The New York Fed recently released its latest set of Equitable Growth Indicators (EGIs). Updated quarterly, the EGIs continue to report demographic and geographic differences in inflation, earnings (real and nominal), employment, and consumer spending (real and nominal) at the national level. This release also launches a set of national wealth EGIs (which will be examined more closely on Liberty Street Economics early next year). Going forward, EGI releases will also include a set of regional EGIs, which will present disparities in inflation, earnings (real and nominal), employment, and consumer spending (real and nominal) in our region. Drawing on the just released EGIs, in this post, we present recent gender gaps in the labor market at the national and regional levels. We provide a picture of how gender wage and employment disparities have evolved since the pandemic, examining and contrasting gaps at the national and regional level. We find that the gaps between the employment rates and earnings of men and women have declined steadily following the pandemic, but have declined perceptibly more so in our region than in the nation.
We continue our series on military service and consider veterans’ earnings and labor market outcomes. We find that veterans earn more than 12 percent less and are 4 percentage points (18 percent) more likely to be out of the labor force than comparable nonveterans. Interestingly, accounting for veterans’ differences from comparable nonveterans in terms of education and disability status largely explains these labor market differences.
Job gains exceeded output growth in 2022, bringing GDP per worker back down to its trend level after being well above for an extended period. Employment is consequently set to grow slower than output going forward, as it typically does. Breaking down the GDP per worker by industry, though, shows a significant divergence between the services and goods-producing sectors. Productivity in the services sector was modestly above its pre-pandemic path at the end of last year, suggesting room for relatively strong employment growth, with the gap particularly large in the health care, professional and business services, and leisure and hospitality sectors. Productivity in goods-producing industries, though, was depressed, implying that payroll growth is set to lag that sector’s GDP growth.
The tri-state region’s economy was hit especially hard by the pandemic, but three years on, is close to recovering the jobs that were lost. Indeed, employment initially 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 experienced similar declines, creating a much larger hole than in other parts of the country. Three years later, the recovery has been uneven: Recent job growth has been particularly strong in New York City, where employment remains just slightly below pre-pandemic levels, and in Northern New Jersey, which has more than recovered all of the jobs lost early in the pandemic. But it has been sluggish in downstate New York outside of New York City, and in upstate New York, and employment across the region has clearly not reached the level implied by pre-pandemic trends. A dearth of available workers remains a significant constraint on growth in the region, particularly in upstate New York, which had already been suffering from a lack of workers well before the pandemic began
The initial phase of the pandemic saw the euro area and U.S unemployment rates behave quite differently, with the rate for the United States rising much more dramatically than the euro area rate. Two years on, the rates for both regions are back near pre-pandemic levels. A key difference, though, is that U.S. employment levels were down by 3.0 million jobs in 2021:Q4 relative to pre-pandemic levels, while the number of euro area jobs was up 600,000. A look at employment by industry shows that both regions had large shortfalls in the accommodation and food services industries, as expected. A key difference is the government sector, with the number of those jobs in the euro area up by 1.5 million, while the government sector in the United States shed 600,000.
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.
Seasonal adjustment is a key statistical procedure underlying the creation of many economic series. Large economic shocks, such as the 2007-09 downturn, can generate lasting seasonal echoes in subsequent data. In this Liberty Street Economics post, we discuss the prospects for these echo effects after last year’s sharp economic contraction by focusing on the payroll employment series published by the U.S. Bureau of Labor Statistics (BLS). We note that seasonal echoes may lead the official numbers to overstate actual changes in payroll employment modestly between March and July of this year after which distortions flip the other way.
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 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.
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.