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Putting Quantitative Models to the Test: An Application to Trump’s Trade War

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  • Rodrigo Adão
  • Arnaud Costinot
  • Dave Donaldson

Abstract

The primary motivation behind quantitative modeling in international trade and many other fields is to shed light on the economic consequences of policy changes. 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 our IV-based goodness-of-fit measure in practice, we revisit the welfare consequences of Trump's trade war predicted by Fajgelbaum, Goldberg, Kennedy and Khandelwal (2020).

Suggested Citation

  • Rodrigo Adão & Arnaud Costinot & Dave Donaldson, 2023. "Putting Quantitative Models to the Test: An Application to Trump’s Trade War," NBER Working Papers 31321, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:31321
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    More about this item

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C68 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computable General Equilibrium Models
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • F10 - International Economics - - Trade - - - General
    • R10 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - General

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