Research

We evaluate the quantitative effects of trade policy on the location of firms across space and over time. We develop a multi-country, multi-sector dynamic general-equilibrium trade and spatial model with forward-looking decisions of workers on where to supply labor, forward-looking decisions of firms on where to locate produc-tion, endogenous capital structure accumulation, and trade in intermediate goods with sectoral linkages. We bring the model to data using trade, production, and data on firm demographics across sector and locations. We use the model to study if trade protectionism can revert the declining trend in the U.S. manufacturing em-ployment and firms; and its impact on the location of production across space and over time. We feed into the model the raise in import tariffs between the U.S. and its major trade partners in the year 2018. We find that these changes in trade policy can result in a persistent increase on manufacturing employment and firms. However, these effects do not revert the long run decline in manufacturing employment and firms. Importantly, the relocation of production comes at the cost of higher prices, lower welfare for households, and heterogeneous effects on firm entry across space.

Economists often point to the superiority of cash transfers over in-kind assistance as a means of redistribution because recipients can choose how to use these resources. However, among the trillions of dollars of annual U.S. transfers, redistribution is mostly in-kind. We conducted a survey experiment—using a choice between a cash transfer and a transfer that could be spent only on a bundle of “necessities”—to help explain why. We show that the general population overwhelmingly prefers in-kind redistribution, largely for paternalistic reasons. This preference was common to a majority of virtually all segments of the general population, though not to a sample of educational elites. A persuasion treatment on the value of choice, while impactful, did not change this overall preference for in-kind. For an equal-sized program, below-poverty respondents preferred receiving cash. But they appeared to prefer the larger in-kind transfer to the smaller cash transfer that the general population was willing to support. This suggests that an in-kind transfer may be preferable to both recipients and the general population.

We uncover political dynamics that reward and reinforce increases in US health spending by studying the passage of the 2003 Medicare Modernization (MMA). We focus on a provision added to the MMA, which allowed hospitals to apply for temporary Medicare payment increases. Hospitals represented by members of Congress who voted ‘Yea’ to the MMA were more likely to receive payment increases. The payment increases raised local health spending and led to suggestive increases in health sector employment. Members of Congress representing hospitals that got a payment increase received large increases in campaign contributions before and after the program was extended.

Using city-level crime data for six major U.S. cities from Jan 21 to May 30 2020, we document an approximately 20% average reduction in reported crimes during March, simultaneous with sharp economic downturn and heightened social distancing restrictions. We also decompose trends by crime type and location. Our key findings are:

• Since the steep 20% crime drop in March, overall rates have steadily risen but remain below pre-pandemic levels on average.
• Crimes committed in commercial and street settings (as opposed to residential areas) account for most of the drop in crimes.
• Violent crimes decline in similar proportion to nonviolent crimes.
• Though larcenies fall by one-third, other kinds of theft like burglary and auto theft rise.

Caveats to our findings include the possibility of simultaneous changes in reporting and policing activities.

Climate policies vary widely across countries, with some countries imposing stringent emissions policies and others doing very little. When climate policies vary across countries, energy- intensive industries have an incentive to relocate to places with few or no emissions restrictions, an effect known as leakage. Relocated industries would continue to pollute but would be operating in a less desirable location. We consider solutions to the leakage problem in a simple setting where one region of the world imposes a climate policy and the rest of the world is passive. We solve the model analytically and also calibrate and simulate the model. Our model and analysis imply: (1) optimal climate policies tax both the supply of fossil fuels and the demand for fossil fuels; (2) on the demand side, absent administrative costs, optimal policies would tax both the use of fossil fuels in domestic production and the domestic consumption of goods created with fossil fuels, but with the tax rate on production lower due to leakage; (3) taxing only production (on the demand side), however, would be substantially simpler, and almost as effective as taxing both production and consumption, because it would avoid the need for border adjustments on imports of goods; (4) the effectiveness of the latter strategy depends on a low foreign elasticity of energy supply, which means that forming a taxing coalition to ensure a low foreign elasticity of energy supply can act as a substitute for border adjustments on goods

Nursing homes and other long-term care facilities account for a disproportionate share of COVID-19 cases and fatalities worldwide. Outbreaks in U.S. nursing homes have persisted despite nationwide visitor restrictions beginning in mid-March. An early report issued by the Centers for Disease Control and Prevention identified staff members working in multiple nursing homes as a likely source of spread from the Life Care Center in Kirkland, Washington to other skilled nursing facilities. The full extent of staff connections between nursing homes—and the role these connections serve in spreading a highly contagious respiratory infection—is currently unknown given the lack of centralized data on cross-facility employment. We perform the first large-scale analysis of nursing home connections via shared staff and contractors using device-level geolocation data from 50 million smartphones, and find that 5.1 percent of smartphone users who visit a nursing home for at least one hour also visit another facility during our 11-week study period—even after visitor restrictions were imposed. We construct network measures of connectedness and estimate that nursing homes, on average, share connections with 7 other facilities. Controlling for demographic and other factors, a home’s staff-network connections and its centrality within the greater network strongly predict COVID-19 cases. Traditional federal regulatory metrics of nursing home quality are unimportant in predicting outbreaks, consistent with recent research. Multivariate regressions comparing demographically and geographically similar nursing homes suggest that 49 percent of COVID cases among nursing home residents are attributable to staff movement between facilities.

Recently in economics there has been discussion of how to increase diversity in the profession and how to improve the work life of diverse peoples. We conducted surveys and interviews with Black, Latinx and Native American people. These groups have long been underrepresented in the economics profession. Participants were at various stages along the economics career trajectory, or on the trajectory no longer, and used their lived experience to reflect on what helps and hurts underrepresented minorities in economics. We heard a few consistent themes: bias, hostile climate, and the lack of information and good mentoring among them. Respondents' insights and experience point toward action steps that you can take today to increase the presence and improve the work life of underrepresented minorities in the economics profession.

