Economic research and trade policy analysis
Acknowledgements
This report was approved by Marion Jansen (Director, Trade and Agriculture Directorate, OECD) and Ralph Ossa (Director, Economic Research and Statistics Division, WTO). The authors of the report are Andrea Andrenelli (OECD), Eddy Bekkers (WTO), Javier López González (OECD), Gabrielle Marceau (WTO) and Roger So (WTO). We are grateful for the useful comments received from Julia Nielson, Susan Stone, Clarisse Girot, and Frank Van Tongeren from the OECD, Johanna Hill, Bright Okogu, Ralph Ossa, Marc Bacchetta and Antonia Carzaniga from the WTO, as well as Anabel Gonzalez (IADB) and Robert Teh. We also acknowledge the useful discussions at the: G7 Scientific Roundtable on Digital Policy and Data Governance in the age of AI held in June 2024, and the comments received during the BIICL 2023 Annual WTO Conference on Trade and Technology: Challenges and Opportunities and the 27th GTAP Conference in Bordeaux in 2023.
C.1. Introducing the data flow shocks one by one
The channels of transmission across the different shocks can be gleaned by introducing the shocks one by one, cumulatively, starting from the change in trade costs, followed by the change in willingness to pay (Figure A C.1).
Conclusions
Hydrogen and hydrogen-derived commodities (ammonia, methanol and e-kerosene) are expected to play a crucial role in the energy transition and – in particular – the decarbonisation of many hard-to-abate end uses across industry and heavy-duty transport.
Introduction
Cross-border data flows underpin today’s economic and social interactions. They help people connect with family and friends located in different geographical locations; they support research addressing global challenges (as was the case during the COVID-19 pandemic); they enable the co-ordination of production along global supply chains; and they allow firms, notably smaller ones, and people to access global markets. In sum, cross-border data flows have become the lifeblood of modern day social and economic activities.
Foreword by the WTO Director-General
We live in troubled times. Beyond geopolitical tensions, uncertainty in the global economy, and stalling progress on collective challenges from poverty reduction and hunger to climate change, the world is witnessing the highest level of active conflicts since the end of the Second World War. According to the 2024 Global Peace Index compiled by the Institute of Economics and Peace, a think tank, fewer conflicts are being resolved, while they are becoming more internationalized.
Policy implications
There are manifold reasons economies are reviewing their data policy. These include considerations related to privacy and data protection, national security, regulatory control or audit, digital security, and also new forms of digital industrial policy (Casalini, López González and Nemoto, 2021). While there are legitimate reasons for the diversity in regulations across economies, the regulatory landscape that underpins cross-border data flows and data localisation is becoming increasingly complex.
Executive Summary
The comparison of tariffs across time poses significant challenges when data are expressed in different versions of the Harmonized System (HS).
Conclusions
The study highlights that incorporating NLP techniques into HS transposition processes offers substantial potential to enhance the efficiency and accuracy of tariff analysis, making it an invaluable tool for trade statisticians.
Tariff Verification
Both the simple and complex tariff scenarios discussed above indicate that a level of human verification is still ultimately required to ensure the quality of results after the automated tariff transposition, depending on the quality of the original tariffs datasets.
Introduction
Tariff line level Harmonized System (HS) transposition beyond the harmonized 6-digit level has long been a labor-intensive process in trade statistics.
Motivation
The regular work of the Regional Trade Agreements (RTA) section in the Trade Policies Review Division (TPRD) of the World Trade Organization is one among several statistical work streams that regularly require tariff line HS transposition.
Literature Review
Natural Language Processing (NLP) is one among many sub-branches of artificial intelligence (AI) that specifically deals with text as data.
Results
After running both transposition methods, the final output is a transposed tariffs table ("TC" table, in WTO IDB parlance) providing the full set of correlated HS codes in two HS nomenclatures, with each preferential tariff line allocated a corresponding MFN duty code.
Further Work
In future, further refinement and testing on diverse datasets is recommended to optimize these methods for broader application. For instance, other models such as OpenAI's Text Embedding model could be compared with SBERT to compare performance rates.
