home
Home
navigate_next
Search results
Search results
Abstract
The issue of invalid votes receives few scholarly attentions. Many consider invalid votes as the result of unintended behavior and do not explore the factors that may influence the incidence of invalid votes. We examine 37 elections of different levels between 1992 and 2008 in Taiwan by using panel data analysis. We find that the distribution of invalid votes are not random but are influenced by institutional and socioeconomic factors. Regarding institutional factors, the elections codes, the complexity of elections, the importance of elections, and years after the democratic transition are the main influencing factors. Years of education, the percentage of elders, population density, and percentage of indigenous citizens are the main socioeconomic variables that affect the incidence of invalid votes. The two strings of factors can explain about 34% of the variance in invalid votes. In addition to the pooled OLS model, we also employ spatial lag model and spatial error model. The two models show that the distribution of invalid votes exhibit positive spatial autocorrelation. In addition, some areas also exhibit spatial heterogeneity, which is likely to be attributed to the alienation of voters in the districts. We might need to pay special attention to these areas to enhance the quality of democracy.
Abstract
We investigate the relationship between environmental protests and parties' vote shares. Whether environmental protest contributes to the vote share of the Green party? As Green party emphasizes environment protection, people who suffer from environmental pollution is more likely to endorse Green Party. If not, what are the factors behind the situation? We collect and categorize environmental protest data between 1987 and 2009. Applying GIS and spatial analysis, we collapse protest events by township and issue types. Combining legislative election results, we analyze the influence of environmental protests on the vote shares of parties. The empirical result shows that anti-industrial pollution protests exert the most significant effect on party vote share but the influence varies across parties. First, anti-industrial pollution protest is not significantly associated with the vote share of Green Party. The larger the number of anti-industrial pollution protest in a township, the higher the DPP's vote share and the lower the KMT's vote share. For the other types of environmental protests, we do not find comparable effect of protests on vote sharing. In this article we also find that it is socio-economic status of a township rather than the intensity of environmental protest that affect the electoral performance of Green party. Finally, the empirical model also demonstrates the significance of neighborhood effect on parties' vote shares.
