Housing Returns in Big and Small Cities
Houses are the largest asset for most households in the United States, as is the case in many other countries as well. Within countries, there is substantial regional variation in house prices—compare real estate values in Manhattan, New York City, with those in Manhattan, Kansas, for example. But what about returns on investment? Are long-run returns on real estate investment—the sum of price appreciation and rental income flows—higher in superstar cities like New York than in the rest of the country? In this blog post, we present new and potentially surprising insights from research comparing long-run returns on residential real estate in a nation’s largest cities to those experienced in the rest of the country (Amaral et al., 2021), covering the U.S. and fourteen other advanced economies over the past century.
The Role of Educational Attainment in Household Debt and Delinquency Disparities
This post concludes a three-part series exploring the gender, racial, and educational disparities of debt outcomes of college students. In the previous two posts, we examined how debt holding and delinquency behaviors vary among students of different race and gender, breaking up our analyses by level of degree pursued by the student. We found that Black and Hispanic students were less likely than white students to take on credit card debt, auto loans, and mortgage debt, but experienced higher rates of delinquency in each of these debt areas by the age of 30. In contrast, Black students were more likely to take out student debt and both Black and Hispanic students experienced higher rates of student debt delinquency. We found that Asian students broadly followed reverse patterns from Black and Hispanic students by age 30. They were more likely than white students to acquire mortgages and less likely to hold student debt, but their delinquency patterns were in general similar to those of white students. Women were less likely to hold an auto loan or mortgage and more likely to hold student debt by age 30, and in most cases their delinquency outcomes were indistinguishable from males. In this post, we seek to understand mechanisms behind these racial and gender disparities and examine the role of educational attainment in explaining these patterns.
Unequal Distribution of Delinquencies by Gender, Race, and Education
This post is the second in a three-part series exploring racial, gender, and educational differences in household debt outcomes. In the first post, we examined how the propensity to take out household debt and loan amounts varied among students by race, gender, and education level, finding notable differences across all of these dimensions. Were these disparities in debt behavior by gender, race, and education level associated with differences in financial stress, as captured by delinquencies? This post focuses on this question.
Uneven Distribution of Household Debt by Gender, Race, and Education
Household debt has risen markedly since 2013 and amounts to more than $15 trillion dollars. While the aggregate volume of household debt has been well-documented, literature on the gender, racial and education distribution of debt is lacking, largely because of an absence of adequate data that combine debt, demographic, and education information. In a three-part series beginning with this post, we seek to bridge this gap. In this first post, we focus on differences in debt holding behavior across race and gender. Specifically, we explore gender and racial disparities in different types of household debt and delinquencies—for auto, mortgage, credit card, and student loans—while distinguishing between students pursuing associate’s (AA) and bachelor’s (BA) degrees. In the second post in this series, we investigate gender and racial disparities in delinquencies across these various kinds of consumer debt. We close with a third post where we try to understand some of the mechanisms behind differences in debt and delinquencies across gender and race.
Credit Card Trends Begin to Normalize after Pandemic Paydown
Today, the New York Fed’s Center for Microeconomic Data released its Quarterly Report on Household Debt and Credit for the third quarter of 2021. Overall debt balances increased, bolstered primarily by a sizeable increase in mortgage balances, and for the second consecutive quarter, an increase in credit card balances. The changes in credit card balances in the second and third quarters of 2021 are remarkable since they appear to be a return to the normal seasonal patterns in balances. In a Liberty Street Economics post earlier this year we wrote about some demographic variation in these balance changes and the likely role of stimulus checks and forbearance programs in helping borrowers pay down expensive revolving debt balances. Here, we’ll take a fresh look at credit card balances and at the dynamics behind new and closing credit card accounts and limit changes, to examine how credit access and usage continue to evolve. The Quarterly Report and this analysis are based on our Consumer Credit Panel, which is itself based on Equifax credit data.
If Prices Fall, Mortgage Foreclosures Will Rise
In our previous post, we illustrated the recent extraordinarily strong growth in home prices and explored some of its key spatial patterns. Such price increases remind many of the first decade of the 2000s when home prices reversed, contributing to a broad housing market collapse that led to a wave of foreclosures, a financial crisis, and a prolonged recession. This post explores the risk that such an event could recur if home prices go into reverse now. We find that although the situation looks superficially similar to the brink of the last crisis, there are important differences that are likely to mitigate the risks emanating from the housing sector.
Forbearance Participation Declines as Programs’ End Nears
The Federal Reserve Bank of New York’s Center for Microeconomic Data today released its Quarterly Report on Household Debt and Credit for the second quarter of 2021. It showed that overall household debt increased at a quick clip over the period, with a $322 billion increase in balances, boosted primarily by a 2.8 percent increase in mortgage balances, a 2.2 percent increase in credit card balances, and a 2.4 percent increase in auto balances. Mortgage balances in particular were boosted by a record $1.22 trillion in newly originated loans. Although some borrowers are originating new loans, struggling borrowers remain in forbearance programs, where they are pausing repayment on their debts and creating an additional upward pressure on outstanding mortgage balances.
Credit, Income, and Inequality
Access to credit plays a central role in shaping economic opportunities of households and businesses. Access to credit also plays a crucial role in helping an economy successfully exit from the pandemic doldrums. The ability to get a loan may allow individuals to purchase a home, invest in education and training, or start and then expand a business. Hence access to credit has important implications for upward mobility and potentially also for inequality. Adverse selection and moral hazard problems due to asymmetric information between lenders and borrowers affect credit availability. Because of these information issues, lenders may limit credit or post higher lending rates and often require borrowers to pledge collateral. Consequently, relatively poor individuals with limited capital endowment may experience credit denial, irrespective of the quality of their investment ideas. As a result, their exclusion from credit access can hinder economic mobility and entrench income inequality. In this post, we describe the results of our recent paper which contributes to the understanding of this mechanism.
What Happens during Mortgage Forbearance?
As we discussed in our previous post, millions of mortgage borrowers have entered forbearance since the beginning of the pandemic, and over 2 million remain in a program as of March 2021. In this post, we use our Consumer Credit Panel (CCP) data to examine borrower behavior while in forbearance. The credit bureau data are ideal for this purpose because they allow us to follow borrowers over time, and to connect developments on the mortgage with those on other credit products. We find that forbearance results in reduced mortgage delinquencies and is associated with increased paydown of other debts, suggesting that these programs have significantly improved the financial positions of the borrowers who received them.