Predictive Estimation in Canadian Federal Elections

Date created: 
2017-04-20
Identifier: 
etd10116
Keywords: 
Assumption violation
Descriptive analysis
Seat prediction
Simulation study
Variance estimation
Abstract: 

Various estimation methods are employed to provide seat projections during Canadian federal elections. This project explores discrepancies between the real outcomes of recent Canadian federal elections and the predictions by the existing approaches such as the ones proposed by Grenier and Rosenthal. It appears that each seat projection procedure requires a set of assumptions, but the assumptions are not explicitly listed in the accessible references. We formulate the required assumptions used in the two prediction procedures proposed by Rosenthal, and present variance estimation procedures. Departures from the assumptions are explored with real data from the 2006, 2008, 2011, and 2015 federal election. An extensive simulation study is conducted to examine potential impacts of various deviations from the assumptions. The simulation indicates that, compared to other assumption violations, misleading polling results may cause the most damage to the prediction. In addition, we find by the simulation that the prediction is least affected by a change in number of voters and the heterogeneity of riding patterns within a region may not affect the the prediction at the national level.

Document type: 
Graduating extended essay / Research project
Rights: 
This thesis may be printed or downloaded for non-commercial research and scholarly purposes. Copyright remains with the author.
File(s): 
Supervisor(s): 
Joan Hu
Department: 
Science: Department of Statistics and Actuarial Science
Thesis type: 
(Project) M.Sc.
Statistics: