The Federal Reserve Bank of New York works to promote sound and well-functioning financial systems and markets through its provision of industry and payment services, advancement of infrastructure reform in key markets and training and educational support to international institutions.
Andrew Haughwout, Donghoon Lee, Joelle Scally, and Wilbert van der Klaauw
Today, the New York Fed’s Center for Microeconomic Data reported that total household debt balances increased slightly in the third quarter of 2020, according to the latest Quarterly Report on Household Debt and Credit. This increase marked a reversal from the modest decline in the second quarter of 2020, a downturn driven by a sharp contraction in credit card balances. In the third quarter, credit card balances declined again, even as consumer spending recovered somewhat; meanwhile, mortgage originations came in at a robust $1.049 trillion, the highest level since 2003. Many of the efforts to stabilize the economy in response to the COVID-19 crisis have focused on consumer balance sheets, both through direct cash transfers and through forbearances on federally backed debts. Here, we examine the uptake of forbearances on mortgage and auto loans and its impact on their delinquency status and the borrower’s credit score. This analysis, as well as the Quarterly Report on Household Debt and Credit, is based on anonymized Equifax credit report data.
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.
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.
James Conklin, W. Scott Frame, Kristopher Gerardi, and Haoyang Liu
Editor’s note: When this post was first published, the chart labels for “Non-Boom Counties” were incorrect; the labels have been corrected. (February 26, 12:00 pm)
The role of subprime mortgage lending in the U.S. housing boom of the 2000s is hotly debated in academic literature. One prevailing
narrative ascribes the unprecedented home price growth during the mid-2000s to an expansion in mortgage lending to subprime borrowers. This post, based on our recent working paper, “Villains or Scapegoats? The Role of Subprime Borrowers in Driving the U.S. Housing Boom,” presents evidence that is inconsistent with conventional wisdom. In particular, we show that the housing boom and the subprime boom occurred in different places.
Olivier Armantier, Andrew F. Haughwout, Gizem Kosar, Donghoon Lee, Joelle Scally, and Wilbert van der Klaauw
The New York Fed today held a press briefing on homeownership in the United States, in connection with its release of the 2019 Survey of Consumer Expectations Housing Survey. The briefing opened with remarks from New York Fed President John Williams, who provided commentary on the macroeconomic outlook and summarized the prospects for homeownership. He noted that the labor market remains very strong and that there seems to be little evidence of inflationary pressures, meaning that the economy is on a healthy growth path.
From the fourth quarter of 2017 through the third quarter of 2018, the average contract interest rate on new thirty-year fixed rate mortgages rose by roughly 70 basis points—from 3.9 percent to 4.6 percent. During this same period, there was a broad-based slowing in housing market activity with sales of new single-family homes declining by 7.6 percent while sales of existing single-family homes fell by 4.6 percent. Interestingly though, these declines in home sales were larger than in the two previous episodes when mortgage interest rates rose by a comparable amount. This post considers whether provisions in the Tax Cuts and Jobs Act of 2017 (TCJA) might have also contributed to the recent decline in housing market activity.
In this post we take up the important question of the sustainability of homeownership for first-time buyers. The evaluation of public policies aimed at promoting the transition of individuals from renting to owning should depend not only on the degree to which such policies increase the number of first-time buyers, but also importantly on whether these new buyers are able to sustain their homeownership. If a buyer is unprepared to manage the financial responsibilities of owning a home and consequently must return to renting, then the household may have made little to no progress in wealth accumulation. Despite the importance of sustainability, to date there have been no efforts at measuring the sustainability of first-time homeownership. We provide an example of a first-time homebuyer sustainability scorecard.
In our previous post, we presented a new measure of first-time homebuyers. In this post, we use this improved measure to describe the characteristics of first-time buyers and how those characteristics change over time. Having an accurate assessment of first-time buyers is important given that the aim of many housing policies is to support the transition from renting to owning. A proper assessment of these housing policies requires an understanding of the impact of these policies on the share of first-time buyers and the characteristics of these buyers. Our third post will directly examine the sustainability of homeownership by first-time buyers.
Liberty Street Economics features insight and analysis from New York Fed economists working at the intersection of research and policy. Launched in 2011, the blog takes its name from the Bank’s headquarters at 33 Liberty Street in Manhattan’s Financial District.
The editors are Michael Fleming, Andrew Haughwout, Thomas Klitgaard, and Asani Sarkar, all economists in the Bank’s Research Group.
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