Liberty Street Economics
Return to Liberty Street Economics Home Page

29 posts on "Demographics"
February 9, 2021

Some Workers Have Been Hit Much Harder than Others by the Pandemic

Abel and Deitz look at the outsized impact of the COVID-19 pandemic on some workers, particularly those who are in lower-wage jobs, without a college degree, female, minority, and younger.

January 12, 2021

Understanding the Racial and Income Gap in COVID-19: Public Transportation and Home Crowding

This is the second post in a series that aims to understand the gap in COVID-19 intensity by race and income. In our post yesterday, we looked at how comorbidities, uninsurance rates, and health resources may help to explain the race and income gap observed in COVID-19 intensity. We found that a quarter of the income gap and more than a third of the racial gap in case rates are explained by health status and system factors. In this post, we look at two factors related to indoor density—namely the use of public transportation and increased home crowding. Here, we will aim to understand whether these two factors affect overall COVID-19 intensity, whether the income and racial gaps of COVID can be further explained when we additionally include these factors, and whether and to what extent these factors independently account for income and racial gaps in COVID-19 intensity (without controlling for the factors considered in the other posts in this series).

Posted at 10:01 am in Demographics, Inequality, Pandemic | Permalink | Comments (0)

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).

September 25, 2020

Investigating the Effect of Health Insurance in the COVID-19 Pandemic

Does health insurance improve health? This question, while apparently a tautology, has been the subject of considerable economic debate. In light of the COVID-19 pandemic, it has acquired a greater urgency as the lack of universal health insurance has been cited as a cause of the profound racial gap in coronavirus cases, and as a cause of U.S. difficulties in managing the pandemic more generally. However, estimating the effect of health insurance is difficult because it is (generally) not assigned at random. In this post, we approach this question in a novel way by exploiting a natural experiment—the adoption of the Affordable Care Act (ACA) Medicaid expansion by some states but not others—to tease out the causal effect of a type of health insurance on COVID-19 intensity.

August 19, 2020

Debt Relief and the CARES Act: Which Borrowers Face the Most Financial Strain?

In part I of our analysis, we studied the expected debt relief from the CARES Act on mortgagors and student debt borrowers. We now turn our attention to the 63 percent of American borrowers who do not have a mortgage or student loan. These borrowers will not directly benefit from the loan forbearance provisions of the CARES Act, although they may be able to receive some types of leniency that many lenders have voluntarily provided. We ask who these borrowers are, by age, geography, race and income, and how does their financial health compare with other borrowers.

August 18, 2020

Debt Relief and the CARES Act: Which Borrowers Benefit the Most?

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.

August 17, 2020

Are Financially Distressed Areas More Affected by COVID-19?

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-heterogeneity series looking at heterogeneity in the credit market as it pertains to COVID-19 incidence and CARES Act debt relief.

July 7, 2020

Introduction to Heterogeneity Series III: Credit Market Outcomes

Following up series on heterogeneity and inequality broadly and in labor market outcomes specifically, we turn our focus to further documenting heterogeneity in credit market outcomes, looking at disparities in home ownership rates, varying exposure to evictions, differing gains from tuition support and Medicare programs, and more.

June 15, 2020

Distribution of COVID-19 Incidence by Geography, Race, and Income

In this post, we study whether (and how) the spread of COVID-19 across the United States varied by geography, race, income, and population density. Were urban areas more affected by COVID-19 than rural areas? Did population density matter in the spread? Were certain races and income groups affected more by the spread of this deadly coronavirus? Our analysis uncovers stark demographic trends among places affected most severely by the pandemic thus far.

December 3, 2018

Just Released: A Closer Look at Recent Tightening in Consumer Credit

The Federal Reserve Bank of New York released results today from its October 2018 SCE Credit Access Survey, which provides information on consumers’ experiences with and expectations about credit demand and credit access. The survey is fielded every four months and was previously fielded in June.

About the Blog

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.

Liberty Street Economics does not publish new posts during the blackout periods surrounding Federal Open Market Committee meetings.

The views expressed are those of the authors, and do not necessarily reflect the position of the New York Fed or the Federal Reserve System.

Economic Research Tracker

Liberty Street Economics is now available on the iPhone® and iPad® and can be customized by economic research topic or economist.

Most Viewed

Last 12 Months

Comment Guidelines

We encourage your comments and queries on our posts and will publish them (below the post) subject to the following guidelines:

Please be brief: Comments are limited to 1500 characters.

Please be quick: Comments submitted after COB on Friday will not be published until Monday morning.

Please be aware: Comments submitted shortly before or during the FOMC blackout may not be published until after the blackout.

Please be on-topic and patient: Comments are moderated and will not appear until they have been reviewed to ensure that they are substantive and clearly related to the topic of the post. We reserve the right not to post any comment, and will not post comments that are abusive, harassing, obscene, or commercial in nature. No notice will be given regarding whether a submission will or will not be posted.‎

Send Us Feedback

Disclosure Policy

The LSE editors ask authors submitting a post to the blog to confirm that they have no conflicts of interest as defined by the American Economic Association in its Disclosure Policy. If an author has sources of financial support or other interests that could be perceived as influencing the research presented in the post, we disclose that fact in a statement prepared by the author and appended to the author information at the end of the post. If the author has no such interests to disclose, no statement is provided. Note, however, that we do indicate in all cases if a data vendor or other party has a right to review a post.