A Meta-Analysis of Determinants of Success and Failure of Economic Sanctions
Political scientists and economists often assert that they understand how economic sanctions function as a foreign policy tool and claim to have backed their theories with compelling statistical evidence. The research puzzle that this article addresses is the observation that despite almost four dec...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-04-01
|
| Series: | Econometrics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2225-1146/13/2/16 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Political scientists and economists often assert that they understand how economic sanctions function as a foreign policy tool and claim to have backed their theories with compelling statistical evidence. The research puzzle that this article addresses is the observation that despite almost four decades of empirical research on economic sanctions, there is still no consensus on the direction and magnitude of the key variables that theoretically determine the success of economic sanctions. To address part of this research puzzle, we conducted a meta-analysis of 37 studies published between 1985 and 2018, focusing on three key determinants of sanction success: trade linkage, prior relations, and duration. Our analysis examines the factors contributing to the variation in findings reported by these primary studies. By constructing up to 27 moderator variables that capture the contexts in which researchers derive their estimates, we found that the differences across studies are primarily influenced by the data used, the variables controlled for in estimation methods, publication quality, and author characteristics. Our results reveal highly significant effects, indicating that sanctions are more likely to succeed when there is strong pre-sanction trade, when sanctions are implemented swiftly, and when they involve countries with better pre-sanction relationships. In our robustness checks, we consistently confirmed these core findings across different estimation techniques. |
|---|---|
| ISSN: | 2225-1146 |