How will the U.S. economy emerge from the ongoing COVID-19 pandemic? Will it struggle to return to prior levels of employment and activity, or will it come roaring back as soon as vaccinations are widespread and Americans feel comfortable travelling and eating out? Part of the answer to these questions hinges on what will happen to the large amount of “excess savings” that U.S. households have accumulated since last March. According to most estimates, these savings are around $1.6 trillion and counting. Some economists have expressed the concern that, if a considerable fraction of these accumulated funds is spent as soon as the economy re-opens, the ensuing rush of demand might be destabilizing. This post argues that these savings are not that excessive, when considered against the backdrop of the unprecedented government interventions adopted over the past year in support of households and that they are unlikely to generate a surge in demand post-pandemic.
Understanding the Racial and Income Gap in Covid-19: Health Insurance, Comorbidities, and Medical Facilities
Our previous work documents that low-income and majority-minority areas were considerably more affected by COVID-19, as captured by markedly higher case and death rates. In a four-part series starting with this post, we seek to understand the reasons behind these income and racial disparities. Do disparities in health status translate into disparities in COVID-19 intensity? Does the health system play a role through health insurance and hospital capacity? Can disparities in COVID-19 intensity be explained by high-density, crowded environments? Does social distancing, pollution, or the age composition of the county matter? Does the prevalence of essential service jobs make a difference? This post will focus on the first two questions. The next three posts in this series will focus on the remaining questions. The posts will follow a similar structure. In each post, we will aim to understand whether the factors considered in that post affect overall COVID-19 intensity, whether the racial and income gaps can be further explained when we additionally include the factors in consideration in that post, and whether and to what extent the factors under consideration in that post independently affect racial and income gaps in COVID-19 intensity (without controlling for the factors considered in the other posts in this series).
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.
Leading up to the COVID-19 outbreak, there were growing concerns about corporate sector indebtedness. High levels of borrowing may give rise to a “debt overhang” problem, particularly during downturns, whereby firms forego good investment opportunities because of an inability to raise additional funding. In this post, we show that firms with high levels of borrowing at the onset of the Great Recession underperformed in the following years, compared to similar—but less indebted—firms. These findings, together with early data on the revenue contractions following the COVID-19 outbreak, suggest that debt overhang during the COVID-recession could lead to an up to 10 percent decrease in growth for firms in industries most affected by the economic repercussions of the battle against the outbreak.
The U.S. federal funds market played a central role in the financial system during the 2007-09 crisis, because it was the market which provided banks with immediate liquidity, even late in the day. Interpreting changes in fed funds rates is notoriously difficult, however, as many of the economic drivers behind the rates are simultaneously changing. In this post, I highlight results from a working paper which untangles the impact of these economic drivers and measures their respective effects on the marketplace using data over a sample period leading up to and during the financial crisis. The analysis shows that the spread between fed funds sold and bought widened because of increases in counterparty risk. Further, there was a large increase in the supply of cash into this market, suggesting that banks viewed fed funds as a relatively safe place to invest cash in a crisis environment.
Did the 2007-09 financial crisis or the regulatory reforms that followed alter how banks change their underwriting standards over the course of the business cycle? We provide some simple, “narrative” evidence on that question by studying the reasons banks cite when they report a change in commercial credit standards in the Federal Reserve’s Senior Loan Officer Opinion Survey. We find that the economic outlook, risk tolerance, and other real factors generally drive standards more than financial factors such as bank capital and loan market liquidity. Those financial factors have mattered more since the crisis, however, and their importance increased further as post-crisis reforms were phased in in the middle of the following decade.
In this post, we examine how households used economic impact payments, a large component of the CARES Act signed into law on March 27 that directed stimulus payments to many Americans to help offset the economic fallout from the coronavirus pandemic. An important question in evaluating how much this part of the CARES Act stimulated the economy concerns what share of these payments households used for consumption— what economists call the marginal propensity to consume (MPC). There also is interest in learning the extent to which the payments contributed to the sharp increase in the U.S. personal saving rate during the early months of the pandemic. We find in this analysis that as of the end of June 2020, a relatively small share of stimulus payments, 29 percent, was used for consumption, with 36 percent saved and 35 percent used to pay down debt. Reported expected uses for a potential second stimulus payment suggest an even smaller MPC, with households expecting to use more of the funds to pay down their debts. We find similarly small estimated average consumption out of unemployment insurance (UI) payments, but with somewhat larger shares of these funds used to pay down debt.
Anna Kovner and Antoine Martin argue that the “credit” and lending facilities established by the Fed in response to the COVID-19 pandemic, while unprecedented, are a natural extension of the central bank’s existing toolkit.
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.
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.