American Journal of Applied Mathematics and Statistics
ISSN (Print): 2328-7306 ISSN (Online): 2328-7292 Website: http://www.sciepub.com/journal/ajams Editor-in-chief: Mohamed Seddeek
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American Journal of Applied Mathematics and Statistics. 2017, 5(3), 101-105
DOI: 10.12691/ajams-5-3-3
Open AccessArticle

Bias Correction by Sub-population Weighting for the 2016 United States Presidential Election

Bumjun Park1,

1International Department, Hankuk Academy of Foreign Studies, Yongin, South Korea

Pub. Date: August 21, 2017

Cite this paper:
Bumjun Park. Bias Correction by Sub-population Weighting for the 2016 United States Presidential Election. American Journal of Applied Mathematics and Statistics. 2017; 5(3):101-105. doi: 10.12691/ajams-5-3-3

Abstract

The 2016 Presidential Election was an international surprise, as President Donald Trump came back from a seemingly large deficit in the pre-election opinion polls. As most, if not all, of the major polls missed the election results, the public started to doubt the credibility of pre-election polls. This article proposes that there was a methodological error in the polls. The polls used the census data of American population to weigh their data. However, population may not have a correlation with turnout, meaning that a certain population group may not vote much; not contributing to the electorate. For this reason, the polls based on population might systematically over or underestimate a particular candidate. Thereby, the proposition is that the polling agencies should consider the electorate, not the population for modifying the polling results. The proposition is substantiated with a series of statistical simulations supporting the claim that a poll conducted based on the electorate resembles the actual result more accurately. Conclusively, it argues that, as the polls play a pivotal role in affecting the media and the electorate, the improvement of polls is necessary for well-informed forecasts to be available.

Keywords:
election polls bias correction sub-population weighting turnout rate simulation prediction

Creative CommonsThis work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

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References:

[1]  Gelman, A., and King, G., "Why are American presidential election campaign polls so variable when votes are so predictable?" British Journal of Political Science, 23 (4), 409-451. Oct. 1993
 
[2]  Lichtman, J. A., "The keys to the white house: An index forecast for 2008," International Journal of Forecasting, 24 (2), 301-309. Jun. 2008.
 
[3]  Silver, N. "The Worst Pollster in the World Strikes Again." FiveThirtyEight, Mar. 2009. fivethirtyeight.com/features/worst-pollster-in-world-strikes-again/.
 
[4]  Hillygus, D. S., "The evolution of election polling in the United States". Public Opinion Quarterly, 75 (5), 962-981. Dec. 2011
 
[5]  Broh, A. C., "Horse-race journalism: Reporting the polls in the 1976 presidential election," Public Opinion Quarterly, 44 (4), 514-529. Jan. 1980.
 
[6]  Mosteller, F., The Pre-election Polls of 1948: The Report to the Committee on Analysis of Pre-election Polls and Forecasts. Social Science Research Council, New York, 1949.
 
[7]  Shipman, J., & Leve, J. H., "A New "Interval" Measure of Election Poll Accuracy," Paper presented at the annual meeting of the American Association For Public Opinion Association. May. 2005.
 
[8]  Burden, B. C., "Voter turnout and the national election studies," Political Analysis, 8 (4), 389-398. Jul. 2000.
 
[9]  Reiter, H. L., "Why is turnout down?" Public Opinion Quarterly, 43 (3), 297-311. Jan. 1979.
 
[10]  Shaffer, S. D., "A multivariate explanation of decreasing turnout in presidential elections 1960-1976", American Journal of Political Science, 25 (1), 68-95. Feb. 1981.
 
[11]  Ladd, E. C., "The Shifting Party Coalitions, 1932-1976," Emerging Coalitions in American Politics, 81-102, Jan. 1978.