Do Foreign Aid Projects Attract Transnational Terrorism?
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Andrew Boutton
Abstract
Governments and NGOs establish aid projects in order to improve the quality of life for local residents around the world. While recent news stories about aid workers being kidnapped or killed by terrorist groups are alarming, they mask a broader question: Are aid projects effective in promoting humanitarian aims and pacifying the areas to which it is sent? Or, conversely, does their presence actually attract more violence? Although humanitarian assistance is ostensibly non-political, aid projects themselves may make popular targets for terrorist groups. In addition to increasing resources available to plunder, aid provides an appealing foreign target, allowing terrorist groups to reach wider audiences with their attacks and to reinforce the narrative that the government lacks capacity to protect and provide for civilians. In this paper we combine subnational, project-level aid data with newly-assembled subnational data on transnational terrorism to explore terrorist targeting of aid locations. After presenting our matched-sample analysis of terrorist targeting of aid, we outline avenues for future inquiry using high-resolution, subnational data to investigate the strategic vulnerabilities of foreign aid projects.
Appendix
Balance test: matched vs. full sample.
Full sample: rare events logit-transnational attacks 1995–2013.
| Presence of aid | Num. of aid projects | Num. of aid locations | |
|---|---|---|---|
| Foreign aid | 0.460∗∗∗ | 0.106∗∗∗ | 0.00922∗∗ |
| (Lagged) | (0.120) | (0.0212) | (0.00282) |
| Civil conflict in cell | 0.853∗∗∗ | 0.878∗∗∗ | 0.856∗∗∗ |
| (0.109) | (0.110) | (0.109) | |
| Dist. to intl. border | −0.172∗∗∗ | −0.172∗∗∗ | −0.170∗∗∗ |
| (0.0267) | (0.0265) | (0.0267) | |
| Dist. to capital | −0.0828∗∗∗ | −0.0832∗∗∗ | −0.0869∗∗∗ |
| (0.0147) | (0.0146) | (0.0149) | |
| Urban | −0.0230∗∗∗ | −0.0228∗∗∗ | −0.0240∗∗∗ |
| (0.00280) | (0.00282) | (0.00271) | |
| Population | 0.438∗∗∗ | 0.441∗∗∗ | 0.482∗∗∗ |
| (Logged) | (0.0619) | (0.0590) | (0.0559) |
| Economic activity | 0.579∗∗∗ | 0.563∗∗∗ | 0.525∗∗∗ |
| (Logged) | (0.0868) | (0.0819) | (0.0788) |
| Excl. ethnic groups | 0.296∗∗∗ | 0.292∗∗∗ | 0.281∗∗∗ |
| (0.0606) | (0.0601) | (0.0615) | |
| Infant mortality rate | 0.0571∗∗∗ | 0.0561∗∗∗ | 0.0602∗∗∗ |
| (0.0154) | (0.0154) | (0.0155) | |
| Precipitation | −0.578 | −0.579 | −0.500 |
| (0.342) | (0.345) | (0.341) | |
| Land area | −0.494∗∗∗ | −0.493∗∗∗ | −0.504∗∗∗ |
| (Logged) | (0.0868) | (0.0865) | (0.0873) |
| Spatial lag | 0.820∗∗∗ | 0.814∗∗∗ | 0.801∗∗∗ |
| (0.114) | (0.115) | (0.110) | |
| Lagged DV | 3.072∗∗∗ | 3.053∗∗∗ | 3.053∗∗∗ |
| (0.165) | (0.166) | (0.168) | |
| Constant | −3.897∗∗∗ | −3.827∗∗∗ | −3.644∗∗∗ |
| (0.421) | (0.404) | (0.394) | |
| Observations | 571,198 | 571,198 | 571,198 |
Clustered standard errors in parentheses.
∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001.
Full sample: attacks disaggregated by sector and attack mode.
