IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/32026.html
   My bibliography  Save this paper

(Almost) 200 Years of News-Based Economic Sentiment

Author

Listed:
  • Jules H. van Binsbergen
  • Svetlana Bryzgalova
  • Mayukh Mukhopadhyay
  • Varun Sharma

Abstract

Using text from 200 million pages of 13,000 US local newspapers and machine learning methods, we construct a 170-year-long measure of economic sentiment at the country and state levels, that expands existing measures in both the time series (by more than a century) and the cross-section. Our measure predicts GDP (both nationally and locally), consumption, and employment growth, even after controlling for commonly-used predictors, as well as monetary policy decisions. Our measure is distinct from the information in expert forecasts and leads its consensus value. Interestingly, news coverage has become increasingly negative across all states in the past half-century.

Suggested Citation

  • Jules H. van Binsbergen & Svetlana Bryzgalova & Mayukh Mukhopadhyay & Varun Sharma, 2024. "(Almost) 200 Years of News-Based Economic Sentiment," NBER Working Papers 32026, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:32026
    Note: AP CF EFG ME
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w32026.pdf
    Download Restriction: Access to the full text is generally limited to series subscribers, however if the top level domain of the client browser is in a developing country or transition economy free access is provided. More information about subscriptions and free access is available at http://www.nber.org/wwphelp.html. Free access is also available to older working papers.
    ---><---

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

    Citations

    Blog mentions

    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. Are Things Really that Bad?
      by noreply@blogger.com (Michael Ward) in Managerial Econ on 2024-01-11 17:31:00

    Citations

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


    Cited by:

    1. Manish Jha & Jialin Qian & Michael Weber & Baozhong Yang, 2024. "Harnessing Generative AI for Economic Insights," Papers 2410.03897, arXiv.org, revised Oct 2024.
    2. Beckmann, Joscha & Czudaj, Robert L. & Murach, Michael, 2024. "Macroeconomic Effects from Media Coverage of the China-U.S. Trade War on selected EU Countries," MPRA Paper 121751, University Library of Munich, Germany.

    More about this item

    JEL classification:

    • E2 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment
    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles
    • E4 - Macroeconomics and Monetary Economics - - Money and Interest Rates
    • E40 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - General
    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G01 - Financial Economics - - General - - - Financial Crises
    • G1 - Financial Economics - - General Financial Markets
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation
    • G40 - Financial Economics - - Behavioral Finance - - - General

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:nbr:nberwo:32026. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/nberrus.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.