IDEAS home Printed from https://ideas.repec.org/a/ucp/ecdecc/doi10.1086-738470.html

Spatial Clustering of Natural Disasters, Selection in Migration, and Economic Outcomes

Author

Listed:
  • Junni Pan

Abstract

This paper shows that natural disasters with higher spatial clustering are associated with positive selection in migration. Focusing on extreme precipitation events in rural Chinese counties, I analyze their effects using census and rainfall data within a difference-in-differences framework. The results show that natural disasters significantly increase out-migration, primarily by worsening local economic conditions. More spatially clustered disasters induce a stronger response from younger, male, and better-educated individuals, who are associated with longer migration distances and better economic outcomes. A migration decision model suggests that more spatially clustered disasters may exacerbate inequalities in mobility. Targeted subsidies for individuals with lower productivity and higher migration costs could help promote more equitable access to economic opportunities.

Suggested Citation

  • Junni Pan, 2026. "Spatial Clustering of Natural Disasters, Selection in Migration, and Economic Outcomes," Economic Development and Cultural Change, University of Chicago Press, vol. 75(1), pages 431-461.
  • Handle: RePEc:ucp:ecdecc:doi:10.1086/738470
    DOI: 10.1086/738470
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1086/738470
    Download Restriction: Access to the online full text or PDF requires a subscription.

    File URL: http://dx.doi.org/10.1086/738470
    Download Restriction: Access to the online full text or PDF requires a subscription.

    File URL: https://libkey.io/10.1086/738470?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

    for a different version of it.

    More about this item

    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:ucp:ecdecc:doi:10.1086/738470. 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: Journals Division (email available below). General contact details of provider: https://www.journals.uchicago.edu/EDCC .

    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.