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Newsletter
The Stay-at-Home Labor Market: Google Searches, Unemployment Insurance, and Public Health Orders
This article looks at the relationships between internet searches for unemployment-related terms, unemployment insurance (UI), and the public health orders issued in the U.S. during the Covid-19 pandemic. We find that Google searches for unemployment-related subjects surged before the record increase in initial UI claims, which in turn peaked before the public health orders were implemented. As of mid-April 2020, these orders covered the vast majority of the U.S. population. Since then, the rates of increase in both search activity and initial UI claims have slowed.
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.
Working Paper
Tracking U.S. Consumers in Real Time with a New Weekly Index of Retail Trade
We create a new weekly index of retail trade that accurately predicts the U.S. Census Bureau's Monthly Retail Trade Survey (MRTS). The index's weekly frequency provides an early snapshot of the MRTS and allows for a more granular analysis of the aggregate consumer response to fast-moving events such as the Covid-19 pandemic. To construct the index, we extract the co-movement in weekly data series capturing credit and debit card transactions, foot traffic, gasoline sales, and consumer sentiment. To ensure that the index is representative of aggregate retail spending, we implementa novel ...
Working Paper
Tracking U.S. Consumers in Real Time with a New Weekly Index of Retail Trade
We create a new weekly index of retail trade that accurately predicts the U.S. Census Bureau’s Monthly Retail Trade Survey (MRTS). The index’s weekly frequency provides an early snapshot of the MRTS and allows for a more granular analysis of the aggregate implications of policies implemented during the Covid-19 pandemic. To construct the index, we extract the co-movement in several weekly data series capturing credit & debit card transactions and revenues, mobility, and consumer sentiment as well as monthly retail and food services sales excluding automotive spending (ex. autos) from the ...
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 ...
What Can Revisions to the NFCI Tell Us About Stock Market Volatility?
In this blog post, we document that recent revisions to the Chicago Fed’s National Financial Conditions Index (NFCI) have been large and clustered in time—a pattern not seen since the 2007–09 global financial crisis. As financial conditions tightened early on during the Covid-19 outbreak here in the U.S., there were large positive revisions to the NFCI through much of March. We show that revisions of this magnitude and in this direction have often preceded substantial increases in stock market volatility. More recently, in late March and April, the large negative revisions to the NFCI ...
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 ...
Working Paper
Tracking U.S. Consumers in Real Time with a New Weekly Index of Retail Trade
We create a new weekly index of retail trade that accurately predicts the U.S. Census Bureau's Monthly Retail Trade Survey (MRTS). The index's weekly frequency provides an early snapshot of the MRTS and allows for a more granular analysis of the aggregate consumer response to fast-moving events such as the Covid-19 pandemic. To construct the index, we extract the co-movement in weekly data series capturing credit and debit card transactions, mobility, gasoline sales, and consumer sentiment. To ensure that the index is representative of aggregate retail spending, we implement a novel ...
Newsletter
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).