Tunisian constituent assembly elections: how does spatial proximity matter?

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• 作者：Mohamed Amara ; AbdelRahmen El Lahga
• 关键词：Elections ; Spatial analysis ; Spatial Durbin Model ; National Constituent Assembly ; Tunisia
• 刊名：Quality & Quantity
• 出版年：2016
• 出版时间：January 2016
• 年：2016
• 卷：50
• 期：1
• 页码：65-88
• 全文大小：5,557 KB
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• 作者单位：Mohamed Amara (1)
  AbdelRahmen El Lahga (1) (2)
  
  1. High Institute of Management of Sousse, 763, Street of Abdelaziz El Behi, 4000, Sousse, Tunisia
  2. High Institute of Management of Tunis, 41, Street of freedom, City Bouchoucha, Bardo, 2000, Tunis, Tunisia
  
• 刊物类别：Humanities, Social Sciences and Law
• 刊物主题：Social Sciences
  Methodology of the Social Sciences
  Social Sciences
  
• 出版者：Springer Netherlands
• ISSN：1573-7845

文摘

This paper presents an Exploratory Spatial Data Analysis and Spatial Econometric modeling of the 2011 National Constituent Assembly elections (NCA) in Tunisia. By using electoral data at delegation level of the six main political parties (Ennahda, Congress of the Republic, Ettakatol, the Democratic Progressive Party, the Petition and the Democratie Modernist Pole), we show that geographical proximity matters in Tunisia’s voting behavior. The results overwhelmingly support the spatial Durbin model, including spatially weighted independent variables, as the best model to explain the voting phenomenon. Employing LeSage and Pace’s approach, we find that the largest direct and indirect effects are associated with age cohort and level of educational attainment. Voters who live in poorer neighborhoods are more likely to support the Petition list. Our results also show that younger voters are more likely to vote Ennahda, while older voters with high educational attainment are more likely to support Ettakatol and the Democratie Modernist Pole parties. Men are more likely to support Congress of the Republic than women voters.