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Intrinsic Social Incentives in State and Non-State Armed Groups

Published online by Cambridge University Press:  20 April 2022

MICHAEL J. GILLIGAN*
Affiliation:
New York University, United States
PRABIN KHADKA*
Affiliation:
University of Essex, United Kingdom
CYRUS SAMII*
Affiliation:
New York University, United States
*
Michael J. Gilligan, Professor, Department of Politics, New York University, United States, mg5@nyu.edu.
Prabin Khadka, Assistant Professor, Department of Government, University of Essex, United Kingdom, prabin.khadka@essex.ac.uk.
Cyrus Samii, Associate Professor, Department of Politics, New York University, United States, cds2083@nyu.edu.
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Abstract

How do non-state armed groups (NSAGs) survive and even thrive in situations where state armed groups (SAGs) collapse, despite the former’s often greater material adversity? We argue that, optimizing under their different constraints, SAGs invest more in technical military training and NSAGs invest more in enhancing soldiers’ intrinsic payoffs from serving their group. Therefore, willingness to contribute to the group should be more positively correlated with years of service in NSAGs than in SAGs. We confirm this hypothesis with lab-in-the-field and qualitative evidence from SAG and NSAG soldiers in Nepal, Ivory Coast, and Kurdistan. Each field study addresses specific inferential weaknesses in the others. Assembled together, these cases reduce concerns about external validity or replicability. Our findings reveal how the basis of NSAG cohesion differs from that of SAGs, with implications for strategies to counter NSAG mobilization.

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Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited
Copyright
© The Author(s), 2022. Published by Cambridge University Press on behalf of the American Political Science Association
Figure 0

Table 1. Contributions and Years Served in PLA, Regression Estimates

Figure 1

Figure 1. Contributions and Years Served in PLA

Figure 2

Figure 2. Desertion and Killed-in-Action Percentages among Maoist Soldiers by Year of JoiningNote: Points are jittered in the graphs so that masses of observations are visible. For the left graph, a point at, say, (1996, 0) corresponds to a respondent who joined in 1996 and for whom none of their original platoonmates deserted throughout the war. Values greater than 0 mean that some share deserted at some point during the war. The right graph can be interpreted similarly for accumulated killed-in-action (KIA) rates. A local (first-degree) polynomial fit estimates average desertion and KIA rates for cohorts who joined at different years from 1996 to 2006. The gray area is a 95% confidence band on the local polynomial fit.

Figure 3

Table 2. Lab Contributions and Years Served in Ivorian Army and Gbagbo Militia, Regression Estimates

Figure 4

Figure 3. Lab Contribution and Years Served in Ivorian Army and Gbagbo Militia

Figure 5

Figure 4. Desertion and Killed-in-Action Percentages in Ivorian Army and Gbagbo MilitiaNote: See notes to Figure 2 for an explanation of the graphs. The left graphs show desertion and KIA rates for the NSAG (Gbagbo militia), and the right graphs show it for the SAG (Ivorian Army).

Figure 6

Table 3. Years Served and Laboratory Contributions among Peshmerga Cohorts

Figure 7

Figure 5. Lab Contribution and Years Served in Peshmerga for Various CohortsNote: Residual-residual plots, controlling for age, of the relationship between combined amounts given and years served for pre-2003, 2003–13, and post-2013 entry cohorts. The supplementary materials contain a version of this graph without the pre-2003 outlier point, showing very similar results.

Figure 8

Figure 6. Peshmerga Desertion and Killed-in-Action Percentages with Various Key DatesNote: See notes to Figure 2 for an explanation of the graphs. Two key dates, the coalition invasion in 2003 and the Islamic State invasion in 2014, are indicated with vertical lines.

Figure 9

Figure 7. Timing of Maoist Activity in Home Region and Laboratory ContributionsNote: The x-axis shows the year in which cumulative conflict-related deaths reached at least 100 (“war started”) in a subject’s district, as a measure of the onset of Maoist operations in that district. The data for the x-axis are from the Informal Service Sector (INSEC) yearbooks (1996–2007), as reported in Do and Iyer (2010). The y-axis shows game results from sessions with PLA combatants and civilians originating from the respective districts.

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