The Dyadic Militarized Interstate Disputes (MIDs) Dataset Version 3.0: Logic, Characteristics, and Comparisons to Alternative Datasets

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Abstract

We introduce the new, substantially updated, and revised version of the Dyadic Militarized Interstate Disputes (MIDs) dataset. We discuss the underlying logic of constructing dyadic MIDs and demonstrate that these operations generate significant differences between the actual occurrence and properties of MID dyads and those extracted from machine-generated programs such as EUGene, or from the MID participant dataset. We provide some descriptive measures of dyadic MIDs over the period of 1816 to 2010 and compare some of the key dyadic results on the correlates of MIDs using different datasets. We discuss the theoretical and empirical implications of our results.

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Most cited references 35

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Democratic states are in general about as conflict- and war-prone as nondemocracies, but democracies have rarely clashed with one another in violent conflict. We first show that democracy, as well as other factors, accounts for the relative lack of conflict. Then we examine two explanatory models. The normative model suggests that democracies do not fight each other because norms of compromise and cooperation prevent their conflicts of interest from escalating into violent clashes. The structural model asserts that complex political mobilization processes impose institutional constraints on the leaders of two democracies confronting each other to make violent conflict unfeasible. Using different data sets of international conflict and a multiplicity of indicators, we find that (1) democracy, in and of itself, has a consistent and robust negative effect on the likelihood of conflict or escalation in a dyad; (2) both the normative and structural models are supported by the data; and (3) support for the normative model is more robust and consistent.

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Author and article information

Journal

Title: Journal of Conflict Resolution

Abbreviated Title: Journal of Conflict Resolution

Publisher: SAGE Publications

ISSN (Print): 0022-0027

ISSN (Electronic): 1552-8766

Publication date Created: March 2019

Publication date (Electronic): July 05 2018

Publication date (Print): March 2019

Volume: 63

Issue: 3

Pages: 811-835

Affiliations

[1 ]Department of Political Science, University of California, Davis, Davis, CA, USA

[2 ]Joint Warfare Analysis Center, United States Strategic Command, Dahlgren, VA, USA

[3 ]Department of Political Science, Randolph College, Lynchburg VA, USA

Article

DOI: 10.1177/0022002718784158

SO-VID: 82eb75dc-1784-48ff-8af0-02094432f458

License:

http://journals.sagepub.com/page/policies/text-and-data-mining-license

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