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

Rodrigo Adão, Arnaud Costinot and Dave Donaldson

No 10484, CESifo Working Paper Series from CESifo

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 et al. (2020).

Keywords: model testing and validation; computational general equilibrium; international trade; economic geography (search for similar items in EconPapers)
JEL-codes: C52 C68 E17 F10 R10 (search for similar items in EconPapers)
Date: 2023
New Economics Papers: this item is included in nep-geo, nep-int and nep-mfd
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Related works:
Working Paper: Putting quantitative models to the test: An application to Trump's trade war (2024)
Working Paper: Putting quantitative models to the test: an application to Trump's trade war (2024)
Working Paper: Putting Quantitative Models to the Test: An Application to Trump’s Trade War (2023)
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