Search Results
Tracking the Economic Impact of the Pandemic Using High-Frequency Data
High-frequency data can provide a quicker snapshot of economic conditions than data that take weeks or months to become available.
Newsletter
Blending Traditional and Alternative Labor Market Data with CHURN
In this article, we present a new real-time model called CHURN—short for Chicago Fed Unemployment Rate Nowcast. CHURN provides a weekly tracking estimate for the civilian unemployment rate (UR) produced by the U.S. Bureau of Labor Statistics (BLS). To do so, CHURN blends monthly statistics on job flows (i.e., job-finding and job-separation rates) from the BLS and other traditional labor market indicators with alternative high-frequency indicators from private sector sources.
What Causes “Jumps” in Stock Prices?
An analysis examines which types of macroeconomic announcements tend to be most often associated with jumps in U.S. stock prices.
Working Paper
Testing for Multi-Asset Systemic Tail Risk
We develop a testing framework to measure market-wide (systemic) tail risk in the cross-section of asset returns. Using high-frequency data on individual U.S. stocks and sector-specific ETF portfolios, we estimate time-varying jump intensities and test for multi-asset tail risk around Fed policy announcements. The magnitude of the tail risk induced by Fed policy announcements varies over the business cycle, peaks during the global financial crisis, and remains high during phases of unconventional monetary policy. While most FOMC announcements generate systemic left-tail risk, there is no ...
Working Paper
Mind Your Language: Market Responses to Central Bank Speeches
Post-meeting central bank communication often moves markets, but researchers have paid less attention to the more frequent central bankers’ speeches. We create a novel dataset of U.S. Federal Reserve speeches and develop supervised multimodal natural language processing methods to identify how monetary policy news affect bond and stock market volatility and tail risk through implied changes in forecasts of GDP, inflation, and unemployment. We find that forecast revisions derived from FOMC member speeches can help explain volatility and tail risk in both equity and bond markets. Speeches ...
Working Paper
Heterogeneity in the Marginal Propensity to Consume: Evidence from Covid-19 Stimulus Payments
We identify 22,340 recipients of Covid-19 Economic Impact Payments in anonymized transaction-level debit card data from Facteus. We use an event study framework to show that in the two weeks following a sudden $1,200 payment from the IRS, consumers immediately increased spending by an average of $604, implying a marginal propensity to consume (MPC) of 50%. Consumer spending fell back to normal levels after two weeks. Stimulus recipients who live paycheck-to-paycheck spend 62% of the stimulus payment within two weeks, while recipients who save much of their monthly income spend only 35% of the ...
Working Paper
Systemic Tail Risk: High-Frequency Measurement, Evidence and Implications
We develop a new framework to measure market-wide (systemic) tail risk in the cross-section of high-frequency stock returns. We estimate the time-varying jump intensities of asset prices and introduce a testing approach that identifies multi-asset tail risk based on the release times of scheduled news announcements. Using high-frequency data on individual U.S. stocks and sector-specific ETF portfolios, we find that most of the FOMC announcements create systemic left tail risk, but there is no evidence that macro announcements do so. The magnitude of the tail risk induced by Fed news varies ...
Working Paper
Fed-Driven Systemic Tail Risk: High-Frequency Measurement, Evidence and Implications
We develop a framework to measure market-wide (systemic) tail risk in the cross-section of asset returns. Using high-frequency data on individual U.S. stocks and sector-specific ETF portfolios, we estimate time-varying jump intensities and multi-asset tail risk around Fed policy announcements. While most FOMC announcements generate systemic left-tail risk, there is no evidence that macro announcements have a similar effect. The magnitude of the tail risk induced by Fed policy announcements varies over the business cycle, peaks during the global financial crisis and remains high during phases ...
Working Paper
Do Stay-at-Home Orders Cause People to Stay at Home? Effects of Stay-at-Home Orders on Consumer Behavior
We link the county-level rollout of stay-at-home orders during the Covid-19 pandemic to anonymized cell phone records and consumer spending data. We document three patterns. First, stay-at-home orders caused people to stay home: county-level measures of mobility declined 7–8% within two days of when the stay-at-home order went into effect. Second, stay-at-home orders caused large reductions in spending in sectors associated with mobility: small businesses and large retail chains. Third, we estimate fairly uniform responses to stay-at-home orders across the country; effects do not vary by ...
Working Paper
Sluggish news reactions: A combinatorial approach for synchronizing stock jumps
Stock prices often react sluggishly to news, producing gradual and delayed jumps. Econometricians typically treat these sluggish reactions as microstructure effects and settle for a coarse sampling grid to guard against them. We introduce new methods to synchronize mistimed stock returns on a fine sampling grid that allow us to better approximate the true common jumps in the efficient prices of related stocks in an application to Dow 30 data. The synchronized jumps produce better jump covariance estimates and estimates of the realized jump betas with better forecasting power, and superior ...