages 102-111, March.
    2. Joachim Wagner, 2024. "Estimation of empirical models for margins of exports with unknown non-linear functional forms: A Kernel-Regularized Least Squares (KRLS) approach Evidence from eight European countries," Working Paper Series in Economics 424, University of Lüneburg, Institute of Economics.
    3. Joachim Wagner, 2025. "Digitalization Intensity and Extensive Margins of Exports in Manufacturing Firms from 27 EU Countries - Evidence from Kernel-Regularized Least Squares Regression," Economic Analysis Letters, Anser Press, vol. 4(1), pages 22-29, March.
    4. Wagner, Joachim, 2024. "Estimation of empirical models for margins of exports with unknown nonlinear functional forms: A Kernel-Regularized Least Squares (KRLS) approach," KCG Working Papers 32, Kiel Centre for Globalization (KCG).

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    JEL classification:

    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • F14 - International Economics - - Trade - - - Empirical Studies of Trade

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