Research Database

Workers are unequal in the face of the COVID-19 pandemic: Those who work in essential sectors face higher health risk whereas those in non-essential social-consumption sectors face greater economic risk. We study how these health and economic risks cascade into other sectors through supply chains and demand linkages. In the U.S., we find the cascading effects account for about 25-30% of the exposure to both risks. The cascading effect increases the health risk faced by workers in the transportation and retail sectors, and it increases the economic risk faced by workers in the textile and petroleum sectors. We provide sectoral estimates of the health and economic risk for 42 other countries in an online interactive document.

Does job loss cause less economic damage if your parents are higher-income, and what are the implications for intergenerational mobility? In this paper we show that following a layoff, adult children born to parents in the bottom 20% of the income distribution have almost double the unemployment compared with those born to parents in the top 20%, with 118% higher present discounted value losses in earnings. Next, we show that these disparate impacts of job loss have important implications for inequality and intergenerational mobility. They increase the 80:20 income inequality ratio for those impacted by 8% and increase the rank-rank coefficient by 34%, implying large reductions in intergenerational mobility. In a simulation based on our main results, we show that the age 40 rank-rank correlation is 3.9% higher due to the disparate impact and incidence of job loss over the preceding decade. In the last part of the paper, we explore mechanisms and show that "baked in" advantages play an important role in explaining these differences.

There have been growing concerns about long-haulers or individuals with long-term COVID-19 health complications (long-haul COVID). While the medical field has been investigating the health complications, there has been limited research on the relationship between long-haul COVID and labor market outcomes. To investigate this relationship, I used the University of Southern California Understanding America Study COVID-19 longitudinal survey to provide a snapshot of mid-2021. I first find about 24.1% of individuals who have had COVID are long-haulers and 25.9% of long-haulers reported that their long-haul COVID affected employment or work hours. I then find that a majority of these affected long-haulers remained employed and in same employment type. But I find that their mean change in work hours and paycheck declined. Afterwards, I tested whether long-haul COVID is associated with negative changes in labor market outcomes. When I combined long-haulers who reported that their health complications did or did not affect work, I failed to find that long-haulers are less likely to be employed relative to individuals without prior COVID infection. But, when I discern long-haulers by whether long-haul COVID affected work, I find that long-haulers who reported long-haul COVID affected work are 10 percentage points less likely to be employed and, on average, work 50% fewer hours than individuals without prior COVID infection. In contrast, I failed to find evidence that affected long-haulers receive a lower paycheck earning relative to individuals without prior COVID infection. Lastly, when comparing these affected long-haulers against similar individuals, I find evidence that they are more impacted in their employed status and work hours. Due to limitations, future data collection and research would provide a more robust picture.

We build a New Keynesian business-cycle model with rich household heterogeneity. In the model, systematic monetary stabilization policy affects the distribution of income, income risks, and the demand for funds and supply of assets: the demand, because matching frictions render idiosyncratic labor-market risk endogenous; the supply, because markups, adjustment costs, and the tax system mean that the average profitability of firms is endogenous. Disagreement about systematic monetary stabilization policy is pronounced. The wealth-rich or retired tend to favor inflation targeting. The wealth-poor working class, instead, favors unemployment-centric policy. One- and two-agent alternatives can show unanimous disapproval of inflation-centric policy, instead. We highlight how the political support for inflation-centric policy depends on wage setting, the tax system, and the portfolio that households have.

While the savings of retired singles tend to fall with age, those of retired couples tend to rise. We estimate a rich model of retired singles and couples with bequest motives and uncertain longevity and medical expenses. Our estimates imply that while medical expenses are an important driver of the savings of middle-income singles, bequest motives matter for couples and high-income singles, and generate transfers to non-spousal heirs whenever a household member dies. The interaction of medical expenses and bequest motives is a crucial determinant of savings for all retirees. Hence, to understand savings, it is important to model household structure, medical expenses, and bequest motives.