D.1. Introducing the data localisation shocks one by one
Figure A D.1 displays the projected change in real exports and real GDP for the four scenarios with the three types of costs (trade costs, WTP, and data management costs) entered one at a time. In Scenario A No data localisation, there is a small contribution of trade cost reductions, because the interaction of data flow and data localisation policies on trade costs is considered. Lifting data localisation policies would for some regions with less restrictive data flow policies imply a reduction in the costs of transferring data and thus an expansion of trade. At the global level the impact is marginal, because this only happens in isolated cases. The contribution of WTP/trust is larger to the expansion of real GDP and real exports, since the isolated regions would move to a safeguards regime with higher levels of trust when restrictive data localisation policies are lifted.
Identifying the potential economic impact of different broad approaches to data regulation
Modelling the economic impacts of data regulation can help support the policy debate by presenting stakeholders with information on the potential and relative opportunity costs associated with different types of data-related measures. This information can help policy makers think about different regulations that can successfully meet public policy objectives, including privacy and data protection, in a way that imposes the least possible burden on, or trade-offs in terms of, economic activity.
Abstract
This paper explores the application of Natural Language Processing (NLP) techniques to automate Harmonized System (HS) tariff line transposition, employing a three-stage process: unique 1:1 tariff code matching (Round 1), exact description matching (Round 2), and “smart” description matching (Round 3) using Artificial Intelligence (AI) and lexical similarity methods paired with harmonized 6-digit concordance and cosine similarity.
General note and abbreviations
The statistics related to applied tariffs and imports are calculated using data which are based on the HS nomenclature adopted by the country for the reference year. For statistics on bound tariffs, the calculations are based on the approved schedule of concessions of the WTO member.
Introduction
The World Tariff Profiles is a joint publication of the WTO, ITC and UNCTAD devoted to market access for goods.
Acknowledgements
The publication “Pathways to Sustainable Trade and Peace” was prepared under the general responsibility and guidance of Maika Oshikawa, Director of the Accessions Division.
Foreword
I am delighted to present the World Trade Organization Secretariat’s first comprehensive report on artificial intelligence (AI) and international trade. This report marks a milestone in our efforts to understand the impacts AI is having, and will continue to have, on global trade.
How domestic policies can shape the trade and AI relationship to favour inclusive economic growth
Trade policies are a necessary part of any relationship between trade and AI that results in inclusive economic growth.
Foreword by the WTO Director-General
Rapid advances in artificial intelligence (AI) are transforming the world economy, reshaping how work is defined, how value is created, and how opportunities are distributed across societies. Given these far-reaching effects, AI is also transforming world trade.
Introduction
With the launch of ChatGPT in November 2022, artificial intelligence (AI), and in particular generative AI – capable of generating high-quality text, images and other content based on the data on which it is trained – entered into public consciousness and has been experiencing rapid adoption.
Acknowledgements
The World Trade Report 2025 was prepared under the general responsibility and guidance of Johanna Hill, WTO Deputy Director-General, and Ralph Ossa, Chief Economist and Director of the Economic Research and Statistics Division. Director-General Ngozi Okonjo-Iweala, Senior Advisor to the Director-General Uyama Tomochika, and Trineesh Biswas from the Office of the Director-General provided valuable advice and guidance.
Introduction
The development and deployment of artificial intelligence (AI) have accelerated in the last few years, and its applications hold the potential to revolutionize human society and economic activities.
Executive summary
The widespread and transformative impact that artificial intelligence (AI) is currently having on society is being felt in all areas, from work, production and trade to health, arts and leisure activities.
AI, trade and inclusive growth: opportunities and challenges
This chapter provides a detailed economic analysis of the transformative potential of AI, focusing on its impact on trade and inclusive growth.
International cooperation to make trade and AI work for all
As trade shapes the development and deployment of AI, and AI could, in turn, reshape global trade, stronger international trade cooperation, both at the WTO and with other international organizations, is important to ensure that AI is beneficial and that the benefits of AI are more widely shared.
Executive summary
Artificial intelligence (AI) is beginning to reshape the global economy.