Although most of those infected with COVID-19 have recovered relatively quickly, a substantial share has not, and remains symptomatic months or even years later, in what is commonly referred to as long COVID. Data on the incidence of long COVID is scarce, but recent Census Bureau data suggest that sixteen million working age Americans suffer from it. The economic costs of long COVID is estimated to be in the trillions. While many with long COVID have dropped out of the labor force because they can no longer work, many others appear to be working despite having disabilities related to the disease. Indeed, there has been an increase of around 1.7 million disabled persons in the U.S. since the pandemic began, and there are close to one million newly disabled workers. These disabled workers can benefit from workplace accommodations to help them remain productive and stay on the job, particularly as the majority deal with fatigue and brain fog, the hallmarks of long COVID.
The COVID-19 pandemic has dramatically changed the way Americans spend their time. One of the most enduring shifts has occurred in the workplace, with millions of employees making the switch to work from home. Even as the pandemic has waned, more than 15 percent of full-time employees remain fully remote and an additional 30 percent work in hybrid arrangements (Barrero, Bloom, and Davis). These changes have substantially reduced time spent commuting to work; in the aggregate, Americans now spend 60 million fewer hours traveling to work each day. In this post, we investigate how people spend this saved time on other activities. Using detailed data from the American Time Use Survey (ATUS), we find that employed individuals allocate their saved commute time toward leisure activities and sleeping, while reducing overall work hours.
Housing is the single largest element of the typical household’s budget, and data from the SCE Household Spending Survey show that this is especially true for renters. As the housing market heated up in the latter stages of the pandemic, home prices and rents both began to rise sharply. For renters, some protection from these increases was afforded by national, state, and in some cases local eviction moratoria, which greatly reduced the risk of households losing access to stable housing if they couldn’t afford their rent. Yet many of these protections have expired and additional supports will do so soon. In this post, we draw on data from our SCE Housing Survey to explore how renters perceive their housing risk and find that the answers depend to a large degree on their current and past experiences of the housing market.
Today, researchers from the Center for Microeconomic Data released the 2022 Student Loan Update, which contains statistics summarizing who holds student loans along with characteristics of these balances. To compute these statistics, we use the New York Fed Consumer Credit Panel (CCP), a nationally representative 5 percent sample of all U.S. adults with an Equifax credit report. For this update, we focus on individuals with a student loan on their credit report. The update is linked here and shared in the student debt section of the Center for Microeconomic Data’s website. In this post, we highlight three facts from the current student loan landscape.
The recovery since the onset of the pandemic has been characterized by a tight labor market and rising nominal wage growth. In this post, we look at labor market conditions from a more granular, sectoral point of view focusing on data covering the nine major industries. This breakdown is motivated by the exceptionality of the pandemic episode, the way it has asymmetrically affected sectors of the economy, and by the possibility of exploiting sectoral heterogeneities to understand the drivers of recent labor market dynamics. We document that wage pressures are highest in the sectors with the largest employment shortfall relative to their pre-pandemic trend path, but that other factors explain most of the wage growth differentials. We suggest that one key factor is the extent of physical contact that has had to be compensated for by offering higher wages. One implication of our analysis is that, as COVID-related factors recede, sectoral imbalances could be restored from the supply side as employment recovers back toward the pre-pandemic trend.
One of the two monetary policy goals of the Federal Reserve System— one-half of our dual mandate—is to aim for “maximum employment.” However, labor market outcomes are not monolithic, and different demographic and economic groups experience different labor market outcomes. In this post, we analyze heterogeneity in employment rates by race and ethnicity, focusing on the COVID-19 recession of March-April 2020 and its aftermath. We find that the demographic employment gaps temporarily increased during the onset of the pandemic but narrowed back by spring 2022 to close to where they were in 2019. In the second post of this series, we will focus on heterogeneity in inflation rates, the second part of our dual mandate.
The Chinese government has followed a “zero covid strategy” (ZCS) ever since the world’s first COVID-19 lockdowns ended in China around late March and early April of 2020. While this strategy has been effective at maintaining low infection levels and robust manufacturing and export activity, its viability is being severely strained by the spread of increasingly infectious coronavirus variants. As a result, there now appears to be a fundamental incompatibility between the ZCS and the government’s economic growth objectives.
This post provides an update on two earlier blog posts (here and here) in which we discuss how consumers’ views about future inflation have evolved in a continually changing economic environment. Using data from the New York Fed’s Survey of Consumer Expectations (SCE), we show that while short-term inflation expectations have continued to trend upward, medium-term inflation expectations appear to have reached a plateau over the past few months, and longer-term inflation expectations have remained remarkably stable. Not surprisingly given recent movements in consumer prices, we find that most respondents agree that inflation will remain high over the next year. In contrast, and somewhat surprisingly, there is a divergence in consumers’ medium-term inflation expectations, in the sense that we observe a simultaneous increase in both the share of respondents who expect high inflation and the share of respondents who expect low inflation (and even deflation) three years from now. Finally, we show that individual consumers have become more uncertain about what inflation will be in the near future. However, in contrast to the pre-pandemic period, they tend to express less uncertainty about inflation further in the future.
Supply chain disruptions continue to be a major challenge as the world economy recovers from the COVID-19 pandemic. Furthermore, recent developments related to geopolitics and the pandemic (particularly in China) could put further strains on global supply chains. In a January post, we first presented the Global Supply Chain Pressure Index (GSCPI), a parsimonious global measure designed to capture supply chain disruptions using a range of indicators. We revisited our index in March, and today we are launching the GSCPI as a standalone product, with new readings to be published each month. In this post, we review GSCPI readings through April 2022 and briefly discuss the drivers of recent moves in the index.
The pandemic forbearance for federal student loans was recently extended for a sixth time—marking a historic thirty-month pause on federal student loan payments. The first post in this series uses survey data to help us understand which borrowers are likely to struggle when the pandemic forbearance ends. The results from this survey and the experience of some federal borrowers who did not receive forbearance during the pandemic suggest that delinquencies could surpass pre-pandemic levels after forbearance ends. These concerns have revived debates over the possibility of blanket forgiveness of federal student loans. Calls for student loan forgiveness entered the mainstream during the 2020 election with most proposals centering around blanket federal student loan forgiveness (typically $10,000 or $50,000) or loan forgiveness with certain income limits for eligibility. Several studies (examples here, here, and here) have attempted to quantify the costs and distribution of benefits of some of these policies. However, each of these studies either relies on data that do not fully capture the population that owes student loan debt or does not separate student loans owned by the federal government from those owned by commercial banks and are thus not eligible for forgiveness with most proposals. In this post, we use representative data from anonymized credit reports that allows us to identify federal loans, calculate the total cost of these proposals, explore important heterogeneity in who owes federal student loans, and examine who would likely benefit from federal student loan forgiveness.