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Spatial analysis for political scientists

Published online by Cambridge University Press:  11 May 2021

Jessica Di Salvatore  and
Andrea Ruggeri Open the ORCID record for Andrea Ruggeri [Opens in a new window]
Jessica Di Salvatore*
Affiliation:
Department of Politics and International Studies, University of Warwick, Coventry, UK
Andrea Ruggeri
Affiliation:
Department of Politics and International Relations, University of Oxford, Oxford, UK
*
*Corresponding author. Email: Jessica.Di-Salvatore@warwick.ac.uk
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Abstract

How does space matter in our analyses? How can we evaluate diffusion of phenomena or interdependence among units? How biased can our analysis be if we do not consider spatial relationships? All the above questions are critical theoretical and empirical issues for political scientists belonging to several subfields from Electoral Studies to Comparative Politics, and also for International Relations. In this special issue on methods, our paper introduces political scientists to conceptualizing interdependence between units and how to empirically model these interdependencies using spatial regression. First, the paper presents the building blocks of any feature of spatial data (points, polygons, and raster) and the task of georeferencing. Second, the paper discusses what a spatial matrix (W) is, its varieties and the assumptions we make when choosing one. Third, the paper introduces how to investigate spatial clustering through visualizations (e.g. maps) as well as statistical tests (e.g. Moran's index). Fourth and finally, the paper explains how to model spatial relationships that are of substantive interest to some of our research questions. We conclude by inviting researchers to carefully consider space in their analysis and to reflect on the need, or the lack thereof, to use spatial models.

Keywords

connectionsGISinterdependencespatial dataspatial errorspatial models
Type
Research Article
Information
Italian Political Science Review / Rivista Italiana di Scienza Politica , Volume 51 , Special Issue 2: Capturing Causation: Issues of Research Design in Political Science , July 2021 , pp. 198 - 214
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press on behalf of the Società Italiana di Scienza Politica.

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