Identifying Export Opportunities from Large International Trade Datasets: A Methodological Note

Martin Cameron and Wim Naudé
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Martin Cameron: Trade Research Advisory (Pty) Ltd, South Africa
Wim Naudé: RWTH Aachen University, Germany & University of Coimbra, CeBER and Faculty of Economics

No 2026-02, CeBER Working Papers from Centre for Business and Economics Research (CeBER), University of Coimbra

Abstract: In this paper we explain the extended Decision Support Model (DSM) methodology, operationalized through the AEXI Market Finder, which is designed to identify realistic export opportunities from large international trade datasets, such as that of UN Comtrade and CEPII-BACI. Grounded in the scientific literature on the need for and determinants of exports - specifically New New Trade Theory, the Balls-and-Bins model, and the Gravity Equation, we argue that best practice in export promotion must prioritize the provision of information to reduce frictions and correct market failures caused by information asymmetries. We then describe the extended DSM, which processes global trade data through four distinct filters.Furthermore, we compare the DSM’s elimination-based approach to the estimation-based gravity models used by the International Trade Centre (ITC), highlighting the DSM’s distinct ability to incorporate risk and realistic transport costs and transit dimensions, and to support innovation in export marketing. We conclude by discussing the limitations of the approach and offering recommendations for future research.

Keywords: Exports; international trade; data-driven decision making; trade facilitation (search for similar items in EconPapers)
JEL-codes: F13 F14 F17 M31 (search for similar items in EconPapers)
Pages: 50 pages
Date: 2026-01
New Economics Papers: this item is included in nep-int
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