Measuring the Information Content of the Beige Book: A Mixed Data Sampling Approach |
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Authors: | MICHELLE T ARMESTO RUBÉN HERNÁNDEZ-MURILLO† MICHAEL T OWYANG‡ JEREMY PIGER§ |
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Institution: | Michelle T. Armesto;is from the Federal Reserve Bank of St. Louis (E-mail: ). Rubén Hernández-Murillo;is from the Federal Reserve Bank of St. Louis (E-mail: ). Michael T. Owyang;is from the Federal Reserve Bank of St. Louis (E-mail: ). Jeremy Piger;is from the University of Oregon, Eugene (E-mail: ). |
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Abstract: | Studies of the predictive ability of the Federal Reserve's Beige Book for aggregate output and employment have proven inconclusive. This might be attributed, in part, to its irregular release schedule. We use a model that allows for data sampling at mixed frequencies to analyze the predictive power of the Beige Book. We find that the Beige Book's national summary and District reports predict GDP and aggregate employment and that most District reports provide information content for regional employment. In addition, there appears to be an asymmetry in the predictive content of the Beige Book language. |
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Keywords: | C50 E27 R11 |
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