Replication data for: Explaining Support for Combatants during Wartime: A Survey Experiment in Afghanistan (doi:10.7910/DVN/CXNXEZ)

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Part 2: Study Description
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Document Description

Citation

Title:

Replication data for: Explaining Support for Combatants during Wartime: A Survey Experiment in Afghanistan

Identification Number:

doi:10.7910/DVN/CXNXEZ

Distributor:

Harvard Dataverse

Date of Distribution:

2013-09-12

Version:

2

Bibliographic Citation:

Lyall, Jason; Blair, Graeme; Imai, Kosuke, 2013, "Replication data for: Explaining Support for Combatants during Wartime: A Survey Experiment in Afghanistan", https://doi.org/10.7910/DVN/CXNXEZ, Harvard Dataverse, V2

Study Description

Citation

Title:

Replication data for: Explaining Support for Combatants during Wartime: A Survey Experiment in Afghanistan

Identification Number:

doi:10.7910/DVN/CXNXEZ

Authoring Entity:

Lyall, Jason (Yale University)

Blair, Graeme (Princeton University)

Imai, Kosuke (Princeton University)

Distributor:

Harvard Dataverse

Distributor:

American Political Science Review

Date of Deposit:

2013-09-12

Date of Distribution:

2013-09-12

Holdings Information:

https://doi.org/10.7910/DVN/CXNXEZ

Study Scope

Abstract:

How are civilian attitudes toward combatants affected by wartime victimization? Are these effects conditional on which combatant inflicted the harm? We investigate the determinants of wartime civilian attitudes towards combatants using a survey experiment across 204 villages in five Pashtun-dominated provinces of Afghanistan—the heart of the Taliban insurgency. We use endorsement experiments to indirectly elicit truthful answers to sensitive questions about support for different combat- ants. We demonstrate that civilian attitudes are asymmetric in nature. Harm inflicted by the International Security Assistance Force (ISAF) is met with reduced support for ISAF and increased support for the Taliban, but Taliban-inflicted harm does not translate into greater ISAF support. We combine a multistage sampling design with hierarchical modeling to estimate ISAF and Taliban support at the individual, village, and district levels, permitting a more fine-grained analysis of wartime attitudes than previously possible.

Methodology and Processing

Sources Statement

Data Access

Notes:

<a href="http://creativecommons.org/publicdomain/zero/1.0">CC0 1.0</a>

Other Study Description Materials

Related Publications

Citation

Title:

Lyall, Jason, Graeme Blair, and Kosuke Imai (2013). "Explaining Support for Combatants during Wartime: A Survey Experiment in Afghanistan" American Political Science Review 107(4).

Bibliographic Citation:

Lyall, Jason, Graeme Blair, and Kosuke Imai (2013). "Explaining Support for Combatants during Wartime: A Survey Experiment in Afghanistan" American Political Science Review 107(4).

Other Study-Related Materials

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data.RData

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endorseResultsCovariates.area.fit.1.RData

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endorseResultsCovariates.area.fit.2.RData

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endorseResultsCovariates.area.fit.3.RData

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endorseResultsCovariates.individual.fit.1.RData

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endorseResultsCovariates.individual.fit.2.RData

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endorseResultsCovariates.individual.fit.3.RData

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endorseResultsCovariatesProTal.individual.fit.1.RData

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endorseResultsCovariatesProTal.individual.fit.2.RData

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endorseResultsCovariatesProTal.individual.fit.3.RData

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endorseResultsNoCovariates.RData

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endorseSetup.RData

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endorseSetupProTaliban.RData

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model-FamilyHarm.R

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This file runs the standard endorsement experiment model with individual and family harm exposure variables.

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model-ManteqaHarm.R

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This file runs the standard endorsement experiment model with Manteqa (area) variables.

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model-NoCovariates.R

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This file runs the endorsement experiment model with no covariates.

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model-ProTaliban.R

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This file runs the standard endorsement experiment model with interactions indicating tribal affiliation.

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ModelVillageDistrictProvinceCovariates.R

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This file is used by JAGS to compile the Bayesian endorsement experiment model. It is called from the model-*.R files, and cannot be run directly.

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Other Study-Related Materials

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replication.R

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This file replicates all of the key figures from the paper, based on Bayesian MCMC draws included in the Results category.

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