Preferential trade agreements (PTAs) have been proliferating for the last twenty years. A large literature has studied various aspects of this phenomenon. Until recently, however, many large-N studies have paid only scant attention to variation across PTAs in terms of content and design. Our contribution to this literature is a new dataset on the design of trade agreements that is the most comprehensive in terms of both variables coded and agreements covered. We illustrate the dataset's usefulness in re-visiting the questions if and to what extent PTAs impact trade flows. The analysis shows that on average PTAs increase trade flows, but that this effect is largely driven by deep agreements. In addition, we provide evidence that provisions that tackle behind-the-border regulation matter for trade flows. The dataset's contribution is not limited to the PTA literature, however. Broader debates on topics such as institutional design and the legalization of international relations will also benefit from the novel data.

What has been the response of U.S. governors to the COVID-19 pandemic? In this research note, we explore the determinants of implementing stay-at-home orders, focusing on governors’ characteristics in the early stage of the pandemic. In our most conservative estimate, being a Democratic governor increased the probability of implementing a stay-at-home order by more than 50%. Moreover, we found that the probability of implementing a statewide stay-at-home order was about 40% more likely for governors without term limits than governors with term limits. We also found that Democratic governors and governors without term limits were significantly faster to adopt statewide orders than Republican governors and governors with term limits. There is evidence of politics as usual in these unusual times.

While increasing trade and foreign direct investment, international trade agreements create winners and losers. Our paper examines the distributional consequences of preferential trade agreements (PTAs) at the firm level. We contend that PTAs expand trade among the largest and most productive multinationals by lowering preferential tariffs. We examine data covering the near universe of US foreign direct investment and disaggregated tariff data from PTAs signed by the United States. Our results indicate that US preferential tariffs increase sales to the United States from the most competitive subsidiaries of multinational corporations operating in partner countries. We also find increases in market concentration in partner countries following preferential liberalization with the United States. By demonstrating that the gains from preferential liberalization are unevenly distributed across firms, we shed new light on the firm-level, economic sources of political mobilization over international trade and investment policies.

What is the effect of the COVID-19 pandemic on the 2020 US presidential election? Guided by a pre-analysis plan, we estimate the effect of COVID-19 cases and deaths on the change in county-level voting for Donald Trump between 2016 and 2020. To account for potential confounders, we include a large number of COVID-19-related controls as well as demographic and socioeconomic variables. Moreover, we instrument the numbers of cases and deaths with the share of workers employed in meat-processing factories to sharpen our identification strategy. We find that COVID-19 cases negatively affected Trump's vote share. The estimated effect appears strongest in urban counties, in states without stay-at-home orders, in swing states, and in states that Trump won in 2016. A simple counterfactual analysis suggests that Trump would likely have won re-election if COVID-19 cases had been 5 percent lower. We also find some evidence that COVID-19 incidence had a positive effect on voters' mobilization, helping Biden win the presidency.

Globalization and automation have contributed to deindustrialization and the loss of millions of manufacturing jobs, yielding important electoral implications across advanced democracies. Coupling insights from economic voting and social identity theory, we consider how different groups in society may construe manufacturing job losses in contrasting ways. We argue that deindustrialization threatens dominant group status, leading some white voters in affected localities to favor candidates they believe will address economic distress and defend racial hierarchy. Examining three US presidential elections, we find white voters were more likely to vote for Republican challengers where manufacturing layoffs were high, whereas Black voters in hard-hit localities were more likely to vote for Democrats. In survey data, white respondents, in contrast to people of color, associated local manufacturing job losses with obstacles to individual upward mobility and with broader American economic decline. Group-based identities help explain divergent political reactions to common economic shocks.