Many studies use tariff data to measure changes in trade policy. This paper reveals significant errors in one of the standard sources for tariff rates, the World Integrated Trade Solution (WITS), due to incomplete reporting—resulting in measurement errors from false interpolation—and selection bias from dropping tariff rates when no trade is recorded. A new interpolation algorithm is proposed to account for misreporting, and the resulting global tariff dataset is used to demonstrate the practical relevance of missing tariffs by replicating recent studies that rely on WITS data. The findings show that studies leveraging cross-country tariff variation, such as estimates of trade elasticity, are particularly sensitive to the mishandling of tariff data.
Fedora Teti is an IES Postdoctoral Fellow and an Assistant Professor (non-tenure) & Economist at the LMU & Ifo Institute (on leave). Her research interests lie in international trade, particularly trade policy.
This event is co-organised with the Vienna Institute for International Economic Studies (wiiw) and the Research Centre International Economics (FIW). The project leading to this webinar has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 101031139. Any dissemination of the results of this event, reflect only the presenters' view. The European Commission is not responsible for any use that may be made of the information it contains.
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