Tracking human activity in real time and at fine spatial scale is particularly valuable during episodes such as the COVID-19 pandemic. In this paper, we discuss the suitability of smartphone data for quantifying movement and social contact. We show that these data cover broad sections of the US population and exhibit movement patterns similar to conventional survey data. We develop and make publicly available a location exposure index that summarizes county-to-county movements and a device exposure index that quantifies social contact within venues. We use these indices to document how pandemic-induced reductions in activity vary across people and places.

For whom has earnings risk changed, and why? To answer these questions, we develop a filtering method that estimates parameters of an income process and recovers persistent and temporary earnings for every individual at every point in time. Our estimation flexibly allows for first and second moments of shocks to depend upon observables as well as spells of zero earnings (i.e., unemployment) and easily integrates into theoretical models. We apply our filter to a unique linkage of 23.5m SSA-CPS records. We first demonstrate that our earnings-based filter successfully captures observable shocks in the SSA-CPS data, such as job switching and layoffs. We then show that despite a decline in overall earnings risk since the 1980s, persistent earnings risk has risen for both employed and unemployed workers, while temporary earnings risk declined. Furthermore, the size of persistent earnings losses associated with full year unemployment has increased by 50%. Using geography, education, and occupation information in the SSA-CPS records, we refute hypotheses related to declining employment prospects among routine and low-skill workers as well as spatial theories related to the decline of the Rust-Belt. We show that rising persistent earnings risk is concentrated among high-skill workers and related to technology adoption. Lastly, we find that rising persistent earnings risk while employed (unemployed) leads to welfare losses equivalent to 1.8% (0.7%) of lifetime consumption, and larger persistent earnings losses while unemployed lead to a 3.3% welfare loss.

We offer causal evidence of higher returns to experience in big cities. Exploiting a natural experiment that settled refugees across labor markets in Denmark between 1986 and 1998, we find that refugees initially earn similar wages across locations. However, those placed in Copenhagen exhibit 35% faster wage growth with each additional year of experience. Faster sorting of workers towards the type of establishments, occupations, and industries typically found in cities accounts for the vast majority of this urban wage growth premium.

This paper uses a unique large-scale survey administered in April 2020 to assess disparities on several dimensions of wellbeing under rising COVID-19 infections and mitigation restrictions in the US. The survey includes three modules designed to assess different dimensions of well-being in parallel: physical health, mental and social health, and economic and financial security. The survey is unique among early COVID-19 data efforts in that provides insight on diverse dimensions of wellbeing and for subnational geographies. I find dramatic declines in wellbeing from pre-COVID baseline measures across both people and places. Place-level variation is not well explained by local characteristics that either precede or coincide with the pandemic. Analysis by demographic groups also shows large and unequal declines in wellbeing in the COVID era. Hispanic, younger, and lower-earning individuals all faced disproportionately worsening economic conditions, as did those with school-aged children. I conclude that place-based relief policies are unlikely to be efficient relative to support targeted to the neediest individuals. I also find that individual COVID-19 exposure and risk show concerning relationships with employment, protective behavior, and mental health. Those with direct COVID-19 exposure through their households continue working similar hours to others, and those with recent fever symptoms or elevated risk for COVID complications are not reducing their work hours or taking additional precautions, despite negative mental health status changes indicating concern. These findings suggest that some support policies might be directly targeted to households with confirmed infections or heighted risk.

We document new facts about risk in male wages and earnings, household earnings, and pre- and post-tax income in the Netherlands and the United States. We find that, in both countries, earnings display important deviations from the typical assumptions of linearity and normality. Individual-level male wage and earnings risk is relatively high at the beginning and end of the working life, and for those in the lower and upper parts of the income distribution. Hours are the main driver of the negative skewness and, to a lesser extent, the high kurtosis of earnings changes. Even though we find no evidence of added-worker effects, the presence of spousal earnings reduces the variability of household income compared to that of male earnings. In the Netherlands, government transfers are a major source of insurance, substantially reducing the standard deviation, negative skewness, and kurtosis of income changes. In the U.S. the role of family insurance is much larger than in the Netherlands. Family and government insurance reduce, but do not eliminate nonlinearities in household disposable income by age and previous earnings in either country.