Putting Quantitative Models to the Test: An Application to Trump’s Trade War
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).
Date:
6 February 2024, 16:00 (Tuesday, 4th week, Hilary 2024)
Venue:
Manor Road Building, Manor Road OX1 3UQ
Venue Details:
Seminar Room A or https://zoom.us/j/97439169282?pwd=bU1TUWRORUJmaUV0OWpTeS9yVWlBZz09
Speaker:
Dave Donaldson (Massachusetts Institute of Technology)
Organising department:
Department of Economics
Part of:
Applied Microeconomics Seminar
Booking required?:
Not required
Audience:
Members of the University only
Editors:
Shreyasi Banerjee,
Edward Clark
