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Author:Butters, R. Andrew 

Journal Article
A New “Big Data” Index of U.S. Economic Activity

The authors present a new ?big data? index of U.S. economic activity that can be used to track business and inflation cycles in real time and estimate monthly real gross domestic product growth.
Economic Perspectives , Issue 1 , Pages 1-30

Working Paper
Gathering insights on the forest from the trees: a new metric for financial conditions

By incorporating the Harvey accumulator into the large approximate dynamic factor framework of Doz et al. (2006), we are able to construct a coincident index of financial conditions from a large unbalanced panel of mixed frequency financial indicators. We relate our financial conditions index, or FCI, to the concept of a "financial crisis" using Markov-switching techniques. After demonstrating the ability of the index to capture "crisis" periods in U.S. financial history, we present several policy-geared threshold rules for the FCI using Receiver Operator Characteristics (ROC) curve ...
Working Paper Series , Paper WP-2010-07

Working Paper
Forecasting Economic Activity with Mixed Frequency Bayesian VARs

Mixed frequency Bayesian vector autoregressions (MF-BVARs) allow forecasters to incorporate a large number of mixed frequency indicators into forecasts of economic activity. This paper evaluates the forecast performance of MF-BVARs relative to surveys of professional forecasters and investigates the influence of certain specification choices on this performance. We leverage a novel real-time dataset to conduct an out-of-sample forecasting exercise for U.S. real gross domestic product (GDP). MF-BVARs are shown to provide an attractive alternative to surveys of professional forecasters for ...
Working Paper Series , Paper WP-2016-5

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 Series , Paper WP-2020-10

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 Series , Paper WP-2020-10

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 Series , Paper WP 2020-10

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 Series , Paper WP-2020-35

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 Series , Paper WP-2020-35

Journal Article
What is the relationship between large deficits and inflation in industrialized countries?

Examining industrialized countries, the authors find that large deficits are not associated with higher inflation contemporaneously, nor are they associated with the emergence of higher inflation in subsequent years. This finding suggests that countries that can afford large deficits have built solid reputations and institutions supporting a sound monetary policy and the reversion to a stable fiscal regime.
Economic Perspectives , Volume 34 , Issue Q III , Pages 83-100

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).
Chicago Fed Letter , Issue 447 , Pages 5

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