Hostname: page-component-cd9895bd7-lnqnp Total loading time: 0 Render date: 2024-12-23T09:09:55.286Z Has data issue: false hasContentIssue false
  • English
  • Français

Why Forecast? The Value of Forecasting to Political Science

Published online by Cambridge University Press:  15 October 2020

Keith Dowding Open the ORCID record for Keith Dowding [Opens in a new window]
Keith Dowding*
Affiliation:
Australian National University, Canberra
Get access Rights & Permissions [Opens in a new window]

Abstract

An abstract is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content.
Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
Type
Forecasting the 2020 US Elections
Information
PS: Political Science & Politics , Volume 54 , Issue 1 , January 2021 , pp. 104 - 106
Copyright
© The Author(s), 2020. Published by Cambridge University Press on behalf of the American Political Science Association

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Abramowitz, Alan I. 2016. “Will Time for Change Mean Time for Trump?” PS: Political Science & Politics 49 (4): 659–60.Google Scholar
Blanchflower, David. 2016. “Experts Get It Wrong Again by Failing to Predict Trump Victory.” Guardian, November 14. https://www.theguardian.com/business/2016/nov/09experts-trump-victory-economic-political-forecasters-recession.Google Scholar
Cuzan, Alfred G. 2020. “The Campbell Collection of Presidential Election Forecasts: 1984-2016: A Review.” PS: Political Science & Politics doi: 10.1017/S1049096520001341.Google Scholar
Dowding, Keith. 2016. The Philosophy and Methods of Political Science. London: Palgrave.Google Scholar
Dowding, Keith, and Miller, Charles. 2019. “On Prediction in Political Science.” European Journal of Political Research 58 (3): 1003–21.Google Scholar
Erikson, Robert S., and Wlezien, Christopher. 2016. “Forecasting the Presidential Vote with Leading Economic Indicators and the Polls.” PS: Political Science & Politics 49 (4): 669–72.Google Scholar
Hitchcock, Christopher, and Sober, Elliott. 2004. “Prediction versus Accommodation and the Risk of Overfitting. 55(1): 1–34.” British Journal for the Philosophy of Science 55 (1): 1–34.Google Scholar
King, Gary, Keohane, Robert O., and Verba, Sidney. 1994. Designing Social Inquiry: Scientific Inference in Qualitative Research. Princeton: Princeton University Press.Google Scholar
Lewis-Beck, Michael S., and Dassonneville, Ruth. 2015. “Forecasting Elections in Europe: Synthetic Models.” Research and Politics 1 (1): 1–11.Google Scholar
Lewis-Beck, Michael S., and Quinlan, Stephen. 2019. “The Hillary Hypotheses: Testing Candidate Views of Loss.” Perspectives on Politics 17 (3): 646–65.Google Scholar
Lewis-Beck, Michael S., and Stegmaier, Mary. 2014. “US Presidential Election Forecasting.” PS: Political Science & Politics 47 (2): 284–88.Google Scholar
Sances, Michael W. 2019. “How Unusual Was 2016? Flipping Counties, Flipping Voters, and the Education–Party Correlation since 1952.” Perspectives on Politics 17 (3): 666–78.Google Scholar
Schrodt, Philip. 2014. “Seven Deadly Sins of Contemporary Quantitative Political Science.” Journal of Peace Research 5 (12): 287–300.Google Scholar
Shirani-Mehr, Houshmand, Rothschild, David, Goel, Sharad, and Gelman, Andrew. 2018. “Disentangling Bias and Variance in Election Polls.” Journal of the American Statistical Association 113 (522): 607–14.Google Scholar
Westwood, Sean Jeremy, Messing, Soloman, and Leikes, Ypthtach. 2020. “Projecting Confidence: How the Probabilistic Horse Race Confuses and Demobilizes the Public.” Journal of Politics 82 (4): online first.Google Scholar
White, R. 2003. “The Epistemic Advantage of Prediction over Accommodation.” Mind 112 (448): 653–683.Google Scholar