Putting quantitative models to the test: an application to Trump's trade war

Rodrigo Adao, Arnaud Costinot and Dave Donaldson

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

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: international trade; urban economics; testing economic models (search for similar items in EconPapers)
JEL-codes: C52 C68 E17 F10 R10 (search for similar items in EconPapers)
Pages: 41 pages
Date: 2024-06-07
New Economics Papers: this item is included in nep-int
References: Add references at CitEc
Citations:

Downloads: (external link)
http://eprints.lse.ac.uk/126756/ Open access version. (application/pdf)

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 (2023)
Working Paper: Putting Quantitative Models to the Test: An Application to Trump’s Trade War (2023)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ehl:lserod:126756

Access Statistics for this paper

More papers in LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library LSE Library Portugal Street London, WC2A 2HD, U.K.. Contact information at EDIRC.
Bibliographic data for series maintained by LSERO Manager ().