IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/33976.html

State of the Art: Economic Development Through the Lens of Paintings

Author

Listed:
  • Clément Gorin
  • Stephan Heblich
  • Yanos Zylberberg

Abstract

This paper uses 627,369 paintings since 1400 to study how societies experienced major socioeconomic transformations. We develop computer vision algorithms to extract two signals from each artwork—emotional expression and visual indicators of material living standards—and validate them against modern measures of wellbeing and economic output. Our empirical analysis documents how populations experienced socioeconomic changes by exploiting variation in emotional and material signals within artists’ oeuvres and conditional on painting sub-genres. While both respond to shocks to living standards, such as climate or trade, emotional expression also varies with broader economic and institutional conditions, often without corresponding changes in material outcomes. These findings suggest that paintings provide a long-run measure of experienced welfare, complementing conventional indicators of economic performance.

Suggested Citation

  • Clément Gorin & Stephan Heblich & Yanos Zylberberg, 2025. "State of the Art: Economic Development Through the Lens of Paintings," NBER Working Papers 33976, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:33976
    Note: DAE POL
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w33976.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 look for a different version below or

    for a different version of it.

    Other versions of this item:

    Citations

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


    Cited by:

    1. Sukjin Han & Kyungho Lee, 2025. "Copyright and Competition: Estimating Supply and Demand with Unstructured Data," Papers 2501.16120, arXiv.org, revised Sep 2025.
    2. Jacob Carlson, 2025. "Making Interpretable Discoveries from Unstructured Data: A High-Dimensional Multiple Hypothesis Testing Approach," Papers 2511.01680, arXiv.org, revised Jul 2026.

    More about this item

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • O10 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - General
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
    • Z1 - Other Special Topics - - Cultural Economics

    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:33976. 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.