IDEAS home Printed from https://ideas.repec.org/a/eee/intfor/v15y1999i2p137-142.html
   My bibliography  Save this article

Using state polls to forecast presidential election outcomes in the American states

Author

Listed:
  • Holbrook, Thomas M.
  • DeSart, Jay A.

Abstract

No abstract is available for this item.

Suggested Citation

  • Holbrook, Thomas M. & DeSart, Jay A., 1999. "Using state polls to forecast presidential election outcomes in the American states," International Journal of Forecasting, Elsevier, vol. 15(2), pages 137-142, April.
    • Handle: RePEc:eee:intfor:v:15:y:1999:i:2:p:137-142
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0169-2070(98)00060-0
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Souren Soumbatiants & Henry Chappell & Eric Johnson, 2006. "Using state polls to forecast U.S. Presidential election outcomes," Public Choice, Springer, vol. 127(1), pages 207-223, April.
    2. Strömberg, David, 2002. "Optimal Campaigning in Presidential Elections: The Probability of Being Florida," CEPR Discussion Papers 3372, C.E.P.R. Discussion Papers.
    3. Liu, Yezheng & Ye, Chang & Sun, Jianshan & Jiang, Yuanchun & Wang, Hai, 2021. "Modeling undecided voters to forecast elections: From bandwagon behavior and the spiral of silence perspective," International Journal of Forecasting, Elsevier, vol. 37(2), pages 461-483.
    4. Mongrain, Philippe & Nadeau, Richard & Jérôme, Bruno, 2021. "Playing the synthesizer with Canadian data: Adding polls to a structural forecasting model," International Journal of Forecasting, Elsevier, vol. 37(1), pages 289-301.
    5. Elliot Tonkes & Dharma Lesmono, 2010. "Consistency in the US Congressional Popular Opinion Polls and Prediction Markets," Journal of Prediction Markets, University of Buckingham Press, vol. 4(2), pages 45-64, September.
    6. Lesmono, Dharma & Tonkes, Elliot & Burrage, Kevin, 2009. "Opportunistic timing and manipulation in Australian Federal Elections," European Journal of Operational Research, Elsevier, vol. 192(2), pages 677-691, January.
    7. A. Kamakura, Wagner & Afonso Mazzon, Jose & De Bruyn, Arnaud, 2006. "Modeling voter choice to predict the final outcome of two-stage elections," International Journal of Forecasting, Elsevier, vol. 22(4), pages 689-706.

    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:eee:intfor:v:15:y:1999:i:2:p:137-142. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ijforecast .

    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.