IDEAS home Printed from
   My bibliography  Save this paper

A Spatio‐Temporal Analysis of Climate Change on Corn Yield


  • Wang, Zidong
  • McCarl, Bruce A.
  • Kapilakanchana, Montalee


Crop yields tend to be spatially and temporally correlated due to the systemic nature of land and weather conditions. Recent concern has been focused on whether climate change such as increasing extreme weather events would affect crop yield and yield volatility (Goodwin 2001, Ozaki, et al. 2008). In this paper, a spatio-temporal Conditional Autoregressive Model (ST-CAR model) (Mariella and Tarantino, 2010) will be used to analyze the impact of climate change on crop yield and yield volatility. State level crop yield data from 1950 to 2014 is collected for this study. As an extension of the standard CAR model, a space-time autoregressive matrix will be used in the ST-CAR model to handle both spatial dependence between states and temporal dependence among the examined period. Specifically, the spatial correlation parameter in ST-CAR model varies along time, making it possible to reveal the potential impact of climate change on spatial correlation. Future yield projections will be generated and used in the FASOM model to conduct a welfare analysis. Preliminary results of segment regression shows that breakpoints exist for many states in the US for the last few decades, indicating the potential impact of climate change on yield and yield volatility.

Suggested Citation

  • Wang, Zidong & McCarl, Bruce A. & Kapilakanchana, Montalee, 2016. "A Spatio‐Temporal Analysis of Climate Change on Corn Yield," 2016 Annual Meeting, February 6-9, 2016, San Antonio, Texas 230043, Southern Agricultural Economics Association.
  • Handle: RePEc:ags:saea16:230043

    Download full text from publisher

    File URL:
    Download Restriction: no

    More about this item


    Environmental Economics and Policy; Production Economics;

    NEP fields

    This paper has been announced in the following NEP Reports:


    Access and download statistics


    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:ags:saea16:230043. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (AgEcon Search). General contact details of provider: .

    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 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.