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Economists face a significant challenge in their study of economic sanctions, particularly in effectively simulating their impact within econometric models. A common strategy involves the use of binary variables, where a value of zero denotes the absence of sanctions, and one indicates their implementation. Another approach involves counterfactual regressions, enabling a comparison between the actual outcomes following sanction implementation and what might have occurred in the absence of intervention.
However, a notable drawback emerges from these methodologies. The ambiguity arises as to whether the observed changes are exclusively attributable to the sanctions themselves or if they are influenced by alterations in other critical exogenous variables.
To address this issue, we use the three-parameter framework introduced in Bali & Rapelanoro (2021) to create dedicated time-varying sanction variables that precisely imitate coercive economic measures in econometric models. The Sanction Indices Database (SIDB) gathers these time-varying sanction indices. Our indices are created per country using sanction lists, trade data between the sanctioning country and its target, and the termination date of sanctions (if not available, a decay rate is used instead).
Notes:
SIDB 1.1 is partly supported by U.S. Department of Defense Minerva Program Grant No. FA9550-21-1-0156 and Duke University.
The SIDB is expected to be published by the end of 2024. Early requests and cooperation offers may be submitted by e-mail at morad.bali@irnc.org.
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- Research Services
- Keywords
- Research, Economics, Sanctions.
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Sanction Indices Database's LinkedIn profile is https://www.linkedin.com/company/si-db
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Sanction Indices Database's categories are Research Services
Sanction Indices Database's founding year is 2023
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Aaron Lam
Dean'S Research Fellow @ Duke…
Durham, North Carolina, United States, United States -
Kelly Shahu
Computer Science @Duke
United States, United States
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