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An Empirical Evaluation of Explanations for State Repression

  • DANIEL W. HILL (a1) and ZACHARY M. JONES (a2)
Abstract

The empirical literature that examines cross-national patterns of state repression seeks to discover a set of political, economic, and social conditions that are consistently associated with government violations of human rights. Null hypothesis significance testing is the most common way of examining the relationship between repression and concepts of interest, but we argue that it is inadequate for this goal, and has produced potentially misleading results. To remedy this deficiency in the literature we use cross-validation and random forests to determine the predictive power of measures of concepts the literature identifies as important causes of repression. We find that few of these measures are able to substantially improve the predictive power of statistical models of repression. Further, the most studied concept in the literature, democratic political institutions, predicts certain kinds of repression much more accurately than others. We argue that this is due to conceptual and operational overlap between democracy and certain kinds of state repression. Finally, we argue that the impressive performance of certain features of domestic legal systems, as well as some economic and demographic factors, justifies a stronger focus on these concepts in future studies of repression.

Copyright
Corresponding author
Daniel W. Hill, Jr. is Assistant Professor, Department of International Affairs, University of Georgia (dwhill@uga.edu), and is responsible for the research question, design of the cross-validation analysis, selection of the data, and the majority of the writing.
Zachary M. Jones is Ph.D. student, Department of Political Science, Pennsylvania State University (zmj@zmjones.com), and is responsible for design of the random forest analysis and multiple imputation, all data analysis and visualization, and description of the methods.
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