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19 posts on "inequality"
January 7, 2022

The Effect of Inequality on the Transmission of Monetary and Fiscal Policy

Monetary policy can have a meaningful impact on inequality, as recent theoretical and empirical studies suggest. In light of this, how should policy be conducted? And how does inequality affect the transmission of monetary policy? These are the topics covered in the second part of the recent symposium on “Heterogeneity in Macroeconomics: Implications for Policy,” hosted by the new Applied Macroeconomics and Econometrics Center (AMEC) of the New York Fed on November 12.

November 17, 2021

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.

July 1, 2021

Credit, Income, and Inequality

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.

February 9, 2021

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

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, this 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.

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

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).

Posted at 10:00 am in Crisis, Demographics, Inequality, Pandemic | Permalink
March 3, 2020

Introduction to Heterogeneity Series II: Labor Market Outcomes

Rajashri Chakrabarti introduces a new Liberty Street Economics series exploring dimensions of heterogeneity in the labor market experience of U.S. workers.

February 24, 2020

Understanding Heterogeneous Agent New Keynesian Models: Insights from a PRANK

To shed light on the macroeconomic consequences of heterogeneity, Acharya and Dogra develop a stylized HANK model that contains key features present in more complicated HANK models.

October 15, 2019

Does U.S. Health Inequality Reflect Income Inequality—or Something Else?

Health is an integral part of well-being. The United Nations Human Development Index uses life expectancy (together with GDP per capita and literacy) as one of three key indicators of human welfare across the world. In this post, I discuss the state of life expectancy inequality in the United States and examine some of the underlying factors in its evolution over the past several decades.

Posted at 7:01 am in Inequality | Permalink
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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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Economic Inequality

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This ongoing Liberty Street Economics series analyzes disparities in economic and policy outcomes by race, gender, age, region, income, and other factors.

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