IDEAS home Printed from https://ideas.repec.org/a/eee/jmacro/v37y2013icp81-92.html
   My bibliography  Save this article

Soft information and economic activity: Evidence from the Beige Book

Author

Listed:
  • Sadique, Shibley
  • In, Francis
  • Veeraraghavan, Madhu
  • Wachtel, Paul

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.

Suggested Citation

  • Sadique, Shibley & In, Francis & Veeraraghavan, Madhu & Wachtel, Paul, 2013. "Soft information and economic activity: Evidence from the Beige Book," Journal of Macroeconomics, Elsevier, vol. 37(C), pages 81-92.
    • Handle: RePEc:eee:jmacro:v:37:y:2013:i:c:p:81-92
    DOI: 10.1016/j.jmacro.2013.01.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0164070413000189
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jmacro.2013.01.004?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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. Mitchel Y. Abolafia (ed.), 2005. "Markets," Books, Edward Elgar Publishing, number 2788.
    3. 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 923-950, July.
    4. Paul C. Tetlock, 2011. "All the News That's Fit to Reprint: Do Investors React to Stale Information?," The Review of Financial Studies, Society for Financial Studies, vol. 24(5), pages 1481-1512.
    5. Angela K. Davis & Jeremy M. Piger & Lisa M. Sedor, 2012. "Beyond the Numbers: Measuring the Information Content of Earnings Press Release Language," Contemporary Accounting Research, John Wiley & Sons, vol. 29(3), pages 845-868, September.
    6. 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.
    7. 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, June.
    8. Harding, Don & Pagan, Adrian, 2002. "Dissecting the cycle: a methodological investigation," Journal of Monetary Economics, Elsevier, vol. 49(2), pages 365-381, March.
    9. Refet S Gürkaynak & Brian Sack & Eric Swanson, 2005. "Do Actions Speak Louder Than Words? The Response of Asset Prices to Monetary Policy Actions and Statements," International Journal of Central Banking, International Journal of Central Banking, vol. 1(1), May.
    10. 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.
    11. Donna K. Ginther & Madeline Zavodny, 2001. "The Beige Book: Timely information on the regional economy," Economic Review, Federal Reserve Bank of Atlanta, vol. 86(Q3), pages 19-29.
    12. 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.
    13. Michelle T. Armesto & Rub…N Hern¡Ndez-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, February.
    14. Ronchetti, Elvezio, 1985. "Robust model selection in regression," Statistics & Probability Letters, Elsevier, vol. 3(1), pages 21-23, February.
    15. 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, June.
    16. 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, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Niţoi, Mihai & Pochea, Maria-Miruna & Radu, Ştefan-Constantin, 2023. "Unveiling the sentiment behind central bank narratives: A novel deep learning index," Journal of Behavioral and Experimental Finance, Elsevier, vol. 38(C).
    2. Picault, Matthieu & Renault, Thomas, 2017. "Words are not all created equal: A new measure of ECB communication," Journal of International Money and Finance, Elsevier, vol. 79(C), pages 136-156.
    3. Huang, Yu-Lieh & Kuan, Chung-Ming, 2021. "Economic prediction with the FOMC minutes: An application of text mining," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 751-761.
    4. Cuaresma, Jesús Crespo & Huber, Florian & Onorante, Luca, 2019. "The macroeconomic effects of international uncertainty," Working Paper Series 2302, European Central Bank.
    5. Dooruj Rambaccussing & Craig Menzies & Andrzej Kwiatkowski, 2022. "Look who’s Talking: Individual Committee members’ impact on inflation expectations," Dundee Discussion Papers in Economics 305, Economic Studies, University of Dundee.
    6. Ingrid E. Fisher & Margaret R. Garnsey & Mark E. Hughes, 2016. "Natural Language Processing in Accounting, Auditing and Finance: A Synthesis of the Literature with a Roadmap for Future Research," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 23(3), pages 157-214, July.
    7. Weber, Christoph S., 2019. "The effect of central bank transparency on exchange rate volatility," Journal of International Money and Finance, Elsevier, vol. 95(C), pages 165-181.
    8. Ngomba Bodi, Francis Ghislain & Tadadjeu Wemba, Dessy-Karl & Soulemanou, Soulemanou, 2020. "Transparence des Banques Centrales et efficacité de la politique monétaire : quelles implications pour la Banque des Etats de l’Afrique Centrale ? [Central Bank's Transparency and effectiveness of ," MPRA Paper 116436, University Library of Munich, Germany.
