Federal Reserve Bank of San Francisco

Abstract This paper develops a multisector, multicountry model of international trade and profit shifting that embeds imperfect competition into Eaton and Kortum (2002)’s Ricardian trade model and allows markup distributions for both imports and exports to vary across sectors and countries. We first show theoretically how the gains from trade liberalization depend on the markup distribution for imported relative to exported goods. To bring the model to the data, we estimate both trade elasticities and a rich set of country- and industry-specific import demand elasticities for over 36,000 distinct sector-country pairs. We find that cross-country heterogeneities in export markups relative to import markups are a first-order determinant of the gains from trade and especially the welfare losses from tariffs. By flexibly taking heterogeneity in markups into account, these losses are up to three times larger for net exporters of high-markup products. We apply our model to the 2018–19 U.S.–China trade war and show that U.S. welfare losses from the tariff war are more than twice as high once markups and profit shifting are taken into account, whereas China benefited slightly overall.

BackgroundKimura disease is a rare inflammatory condition that typically manifests with subcutaneous nodules of the head and neck. This is the first documented case of intracardiac Kimura disease.Case SummaryA 57-year-old woman presented with a heart murmur and dyspnea. Echocardiography uncovered a 3-cm mass obstructing the right ventricular outflow tract. The mass was resected, and the pulmonary valve was replaced. Pathology yielded the diagnosis of Kimura disease.DiscussionTreatment of Kimura disease may include surgery, steroids, and radiation therapy. There is potential for disease recurrence.Take-Home MessagesThis is the first reported case of intracardiac Kimura disease, an inflammatory condition usually involving the head and neck. The working diagnosis for the right ventricular outflow tract mass was myxoma until final pathologic analysis was obtained. Our patient underwent surgical resection without steroids or radiation. Active surveillance with patient follow-up and surveillance echocardiography over 1 year demonstrated no recurrence.

ABSTRACT We propose a local projections (LPs)‐based difference‐in‐differences (DiD) approach that subsumes many of the recent solutions proposed in the literature to address possible biases arising from negative weighting. We combine LPs with a flexible “clean control” condition to define appropriate sets of treated and control units. Our proposed LP‐DiD estimator can be implemented with various weighting and normalization schemes for different target estimands, can be extended to include covariates or accommodate nonabsorbing treatment, and is simple and fast to implement. A simulation and two empirical applications demonstrate that the LP‐DiD estimator performs well in common applied settings.

We study the implications of trade uncertainty for reshoring, automation, and U.S. labor markets. Rising trade uncertainty creates incentives for firms to reduce exposure to foreign suppliers by moving production and distribution processes to domestic producers. However, we argue that reshoring does not necessarily bring jobs back to the home country or boost domestic wages, especially when firms have access to labor-substituting technologies such as automation. Automation improves labor productivity and facilitates reshoring, but it can also displace jobs. Furthermore, automation poses a threat that weakens the bargaining power of unskilled workers in wage negotiations, depressing their wages and raising the skill premium and wage inequality. Our model predictions are in line with industry-level empirical evidence.

Climate change threatens global food systems1, but the extent to which adaptation will reduce losses remains unknown and controversial2. Even within the well-studied context of US agriculture, some analyses argue that adaptation will be widespread and climate damages small3,4, whereas others conclude that adaptation will be limited and losses severe5,6. Scenario-based analyses indicate that adaptation should have notable consequences on global agricultural productivity7, 8–9, but there has been no systematic study of how extensively real-world producers actually adapt at the global scale. Here we empirically estimate the impact of global producer adaptations using longitudinal data on six staple crops spanning 12,658 regions, capturing two-thirds of global crop calories. We estimate that global production declines 5.5 × 1014 kcal annually per 1 °C global mean surface temperature (GMST) rise (120 kcal per person per day or 4.4% of recommended consumption per 1 °C; P < 0.001). We project that adaptation and income growth alleviate 23% of global losses in 2050 and 34% at the end of the century (6% and 12%, respectively; moderate-emissions scenario), but substantial residual losses remain for all staples except rice. In contrast to analyses of other outcomes that project the greatest damages to the global poor10,11, we find that global impacts are dominated by losses to modern-day breadbaskets with favourable climates and limited present adaptation, although losses in low-income regions losses are also substantial. These results indicate a scale of innovation, cropland expansion or further adaptation that might be necessary to ensure food security in a changing climate.