Jaison R. Abel, Jason Bram, Richard Deitz, and Jonathan Hastings



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. Cases didn’t reach nearly as high in upstate New York, and have held fairly low in recent weeks. By contrast, cases have been trending higher in Puerto Rico and the U.S. Virgin Islands since mid-July.

Jaison R. Abel, Jason Bram, Richard Deitz, and Benjamin G. Hyman



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.

Rajashri Chakrabarti and William Nober



In this post, we study whether (and how) the spread of COVID-19 across the United States has varied by geography, race, income, and population density. Have urban areas been more affected by COVID-19 than rural areas? Has population density mattered in the spread? Has the coronavirus's impact varied by race and income? Our analysis uncovers stark demographic and geographic differences in the effects of the pandemic thus far.

Jason Bram and Fatih Karahan



News headlines highlighting the loss of at least 30 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.

Jaison R. Abel, Jason Bram, and Richard Deitz



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.

Jason Bram and Richard Deitz



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.

Jaison R. Abel, Jason Bram, and Richard Deitz




As a result of the coronavirus outbreak, New York State, New Jersey, and Connecticut have closed nonessential businesses and schools and asked residents to stay home in an effort to slow the spread of the virus. These actions are unprecedented, and the economic impacts are likely to be temporary but severe, and difficult to track and measure. With conditions changing so rapidly, timely data on the economic impacts of the outbreak and resultant policies on businesses and people are both scarce and important. In this post, we provide some very recent information on the economic effects of the coronavirus outbreak in the tri-state region based on responses to a special survey we fielded between March 20 and March 24. The results are striking, though perhaps not surprising: roughly half of the service firms surveyed and well over a third of manufacturers said they have already implemented at least a partial temporary shutdown, and more firms plan to do so in the near future. Further, 40 percent of service firms and 30 percent of manufacturers are reporting staff reductions, and many firms are noting difficulty accessing credit and are concerned about their solvency.

Rajashri Chakrabarti



While average outcomes serve as important yardsticks for how the economy is doing, understanding heterogeneity—how outcomes vary across a population—is key to understanding both the whole picture and the implications of any given policy. Following our six-part look at heterogeneity in October 2019, we now turn our focus to heterogeneity in the labor market—the subject of four posts set for release tomorrow morning. Average labor market statistics mask a lot of underlying variability—disparities that factor into labor market dynamics. While we have written about labor market heterogeneity before, this series is an attempt to pull together in a cohesive way new insights on the labor market and highlight details that are not immediately obvious when we study aggregate labor market statistics.

Jaison R. Abel, Jason Bram, Richard Deitz, and Jonathan Hastings



At today’s regional economic press briefing, we highlighted some recent softening in the tri-state regional economy (New York, Northern New Jersey, and Fairfield County, Connecticut)—a noteworthy contrast from our briefing a year ago, when economic growth and job creation were fairly brisk. We also showed that Puerto Rico and the U.S. Virgin Islands, which are part of the New York Fed’s district, both continue to face major challenges but have made significant economic progress following the catastrophic hurricanes of 2017.

Jaison R. Abel and Richard Deitz



Economic inequality in the United States is much more pronounced in some parts of the country than others. In this post, we examine the geography of wage inequality, drawing on our recent Economic Policy Review article. We find that the most unequal places tend to be large urban areas with strong economies where wage growth has been particularly strong for those at the top of the wage distribution. The least unequal places, on the other hand, tend to have relatively sluggish economies that deliver slower wage growth for high, middle, and lower wage earners alike. Many of the least unequal places are concentrated in the Rust Belt. These differences in the degree of wage inequality are tied to powerful economic forces arising from technological change and globalization, which have pushed up wages strongly for high-skilled workers in locations that have become the most unequal. Yet those same forces have kept wage growth compressed within a fairly narrow range for workers in places that are the least unequal.