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Use of advanced technologies and extensive margins of exports in manufacturing firms from 27 EU countries in 2025

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  • Wagner, Joachim

Abstract

The use of advanced technologies like artificial intelligence, robotics, or smart devices will go hand in hand with higher productivity, higher product quality, and lower trade costs. Therefore, it can be expected to be positively related to export activities. This paper uses firm level data for manufacturing enterprises from the 27 member countries of the European Union collected in 2025 to shed further light on this issue by investigating the link between the use of advanced technologies and extensive margins of exports. Applying a new machine-learning estimator, Kernel-Regularized Least Squares (KRLS), which does not impose any restrictive assumptions for the functional form of the relation between margins of exports, use of advanced technologies, and any control variables, we find that firms which use more advanced technologies do more often export and do export to more different destinations.

Suggested Citation

  • Wagner, Joachim, 2026. "Use of advanced technologies and extensive margins of exports in manufacturing firms from 27 EU countries in 2025," KCG Working Papers 36, Kiel Centre for Globalization (KCG).
    • Handle: RePEc:zbw:kcgwps:334537
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    References listed on IDEAS

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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.
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    4. 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.
    5. 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..
    6. Ferwerda, Jeremy & Hainmueller, Jens & Hazlett, Chad J., 2017. "Kernel-Based Regularized Least Squares in R (KRLS) and Stata (krls)," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 79(i03).
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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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