Skip to main content Accessibility help
×
Home
Hostname: page-component-558cb97cc8-kfd6t Total loading time: 0.256 Render date: 2022-10-06T12:23:50.930Z Has data issue: true Feature Flags: { "shouldUseShareProductTool": true, "shouldUseHypothesis": true, "isUnsiloEnabled": true, "useRatesEcommerce": false, "displayNetworkTab": true, "displayNetworkMapGraph": true, "useSa": true } hasContentIssue true

Ensemble Predictions of the 2012 US Presidential Election

Published online by Cambridge University Press:  27 September 2012

Jacob M. Montgomery
Affiliation:
Washington University, St. Louis
Florian M. Hollenbach
Affiliation:
Duke University
Michael D. Ward
Affiliation:
Duke University

Extract

For more than two decades, political scientists have created statistical models aimed at generating out-of-sample predictions of presidential elections. In 2004 and 2008, PS: Political Science and Politics published symposia of the various forecasting models prior to Election Day. This exercise serves to validate models based on accuracy by garnering additional support for those that most accurately foretell the ultimate election outcome. Implicitly, these symposia assert that accurate models best capture the essential contexts and determinants of elections. In part, therefore, this exercise aims to develop the “best” model of the underlying data generating process. Scholars comparatively evaluate their models by setting their predictions against electoral results while also giving some attention to the models' inherent plausibility, parsimony, and beauty.

Type
Symposium: Forecasting the 2012 American National Elections
Copyright
Copyright © American Political Science Association 2012

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

Bartels, L. M., 1997. “Specification Uncertainty and Model Averaging.” American Journal of Political Science 41 (2): 641–74.CrossRefGoogle Scholar
Bartels, L. M., and Zaller, J.. 2001. “Presidential Vote Models: A Recount.” PS: Political Science and Politics 34 (1): 920.Google Scholar
Berrocal, V. J., Raftery, A. E., Gneiting, T., and Steed, R. C.. 2010. “Probabilistic Weather Forecasting for Winter Road Maintenance.” Journal of the American Statistical Association 105 (490): 522–37.CrossRefGoogle Scholar
Billio, M., Casarin, R., Van Dijk, H. K., and Ravazzolo, F.. 2010. Combining Predictive Densities Using Bayesian Filtering with Applications to US Economics Data. Norges Bank Working Paper. http://ssrn.com/abstract=1735421 (accessed June 1, 2011).Google Scholar
Brock, W. A., Durlauf, S. N., and West, K. D.. 2007. “Model Uncertainty and Policy Evaluation: Some Theory and Empirics.” Journal of Econometrics 136 (2): 629–64.CrossRefGoogle Scholar
Chmielecki, R. M., and Raftery, A. E.. 2010. “Probabilistic Visibility Forecasting Using Bayesian Model Averaging.” Monthly Weather Review 139 (5): 1626–36.CrossRefGoogle Scholar
Feldkircher, M. 2012. “Forecast Combination and Bayesian Model Averaging: A Prior Sensitivity Analysis.” Journal of Forecasting 31 (4): 361–76.CrossRefGoogle Scholar
Fraley, C., Raftery, A. E., and Gneiting, T.. 2010. “Calibrating Multimodel Forecast Ensembles with Exchangeable and Missing Members Using Bayesian Model Averaging.” Monthly Weather Review 138 (1): 190202.CrossRefGoogle Scholar
Gneiting, T., and Thorarinsdottir, T. L.. 2010. “Predicting Inflation: Professional Experts Versus No-Change Forecasts.” Working Paper. http://arxiv.org/abs/1010.2318v1 (accessed June 15, 2011).Google Scholar
Koop, G., and Korobilis, D.. 2009. “Forecasting Inflation Using Dynamic Model Averaging.” Working Paper. http://personal.strath.ac.uk/gary.koop/koop_korobilis_forecasting_inflation_using_DMA.pdf (accessed May 25, 2011).Google Scholar
Montgomery, J. M., Hollenbach, F. M., and Ward, M. D.. 2012a. “Improving Predictions Using Ensemble Bayesian Model Averaging.” Political Analysis 20 (3): 271–91.CrossRefGoogle Scholar
Montgomery, J. M., Hollenbach, F. M., and Ward, M. D.. 2012b. “Say Yes to the Guess: Ensemble Methods to Predict Unemployment and Inflation.” In Proceedings of the 2012 Annual Meeting. New Orleans, USA, Aug/Sept Prepared for the 2012 Annual Meeting. American Political Science Association.Google Scholar
Montgomery, J. M., and Nyhan, B.. 2010. “Bayesian Model Averaging: Theoretical Developments and Practical Applications.” Political Analysis 18 (2): 245–70.CrossRefGoogle Scholar
Raftery, A. E., Gneiting, T., Balabdaoui, F., and Polakowski, M.. 2005. “Using Bayesian Model Averaging to Calibrate Forecast Ensembles.” Monthly Weather Review 133 (5): 1155–74.CrossRefGoogle Scholar
Stevens, J., 2012. “Political Scientists Are Lousy Forecasters.” New York Times Sunday Review, 24 June. SR6.Google Scholar
Wright, J. H. 2008. “Bayesian Model Averaging and Exchange Rate Forecasts.” Journal of Econometrics 146 (2): 329–41.CrossRefGoogle Scholar
Wright, J. H. 2009. “Forecasting US Inflation by Bayesian Model Averaging.” Journal of Forecasting 28 (2): 131–44.CrossRefGoogle Scholar
6
Cited by

Save article to Kindle

To save this article to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Ensemble Predictions of the 2012 US Presidential Election
Available formats
×

Save article to Dropbox

To save this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you used this feature, you will be asked to authorise Cambridge Core to connect with your Dropbox account. Find out more about saving content to Dropbox.

Ensemble Predictions of the 2012 US Presidential Election
Available formats
×

Save article to Google Drive

To save this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you used this feature, you will be asked to authorise Cambridge Core to connect with your Google Drive account. Find out more about saving content to Google Drive.

Ensemble Predictions of the 2012 US Presidential Election
Available formats
×
×

Reply to: Submit a response

Please enter your response.

Your details

Please enter a valid email address.

Conflicting interests

Do you have any conflicting interests? *