Matched Wake Analysis: Finding Causal Relationships in Spatiotemporal Event Data

Political Geography 41 (2014) 1-10

39 Pages Posted: 17 Apr 2014 Last revised: 11 Feb 2017

See all articles by Sebastian Schutte

Sebastian Schutte

ETH Zürich - Department of Humanities, Social and Political Sciences (GESS)

Karsten Donnay

Department of Political Science, University of Zurich

Date Written: April 14, 2014

Abstract

This paper introduces a new method for finding causal relationships in spatiotemporal event data with potential applications in conflict research, criminology, and epidemiology. The method analyzes how different types of interventions affect subsequent levels of reactive events. Sliding spatiotemporal windows and statistical matching are used for robust and clean causal inference. Thereby, two well-described empirical problems in establishing causal relationships in event data analysis are resolved: the modifiable areal unit problem and selection bias. The paper presents the method formally and demonstrates its effectiveness in Monte Carlo simulations and an empirical example by showing how instances of civilian assistance to US forces changed in response to indiscriminate insurgent violence in Iraq.

Keywords: GIS, Civil War, Causal Inference, Indiscriminate Violence

Suggested Citation

Schutte, Sebastian and Donnay, Karsten, Matched Wake Analysis: Finding Causal Relationships in Spatiotemporal Event Data (April 14, 2014). Political Geography 41 (2014) 1-10, Available at SSRN: https://ssrn.com/abstract=2425119 or http://dx.doi.org/10.2139/ssrn.2425119

Sebastian Schutte (Contact Author)

ETH Zürich - Department of Humanities, Social and Political Sciences (GESS) ( email )

ETH-Zentrum SEW E 26
CH-8092 Zurich, Zurich 8006
Switzerland

Karsten Donnay

Department of Political Science, University of Zurich ( email )

Affolternstrasse 56
Zürich, CH-8050
Switzerland

HOME PAGE: http://www.karstendonnay.net

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