Figure 1: TFP dispersion, 1987–2021

TFP dispersion across firms rises sharply during recessions. The 90th–10th percentile spread within industries widens in each of the four recessions in the sample, consistent with the model's prediction that credit rationing intensifies when aggregate conditions deteriorate.

Cyclical Fluctuations, Financial Frictions, and Productivity Differences across Firms

Within narrowly defined industries, the most productive firms produce far more than the least productive from the same inputs, and this dispersion widens in downturns. We build a tractable model in which financial frictions—adverse selection and moral hazard—make firms sort endogenously into lenders, strategic defaulters, and producers. As credit conditions vary, the resulting misallocation gives aggregate total factor productivity (TFP) an endogenous component that accounts for about 30 percent of the variance of TFP at business-cycle frequencies, a third of it from strategic default. We show that our tractable model can match key features of the observed distribution of productivity across firms and its co-movement with output growth and credit conditions in the data.

Figure 1: The Flaaen–Pierce design — tariff and TFP gaps between more- and less-exposed industries, 2013–2022, relative to 2017

Industries more exposed to the 2018–19 tariffs break from their pre-war productivity trend. The top row shows the gap in tariffs between more- and less-exposed industries, the bottom row the gap in total factor productivity relative to 2017, with 90 percent bands. The left column compares industries across the interquartile range of exposure, the right column the top against the bottom quartile.

Tariffs, Productivity, and the Welfare Effects of Protectionism

In 2018–19 the United States raised tariffs on more than $350 billion of imports. I ask how these tariffs affected the productivity of the targeted manufacturing industries and what that implies for welfare. The added tariff was nearly uniform, 25 percent on most covered goods, but the share of an industry’s home market supplied by newly tariffed imports differed widely across industries. Using a difference-in-differences design, I find that the more exposed industries broke from their pre-war productivity trend relative to the less exposed ones, with total factor productivity about 2 percent lower by 2019 for an interquartile difference in exposure. To draw the welfare implications, I extend the workhorse macro-trade model of Ghironi and Melitz (2005) to sectors with different exposure to the tariffs. The tariffs shift production toward less productive firms, but the resulting gap in measured productivity falls far short of the evidence. Matching it requires an exogenous technology shock that can reverse the welfare gain from the terms-of-trade improvement generated by the tariffs.