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Looking down the road with ALEX: Forecasting U.S. GDP
In this article, we examine the recovery from the recession that began with the onset of the Covid-19 pandemic in the U.S. To do so, we present and discuss for the first time the results from a mixed-frequency Bayesian vector autoregressive model called ALEX. This model uses 107 monthly and quarterly indicators of economic activity to forecast the near-term path of U.S. real gross domestic product (GDP).
Working Paper
The perils of working with Big Data and a SMALL framework you can use to avoid them
The use of “Big Data” to explain fluctuations in the broader economy or guide the business decisions of a firm is now so commonplace that in some instances it has even begun to rival more traditional government statistics and business analytics. Big data sources can very often provide advantages when compared to these more traditional data sources, but with these advantages also comes the potential for pitfalls. We lay out a framework called SMALL that we have developed in order to help interested parties as they navigate the big data minefield. Based on a set of five questions, the SMALL ...
Newsletter
Measuring the Effects of the Covid-19 Delta Wave on the U.S. Hourly Labor Market
In this article, we take a closer look at the implications of rising Covid-19 cases and vaccination rates for the U.S. hourly labor market. To do so, we rely on geographic variation in the high-frequency data collected by the firm Homebase with its timekeeping software. This data source allows us to make use of U.S. state-level variation on a daily basis in order to decompose the effects on hourly employees and hours worked from both rising cases and vaccinations.
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.
Working Paper
Charged and Almost Ready—What Is Holding Back the Resale Market for Battery Electric Vehicles?
We utilize vehicle registration microdata for all new and used vehicles registered in the U.S. for model years 2010-2022 to study the market for used battery electric vehicles (BEVs). From these records, we establish two stylized facts: 1) BEVs enter the used market at the slowest rate compared to any other powertrain technology, and 2) BEVs are driven significantly less than vehicles featuring other powertrain technologies. We connect these facts through a statistical model of used vehicle registration counts and find that there are significant behavioral differences between BEV and other ...
A Closer Look at the Correlation Between Google Trends and Initial Unemployment Insurance Claims
Since the onset of the pandemic, there has been growing interest in tracking labor market activity with “big data” sources like Google Trends.1 Just as an example, one can track how the number of Google searches with the term unemployment office has changed over the past week for the Chicago metro area or explore how unemployment became one of the top searched issues across the U.S. during the early months of the pandemic here.
Introducing the Chicago Fed Labor Market Indicators
On September 23, 2025, we debuted the Chicago Fed Labor Market Indicators. Updated twice per month, this new data release provides an early read on U.S. labor market conditions: The Chicago Fed Real-Time Unemployment Rate Forecast is a forecast of the U.S. civilian unemployment rate while the Chicago Fed Layoffs and Other Separations Rate and the Chicago Fed Hiring Rate for Unemployed Workers provide further context for the job flows that influence the unemployment rate. In this article, we describe these new indicators and provide additional analysis for their first release for September ...
Working Paper
Using the Eye of the Storm to Predict the Wave of Covid-19 UI Claims
We leverage an event-study research design focused on the seven costliest hurricanes to hit the US mainland since 2004 to identify the elasticity of unemployment insurance filings with respect to search intensity. Applying our elasticity estimate to the state-level Google Trends indexes for the topic “unemployment,” we show that out-of-sample forecasts made ahead of the official data releases for March 21 and 28 predicted to a large degree the extent of the Covid-19 related surge in the demand for unemployment insurance. In addition, we provide a robust assessment of the uncertainty ...
Working Paper
Using the Eye of the Storm to Predict the Wave of Covid-19 UI Claims
We leverage an event-study research design focused on the seven costliest hurricanes to hit the US mainland since 2004 to identify the elasticity of unemployment insurance filings with respect to search intensity. Applying our elasticity estimate to the state-level Google Trends indexes for the topic “unemployment,” we show that out-of-sample forecasts made ahead of the official data releases for March 21 and 28 predicted to a large degree the extent of the Covid-19 related surge in the demand for unemployment insurance. In addition, we provide a robust assessment of the uncertainty ...
What Does the NFCI Tell Us About Future Economic Growth?
The Federal Reserve’s policy tools rely on financial markets to transmit changes in monetary policy to the real economy. For instance, changes in short-term interest rates set by the Fed and faced by financial institutions—e.g., the federal funds rate—affect longer-term rates paid by firms and households. These rate changes in turn impact borrowing and spending decisions. Understanding the current state of financial conditions is, thus, both critical to central bankers and of interest to the wider public.