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Soft information and economic activity: Evidence from the Beige Book

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  • Sadique, Shibley
  • In, Francis
  • Veeraraghavan, Madhu
  • Wachtel, Paul
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    Abstract

    This study employs text-analysis software to analyze the contents of the Federal Reserve Beige Book summary of national economic and business conditions, with a particular focus on the predictive content of the text. We show that the Beige Book language is a good predictor of economic turning points as it often provides an early indication of future economic activities. During economic upswings, positive tone becomes more prominent and negative tone becomes less prominent. In addition, this study is the first to document that Beige Book tone affects stock market volatility and trading volume.

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    Bibliographic Info

    Article provided by Elsevier in its journal Journal of Macroeconomics.

    Volume (Year): 37 (2013)
    Issue (Month): C ()
    Pages: 81-92

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    Handle: RePEc:eee:jmacro:v:37:y:2013:i:c:p:81-92

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    Web page: http://www.elsevier.com/locate/inca/622617

    Related research

    Keywords: Textual analysis; Beige Book; General Inquirer; Forecasting; Economic fluctuations;

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    References

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    1. Madeline Zavodny & Donna K. Ginther, 2003. "Does the Beige Book move financial markets?," Working Paper 2003-3, Federal Reserve Bank of Atlanta.
    2. Refet Gürkaynak & Brian Sack, 2005. "Do Actions Speak Louder Than Words?The Response of Asset Prices to Monetary Policy Actions and Statements," Computing in Economics and Finance 2005 323, Society for Computational Economics.
    3. Donna K. Ginther & Madeline Zavodny, 2001. "The Beige Book: Timely information on the regional economy," Economic Review, Federal Reserve Bank of Atlanta, issue Q3, pages 19-29.
    4. Thomas Gilbert & Shimon Kogan & Lars Lochstoer & Ataman Ozyildirim, 2012. "Investor Inattention and the Market Impact of Summary Statistics," Management Science, INFORMS, vol. 58(2), pages 336-350, February.
    5. Paul C. Tetlock, 2011. "All the News That's Fit to Reprint: Do Investors React to Stale Information?," Review of Financial Studies, Society for Financial Studies, vol. 24(5), pages 1481-1512.
    6. Ronchetti, Elvezio, 1985. "Robust model selection in regression," Statistics & Probability Letters, Elsevier, vol. 3(1), pages 21-23, February.
    7. Don Harding & Adrian Pagan, 2000. "Disecting the Cycle: A Methodological Investigation," Econometric Society World Congress 2000 Contributed Papers 1164, Econometric Society.
    8. Nathan S. Balke & D'Ann Petersen, 1998. "How well does the Beige Book reflect economic activity? Evaluating qualitative information quantitatively," Working Papers 9802, Federal Reserve Bank of Dallas.
    9. James Doran & David Peterson & S. Price, 2012. "Earnings Conference Call Content and Stock Price: The Case of REITs," The Journal of Real Estate Finance and Economics, Springer, vol. 45(2), pages 402-434, August.
    10. Tim Loughran & Bill Mcdonald, 2011. "When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10‐Ks," Journal of Finance, American Finance Association, vol. 66(1), pages 35-65, 02.
    11. Mitchell, Mark L & Mulherin, J Harold, 1994. " The Impact of Public Information on the Stock Market," Journal of Finance, American Finance Association, vol. 49(3), pages 923-50, July.
    12. Paul C. Tetlock, 2007. "Giving Content to Investor Sentiment: The Role of Media in the Stock Market," Journal of Finance, American Finance Association, vol. 62(3), pages 1139-1168, 06.
    13. Michelle T. Armesto & Rubén Hernández-Murillo & Michael T. Owyang & Jeremy Piger, 2009. "Measuring the Information Content of the Beige Book: A Mixed Data Sampling Approach," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(1), pages 35-55, 02.
    14. Paul C. Tetlock & Maytal Saar-Tsechansky & Sofus Macskassy, 2008. "More Than Words: Quantifying Language to Measure Firms' Fundamentals," Journal of Finance, American Finance Association, vol. 63(3), pages 1437-1467, 06.
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