The DOI matches its Crossref record; 54 of the 65 references it cites were found in a registry or an index.
Combining forecasts: An application to elections
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Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Combining forecasts has reduced errors from about 10% to 58% (depending on the conditions) compared to the average errors of the uncombined individual forecasts (Graefe, et al 2011).”
From Illusions in Regression Analysis (2011) · cites this paper as Graefe, et al 2011
Citations
Cites
Bates, J. M., & Granger, C. W. J. (1969) · Journal of the Operational Research Society · doi:10.1057/jors.1969.103 · Cited by 3,201
Combining forecasts: A review and annotated bibliography
Clemen, R. T. (1989) · International Journal of Forecasting · doi:10.1016/0169-2070(89)90012-5 · Cited by 2,172
The robust beauty of improper linear models in decision making.
Dawes, R. M. (1979) · American Psychologist · doi:10.1037/0003-066x.34.7.571 · Cited by 2,046
Combination forecasts of output growth in a seven‐country data set
Stock, J. H., & Watson, M. W. (2004) · Journal of Forecasting · doi:10.1002/for.928 · Cited by 1,139
Unit weighting schemes for decision making
Einhorn, H. J., & Hogarth, R. M. (1975) · Organizational Behavior and Human Performance · doi:10.1016/0030-5073(75)90044-6 · Cited by 673
Information Cascades in the Laboratory
Anderson, L. R., & Holt, C. A. (1997) · American Economic Review · Cited by 460
Strategies for revising judgment: How (and how well) people use others’ opinions.
Soll, J. B., & Larrick, R. P. (2009) · Journal of Experimental Psychology Learning Memory and Cognition · doi:10.1037/a0015145 · Cited by 424
Intuitions about combining opinions: misappreciation of the averaging principle
Larrick, R. P., & Soll, J. B. (2006) · Management Science · doi:10.1287/mnsc.1050.0459 · Cited by 410
Measuring forecast uncertainty by disagreement: The missing link
Lahiri, K., & Sheng, X. S. (2010) · Journal of Applied Econometrics · doi:10.1002/jae.1167 · Cited by 362
Armstrong, J. S. (2001) · International series in management science/operations research/International series in operations research & management science · doi:10.1007/978-0-306-47630-3_19 · Cited by 350
Self-citation
Flagged first, then by citations
11 of the 65 references couldn’t be matched to a known paper.
Research works printed but not linked: 19
- Abramowitz, 2012, Forecasting in a polarized era: the time for change model and the 2012 presidential election, PS: Political Science and Politics, 45, 618
- Armstrong, 2007, Significance tests harm progress in forecasting, International Journal of Forecasting, 23, 321, 10.1016/j.ijforecast.2007.03.004 · DOI
- Berry, 2012, Forecasting the 2012 presidential election with state-level economic indicators, PS: Political Science and Politics, 45, 669
- Campbell, 2012, Forecasting the presidential and congressional elections of 2012: the trial-heat and the seats-in-trouble models, PS: Political Science and Politics, 45, 630
- Cuzán, 2005, How we computed the PollyVote, Foresight: The International Journal of Applied Forecasting, 1, 51
- Erikson, 2001, Was the 2000 presidential election predictable?, PS: Political Science and Politics, 34, 815
- Graefe, 2012, Issue and leader voting in US presidential elections, Electoral Studies
- Graefe, A. (2013). Conditions of ensemble Bayesian model averaging for political forecasting. Working Paper. Available at http://ssrn.com/abstract=2266307.
