Rajashri Chakrabarti, Andrew Haughwout, Donghoon Lee, William Nober, Joelle Scally, and Wilbert van der Klaauw



COVID-19 and associated social distancing measures have had major labor market ramifications, with massive job losses and furloughs. Millions of people have filed jobless claims since mid-March—6.9 million in the week of March 28 alone. These developments will surely lead to financial hardship for millions of Americans, especially those who hold outstanding debts while facing diminishing or disappearing wages. The CARES Act, passed by Congress on April 2, 2020, provided $2.2 trillion in disaster relief to combat the economic impacts of COVID-19. Among other measures, it included mortgage and student debt relief measures to alleviate the cash flow problems of borrowers. In this post, we examine who could benefit most (and by how much) from various debt relief provisions under the CARES Act.

Rajashri Chakrabarti, William Nober, and Maxim Pinkovskiy

Editor’s note: When this post was first published, the columns in the second table were mislabeled; the table has been corrected. (August 19, 9:30 a.m.)



Building upon our earlier Liberty Street Economics post, we continue to analyze the heterogeneity of COVID-19 incidence. We previously found that majority-minority areas, low-income areas, and areas with higher population density were more affected by COVID-19. The objective of this post is to understand any differences in COVID-19 incidence by areas of financial vulnerability. Are areas that are more financially distressed affected by COVID-19 to a greater extent than other areas? If so, this would not only further adversely affect the financial well-being of the individuals in these areas, but also the local economy. This post is the first in a three-part series looking at heterogeneity in the credit market as it pertains to COVID-19 incidence and CARES Act debt relief.

Jaison R. Abel and Richard Deitz



Many students are reconsidering their decision to go to college in the fall due to the coronavirus pandemic. Indeed, college enrollment is expected to be down sharply as a growing number of would-be college students consider taking a gap year. In part, this pullback reflects concerns about health and safety if colleges resume in-person classes, or missing out on the “college experience” if classes are held online. In addition, poor labor market prospects due to staggeringly high unemployment may be leading some to conclude that college is no longer worth it in this economic environment. In this post, we provide an economic perspective on going to college during the pandemic. Perhaps surprisingly, we find that the return to college actually increases, largely because the opportunity cost of attending school has declined. Furthermore, we show there are sizeable hidden costs to delaying college that erode the value of a college degree, even in the current economic environment. In fact, we estimate that taking a gap year reduces the return to college by a quarter and can cost tens of thousands of dollars in lost lifetime earnings.

Rajashri Chakrabarti, William Nober, and Wilbert van der Klaauw



In an October post, we showed the effect of college tuition subsidies in the form of merit-based financial aid on educational and student debt outcomes, documenting a large decline in student debt for those eligible for merit aid. Additionally, we reported striking differences in these outcomes by demographics, as proxied by neighborhood race and income. In this follow-up post, we examine whether and how this effect passes through to other debt and consumption outcomes, namely those related to autos, homes, and credit cards. We find that access to merit aid leads to an immediate but temporary increase in eligible individuals’ consumption in these categories. The increase is followed by a decline in consumption and a reduction in total debt of these types in the longer term. Importantly, there are marked differences in these consumption and debt patterns across income and race groups.

Rajashri Chakrabarti, William Nober, and Wilbert van der Klaauw



Across the United States, the cost of all types of higher education has been rising faster than overall inflation for more than two decades. Despite rising costs, aggregate undergraduate enrollment rose steadily between 2000 and 2010 before leveling off and dipping slightly to its current level. Rising college costs have steadily increased dependence on student debt for college financing, with many students and parents turning to federal and private loans to pay for higher education. An earlier post in this series reported that borrowers in majority Black areas have higher student loan balances and rates of default than those in both majority white and majority Hispanic areas. In this post, we study how differences in college attendance rates and in the types of colleges attended generate heterogeneity in loan experiences. Specifically, using nationwide data, we analyze heterogeneities in college-going and heterogeneities in student debt and default experiences by college type across individuals living in majority Black, majority Hispanic, and majority white zip codes.

Rajashri Chakrabarti



Average economic outcomes serve as important indicators of the overall state of the economy. However, they mask a lot of underlying variability in how people experience the economy across geography, or by race, income, age, or other attributes. Following our series on heterogeneity broadly in October 2019 and in labor market outcomes in March 2020, we now turn our focus to further documenting heterogeneity in the credit market. While we have written about credit market heterogeneity before, this series integrates insights on disparities in outcomes in various parts of the credit market. The analysis includes a look at differing homeownership rates across populations, varying exposure to foreclosures and evictions, and uneven student loan burdens and repayment behaviors. It also covers heterogeneous effects of policies by comparing financial health outcomes for those with access to public tuition subsidies and Medicare versus those not eligible. The findings underscore that a measure of the average, particularly relating to policy impact, is far from complete. Rather, a sharper picture of the diverse effects is essential to understanding the efficacy of policy.

Anna Snider



With each new Liberty Street Economics post, we aim to build familiarity with New York Fed research and policy analysis, and to share the expertise of our staff when it is relevant to the issues of the day. More than sixty economists contribute, and we tap coauthors from other central banks and academia as well, so the topics vary widely, covering the alphabet of “JEL Codes” in the economics literature plus numerous policy themes. Judging from our internet traffic, we have a core group that checks in to read nearly everything. Some posts break out to a wider public, prompted by news articles that cite our findings and even a mention in a presidential candidate’s tweet. Take a look at our top five most-read posts of 2019.

Andrew F. Haughwout, Donghoon Lee, Joelle Scally, and Wilbert van der Klaauw



Total household debt balances increased by $92 billion in the third quarter of 2019, according to the latest Quarterly Report on Household Debt and Credit from the New York Fed’s Center for Microeconomic Data. The balance increase reflected nearly across the board gains in various types of debt, with the largest gains of $31 billion in mortgage balances (0.3 percent) and $20 billion in student loan balances (1.4 percent). The Quarterly Report, and the following analysis, are both based on the New York Fed’s Consumer Credit Panel, which is itself based on anonymized Equifax credit report data. Our report also provides breakouts by age, and by state, demonstrating that patterns of borrowing and repayment are heterogeneous by those factors. But there are many other dimensions across which we see varying credit market outcomes.

Andrew F. Haughwout, Donghoon Lee, Joelle Scally, and Wilbert van der Klaauw



Student loans are increasingly a focus of discourse among politicians, policymakers, and the news media, resulting in a range of new ideas to address the swelling aggregate debt. Evaluating student loan policy proposals requires understanding the challenges faced by student borrowers. In this post, we explore the substantial variation in the experiences of borrowers and consider the distributional effects of various policy options.

Gizem Kosar, Kyle Smith, and Wilbert van der Klaauw



Today we are releasing new data on individuals’ experiences and expectations regarding household spending. These data have been collected every four months since December 2014 as part of our Survey of Consumer Expectations (SCE). The goal of this blog post is to introduce the SCE Household Spending Survey and highlight some of its features.