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.
In this post we analyze consumer beliefs about the duration of the economic impact of the pandemic and present new evidence on their expected spending, income, debt delinquency, and employment outcomes, conditional on different scenarios for the future path of the pandemic. We find that between June and August respondents to the New York Fed Survey of Consumer Expectations (SCE) have grown less optimistic about the pandemic’s economic consequences ending in the near future and also about the likelihood of feeling comfortable in crowded places within the next three months. Although labor market expectations of respondents differ considerably across fairly extreme scenarios for the evolution of the COVID pandemic, the difference in other economic outcomes across scenarios appear relatively moderate on average. There is, however, substantial heterogeneity in these economic outcomes and some vulnerable groups (for example, lower income, non-white) appear considerably more exposed to the evolution of the pandemic.
In our previous post, we looked at the effects that the reopening of state economies across the United States has had on consumer spending. We found a significant effect of reopening, especially regarding spending in restaurants and bars as well as in the healthcare sector. In this companion post, we focus specifically on small businesses, using two different sources of high-frequency data, and we employ a methodology similar to that of our previous post to study the effects of reopening on small business activity along various dimensions. Our results indicate that, much like for consumer spending, reopenings had positive and significant effects in the short term on small business revenues, the number of active merchants, and the number of employees working in small businesses. It is important to stress that we are not expressing any views in this post on the normative question of whether, when, or how states should loosen or tighten restrictions aimed at controlling the COVID-19 pandemic.
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.
The Federal Reserve Bank of New York’s June business surveys show some signs of improvement in the regional economy. Following two months of unprecedented decline due to the coronavirus pandemic, indicators of business activity point to a slower pace of contraction in the service sector and signs of a rebound in the manufacturing sector. Even more encouraging, as the regional economy has begun to reopen, many businesses have started to recall workers who were laid off or put on furlough since the start of the pandemic. Some have even hired new workers. Moreover, businesses expect to recall even more workers over the next month. Looking ahead, firms have become increasingly optimistic that conditions will improve in the coming months.
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?
News headlines highlighting the loss of 26 million jobs (so far) underscore the massive shock that has hit the U.S. economy and the dislocation, hardship, and stress it has caused for so many American workers. But how accurately does this number actually capture the number of net job losses? In this post, we look at some of the statistical anomalies and quirks in the weekly claims series and offer a guide to interpreting these numbers. What we find is that the relationship between jobless claims and payroll employment for the month can vary substantially, depending on the nature, timing, and persistence of the disaster.
Indicators of regional business activity plunged to historic lows in early April, as efforts to slow the spread of the coronavirus kept many people at home and shut down large parts of the regional economy, according to the Federal Reserve Bank of New York’s two business surveys. The headline index for both surveys plummeted to nearly -80, well below any historical precedent including the depths of the Great Recession. About 60 percent of service firms and more than half of manufacturers reported at least a partial shutdown of their operations thus far. Layoffs were widespread, with half of all businesses surveyed reporting lower employment levels in early April.
It’s tempting to compare the economic fallout from the coronavirus pandemic to prior business cycle downturns, particularly the Great Recession. However, such comparisons may not be particularly apt—as evidenced by the unprecedented surge in initial jobless claims over the past three weeks. Recessions typically develop gradually over time, reflecting underlying economic and financial conditions, whereas the current economic situation developed suddenly as a consequence of a fast-moving global pandemic. A more appropriate comparison would be to a regional economy suffering the effects of a severe natural disaster, like Louisiana after Hurricane Katrina or Puerto Rico after Hurricane Maria. To illustrate this point, we track the recent path of unemployment claims in the United States, finding a much closer match with Louisiana after Katrina than the U.S. economy following the Great Recession.
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.