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
Federal government actions in response to the pandemic have taken many forms. One set of policies is intended to reduce the risk that the pandemic will result in a housing market crash and a wave of foreclosures like the one that accompanied the Great Financial Crisis. An important and novel tool employed as part of these policies is mortgage forbearance, which provides borrowers the option to pause or reduce debt service payments during periods of hardship, without marking the loan delinquent on the borrower’s credit report. Widespread take-up of forbearance over the past year has significantly changed the housing finance system in the United States, in different ways for different borrowers. This post is the first of four focusing attention on the effects of mortgage forbearance and the outlook for the mortgage market. Here we use data from the New York Fed’s Consumer Credit Panel (CCP) to examine the effects of these changes on households during the pandemic.
During the COVID-19 pandemic, many industries adapted to new social distancing guidelines by adopting new technologies, providing protective equipment for their employees, and digitizing their methods of production. These changes in industries’ supply chains, together with monetary and fiscal stimulus, contributed to dampening the economic impact of COVID-19 over time. In this post, I discuss a new framework that analyzes how changes in supply chains can drive economic growth in the long run and mitigate recessions in the short run.
David Dam, Meghana Gaur, Fatih Karahan, Laura Pilossoph, and Will Schirmer
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.
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.
At the end of March, we launched the Weekly Economic Index (WEI) as a tool to monitor changes in real activity during the pandemic. The rapid deterioration in economic conditions made it important to assess developments as soon as possible, rather than waiting for monthly and quarterly data to be released. In this post, we describe how the WEI has measured the effects of COVID-19. So far in 2020, the WEI has synthesized daily and weekly data to measure GDP growth remarkably well. We document this performance, and we offer some guidance on evaluating the WEI’s forecasting abilities based on 2020 data and interpreting WEI updates and revisions.
Uyanga Byambaa, Beverly Hirtle, Anna Kovner, and Matthew Plosser
Supervision and regulation are critical tools for the promotion of stability and soundness in the financial sector. In a prior post, we discussed findings from our recent research paper which examines the impact of supervision on bank performance (see earlier post How Does Supervision Affect Banks?). As described in that post, we exploit new supervisory data and develop a novel strategy to estimate the impact of supervision on bank risk taking, earnings, and growth. We find that bank holding companies (BHCs or “banks”) that receive more supervisory attention have less risky loan portfolios, but do not have lower growth or profitability. In this post, we examine the benefits of supervision over time, and especially during banking industry downturns.
The COVID-19 outbreak has sparked urgent questions about the impact of pandemics, and associated countermeasures, on the real economy. Policymakers are in uncharted territory, with little guidance on what the expected economic fallout will be and how the crisis should be managed. In this blog post, we use insights from a recent research paper to discuss two sets of questions. First, what are the real economic effects of a pandemic—and are these effects temporary or persistent? Second, how does the local public health response affect the economic severity of the pandemic? In particular, do non-pharmaceutical interventions (NPIs) such as social distancing have economic costs, or do policies that slow the spread of the pandemic also reduce its economic severity?
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.
In recent years there has been a lot of interest in the effect of income inequality (heterogeneity) on the economy, from both academics and policymakers. Researchers have developed Heterogeneous Agent New Keynesian (HANK) models that incorporate heterogeneity and uninsurable idiosyncratic risk into the New Keynesian models that have become a cornerstone of monetary policy analysis. This research has argued that heterogeneity and idiosyncratic risk change many features of New Keynesian models – the
transmission of conventional monetary policy, the forward guidance puzzle, fiscal multipliers, the efficacy of targeted transfers and automatic stabilizers, among others. However, the source of the difference between HANK and representative agent New Keynesian (RANK) models remains unclear. This is because HANK models are typically not analytically tractable, leaving it unclear what exactly is driving the results. To shed light on the macroeconomic consequences of heterogeneity, we develop a stylized HANK model that contains key features present in more complicated HANK models.
In our previous post, we presented evidence suggesting that labor market indicators provide the most reliable information for dating the U.S. business cycle. In this post, we further develop the case. In fact, the unemployment rate has provided an almost perfect record of distinguishing the beginning of recessions in the post-war U.S. economy. We also show that using more granular labor market data, such as by region or industry, also provides valuable information about the state of the business cycle.
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.
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