Contagion, Confounding, and Causality: Confronting the Three C's of Observational Political Networks Research

Medha Uppala, Bruce A. Desmarais

Research output: Contribution to journalArticlepeer-review

Abstract

Contagion across various types of connections is a central process in the study of many political phenomena (e.g., democratization, civil conflict, and voter turnout). Over the last decade, the methodological literature addressing the challenges in causally identifying contagion in networks has exploded. In one of the foundational works in this literature, Shalizi and Thomas (2011, Sociological Methods and Research 40, 211-239.) propose a permutation test for contagion in longitudinal network data that is not confounded by selection (e.g., homophily). We illustrate the properties of this test via simulation. We assess its statistical power under various conditions of the data, including the nature of the contagion, the structure of the network through which contagion occurs, and the number of time periods included in the data. We then apply this test to an example domain that is commonly considered in the context of observational research on contagion - the international spread of democracy. We find evidence of international contagion of democracy. We conclude with a discussion of the practical applicability of the Shalizi and Thomas test to the study of contagion in political networks.

Original languageEnglish (US)
Pages (from-to)472-479
Number of pages8
JournalPolitical Analysis
Volume31
Issue number3
DOIs
StatePublished - Jul 9 2023

All Science Journal Classification (ASJC) codes

  • Sociology and Political Science
  • Political Science and International Relations

Cite this