Understanding the Racial and Income Gap in Commuting for Work Following COVID‑19
The introduction of numerous social distancing policies across the United States, combined with voluntary pullbacks in activity as responses to the COVID-19 outbreak, resulted in differences emerging in the types of work that were done from home and those that were not. Workers at businesses more likely to require in-person work—for example, some, but not all, workers in healthcare, retail, agriculture and construction—continued to come in on a regular basis. In contrast, workers in many other businesses, such as IT and finance, were generally better able to switch to working from home rather than commuting daily to work. In this post, we aim to understand whether following the onset of the pandemic there was a wedge in the incidence of commuting for work across income and race. And how did this difference, if any, change as the economy slowly recovered? We take advantage of a unique data source, SafeGraph cell phone data, to identify workers who continued to commute to work in low income versus higher income and majority-minority (MM) versus other counties.
Job Seekers’ Beliefs and the Causes of Long‑Term Unemployment
In addition to its terrible human toll, the COVID-19 pandemic has also caused massive disruption in labor markets. In the United States alone, more than 25 million people lost their jobs during the first wave of the pandemic. While many have returned to work since then, a large number have remained unemployed for a prolonged period of time. The number of long-term unemployed (defined as those jobless for twenty-seven weeks or longer) has surged from 1.1 million to almost 4 million. An important concern is that the long-term unemployed face worse employment prospects, but prior work has provided no consensus on what drives this decline in employment prospects. This post discusses new findings using data on elicited beliefs of unemployed job seekers to uncover the forces driving long-term unemployment.
The Regional Economy during the Pandemic
The New York-Northern New Jersey region experienced an unprecedented downturn earlier this year, one more severe than that of the nation, and the region is still struggling to make up the ground that was lost. That is the key takeaway at an economic press briefing held today by the New York Fed examining economic conditions during the pandemic in the Federal Reserve’s Second District. Despite the substantial recovery so far, business activity, consumer spending, and employment are all still well below pre-pandemic levels in much of the region, and fiscal pressures are mounting for state and local governments. Importantly, job losses among lower-income workers and people of color have been particularly consequential. The pace of recovery was already slowing in the region before the most recent surge in coronavirus cases, and we are now seeing signs of renewed weakening as we enter the winter.
What’s Up with the Phillips Curve?
U.S. inflation used to rise during economic booms, as businesses charged higher prices to cope with increases in wages and other costs. When the economy cooled and joblessness rose, inflation declined. This pattern changed around 1990. Since then, U.S. inflation has been remarkably stable, even though economic activity and unemployment have continued to fluctuate. For example, during the Great Recession unemployment reached 10 percent, but inflation barely dipped below 1 percent. More recently, even with unemployment as low as 3.5 percent, inflation remained stuck under 2 percent. What explains the emergence of this disconnect between inflation and unemployment? This is the question we address in “What’s Up with the Phillips Curve?,” published recently in Brookings Papers on Economic Activity.
Delaying College During the Pandemic Can Be Costly
Many students are reconsidering their decision to go to college in the fall due to the coronavirus pandemic. Indeed, college enrollment is expected to be down sharply as a growing number of would-be college students consider taking a gap year. In part, this pullback reflects concerns about health and safety if colleges resume in-person classes, or missing out on the “college experience” if classes are held online. In addition, poor labor market prospects due to staggeringly high unemployment may be leading some to conclude that college is no longer worth it in this economic environment. In this post, we provide an economic perspective on going to college during the pandemic. Perhaps surprisingly, we find that the return to college actually increases, largely because the opportunity cost of attending school has declined. Furthermore, we show there are sizeable hidden costs to delaying college that erode the value of a college degree, even in the current economic environment. In fact, we estimate that taking a gap year reduces the return to college by a quarter and can cost tens of thousands of dollars in lost lifetime earnings.
Job Training Mismatch and the COVID‑19 Recovery: A Cautionary Note from the Great Recession
Displaced workers have been shown to endure persistent losses years beyond their initial job separation events. These losses are especially amplified during recessions. (1) One explanation for greater persistence in downturns relative to booms, is that firms and industries on the margin of structural change permanently shift the types of tasks and occupations demanded after a large negative shock (Aghion et al. (2005)), but these new occupations do not match the stock of human capital held by those currently displaced. In response to COVID-19, firms with products and services that complement social-distancing (like Amazon distribution centers) may continue hiring during and beyond the recovery, while workers displaced from higher risk industries with more stagnant demand (for example, airport personnel, local retail clerks) are left to adjust to unfamiliar job opportunities. As some industries reopen gradually while others remain stunted, what role might workforce development programs have in bridging the skill gap such that displaced workers are best prepared for this new reality of work?
How Does Credit Access Affect Job‑Search Outcomes and Sorting?
Job Ladders and Careers
Workers in the United States experience vast differences in lifetime earnings. Individuals in the 90th percentile earn around seven times more than those in the 10th percentile, and those in the top percentile earn almost twenty times more. A large share of these differences arise over the course of people’s careers. What accounts for these vastly different outcomes in the labor market? Why do some individuals experience much steeper earnings profiles than others? Previous research has shown that the “job ladder”—in which workers obtain large pay increases when they switch to better jobs or when firms want to poach them—is important for wage growth. In this post, we investigate how job ladders differ across workers.
How Has Germany’s Economy Been Affected by the Recent Surge in Immigration?
Germany emerged as a leading destination for immigration around 2011, as the country’s labor market improved while unemployment climbed elsewhere in the European Union. A second wave began in 2015, with refugees from the Middle East adding to already heavy inflows from Eastern Europe. The demographic consequences of the surge in immigration include a renewed rise in Germany’s population and the stabilization of the country’s median age. The macroeconomic consequences are hard to measure but look promising, since per capita income growth has held up and unemployment has declined. Data on labor-market outcomes specific to immigrants are similarly favorable through 2015, but challenges are evident in how well the economy is adjusting to the second immigration wave.
Expecting the Unexpected: Job Losses and Household Spending
Unemployment risk constitutes one of the most significant sources of uncertainty facing workers in the United States. A large body of work has carefully documented that job loss may have long-term effects on one’s career, depressing earnings by as much as 20 percent after fifteen to twenty years. Given the severity of a job loss for earnings, an important question is how much such an event affects one’s standard of living during a spell of unemployment. This blog post explores how unemployment and expectations of job loss interact to affect household spending.