This paper provides evidence on the consumption effects of trade shocks by exploiting changes in US and Chinese trade policy between 2017 and 2018. The analysis uses a unique data set with the universe of new auto sales at the US county level, at a monthly frequency, and a simple difference-in-difference approach to measure the effect of changes in trade policy on county-level consumption. As a lower bound, I estimate the elasticity of consumption growth to Chinese retaliatory tariffs to be around -1. This implies that counties in the upper quartile of the retaliatory-tariff distribution experienced a 3.8 percentage point decline in consumption growth. I further show that the consumption response corresponds with a decline in employment growth. These results suggest that Chinese retaliation is leading to concentrated welfare losses in the US.

This paper develops a dynamic model of trade and growth that we use to study how openness affects economic growth. In our model, heterogeneous firms choose to either produce with their existing technology or search within the domestic economy to adopt a better technology. These choices determine the productivity distribution from which firms can acquire new technologies and, hence, the equilibrium rate of technological diffusion. Opening to trade changes the relative profitability between high and low productivity firms through expanded export opportunities and foreign competition. These reallocation effects change the timing of when firms adopt new technologies and, thus, the rate of technological diffusion. This results in growth effects from openness via within-firm productivity improvements.

Abstract: Quantitative results from a large class of international trade models depend critically on the elasticity of trade with respect to trade frictions. We develop a simulated method of moments estimator to estimate this elasticity from disaggregate price and trade-flow data using the Ricardian model. We motivate our estimator by proving that the estimator developed in Eaton and Kortum (2002) is biased in any finite sample. We quantitatively show that the bias is severe and that the data requirements necessary to eliminate it in practice are extreme. Applying our estimator to new disaggregate price and trade-flow data for 123 countries in the year 2004 yields a trade elasticity of roughly four, nearly fifty percent lower than Eaton and Kortum's (2002) approach. This difference doubles the welfare gains from international trade

We argue that the welfare gains from trade in new models with micro-level margins exceed those in frameworks without these margins. Theoretically, we show that for fixed trade elasticity, different models predict identical trade flows, but different patterns of micro-level price variation. Thus, given data on trade flows and micro-level prices, different models have different implied trade elasticities and welfare gains. Empirically, models with extensive or variable mark-up margins yield significantly larger welfare gains. The results are robust to incorporating into the estimation moment conditions that use trade-flow and tariff data, which imply a common trade elasticity across models.

Common wisdom dictates that uncertainty impedes trade--we show that uncertainty can fuel more trade in a simple general equilibrium trade model with information frictions. In equilibrium, increases in uncertainty increase both the mean and the variance in returns to exporting implying that trade can increase or decrease with uncertainty depending on preferences. Under general conditions on preferences, we characterize the importance of these forces using a sufficient statistics approach. Higher uncertainty leads to increases in trade because agents receive improved terms of trade, particularly in states of nature where consumption is most valuable. Trade creates value, in part, by offering a mechanism to share risk and risk sharing is most effective when both parties are uninformed.

Common wisdom holds that uncertainty impedes trade, yet we show that uncertainty can fuel more trade in a simple general equilibrium trade model with information frictions. In equilibrium, increases in uncertainty increase both the mean and variance in returns to exporting. This implies that trade can increase or decrease with uncertainty, depending on preferences. Under general conditions on preferences, we characterize the importance of these forces using a sufficient statistics approach. Higher uncertainty leads to increases in trade because agents receive improved terms of trade, particularly in states of nature in which consumption is most valuable. Trade creates value, in part, by offering a mechanism for risk sharing, and risk sharing is most effective when both parties are uninformed.

This paper studies the dynamics of international trade flows at business cycle frequencies. We show that introducing dynamic considerations into an otherwise standard model of trade can account for several puzzling features of trade flows at business cycle frequencies. Our insight is that because international trade is time-intensive, variation in the rate at which agents are willing to substitute across time affects how trade volumes respond to changes in output and prices. We formalize this idea and calibrate our model to match key features of U.S. data. We find that, in contrast to standard static models of international trade, our model is quantitatively consistent with salient features of U.S. cyclical import fluctuations. We also find that our model accounts for two-thirds of the peak-to-trough decline in imports during the 2008-2009 recession.