San Francisco
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Measuring News Sentiment
Adam Hale Shapiro, Moritz Sudhof, Daniel J. Wilson
Federal Reserve Research: San Francisco This paper demonstrates state-of-the-art text sentiment analysis tools while developing a new time-series measure of economic sentiment derived from economic and financial newspaper articles from January 1980 to April 2015. We compare the predictive accuracy of a large set of sentiment analysis models using a sample of articles that have […]
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Taking the Fed at its Word: A New Approach to Estimating Central Bank Objectives using Text Analysis
Adam Hale Shapiro, Daniel J. Wilson
Federal Reserve Research: san francisco We propose a new approach to estimating central bank preferences, including the implicit inflation target, that requires no priors on the underlying macroeconomic structure nor observation of monetary policy actions. Our approach entails directly estimating the central bank’s objective function from the sentiment expressed by policymakers in their internal meetings. […]
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Sellin’ in the Rain: Weather, Climate, and Retail Sales
Brigitte Roth Tran
Federal Reserve Research: SAN FRANCISCO I apply a novel machine-learning based “weather index” method to daily store- level sales data for a national apparel and sporting goods brand to examine short-run responses to weather and long-run adaptation to climate. I find that even when considering potentially offsetting shifts of sales between outdoor and indoor stores, […]