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Putting Quantitative Models to the Test: An Application to the U.S.-China Trade War

Author

Listed:
  • Rodrigo Adão
  • Arnaud Costinot
  • Dave Donaldson

Abstract

The primary motivation behind quantitative work in international trade and many other fields is to shed light on the economic consequences of policy changes and other shocks. To help assess and potentially strengthen the credibility of such quantitative predictions, we introduce an IV-based goodness-of-fit measure that provides the basis for testing causal predictions in arbitrary general equilibrium environments as well as for estimating the average misspecification in these predictions. As an illustration of how to use the measure in practice, we revisit the welfare consequences of the U.S.-China trade war predicted by Fajgelbaum et al. (2020).

Suggested Citation

  • Rodrigo Adão & Arnaud Costinot & Dave Donaldson, 2025. "Putting Quantitative Models to the Test: An Application to the U.S.-China Trade War," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 140(2), pages 1471-1524.
    • Handle: RePEc:oup:qjecon:v:140:y:2025:i:2:p:1471-1524.
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    File URL: http://hdl.handle.net/10.1093/qje/qjae041
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    Cited by:

    1. Rodrigo Adão & John Sturm Becko & Arnaud Costinot & Dave Donaldson, 2026. "World Trading System For Whom? Evidence from Global Tariffs," NBER Working Papers 34658, National Bureau of Economic Research, Inc.
    2. Farid Farrokhi & Ahmad Lashkaripour, 2025. "Can Trade Policy Mitigate Climate Change?," Econometrica, Econometric Society, vol. 93(5), pages 1561-1599, September.
    3. Joseph Kopecky, 2026. "E Pluribus Euro: Minimum Fiscal Capacity for Collective Trade Policy in a Currency Union," Trinity Economics Papers tep0426new, Trinity College Dublin, Department of Economics, revised Apr 2026.

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