The pandemic struck the New York-Northern New Jersey region early and hard, and the economy is still struggling to recover nearly two years later. Indeed, employment fell by 20 percent in New York City as the pandemic took hold, a significantly sharper decline than for the nation as a whole, and the rest of the region wasn’t far behind, creating a much larger hole to dig out of than other parts of the country. While the region saw significant growth as the economy began to heal, growth has slowed noticeably, and job shortfalls—that is, the amount by which employment remains below pre-pandemic levels—are some of the largest in the nation. Among major metro areas, job shortfalls in New York City, Buffalo, and Syracuse rank among the five worst in the country. Thus, despite much progress, the region is struggling to recover from the pandemic recession. By contrast, employment has rebounded above pre-pandemic levels in Puerto Rico, reaching a five-year high.
This post concludes a three-part series exploring the gender, racial, and educational disparities of debt outcomes of college students. In the previous two posts, we examined how debt holding and delinquency behaviors vary among students of different race and gender, breaking up our analyses by level of degree pursued by the student. We found that Black and Hispanic students were less likely than white students to take on credit card debt, auto loans, and mortgage debt, but experienced higher rates of delinquency in each of these debt areas by the age of 30. In contrast, Black students were more likely to take out student debt and both Black and Hispanic students experienced higher rates of student debt delinquency. We found that Asian students broadly followed reverse patterns from Black and Hispanic students by age 30. They were more likely than white students to acquire mortgages and less likely to hold student debt, but their delinquency patterns were in general similar to those of white students. Women were less likely to hold an auto loan or mortgage and more likely to hold student debt by age 30, and in most cases their delinquency outcomes were indistinguishable from males. In this post, we seek to understand mechanisms behind these racial and gender disparities and examine the role of educational attainment in explaining these patterns.
Household debt has risen markedly since 2013 and amounts to more than $15 trillion dollars. While the aggregate volume of household debt has been well-documented, literature on the gender, racial and education distribution of debt is lacking, largely because of an absence of adequate data that combine debt, demographic, and education information. In a three-part series beginning with this post, we seek to bridge this gap. In this first post, we focus on differences in debt holding behavior across race and gender. Specifically, we explore gender and racial disparities in different types of household debt and delinquencies—for auto, mortgage, credit card, and student loans—while distinguishing between students pursuing associate’s (AA) and bachelor’s (BA) degrees. In the second post in this series, we investigate gender and racial disparities in delinquencies across these various kinds of consumer debt. We close with a third post where we try to understand some of the mechanisms behind differences in debt and delinquencies across gender and race.
As the economy continues to recover from the pandemic recession, many businesses are struggling to keep up with surging demand amid widespread supply shortages and delays. While a rare phenomenon before the pandemic, supply chain disruptions have become increasingly common, with transportation of goods becoming especially tricky due to myriad issues such as clogged ports and difficulty finding truck drivers. Indeed, such supply disruptions are expected to continue into next year. Our October regional business surveys asked firms to what extent, if any, they are being affected by supply problems and what measures they have taken in response. Difficulty obtaining supplies was nearly universal among survey respondents, affecting about 80 percent of service firms and 95 percent of manufacturers. A large share of businesses in the region have responded to the disruptions by increasing their selling prices and scaling back their operations.
As we mourn the tragic losses of the 9/11 attacks twenty years on, we thought it would be appropriate to re-examine the remarkable resilience New York City’s economy has shown over the years—a resilience that is once again being tested by the ongoing COVID-19 pandemic. In this Liberty Street Economics post, we look at how Lower Manhattan, in particular, has changed since that tragedy on a number of dimensions, and use that as a framework to think about how the city might change as a result of the COVID pandemic.
Business activity increased in the region’s manufacturing sector in recent weeks but continued to decline in the region’s service sector, continuing a divergent trend seen over the past several months, according to the Federal Reserve Bank of New York’s February regional business surveys. Looking ahead, however, businesses expressed widespread optimism about the near-term outlook, with service firms increasingly confident that the business climate will be better in six months. The surveys also found that supply disruptions were widespread, with manufacturing firms reporting longer delivery times and rising input costs, a likely consequence of such disruptions. Many firms also noted that minimum wage hikes implemented in January in both New York and New Jersey had affected their employment or compensation decisions.
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.
The New York Fed today unveiled a set of charts that track COVID-19 cases in the Federal Reserve’s Second District, which includes New York, Northern New Jersey, Fairfield County Connecticut, Puerto Rico, and the U.S. Virgin Islands. These charts, available in the Indicators section of our Regional Economy webpage, are updated daily with the latest data on confirmed COVID-19 cases from The New York Times, which compiles information from state and local health agencies. Case counts are measured as the seven-day average of new reported daily cases and are presented on a per capita basis to allow comparisons to the nation and between communities in the region. Recent data indicate that after spiking to extraordinary levels in April, new cases have remained relatively low and stable in and around New York City, and in upstate New York. By contrast, cases have been trending higher in Puerto Rico and the U.S. Virgin Islands since mid-July.
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.
Regional employment data provided by the U.S. Bureau of Labor Statistics (BLS) are a critically important tool used to track and assess local economic conditions on a timely basis. However, the primary data used for this purpose are monthly survey-based estimates that are revised once per year, and these revisions can sometimes be substantial and surprising. As a result, initial readings of these data can lead to conclusions about employment trends that may later change. It is possible to anticipate these revisions in advance of their release using a second publicly available data set released by the BLS. Like some of our colleagues at other Federal Reserve Banks, the Federal Reserve Bank of New York is now performing an “early benchmark” of initial monthly employment releases throughout the year and making these benchmarked data available to the public on a monthly basis. Our early benchmarked estimates tend to more closely track revised data than the initial releases do, and can help policymakers and the public better monitor regional economic conditions on a timely basis.