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The long-run impact of digitalization on trade patterns

Author

Listed:
  • Bekkers, Eddy
  • Kalachyhin, Hryhorii
  • Teh, Robert

Abstract

We employ the WTO Global Trade Model (GTM) to generate quantitative projections on the expected long-run impact of digitalization on global trade patterns. Five trends are modelled: (i) adoption of artificial intelligence which raises productivity growth; (ii) digitalization reducing trade costs, (iii) the shift to online sales (e-commerce), (iv) the reduced need for physical face-to-face interaction leading to lower trade costs; and (v) changes in data policies in response to these technologies which also impacts trade costs. We distinguish between a convergence scenario with larger productivity growth and trade cost reductions for low-income economies and a core scenario with uniform changes. The simulations generate three main sets of findings. First, digitalization is expected to provide a strong boost to global trade growth and a shift from merchandise trade towards services, and in particular, digitally deliverable services (DDS). With digitalization, global trade growth rises from 2.3% in the baseline to 4.2% annually between 2018-2040. The share of services trade will rise to 37.2% by 2040 with digitalization compared to 27% in the baseline, while the share of DDS in total trade rises to 17.4% by 2040 (compared to 12.4% in the baseline). Second, digitalization can be a force for inclusion, enabling low-income and lower-middle-income economies to raise their share in global trade and income. Trade growth in DDS is projected to be highest in low-income and lower-middle-income economies in the convergence scenario and the share of low-income and lower-middle-income economies in total trade would increase to 10.6% (compared to 8.2% in the baseline). Third, digitalization is projected to change the organization of production and patterns of revealed comparative advantage (RCA). The share of imported intermediates in exports rises in services but falls in manufacturing. In the convergence scenario, low-income economies will expand their RCA in DDS, although high-income economies will continue to retain a strong RCA in this sector

Suggested Citation

  • Bekkers, Eddy & Kalachyhin, Hryhorii & Teh, Robert, 2025. "The long-run impact of digitalization on trade patterns," WTO Staff Working Papers ERSD-2025-01, World Trade Organization (WTO), Economic Research and Statistics Division.
  • Handle: RePEc:zbw:wtowps:309423
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    References listed on IDEAS

    as
    1. Ali Hortaçsu & F. Asís Martínez-Jerez & Jason Douglas, 2009. "The Geography of Trade in Online Transactions: Evidence from eBay and MercadoLibre," American Economic Journal: Microeconomics, American Economic Association, vol. 1(1), pages 53-74, February.
    2. Aguiar, Angel & Corong, Erwin L. & van der Mensbrugghe, Dominique & Bekkers, Eddy & Koopman, Robert Bernard & Teh, Robert, 2019. "The WTO Global Trade Model: Technical documentation," WTO Staff Working Papers ERSD-2019-10, World Trade Organization (WTO), Economic Research and Statistics Division.
    3. Keith Head & John Ries, 2001. "Increasing Returns versus National Product Differentiation as an Explanation for the Pattern of U.S.-Canada Trade," American Economic Review, American Economic Association, vol. 91(4), pages 858-876, September.
    4. Daron Acemoglu, 2024. "The Simple Macroeconomics of AI," NBER Working Papers 32487, National Bureau of Economic Research, Inc.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Dynamic CGE-Modelling; Structural Change; Digitalization;
    All these keywords.

    JEL classification:

    • F14 - International Economics - - Trade - - - Empirical Studies of Trade
    • F43 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Economic Growth of Open Economies
    • I25 - Health, Education, and Welfare - - Education - - - Education and Economic Development

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