NLP Approach to the Study Economic Sanctions

20 Pages Posted: 25 Mar 2021

See all articles by Ashrakat Elshehawy

Ashrakat Elshehawy

University of Oxford

Nikolay Marinov

University of Houston - Department of Political Science

Federico Nanni

Data and Web Science Group

Jordan Tama

American University

Date Written: February 22, 2021

Abstract

Existing datasets of economic sanctions rely on secondary sources to record instances of economic coercion. This approach may miss economic sanctions and does not capture important details in how sanctions are threatened, imposed and removed, among other information. We present a computer-assisted analysis approach of text to retrieving sanctions-related government documents. We collect all sanctions events originating in the office of the U.S. President, and all Congressional sanctions for 1988-2016. Our approach has three advantages: (1) it is more complete, (2) it is disaggregated, (3) it includes the original language of the measures. These features directly shed light inter-branch delegation, (partisan) conflict, and policy priorities. Indirectly, they help us both measure and analyze the sources of effectiveness. The data and approach can advance the study of economic sanctions, and can facilitate progress in other areas of research in political science.

Suggested Citation

Elshehawy, Ashrakat and Marinov, Nikolay and Nanni, Federico and Tama, Jordan, NLP Approach to the Study Economic Sanctions (February 22, 2021). Available at SSRN: https://ssrn.com/abstract=3790866 or http://dx.doi.org/10.2139/ssrn.3790866

Ashrakat Elshehawy

University of Oxford ( email )

Oxford
United Kingdom

Nikolay Marinov (Contact Author)

University of Houston - Department of Political Science ( email )

TX 77204-3011
United States

HOME PAGE: http://www.nikolaymarinov.com

Federico Nanni

Data and Web Science Group ( email )

Germany

Jordan Tama

American University ( email )

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