Logan T. Lewis

We evaluate high-frequency bill of lading data for its suitability in international trade research. These data offer many advantages over both other publicly accessible official trade data and confidential datasets, but they also have clear drawbacks. We provide a comprehensive overview for potential researchers to understand these strengths and weaknesses as these data become more widely available. Drawing on the strengths of the data, we analyze three aspects of trade during the COVID-19 pandemic. First, we show how the high-frequency data capture features of the within-month collapse of trade between the United States and India that are not observable in official monthly data. Second, we demonstrate how U.S. buyers shifted their purchases across suppliers over time during the recovery. And third, we show how the data can be used to measure vessel delivery bottlenecks in near real time.

Heavy tails play an important role in modern macroeconomics and international economics. Previous work often assumes a Pareto distribution for firm size, typically with a shape parameter approaching Zipf's law. This convenient approximation has dramatic consequences for the importance of large firms in the economy. But we show that a lognormal distribution, or better yet, a convolution of a lognormal and a non-Zipf Pareto distribution, provides a better description of the U.S. economy, using confidential Census Bureau data. These findings hold even far in the upper tail and suggest heterogeneous firm models should more systematically explore deviations from Zipf's law.

Services, which are less traded than goods, rose from 55 percent of world expenditure in 1970 to 75 percent in 2015. Using a Ricardian trade model incorporating endogenous structural change, we quantify how this substantial shift in consumption has affected trade. Without structural change, we find that the world trade to GDP ratio would be 13 percentage points higher by 2015, about half the boost delivered from declining trade costs. In addition, a world without structural change would have had about 40 percent greater welfare gains from the trade integration over the past four decades. Absent further reductions in trade costs, ongoing structural change implies that world trade as a share of GDP would eventually decline. Going forward, higher income countries gain relatively more from reducing services trade costs than from reducing goods trade costs.

U.S. imports and exports respond little to exchange rate changes in the short run. Firms' pricing behavior is thought central to explaining this response: if local prices do not respond to exchange rates, neither will trade flows. Sticky prices, strategic complementarities, and imported intermediates can reduce the trade response, and they are necessary to match newly available international micro price data. Using trade flow data, I test models designed to match these trade price data. Even with significant pricing frictions, the models imply a stronger trade response to exchange rates than found in the data. Moreover, despite substantial cross-sector heterogeneity, differential responses implied by the model find little to no support in the data.

This paper examines how nominal uncertainty affects the choice firms face to serve a foreign market through exports or to produce abroad as a multinational. I develop a two-country, stochastic general equilibrium model in which firms make production and pricing decisions in advance, and I consider its implications for the relative attractiveness of exporting and multinational production. I find that when multinational sales are priced in the local currency while exports are priced in the producer currency, destination volatility benefits exporters: during a foreign nominal contraction, the foreign exchange rate appreciates, causing exports to be relatively cheaper. Exporters gain non-linearly through demand, making profit convex in prices. As foreign volatility rises, the model implies that the home country should serve the foreign country relatively more through exports. I take this implication to bilateral U.S. data, using inflation volatility as a proxy for nominal volatility. Using sectoral data on sales by majority-owned foreign affiliates matched with U.S. exports, I find that higher inflation volatility is associated with a significantly lower ratio of multinational sales to total foreign sales.

Since Bernanke, Gertler and Watson (1997), a common view in the literature has been that systematic monetary policy responses to the inflation caused by oil price shocks are an important source of aggregate fluctuations in the U.S. economy, yet post-1987 data reveal no evidence of systematic policy responses to oil price shocks. Even prior to 1987, the Federal Reserve was not responding to the inflation triggered by oil price shocks, but rather to the oil price shocks directly, consistent with a preemptive move by the Federal Reserve to counteract potential inflationary pressures. There are indications that this response is poorly identified, however, and there is no evidence that this policy response in the pre-1987 period caused substantial fluctuations in the Federal Funds rate or in real output. One explanation of the low explanatory power of systematic policy responses to oil price shocks is that the Fed has been responding differently to different types of oil price shocks. Our analysis suggests that the traditional monetary policy reaction framework explored by BGW and incorporated in subsequent DSGE models should be replaced by DSGE models that take account of the endogeneity of the real price of oil and that allow policy responses to depend on the underlying causes of oil price shocks.

One of the most striking aspects of the recent recession is the collapse in international trade. This paper uses disaggregated data on U.S. imports and exports to shed light on the anatomy of this collapse. We find that the recent reduction in trade relative to overall economic activity is far larger than in previous downturns. Information on quantities and prices of both domestic absorption and imports reveals a 40% shortfall in imports, relative to what would be predicted by a simple import demand relationship. In a sample of imports and exports disaggregated at the 6-digit NAICS level, we find that sectors used as intermediate inputs experienced significantly higher percentage reductions in both imports and exports. We also find support for compositional effects: sectors with larger reductions in domestic output had larger drops in trade. By contrast, we find no support for the hypothesis that trade credit played a role in the recent trade collapse.

This paper explores the role of financial factors in the 2008-9 collapse of U.S. imports and exports. Using highly disaggregated international trade data, we examine whether the cross-sectoral variation in how much imports or exports fell during this episode can be explained by financial variables. To do this, we employ a wide variety of possible indicators, such as standard measures of trade credit and external finance dependence, proxies for shipping lags at the sector level, and shares of intra-firm trade in each sector. Overall, there is very little evidence that financial factors played a role in the collapse of U.S. trade.