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

B-Tier
Journal: Journal of Money, Credit, and Banking
Year: 2009
Volume: 41
Issue: 1
Pages: 35-55

Authors (4)

MICHELLE T. ARMESTO (not in RePEc) RUBÉN HERNÁNDEZ‐MURILLO (not in RePEc) MICHAEL T. OWYANG (Federal Reserve Bank of St. Lo...) JEREMY PIGER (University of Oregon)

Score contribution per author:

0.503 = (α=2.01 / 4 authors) × 1.0x B-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

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.

Technical Details

RePEc Handle
repec:wly:jmoncb:v:41:y:2009:i:1:p:35-55
Journal Field
Macro
Author Count
4
Added to Database
2026-01-26