IDEAS home Printed from https://ideas.repec.org/a/uwp/jhriss/v58y2023i4p1207-1241.html
   My bibliography  Save this article

Risk Attitudes, Investment Behavior, and Linguistic Variation

Author

Listed:
  • Juliana Bernhofer
  • Francesco Costantini
  • Matija Kovacic

Abstract

This study explores the relationship between linguistic variation and individual attitudes toward risk and uncertainty. We propose an innovative marker that classifies languages according to the number of nonindicative moods in the grammatical contexts involving uncertainty. We find that speakers of languages that use these moods more intensively are on average more risk averse. Our marker is then used to instrument risk aversion in the model for financial asset accumulation. In addition, by using the Chen (2013) future time reference linguistic marker as a proxy for the subjective discount rate, we disentangle the effects of risk aversion and time preferences on asset accumulation.

Suggested Citation

  • Juliana Bernhofer & Francesco Costantini & Matija Kovacic, 2023. "Risk Attitudes, Investment Behavior, and Linguistic Variation," Journal of Human Resources, University of Wisconsin Press, vol. 58(4), pages 1207-1241.
  • Handle: RePEc:uwp:jhriss:v:58:y:2023:i:4:p:1207-1241
    Note: DOI: https://doi.org/10.3368/jhr.59.2.0119-9999R2
    as

    Download full text from publisher

    File URL: http://jhr.uwpress.org/cgi/reprint/58/4/1207
    Download Restriction: A subscripton is required to access pdf files. Pay per article is available.
    ---><---

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

    Citations

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


    Cited by:

    1. Andrew E Clark & Rong Zhu, 2024. "Taking Back Control? Quasi-Experimental Evidence on the Impact of Retirement on Locus of Control," The Economic Journal, Royal Economic Society, vol. 134(660), pages 1465-1493.
    2. Matija Kovacic & Cristina Elisa Orso, 2024. "Historical roots of women's sorting into STEM occupations," Working Papers 2024: 08, Department of Economics, University of Venice "Ca' Foscari".

    More about this item

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • Z13 - Other Special Topics - - Cultural Economics - - - Economic Sociology; Economic Anthropology; Language; Social and Economic Stratification
    • D14 - Microeconomics - - Household Behavior - - - Household Saving; Personal Finance

    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:uwp:jhriss:v:58:y:2023:i:4:p:1207-1241. 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: http://jhr.uwpress.org/ .

    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.