We propose a method for identifying exposure to changes in trade policy based on asset prices that has several advantages over standard measures: it encompasses all avenues of exposure, it is natively firm-level, it yields estimates for both goods and service producers, and it can be used to study reductions in difficult-to-quantify non-tariff barriers in a way that controls naturally for broader macroeconomic shocks. Applying our method to two well-studied US trade liberalizations provides new insight into service sector responses to trade liberalizations as well as dramatically different responses among small versus large firms, even within narrow industries.

The onset of the Covid-19 pandemic has led to a dramatic reduction in employment and hours worked in the US economy. The decline can be measured using conventional data sources such as the Current Population Survey and in the number of individuals filing for unemployment. However, given the unprecedented pace of the ongoing changes to labor market conditions, detailed, up-to-date, high frequency data on wages, employment, and hours of work is needed. Such data can provide insights into how firms and workers have been affected by the pandemic so far, and how those effects differ by type of firm and worker wage level. It can also be used to detail – in real time – the state of the labor market.

We study the role of European Immigration on local and aggregate economic growth in the United States between 1880 and 1920. We employ a big data approach and link, at the individual-level, information from the Population Census, the universe of patents and millions of historical immigration records. We find that immigrants were more prolific innovators than natives, and document large differences in innovation potential across nationalities and regions in the United States. To measure the importance of immigrants for the creation of new ideas and economic growth, we develop a new spatial model of growth through dissemination of knowledge and workers’ mobility. The model allows us to use our micro and regional empirical findings to measure immigrants’ innovation human capital and the degree of knowledge diffusion which regulates scale effects. We quantitatively analyze the effects of imposing major immigration restrictions on American economic growth in the 19th and early 20th century. We find large, accumulating, losses from these restrictions. Both the scale effects and the exclusion of high-human capital immigrants contribute significantly to these losses.

The Paycheck Protection Program (PPP) extended 669 billion dollars of forgivable loans in an unprecedented effort to support small businesses affected by the COVID-19 crisis. This paper provides evidence that information frictions and the “first-come, first-served” design of the PPP program skewed its resources towards larger firms and may have permanently reduced its effectiveness. Using new daily survey data on small businesses in the U.S., we show that the smallest businesses were less aware of the PPP and less likely to apply. If they did apply, the smallest businesses applied later, faced longer processing times, and were less likely to have their application approved. These frictions may have mattered, as businesses that received aid report fewer layoffs, higher employment, and improved expectations about the future.

This note provides new evidence on how small business owners have been impacted by COVID-19, and how these effects have evolved since the passage of the CARES Act. As part of a broader and ongoing project, we collected survey data from more than 8,000 small business owners in the U.S. from March 28th, one day after the CARES Act was passed, through April 20th. The data include information on firm size, layoffs, beliefs about the future prospects of their businesses, as well as awareness of existing government relief programs. We provide three main findings. First, by the time the CARES Act was passed, surveyed small business owners were already severely impacted by COVID-19-related disruptions: 60% had already laid off at least one worker. Second, business owners’ expectations about the future are negative and have deteriorated throughout our study period, with 37% of respondents in the first week reporting that they did not expect to recover within 2 years, growing to 46% by the last week. Third, the smallest businesses had the least awareness of government assistance programs, the slowest growth in awareness after the passage of the CARES Act, and never caught up with larger businesses. The last finding indicates that small businesses may have missed out on initial Paycheck Protection Program funds because of low baseline awareness and differential access to information relative to larger firms.

The coronavirus disease 2019 (COVID-19) pandemic is leading to social (physical) distancing policies worldwide, including in the USA. Some of the first actions taken by governments are the closing of schools. The evidence that mandatory school closures reduce the number of cases and, ultimately, mortality comes from experience with influenza or from models that do not include the effect of school closure on the health-care labour force. The potential benefits from school closures need to be weighed against costs of health-care worker absenteeism associated with additional child-care obligations. In this study, we aimed to measure child-care obligations for US health-care workers arising from school closures when these are used as a social distancing measure. We then assessed how important the contribution of health-care workers would have to be in reducing mortality for their absenteeism due to child-care obligations to undo the benefits of school closures in reducing the number of cases.

We estimated that, combined with reasonable parameters for COVID-19 such as a 15·0% case reduction from school closings and 2·0% baseline mortality rate, a 15·0% decrease in the health-care labour force would need to decrease the survival probability per percent health-care worker lost by 17·6% for a school closure to increase cumulative mortality. Our model estimates that if the infection mortality rate of COVID-19 increases from 2·00% to 2·35% when the health-care workforce declines by 15·0%, school closures could lead to a greater number of deaths than they prevent.

School closures come with many trade-offs, and can create unintended child-care obligations. Our results suggest that the potential contagion prevention from school closures needs to be carefully weighted with the potential loss of health-care workers from the standpoint of reducing cumulative mortality due to COVID-19, in the absence of mitigating measures.

As children reach adolescence, peer interactions become increasingly central to their development, whereas the direct influence of parents wanes. Nevertheless, parents may continue to exert leverage by shaping their children's peer groups. We study interactions of parenting style and peer effects in a model where children's skill accumulation depends on both parental inputs and peers, and where parents can affect the peer group by restricting who their children can interact with. We estimate the model and show that it can capture empirical patterns regarding the interaction of peer characteristics, parental behavior, and skill accumulation among US high school students. We use the estimated model for policy simulations. We find that interventions (e.g., busing) that move children to a more favorable neighborhood have large effects but lose impact when they are scaled up because parents' equilibrium responses push against successful integration with the new peer group.