Tackling Discrepancies in Trade Data: The Harvard Growth Lab International Trade Datasets

Sebastian Bustos (), Ellie Jackson, David Torun, Brendan Leonard, Nil Tuzcu, Piotr Lukaszuk, Annie White, Ricardo Hausmann and Muhammed A. Yildirim
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Sebastian Bustos: Center for International Development at Harvard University
Ellie Jackson: Harvard's Growth Lab
Brendan Leonard: Harvard's Growth Lab
Nil Tuzcu: Harvard's Growth Lab
Annie White: Harvard's Growth Lab
Muhammed A. Yildirim: Center for International Development at Harvard University

No 251, Growth Lab Working Papers from Harvard's Growth Lab

Abstract: Bilateral trade data informs foreign and domestic policy decisions, serves as a growth indicator, determines tariffs, and is the basis for financial and investment decisions for corporations. Accurate trade data translates into better decision-making. However, the raw bilateral trade data reported by UN Comtrade suffer from two structural problems: reporting differences between country partners and countries reporting in different product classification systems, which require product-level harmonization to compare data across countries. In this paper, we address these challenges by combining a mirroring technique and a data-driven concordance method. Mirroring reconciles importer and exporter differences by imputing country reliability scores and applying a weighted country-pair average to calculate the estimated trade value. We harmonize product classifications across vintages by calculating conversion weights that reflect a product’s market share. The resulting publicly available datasets mitigate issues in raw trade statistics, reducing reporting inconsistencies while maintaining product-level granularity across six decades.

Keywords: Trade; Foreign Direct Investment (search for similar items in EconPapers)
Date: 2025-07
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Persistent link: https://EconPapers.repec.org/RePEc:glh:wpfacu:251

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