Qiuomars Yazdanpanah Dero; Saba Sofizade
Abstract
Electoral geography is often considered a major branch of behavioral geography, which takes into account certain political functionalities. This analysis is particularly important in ...
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Electoral geography is often considered a major branch of behavioral geography, which takes into account certain political functionalities. This analysis is particularly important in the case of Iran, where political behaviors and social, behavioral, and geographical complexities take on a unique form. This in turn certainly impacts the combination and function of different political institutions in Iran, especially in the case of presidential elections, at various local, regional, and national scales. In this light, the present study proceeds with an exploratory analysis of spatial data on different electoral sectors to find a balanced spatial division (zoning) of Iran based on principles of electoral geography, which also provides certain indications into existing spatial inequalities. The analysis is based on the assumption that concepts of electoral geography-consisting of a diverse range of spatial-political aspects of election-integrated with exploratory analyses, may prove helpful in establishing fair elections in Iran. The results of this study reveal that the distribution of election votes shows a significantly positive general spatial autocorrelation, which is indicative of the spatial clustering of votes in Iran. Regarding the relationship between the distribution of votes and social and economic variables, votes tallied for Rouhani had positive and significant correlations with factors of relative population aged 25 to 64, relative student population studying at higher education, the ratio of university educated population, unemployment rates, rental rates, housing quality, and the rate of urbanization in all cities. However, for Raeesi, the analysis of the votes indicates a positive and significant correlation between relative population aged 0 to 24, population above 64, employment rates, ratio of households with disabled members, house ownership and ruralization.
