This is the fourth and final post in this series aimed at understanding the gap in COVID-19 intensity by race and by income. The previous three posts focused on the role of mediating variables—such as uninsurance rates, comorbidities, and health resource in the first post; public transportation, and home crowding in the second; and social distancing, pollution, and age composition in the third—in explaining the racial and income gap in the incidence of COVID-19. In this post, we now investigate the role of employment in essential services in explaining this gap.
January 12, 2021
Understanding the Racial and Income Gap in COVID‑19: Social Distancing, Pollution, and Demographics
Chakrabarti, Pinkovskiy, and coauthors investigate the extent to which age, pollution, and social distancing factor in to the income and racial gaps in COVID-19 incidence.
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).
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).
January 6, 2021
The International Spillover of U.S. Monetary Policy via Global Production Linkages
Julian di Giovanni describes work with Galina Hale that employs an empirical framework to quantify the role of the global production network in transmitting U.S. monetary policy across international stock markets.
Posted at 7:00 am in Bank Capital, Banks, Exports, Financial Markets, International Economics, Monetary Policy, Stocks, Tariffs | Permalink
December 23, 2020
Understanding the Impact of COVID‑19: The Top Five LSE Posts of 2020
An annual tradition at Liberty Street Economics is to present our most-read posts of the year. Given the events of 2020, New York Fed economists and guest coauthors focused their analysis on the effects of the coronavirus pandemic, writing some seventy articles since March on the subject. Our leading posts, in terms of traffic, all touch on the theme in some way. Consider this space a hub for COVID-19 coverage for some time to come, and take a look back at the top five posts grabbing attention in 2020.
The New York Fed DSGE Model Forecast—December 2020
This post presents an update of the economic forecasts generated by the Federal Reserve Bank of New York’s dynamic stochastic general equilibrium (DSGE) model. We describe very briefly our forecast and its change since September 2020.
As usual, we wish to remind our readers that the DSGE model forecast is not an official New York Fed forecast, but only an input to the Research staff’s overall forecasting process. For more information about the model and variables discussed here, see our DSGE model Q & A. Note that interactive charts are now available for DSGE model forecasts.
December 22, 2020
How Does Zombie Credit Affect Inflation? Lessons from Europe
Even after the unprecedented stimulus by central banks in Europe following the global financial crisis, Europe’s economic growth and inflation have remained depressed, consistently undershooting projections. In a striking resemblance to Japan’s “lost decades,” the European economy has been recently characterized by persistently low interest rates and the provision of cheap bank credit to impaired firms, or “zombie credit.” In this post, based on a recent staff report, we propose a “zombie credit channel” that links the rise of zombie credit to dis-inflationary pressures.
December 21, 2020
What’s Up with Stocks?
“U.S. stocks are racing toward a second consecutive quarter of dramatic gains, continuing a historic stock-market recovery that few predicted in the depths of the March downturn,” said a September Wall Street Journal article. “The stock market is detached from economic reality. A reckoning is coming,” said the Washington Post. What is going on? In this post, I look not at what stocks have actually done or will do, but at what investors expected should have happened, and what they expect will happen going forward. It turns out that, at least by the particular measure of expectations I consider, investors expected stock returns to be high all along and continue to expect the same in the future.
December 18, 2020
How Did Market Perceptions of the FOMC’s Reaction Function Change after the Fed’s Framework Review?
Survey data reveal a notable shift in market participants’ perceptions of the FOMC’s policy rate “reaction function” in the direction of higher expected inflation and lower expected unemployment ahead of the next rate “liftoff.”
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