IDEAS home Printed from https://ideas.repec.org/a/bla/reesec/v51y2023i5p1079-1107.html
   My bibliography  Save this article

The amenity value of natural views

Author

Listed:
  • Timothy L. Hamilton
  • Erik B. Johnson

Abstract

We estimate nonmarket values for natural views in an urban setting. These views contain the aesthetics of natural areas commonly found in public parks and open space, and offer an aspect of property valuation that previous research is unable to disentangle from proximity to parks and open space. We incorporate machine learning techniques on Google Street View images to identify natural views in an urban setting. We find positive capitalization rates associated with household views of park‐like properties. Estimates are robust to a variety of specifications, including models that are identified off of new developments on neighboring properties and falsification tests that help to rule out the effect of a broader neighborhood environment. From a policy perspective, our results inform as to the optimal size, location, and shape of open space. Furthermore, machine learning methods used in the construction of our view variable provide a potentially powerful tool for other nonmarket valuation studies.

Suggested Citation

  • Timothy L. Hamilton & Erik B. Johnson, 2023. "The amenity value of natural views," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 51(5), pages 1079-1107, September.
    • Handle: RePEc:bla:reesec:v:51:y:2023:i:5:p:1079-1107
    DOI: 10.1111/1540-6229.12451
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/1540-6229.12451
    Download Restriction: no
    File URL: https://libkey.io/10.1111/1540-6229.12451?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
    ---><---

    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:bla:reesec:v:51:y:2023:i:5:p:1079-1107. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/areueea.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.