    9. Charles S. Gascon & Devin Werner, 2022. "Does the Beige Book Reflect U.S. Employment and Inflation Trends?," Economic Synopses, Federal Reserve Bank of St. Louis, issue 13, pages 1-3, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ingrid E. Fisher & Margaret R. Garnsey & Mark E. Hughes, 2016. "Natural Language Processing in Accounting, Auditing and Finance: A Synthesis of the Literature with a Roadmap for Future Research," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 23(3), pages 157-214, July.
    2. Yan Luo & Linying Zhou, 2020. "Textual tone in corporate financial disclosures: a survey of the literature," International Journal of Disclosure and Governance, Palgrave Macmillan, vol. 17(2), pages 101-110, September.
    3. Ahmad, Khurshid & Han, JingGuang & Hutson, Elaine & Kearney, Colm & Liu, Sha, 2016. "Media-expressed negative tone and firm-level stock returns," Journal of Corporate Finance, Elsevier, vol. 37(C), pages 152-172.
    4. Christina Bannier & Thomas Pauls & Andreas Walter, 2019. "Content analysis of business communication: introducing a German dictionary," Journal of Business Economics, Springer, vol. 89(1), pages 79-123, February.
    5. Tom Marty & Bruce Vanstone & Tobias Hahn, 2020. "News media analytics in finance: a survey," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 60(2), pages 1385-1434, June.
    6. Jeon, Yoontae & McCurdy, Thomas H. & Zhao, Xiaofei, 2022. "News as sources of jumps in stock returns: Evidence from 21 million news articles for 9000 companies," Journal of Financial Economics, Elsevier, vol. 145(2), pages 1-17.
    7. Tim Loughran & Bill Mcdonald, 2016. "Textual Analysis in Accounting and Finance: A Survey," Journal of Accounting Research, Wiley Blackwell, vol. 54(4), pages 1187-1230, September.
    8. Ardia, David & Bluteau, Keven & Boudt, Kris, 2022. "Media abnormal tone, earnings announcements, and the stock market," Journal of Financial Markets, Elsevier, vol. 61(C).
    9. Yekini, Liafisu Sina & Wisniewski, Tomasz Piotr & Millo, Yuval, 2016. "Market reaction to the positiveness of annual report narratives," The British Accounting Review, Elsevier, vol. 48(4), pages 415-430.
    10. Chouliaras, Andreas, 2015. "The Pessimism Factor: SEC EDGAR Form 10-K Textual Analysis and Stock Returns," MPRA Paper 65585, University Library of Munich, Germany.
    11. Senave, Elseline & Jans, Mieke J. & Srivastava, Rajendra P., 2023. "The application of text mining in accounting," International Journal of Accounting Information Systems, Elsevier, vol. 50(C).
    12. Bassyouny, Hesham & Abdelfattah, Tarek & Tao, Lei, 2022. "Narrative disclosure tone: A review and areas for future research," Journal of International Accounting, Auditing and Taxation, Elsevier, vol. 49(C).
    13. repec:hal:spmain:info:hdl:2441/3mgbd73vkp9f9oje7utooe7vpg is not listed on IDEAS
    14. Liebmann, Michael & Orlov, Alexei G. & Neumann, Dirk, 2016. "The tone of financial news and the perceptions of stock and CDS traders," International Review of Financial Analysis, Elsevier, vol. 46(C), pages 159-175.
    15. Ferdinand Graf, 2011. "Mechanically Extracted Company Signals and their Impact on Stock and Credit Markets," Working Paper Series of the Department of Economics, University of Konstanz 2011-18, Department of Economics, University of Konstanz.
    16. Paul Hubert & Fabien Labondance, 2016. "Central Bank Sentiment and Policy Expectations," SciencePo Working papers Main hal-03459227, HAL.
    17. Engelberg, Joseph E. & Reed, Adam V. & Ringgenberg, Matthew C., 2012. "How are shorts informed?," Journal of Financial Economics, Elsevier, vol. 105(2), pages 260-278.
    18. Özgür Arslan‐Ayaydin & James Thewissen & Wouter Torsin, 2021. "Disclosure tone management and labor unions," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 48(1-2), pages 102-147, January.
    19. Bannier, Christina E. & Pauls, Thomas & Walter, Andreas, 2017. "CEO-speeches and stock returns," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168192, Verein für Socialpolitik / German Economic Association.
    20. Paul Hubert & Fabien Labondance, 2019. "Central bank tone and the dispersion of views within monetary policy committees," Sciences Po publications 2019 – 08, Sciences Po.
    21. D. G. DeBoskey & Yan Luo & Linying Zhou, 2019. "CEO power, board oversight, and earnings announcement tone," Review of Quantitative Finance and Accounting, Springer, vol. 52(2), pages 657-680, February.

    More about this item

    Keywords

    Textual analysis; Beige Book; General Inquirer; Forecasting; Economic fluctuations;
    All these keywords.

    JEL classification:

    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jmacro:v:37:y:2013:i:c:p:81-92. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/622617 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.