- Graefe, 2009, Combined forecasts of the 2008 election: the Pollyvote, Foresight: The International Journal of Applied Forecasting, 12, 41
- Graefe, 2013, Combined forecasts of the 2012 election: the Pollyvote, Foresight: The International Journal of Applied Forecasting, 28, 50
- Haynes, 2008, A disaggregate approach to economic models of voting in US presidential elections: forecasts of the 2008 election, Economics Bulletin, 4, 1
- Hibbs, 2012, Obama’s reelection prospects under “bread and peace” voting in the 2012 US presidential election, PS: Political Science and Politics, 45, 635
- Holbrook, 2012, Incumbency, national conditions, and the 2012 presidential election, PS: Political Science and Politics, 45, 640
- Jones, 2008, Forecasting US presidential elections: a brief review, Foresight: The International Journal of Applied Forecasting, 10, 29
- Klarner, 2012, State-level forecasts of the 2012 Federal and Gubernatorial elections, PS: Political Science and Politics, 45, 655
- Levins, 1966, The strategy of model building in population biology, American Scientist, 54, 421
- Lockerbie, 2012, Economic expectations and election outcomes: the presidency and the house in 2012, PS: Political Science and Politics, 45, 644
- National Industrial Conference Board (1963). Forecasting sales. Studies in business policy, No. 106. New York.
- Sigelman, 1994, Predicting the 1992 election, Political Methodologist, 5, 14
Cited by
Sorted by citations
Forecasting: theory and practice
Petropoulos, F., Apiletti, D., Assimakopoulos, V., Babaï, M. Z., Barrow, D. K., Taieb, S. B., Bergmeir, C., Bessa, R. J., Bijak, J., Boylan, J. E., et al. (2022) · International Journal of Forecasting · doi:10.1016/j.ijforecast.2021.11.001 · Cited by 1,187
Dormann, C. F., Calabrese, J. M., Guillera‐Arroita, G., Matechou, E., Bahn, V., Bartoń, K. A., Beale, C. M., Ciuti, S., Elith, J., Gerstner, K., et al. (2018) · Ecological Monographs · doi:10.1002/ecm.1309 · Cited by 418
Illusions in regression analysis
Armstrong, J. S. (2012) · International Journal of Forecasting · doi:10.1016/j.ijforecast.2012.02.001 · Cited by 386
Self-citationThe forecast combination puzzle: A simple theoretical explanation
Claeskens, G., Magnus, J. R., Vasnev, A. L., & Wang, W. (2016) · International Journal of Forecasting · doi:10.1016/j.ijforecast.2015.12.005 · Cited by 250
Machine-Learning Models for Sales Time Series Forecasting
Павлишенко, Б. М. (2019) · Data · doi:10.3390/data4010015 · Cited by 245
Metadata
- Authors
- Graefe, A., Armstrong, J. S., Jones, R. J., & Cuzán, A. G.
- Affiliations
- Ludwig-Maximilians-Universität München (DE)
- University of South Australia (AU)
- University of Central Oklahoma (US)
- University of West Florida (US)
- Corresponding author
- Graefe, Andreas
- Venue
- International Journal of Forecasting
- Publisher
- Elsevier BV
- Published
- 2014-01
- Volume
- 30
- Issue
- 1
- Pages
- 43-54
- ISSN
- 0169-2070 (ISSN-L)
- OpenAlex
- W2008534646
- Cited by
- 160
- References
- 65
- Citations by year
- 2026: 4 · 2025: 4 · 2024: 5 · 2023: 6 · 2022: 14 · 2021: 16 · 2020: 14 · 2019: 10 · 2018: 17 · 2017: 15 · 2016: 22 · 2015: 15 · 2014: 12
- FWCI
- 23.68
- Type
- journal article
- Language
- en
- Open access
- green
- papers.ssrn.com
- Locations
- International Journal of Forecasting (publishedVersion)
- SSRN Electronic Journal (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Adelaide Research & Scholarship (AR&S) (University of Adelaide) (submittedVersion)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Forecasting Techniques and Applications
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Sports Analytics and Performance
- Social Sciences › Political Science and International Relations › Electoral Systems and Political Participation
- Keywords
- forecast combination, election forecasting, US presidential election, expert opinion, Iowa Electronic Markets, forecast accuracy, forecast uncertainty, forecast averaging
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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