
Rodrigo Adao
· Associate Professor of EconomicsUniversity of Chicago · Macroeconomics
Active 2015–2026
About
Welcome to my website! I am an associate professor at the University of Chicago Booth School of Business. My primary field of interest is international trade.
Research topics
- Computer Science
- Economics
- Labour economics
- Mathematical analysis
- Econometrics
- Finance
- Demographic economics
- Accounting
- Mathematics
- Business
Selected publications
World Trading System For Whom? Evidence from Global Tariffs
SSRN Electronic Journal · 2026-01-01
preprintOpen access1st authorCorrespondingA World Trading System For Whom? Evidence from Global Tariffs
SSRN Electronic Journal · 2026-01-01
preprintOpen access1st authorCorrespondingFast and Slow Technological Transitions
Journal of Political Economy Macroeconomics · 2024-02-27 · 22 citations
article1st authorCorrespondingDo economies adjust slowly to certain technological innovations and more rapidly to others? We argue that the adjustment is slower when innovations mainly benefit production activities requiring skills that are more different from those used in the rest of the economy. When such skill specificity is stronger, the adjustment of labor markets is driven less by the fast reallocation of older incumbent workers and more by the gradual entry of younger generations. We first document that the US labor market adjusted differently to early twentieth-century manufacturing innovations than to recent information and communication technologies (ICTs). We then build an overlapping-generations model of technological transitions and characterize how skill specificity affects equilibrium dynamics. Skill specificity helps explain why the ICT transition was slower, driven entirely by the entry of younger generations.
Putting Quantitative Models to the Test: An Application to the U.S.-China Trade War
The Quarterly Journal of Economics · 2024-11-27 · 10 citations
article1st authorCorrespondingAbstract 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).
Why is Trade Not Free? A Revealed Preference Approach
2024-05-21 · 6 citations
preprintOpen access1st authorCorrespondingA prominent explanation for why trade is not free is politicians' desire to protect some of their constituents at the expense of others. In this paper we develop a methodology that can be used to reveal the welfare weights that a nation's import tariffs implicitly place on different groups of society. Applied in the context of the United States in 2017, this method implies that redistributive trade protection accounts for a significant fraction of US tariff variation and causes large monetary transfers between US individuals, mostly driven by differences in welfare weights across sectors of employment. Perhaps surprisingly, differences in welfare weights across US states play a much smaller role.
Putting Quantitative Models to the Test: An Application to Trump's Trade War
SSRN Electronic Journal · 2023-01-01
articleOpen access1st authorCorrespondingWhy is Trade Not Free? A Revealed Preference Approach
National Bureau of Economic Research · 2023-10-01 · 2 citations
reportOpen access1st authorCorrespondingA prominent explanation for why trade is not free is politicians' desire to protect some of their constituents at the expense of others.In this paper we develop a methodology that can be used to reveal the welfare weights that a nation's import tariffs implicitly place on different groups of society.Applied in the context of the United States in 2017, this method implies that redistributive trade protection accounts for a significant fraction of US tariff variation and causes large monetary transfers between US individuals, mostly driven by differences in welfare weights across sectors of employment.Perhaps surprisingly, differences in welfare weights across US states play a much smaller role.
Why is Trade Not Free? A Revealed Preference Approach
SSRN Electronic Journal · 2023-01-01 · 3 citations
articleOpen access1st authorCorrespondingPutting Quantitative Models to the Test: An Application to Trump’s Trade War
SSRN Electronic Journal · 2023-01-01 · 4 citations
articleOpen access1st authorCorrespondingWhy is Trade Not Free? A Revealed Preference Approach
SSRN Electronic Journal · 2023-01-01 · 4 citations
articleOpen access1st authorCorresponding
Frequent coauthors
- 93 shared
Dave Donaldson
- 73 shared
Arnaud Costinot
- 38 shared
Nitya Pandalai-Nayar
University of San Diego
- 38 shared
Martin Beraja
Massachusetts Institute of Technology
- 32 shared
Dina Pomeranz
University of Zurich
- 31 shared
Costas Arkolakis
Yale University
- 30 shared
Paul E. Carrillo
- 24 shared
Federico Esposito
Tufts University
Awards & honors
- Distinguished Alumni Award Honorees
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