SPATIAL DEPENDENCE INDEX: METHODOLOGY FOR MEASURING THE NEIGHBORHOOD EFFECT IN SOCIAL SCIENCE
Keywords:
political geography, spatial analysis, spatial dependence, spatial autocorrelation, spatial econometrics, spatial dependence index, neighborhood effectAbstract
This article presents the results of the development and application of improved methodological tools based on spatial econometrics. The authors started with analyzing the spatial distribution of two social phenomena – democratization and suicide level. The following procedures were carried out for each indicator: a selection of reliable and regularly collected and published data, density-measuring zoning on the basis of a diagram and a map of extent, calculation of local indicators of spatial autocorrelation (LISA) and calculation of the authors' proposed spatial dependence index (SDI) to identify and interpret anomalous SDI values. The authors obtained anomalous values indicating the supposedly significant role of geographical factors (SDI >0.08): press freedom, political rights protection and state fragility for political regimes; autonomy index and religiousness level for suicides per 100,000 population.The research results are not intended to be exhaustive; however, the authors conclude that spatial econometrics tools, being extrapolated and used along with other traditional methods of political and social sciences, are useful for finding outputs of spatial relations and distribution of certain socio-economic and political phenomena that are not always logically obvious. In addition, the proposed analysis algorithm can be used for the analysis of other quantifiable and statistically tracked phenomena.DOI: 10.17072/2218-1067-2020-3-82-95References
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