About me

I am an economist whose research agenda lies on the intersection between international trade and macroeconomics; I describe it as “Dynamic Trade and Spatial Macroeconomics.” I am embedding the dynamics of growth emphasized in macroeconomics into canonical trade models and incorporating the spatial dimension emphasized in trade models into macroeconomics. In my empirical work, I combine well-identified partial equilibrium effects using spatial data to inform estimates of general equilibrium effects. I use spatial data to answer questions about growth, trade, and inequality. I teach trade and macroeconomics at Pomona College and write a monthly economics column for O Globo, a Brazilian newspaper.

Recent Working Papers

  • Trade, Growth, and Product Innovation.
    • (Trade, Growth, Structural Modeling) Can trade integration induce product innovation? I document that countries that joined the European Union (EU) started producing more product varieties, investing more in R&D, and trading more compared to candidate countries that did not join at a given horizon. Additionally, I show that a plausibly exogenous increase in market access increases the probability of a given country starting production of and exporting a given product. To rationalize this reduced-form evidence, I propose a new quantitative framework that integrates the forces of specialization and market size. This is a dynamic general equilibrium model of frictional trade and endogenous growth with arbitrarily many asymmetric countries that nests the Eaton-Kortum model of trade and the Romer growth model as special cases. Key results are analytical expressions to decompose: (a) gains from trade into dynamic and static components; and (b) growth and welfare into “Romer” and “Eaton-Kortum” parts. In this framework, the product innovation growth rate increases with higher market access. Finally, a quantitative version of the model suggests that: (a) the EU enlargement increased its long-run yearly growth rate by about 0.10pp; and (b) dynamic gains can account for between 65-90% of total welfare gains from trade.
    • Draft article.
    • Presentations (past or scheduled): Midwest International Trade Meeting; Elon University; Texas A&M University; São Paulo School of Economics - Fundação Getúlio Vargas; University of Chile; UCSD Macroeconomics Seminar; 2023 Southern California Graduate Conference in Applied Economics; UCSD Global Economy Seminar.
  • The Impact of Geopolitical Conflicts on Trade, Growth, and Innovation (with Eddy Bekkers).
    • (Trade, Growth, Structural Modeling) Geopolitical conflicts have increasingly been a driver of trade policy. We study the potential effects of global and persistent geopolitical conflicts on trade, technological innovation, and economic growth. In conventional trade models the welfare costs of such conflicts are modest. We build a multi-sector multi-region general equilibrium model with dynamic sector-specific knowledge diffusion and explore the potential impact of a “decoupling of the global economy.” We divide the global economy into two geopolitical blocs – East and West – based on foreign policy similarity and model decoupling through an increase in trade costs. Results yield three main insights. First, the projected welfare losses for the global economy of a decoupling scenario can be drastic, as large as 12% in some regions and are largest in the lower income regions as they would benefit less from technology spillovers from richer areas. Second, the described size and pattern of welfare effects are specific to the model with diffusion of ideas. Without diffusion of ideas the size and variation across regions of the welfare losses would be substantially smaller. Third, a multi-sector framework exacerbates diffusion inefficiencies induced by trade costs relative to a single-sector one.
    • Draft article; VoxEU Column.
    • Presented at European Central Bank’s Trade Seminar; 8th IMF-WB-WTO Trade Research Conference; 24th Annual Conference on Global Economic Analysis; and WashU at Saint Louis Economics Grad Student Conference.
  • Dynamic Adjustment to Trade Shocks (with Junyuan Chen, Marc Muendler, and Fabian Trottner)
    • (Trade, Supply Chain, Cycle Adjustment, Structural Modeling) Global trade flows and supply chains adjust gradually. Empirical estimates of the trade elasticity for the short run are about half as large as those for the long run and suggest that trade is subject to substantive adjustment frictions. We develop a tractable framework that provides microfoundations for dynamic trade adjustment and rationalizes reduced-form estimation of a time-varying trade elasticity. The model features staggered sourcing decisions and nests the Eaton-Kortum model as the limiting long-run case. We calibrate the model to time-varying trade elasticities and use it to quantify the welfare impact of the 2018 US-China trade war. Staggered sourcing decisions considerably exacerbate losses from the trade war, with cumulative welfare losses 300% larger in the short run and 70% larger in the long run than in the Eaton-Kortum benchmark. Third countries such as Mexico can suffer welfare losses in the short run and welfare gains in the long run.
    • Draft article
    • Presented at NBER’s Trade and Macroeconomics Summer Institute; CESifo Area Conference on Global Economy 2024; FREIT’s Empirical Investigations in Trade and Investment (EITI), 15th Meeting; UCSD Faculty Seminar; and the European Central Bank’s Trade Seminar.


Carlos Góes is Visiting Assistant Professor (2024-27) at Pomona College, a premier liberal arts college located in Claremont, California. Aside from academia, he has previously worked as Senior Economic Advisor at the Office of the President of Brazil and as a researcher at the International Monetary Fund, the World Trade Organization, the World Bank, and U.S. think tanks.

His work has been featured in global outlets such as the Economist, the Wall Street Journal, the Financial Times, El País, and Le Monde.

Góes is an alumnus of UC San Diego (Ph.D.), Johns Hopkins SAIS (MA), and the University of Brasilia (BA). A coding enthusiast, he works in Python, Stata, Eviews, LaTeX, R, Julia, and Matlab.