IDEAS home Printed from https://ideas.repec.org/a/fip/fedles/94348.html
   My bibliography  Save this article

Does the Beige Book Reflect U.S. Employment and Inflation Trends?

Author

Listed:
  • Charles S. Gascon
  • Devin Werner

Abstract

Simple, automated text analysis can extract useful metrics from the Beige Book.

Suggested Citation

  • 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.
    • Handle: RePEc:fip:fedles:94348
    as

    Download full text from publisher

    File URL: https://research.stlouisfed.org/publications/economic-synopses/2022/06/03/does-the-beige-book-reflect-u-s-employment-and-inflation-trends
    File Function: Full text
    Download Restriction: no
    File URL: https://files.stlouisfed.org/files/htdocs/publications/economic-synopses/2022/06/03/does-the-beige-book-reflect-u-s-employment-and-inflation-trends.pdf
    File Function: Full text
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    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. Kevin L. Kliesen & Devin Werner, 2022. "Using Beige Book Text Analysis to Measure Supply Chain Disruptions," Economic Synopses, Federal Reserve Bank of St. Louis, issue 18, pages 1-2, 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. 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.
    2. 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.
    3. Ilias Filippou & Christian Garciga & James Mitchell & My T. Nguyen, 2024. "Regional Economic Sentiment: Constructing Quantitative Estimates from the Beige Book and Testing Their Ability to Forecast Recessions," Working Papers 2024-08, Federal Reserve Bank of Cleveland.
    4. 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.
    5. Santiago Etchegaray Alvarez, 2022. "Proyecciones macroeconómicas con datos en frecuencias mixtas. Modelos ADL-MIDAS, U-MIDAS y TF-MIDAS con aplicaciones para Uruguay," Documentos de trabajo 2022004, Banco Central del Uruguay.
    6. Elena Andreou & Eric Ghysels & Andros Kourtellos, 2013. "Should Macroeconomic Forecasters Use Daily Financial Data and How?," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(2), pages 240-251, April.
    7. Sarun Kamolthip, 2021. "Macroeconomic Forecasting with LSTM and Mixed Frequency Time Series Data," PIER Discussion Papers 165, Puey Ungphakorn Institute for Economic Research.
    8. 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.
    9. 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.
    10. Hanan Naser, 2015. "Estimating and forecasting Bahrain quarterly GDP growth using simple regression and factor-based methods," Empirical Economics, Springer, vol. 49(2), pages 449-479, September.
    11. Paul Gower & Florian Meier & Karl Shutes, 2019. "Regulator Communication and Market Confidence in Difficult Times: Lessons from the Great Financial Crisis," Eurasian Journal of Economics and Finance, Eurasian Publications, vol. 7(4), pages 1-24.
    12. Benjamin Born & Michael Ehrmann & Marcel Fratzscher, 2011. "Macroprudential policy and central bank communication," BIS Papers chapters, in: Bank for International Settlements (ed.), Macroprudential regulation and policy, volume 60, pages 107-110, Bank for International Settlements.
    13. Cuaresma, Jesús Crespo & Huber, Florian & Onorante, Luca, 2019. "The macroeconomic effects of international uncertainty," Working Paper Series 2302, European Central Bank.
    14. Messina, Jeffrey D. & Sinclair, Tara M. & Stekler, Herman, 2015. "What can we learn from revisions to the Greenbook forecasts?," Journal of Macroeconomics, Elsevier, vol. 45(C), pages 54-62.
    15. Hamza Bennani & Matthias Neuenkirch, 2017. "The (home) bias of European central bankers: new evidence based on speeches," Applied Economics, Taylor & Francis Journals, vol. 49(11), pages 1114-1131, March.
    16. 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.
    17. Ghysels, Eric & Ball, Ryan & Zhou, Huan, 2014. "Can we Automate Earnings Forecasts and Beat Analysts?," CEPR Discussion Papers 10186, C.E.P.R. Discussion Papers.
    18. Ilias Filippou & Christian Garciga & James Mitchell & My T. Nguyen, 2024. "Regional Economic Sentiment: Constructing Quantitative Estimates from the Beige Book and Testing Their Ability to Forecast Recessions," Economic Commentary, Federal Reserve Bank of Cleveland, vol. 2024(08), pages 1-8, April.
    19. Herman O. Stekler & Hilary Symington, 2014. "How Did The Fomc View The Great Recession As It Was Happening?: Evaluating The Minutes From Fomc Meetings, 2006-2010," Working Papers 2014-005, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    20. David Bholat & Stephen Hans & Pedro Santos & Cheryl Schonhardt-Bailey, 2015. "Text mining for central banks," Handbooks, Centre for Central Banking Studies, Bank of England, number 33, April.

    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:fip:fedles:94348. 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: Anna Oates (email available below). General contact details of provider: https://edirc.repec.org/data/frbslus.html .

    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.