| All attacks | Bombings | Kidnappings | |
|---|---|---|---|
| Education | 0.386∗∗ | 0.182 | 0.886∗∗∗ |
| (Lagged) | (0.141) | (0.224) | (0.237) |
| Health | −0.244 | −0.161 | −0.603∗ |
| (Lagged) | (0.145) | (0.215) | (0.237) |
| Water and sani. | 0.549∗∗∗ | 0.687∗∗∗ | 0.0523 |
| (Lagged) | (0.141) | (0.196) | (0.288) |
| Gov. and social welf. | 0.0626 | 0.197 | 0.415 |
| (Lagged) | (0.158) | (0.209) | (0.257) |
| Transportation | −0.150 | −0.227 | −0.484 |
| (Lagged) | (0.143) | (0.192) | (0.269) |
| Energy | 0.152 | 0.0828 | 0.0861 |
| (Lagged) | (0.132) | (0.177) | (0.261) |
| Banking | 0.213 | 0.0505 | 0.305 |
| (Lagged) | (0.131) | (0.190) | (0.277) |
| Civil conflict in cell | 0.910∗∗∗ | 0.823∗∗∗ | 1.418∗∗∗ |
| (0.0985) | (0.145) | (0.191) | |
| Dist. to intl. border | −0.168∗∗∗ | −0.165∗∗∗ | −0.277∗∗∗ |
| (0.0249) | (0.0416) | (0.0466) | |
| Dist. to capital | −0.0861∗∗∗ | −0.0803∗∗∗ | −0.0917∗∗∗ |
| (0.0144) | (0.0199) | (0.0249) | |
| Urban | −0.0227∗∗∗ | −0.0292∗∗∗ | −0.0277∗∗∗ |
| (0.00298) | (0.00364) | (0.00530) | |
| Population | 0.446∗∗∗ | 0.546∗∗∗ | 0.304∗∗∗ |
| (Logged) | (0.0536) | (0.0764) | (0.0752) |
| Economic activity | 0.552∗∗∗ | 0.501∗∗∗ | 0.324∗ |
| (Logged) | (0.0797) | (0.115) | (0.150) |
| Excl. ethnic groups | 0.307∗∗∗ | 0.264∗∗ | 0.0973 |
| (0.0560) | (0.0921) | (0.124) | |
| Infant mortality rate | 0.0460∗∗ | 0.0475∗ | 0.0863∗∗∗ |
| (0.0143) | (0.0221) | (0.0231) | |
| Precipitation | −0.417 | −0.686 | 0.960∗ |
| (0.302) | (0.425) | (0.373) | |
| Land area | −0.428∗∗∗ | −0.462∗∗∗ | −0.0334 |
| Logged | (0.0851) | (0.130) | (0.247) |
| Spatial lag | 0.819∗∗∗ | 0.646∗∗∗ | 0.723∗∗∗ |
| (0.116) | (0.0638) | (0.0773) | |
| Lagged DV | 2.930∗∗∗ | 2.743∗∗∗ | 2.825∗∗∗ |
| (0.149) | (0.206) | (0.237) | |
| Constant | −4.017∗∗∗ | −4.649∗∗∗ | −7.194∗∗∗ |
| (0.387) | (0.589) | (0.883) | |
| Observations | 614,894 | 614,894 | 614,894 |
Clustered standard errors in parentheses.
∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001.
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Artikel in diesem Heft
- Editorial
- Introduction to the Proceedings of the 18th Jan Tinbergen European Peace Science Conference
- Survey or Review
- Systematic Study of Gender, Conflict, and Peace
- Letters and Proceedings
- Political Initiatives and Peacekeeping: Assessing Multiple UN Conflict Resolution Tools
- US Military Response to the Risk of Terrorist Attacks
- Do Foreign Aid Projects Attract Transnational Terrorism?
- Military Spending and Inequality in Autocracies
- Beyond a Bag of Words: Using PULSAR to Extract Judgments on Specific Human Rights at Scale
- Predicting Terrorism with Machine Learning: Lessons from “Predicting Terrorism: A Machine Learning Approach”
- Conflict in Cyber-Space: The Network of Cyber Incidents, 2000–2014
- What do they Want? Rebels’ Objectives and Civil War Mediation
Artikel in diesem Heft
- Editorial
- Introduction to the Proceedings of the 18th Jan Tinbergen European Peace Science Conference
- Survey or Review
- Systematic Study of Gender, Conflict, and Peace
- Letters and Proceedings
- Political Initiatives and Peacekeeping: Assessing Multiple UN Conflict Resolution Tools
- US Military Response to the Risk of Terrorist Attacks
- Do Foreign Aid Projects Attract Transnational Terrorism?
- Military Spending and Inequality in Autocracies
- Beyond a Bag of Words: Using PULSAR to Extract Judgments on Specific Human Rights at Scale
- Predicting Terrorism with Machine Learning: Lessons from “Predicting Terrorism: A Machine Learning Approach”
- Conflict in Cyber-Space: The Network of Cyber Incidents, 2000–2014
- What do they Want? Rebels’ Objectives and Civil War Mediation
