PROPENSITY SCORE MATCHING IN THE ELECTION FORECASTING BY FOCUSING ON "UNDECIDED" VOTERS

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2022-8-17

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Köse, Zelal Toprak

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How to deal with "undecided" voters is a big worry among those who conduct and analyze pre-election polls. This group makes it difficult to make inferences about elections so it is important to understand the behavior of undecided voters before making election forecasting. Undecided voters may determine the fate of the next elections in Turkey. This thesis aims to predict the outcome of the next parliamentary election in Turkey using findings of opinion polls based on the undecided voters. In order to analyze the data set, Propensity Score Matching (PSM) is performed. After voters' propensity scores (PS) are calculated, the pairs between decided ("Treated") and undecided ("Control") voters are formed according to their PSs. In order to estimate propensity score, the logistic model, neural network and random forests are conducted. After estimating the propensity score, among the matching methods, the nearest neighbor matching, optimal matching and mahalanobis metric distance are used. With Nearest Neighbor Matching (NNM), for each undecided voter, the algorithm finds a voter in the control group with the nearest PS. The proposed method of the thesis is the NNM with replacement using Mahalanobis distance because it reaches the most successful matching rate with 77.5%. With this method, while Public Alliance wins the next parliamentary election by 10.6 points according to the 2020 data, the Nation Alliance takes the lead by 4.2 points in 2021. Moreover, the balance in covariate distributions between treatment and control groups is checked by using some diagnostic methods.

Subject Keywords

election forecasting, propensity score analysis, matching methods, Mahalanobis Distance

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https://hdl.handle.net/11511/99400

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Graduate School of Natural and Applied Sciences, Thesis

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Citation Formats

Z. T. Köse, “PROPENSITY SCORE MATCHING IN THE ELECTION FORECASTING BY FOCUSING ON “UNDECIDED” VOTERS,” M.S. - Master of Science, Middle East Technical University, 2022.