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21 posts on "Demographics"

February 09, 2021

Black and White Differences in the Labor Market Recovery from COVID-19



LSE_2021_EI-series-covid-recession_karahan_460

The ongoing COVID-19 pandemic and the various measures put in place to contain it caused a rapid deterioration in labor market conditions for many workers and plunged the nation into recession. The unemployment rate increased dramatically during the COVID recession, rising from 3.5 percent in February to 14.8 percent in April, accompanied by an almost three percentage point decline in labor force participation. While the subsequent labor market recovery in the aggregate has exceeded even some of the most optimistic scenarios put forth soon after this dramatic rise, the recovery has been markedly weaker for the Black population. In this post, we document several striking differences in labor market outcomes by race and use Current Population Survey (CPS) data to better understand them.

Continue reading "Black and White Differences in the Labor Market Recovery from COVID-19" »

Understanding the Racial and Income Gap in Commuting for Work Following COVID-19



LSE_2021_Understanding the Racial and Income Gap in Commuting for Work Following COVID-19

The introduction of numerous social distancing policies across the United States, combined with voluntary pullbacks in activity as responses to the COVID-19 outbreak, resulted in differences emerging in the types of work that were done from home and those that were not. Workers at businesses more likely to require in-person work—for example, some, but not all, workers in healthcare, retail, agriculture and construction—continued to come in on a regular basis. In contrast, workers in many other businesses, such as IT and finance, were generally better able to switch to working from home rather than commuting daily to work. In this post, we aim to understand whether following the onset of the pandemic there was a wedge in the incidence of commuting for work across income and race. And how did this difference, if any, change as the economy slowly recovered? We take advantage of a unique data source, SafeGraph cell phone data, to identify workers who continued to commute to work in low income versus higher income and majority-minority (MM) versus other counties.

Continue reading "Understanding the Racial and Income Gap in Commuting for Work Following COVID-19" »

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



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As the COVID-19 pandemic took hold in the United States, in just two months—between February and April 2020—the nation saw well over 20 million workers lose their jobs, an unprecedented 15 percent decline. Since then, substantial progress has been made, but employment still remains 5 percent below its pre-pandemic level. However, not all workers have been affected equally. This post is the first in a three-part series exploring disparities in labor market outcomes during the pandemic—and represents an extension of ongoing research into heterogeneities and inequalities in people’s experience across large segments of the economy including access to credit, health, housing, and education. Here we find that some workers were much more likely to lose their jobs than others, particularly lower-wage workers and those without a college degree, as well as women, minorities, and younger workers. However, as jobs have returned during the recovery, many of these differences have narrowed considerably, though some gaps are widening again as the labor market has weakened due to a renewed surge in the coronavirus. The next post in the series examines differences in patterns of commuting during the pandemic, and finds that workers in low-income and Black- and Hispanic-majority communities were more likely to commute for work. The final post in the series analyzes unemployment dynamics during the pandemic, and finds that Black workers experienced a lower job-finding rate and a higher separation rate into unemployment than white workers during the recovery, though this trend has reversed to some extent recently.

Continue reading "Some Workers Have Been Hit Much Harder than Others by the Pandemic" »

January 12, 2021

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



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This is the second post in a series that aims to understand the gap in COVID-19 intensity by race and income. In our first post, 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 public transportation use and 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-19 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).

Continue reading "Understanding the Racial and Income Gap in COVID-19: Public Transportation and Home Crowding" »

Posted by Blog Author 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




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).

Continue reading "Understanding the Racial and Income Gap in Covid-19: Health Insurance, Comorbidities, and Medical Facilities" »

Posted by Blog Author at 10:00 AM in Crisis, Demographics, Inequality, Pandemic | Permalink | Comments (0)

September 25, 2020

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



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.

Continue reading "Investigating the Effect of Health Insurance in the COVID-19 Pandemic" »

Posted by Blog Author at 7:00 AM in Demographics, Inequality, Pandemic | Permalink | Comments (0)

August 19, 2020

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



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

In yesterday's post, 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.

Continue reading "Debt Relief and the CARES Act: Which Borrowers Face the Most Financial Strain?" »

Posted by Blog Author at 7:00 AM in Credit, Demographics, Household Finance, Inequality, Pandemic | Permalink | Comments (0)

August 18, 2020

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



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.

Continue reading "Debt Relief and the CARES Act: Which Borrowers Benefit the Most?" »

August 17, 2020

Are Financially Distressed Areas More Affected by COVID-19?



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.)

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

Continue reading "Are Financially Distressed Areas More Affected by COVID-19?" »

July 07, 2020

Introduction to Heterogeneity Series III: Credit Market Outcomes



Introduction to Heterogeneity Series III: Credit Market Outcomes

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.

Continue reading "Introduction to Heterogeneity Series III: Credit Market Outcomes" »

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