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Identifying asymmetry in the language of the Beige Book: a mixed data sampling approach

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  • Michelle T. Armesto
  • Ruben Hernandez-Murillo
  • Michael T. Owyang
  • Jeremy M. Piger

Abstract

Studies of the predictive ability of the Federal Reserve's Beige Book, an anecdotal measure of regional economic conditions, for aggregate output and employment have proven inconclusive. This might be attributed, in part, to the irregular release schedule of the Beige Book. In this paper, we use a model that allows for data sampling at mixed frequencies to analyze the predictive power of the Beige Book for both aggregate and regional data. We find that the Beige Book's national summary predicts GDP and aggregate employment, but that the information content in the district reports for regional employment is mixed. In addition, there appears to be an asymmetry in the predictive content of the Beige Book language. At the national level, pessimistic language in the national summary reflects the underlying business cycle phase, while optimistic language is informative for higher frequency fluctuations. At the district level, the reverse is true; pessimistic language reflects sharp, temporary economic fluctuations.

Suggested Citation

  • Michelle T. Armesto & Ruben Hernandez-Murillo & Michael T. Owyang & Jeremy M. Piger, 2007. "Identifying asymmetry in the language of the Beige Book: a mixed data sampling approach," Working Papers 2007-010, Federal Reserve Bank of St. Louis.
  • Handle: RePEc:fip:fedlwp:2007-010
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    References listed on IDEAS

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    1. Balke, Nathan S & Petersen, D'Ann, 2002. "How Well Does the Beige Book Reflect Economic Activity? Evaluating Qualitative Information Quantitatively," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 34(1), pages 114-136, February.
    2. David Fettig & Arthur J. Rolnick & David E. Runkle, 1999. "The Federal Reserve's Beige Book: A better mirror than crystal ball," The Region, Federal Reserve Bank of Minneapolis, vol. 13(Mar), pages 10-13,28-32.
    3. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    4. Angela K. Davis & Jeremy M. Piger & Lisa M. Sedor, 2006. "Beyond the numbers: an analysis of optimistic and pessimistic language in earnings press releases," Working Papers 2006-005, Federal Reserve Bank of St. Louis.
    5. Franklin D. Berger & Keith R. Phillips, 1995. "A new quarterly output measure for Texas," Economic and Financial Policy Review, Federal Reserve Bank of Dallas, issue Q III, pages 16-23.
    6. Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2004. "The MIDAS Touch: Mixed Data Sampling Regression Models," University of California at Los Angeles, Anderson Graduate School of Management qt9mf223rs, Anderson Graduate School of Management, UCLA.
    7. Hernandez-Murillo, Ruben & Owyang, Michael T., 2006. "The information content of regional employment data for forecasting aggregate conditions," Economics Letters, Elsevier, vol. 90(3), pages 335-339, March.
    8. Nathan S. Balke & Mine K. Yücel, 2000. "Evaluating the Eleventh District's Beige Book," Economic and Financial Policy Review, Federal Reserve Bank of Dallas, issue Q IV, pages 2-10.
    9. Madeline Zavodny & Donna K. Ginther, 2005. "Does the Beige Book Move Financial Markets?," Southern Economic Journal, John Wiley & Sons, vol. 72(1), pages 138-151, July.
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    Cited by:

    1. Ralf Becker & Adam Clements & Robert O'Neill, 2010. "A Cholesky-MIDAS model for predicting stock portfolio volatility," Centre for Growth and Business Cycle Research Discussion Paper Series 149, Economics, The University of Manchester.

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    Keywords

    economic conditions - United States; Federal Open Market Committee; Federal Reserve System; Business forecasting;
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