Measuring the Information Content of the Beige Book: A Mixed Data Sampling Approach

Michelle T. Armesto, Ruben Hernandez-Murillo (), Michael T. Owyang () and Jeremy Piger ()

Journal of Money, Credit and Banking, 2009, vol. 41, issue 1, pages 35-55

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. Copyright (c) 2009 The Ohio State University.

Date: 2009

Downloads: (external link)
http://www.blackwell-synergy.com/doi/abs/10.1111/j.1538-4616.2008.00186.x link to full text (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: http://EconPapers.repec.org/RePEc:mcb:jmoncb:v:41:y:2009:i:1:p:35-55

Access Statistics for this article

Journal of Money, Credit and Banking is edited by Pok-Sang Lam, Deborah Lucas, Masao Ogaki and Kenneth D. West

More articles in Journal of Money, Credit and Banking from Blackwell Publishing
Series data maintained by Christopher F. Baum ().