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Abstract
There are three major schools in the study of voting behavior, namely, sociological, sociopsychological and rational. Sociological school presents evidence that structural factors have high correlation coefficients between socioeconomic factors and voting choice. Sociopsychological school indicates that sociological factors are long term indirect determinants while party identification, candidate evalution, and issues are direct determinants. Rational approach suggests that the choices of vote is based on cost and benefit consideration. In this study, using post election survey data from the 1996 presidential election, three major approaches are tested thoroughly. In order to demonstrate that the integrated theory is better than those separated theories, seven possible combinations have been tested. The results show that psychological model is the best single model, ration and structural followed respectively. The best joint model is the combination of structural and psychological, followed by psychological and rational, and structural and rational. The intergrated model has slightly increased the explanatory power in terms of variance explained. Although the increase is not dramatic, the model maintains. This results suggest that the three approaches have overlapping explanation power, and no single model can claim to be the dominate model. Since the combined model can increase explanation power, thus, he integrated model should be emphasized in near future.
Abstract
This paper examines the process of voters' voting decision and develops a way of predicting voters' voting decision. Most surveys on election prediction are based on respondents' answers on their vote choices. However, this paper indicates two serious problems in this way of election prediction. One problem comes from the indecision of most voters, and the other problems comes from measurement errors. To deal with this problem, this paper provides a way of estimating each voter's probabilities of voting for each candidiate. The author indicates that the probability of voting for a particular candidate is not 0, neither is 1. Instead, the probability of voting for a particular candidate ranges from 0 to 1. The author bases on four major variables--candidate evaluations, party identification, incumbent government satisfaction, and ethnicity-- to construct a vote choice model, and estimates the model by way of a multinomial logit model. Then, the author calculates individual voters' probabilities of voting for each of the candidates. The research finding shows that the chance of voting for a particular candidate is large if a voter has a high probability of voting for the candidate. Based on this principle, the paper predicts the outcomes of four elections and two of them are quite accurate.
