IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/33016.html
   My bibliography  Save this paper

Pitfalls of Demographic Forecasts of US Elections

Author

Listed:
  • Richard Calvo
  • Vincent Pons
  • Jesse M. Shapiro

Abstract

Many observers have forecast large partisan shifts in the US electorate based on demographic trends. Such forecasts are appealing because demographic trends are often predictable even over long horizons. We backtest demographic forecasts using data on US elections since 1952. We envision a forecaster who fits a model using data from a given election and uses that model, in tandem with a projection of demographic trends, to predict future elections. Even a forecaster with perfect knowledge of future demographic trends would have performed poorly over this period—worse even than one who simply guesses that each election will have a 50-50 partisan split. Enriching the set of demographics available does not change this conclusion. We discuss both mechanical and economic reasons for this finding, and show suggestive evidence that parties adjust their platforms in accordance with changes in the electorate.

Suggested Citation

  • Richard Calvo & Vincent Pons & Jesse M. Shapiro, 2024. "Pitfalls of Demographic Forecasts of US Elections," NBER Working Papers 33016, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:33016
    Note: POL
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w33016.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 search for a different version of it.

    More about this item

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • D72 - Microeconomics - - Analysis of Collective Decision-Making - - - Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior
    • J11 - Labor and Demographic Economics - - Demographic Economics - - - Demographic Trends, Macroeconomic Effects, and Forecasts
    • P0 - Political Economy and Comparative Economic Systems - - General

    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:33016. 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.