SASCAT: Natural language processing approach to the study of economic sanctions
| Published date | 01 September 2023 |
| DOI | http://doi.org/10.1177/00223433221088712 |
| Date | 01 September 2023 |
| Subject Matter | Special Data Features |
SASCAT: Natural language processing
approach to the study of economic sanctions
Ashrakat Elshehawy
Department of Political Science, University of
Oxford
Nikolay Marinov
Department of Political Science, University of
Houston
Federico Nanni
Alan Turing Institute
Jordan Tama
School of International Service, American
University
Abstract
Existing datasets of economic sanctions rely primarily on secondary sources and do not tend to take full advantage of
government documents related to economic coercion. Such data may miss sanctions, and do not capture important details
in how coercive measures are threatened, imposed and removed. The latter processes often have much to do with the
domestic politics in sender countries. Understanding these processes may be necessary in order to fully account for
sanctions’effectiveness. Wepresent a natural languageprocessing (NLP) approach to retrieving sanctions-relatedgovern-
ment documents. We apply our method to the case of US sanctions. The United States is the world’s pre-eminent user of
sanctions. Our method can be applied to other cases. We collect all sanctions events originating in the office of the US
president, and all congressional sanctions, for 1988–2016. Our approach has three advantages: (1) by design, it captures all
sanctions-related documents; (2) the resulting data are disaggregated by imposing branch of government; (3) the data
include the original language of the measures. These features directly shed light on interbranch delegation, domestic
(partisan) conflict, and policy priorities. We show that our data record more episodes than most existing sanctions’ data, and
have featuresthat other datasets lack. Theavailability of the originaltext opens up new avenues for research and analysis.
Keywords
delegation, deterrence, economic sanctions, text-as-data, US foreign policy
Introduction
The primary motivation for research on economic sanc-
tions is to answer the question of whether this foreign
policy tool ‘works’ – achieves the goals it is meant to.
Scholars have argued variously that: (1) sanctions work;
(2) sanctions do not work; and (3) sanctions work but
their effect is conditional and non-trivial to detect.
1
On
(1), it could be that sanctions work most of the time but
we can only appreciate that if we define the menu of
interventions and the expectations of the sender appro-
priately (Baldwin, 1999). On (2), sanctions may not
work because of sanctions-busting or nationalist rally-
around-the-flag effects (Early, 2015; Barry & Kleinberg,
2015; Grossman, Manekin & Margalit, 2018).
2
Type
(3) research has been particularly productive (Drezner,
2003). This is where our contribution lies – we ask how
the domestic politics and legislative processes of sender
Corresponding author:
niki.marinov@gmail.com
1
An importantpoint in the literature is that the economic costs a state
bearsand the political costsborne by the politicalagent or agents holding
office should not be equated (Galtung, 1967; Tsebelis, 1990; Smith,
1996; Pape, 1997; Rowe, 2001). See also work by Allen (2008); Barry
& Kleinberg (2015); Biersteker, Eckert & Tourinho (2016); Dashti-
Gibson, Davis & Radcliff (1997); Drezner (2000); Drury & Li (2006);
Early (2015); Escriba
`-Folch & Wright (2010); Grauvogel & von Soest
(2010); Lektzian & Souva (2001); McLean & Whang (2010); Marinov
(2005); Martin (1992); Miller (2014); Pape (1997); Peksen & Drury
(2010); Peterson (2013); Farrell & Newman (2019); Jentleson (2022).
2
Other work in this vein includes Pape (1997), Marinov (2005),
Licht (2017), and Alexeev & Hale (2020).
Journal of Peace Research
2023, Vol. 60(5) 877–885
ªThe Author(s) 2021
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DOI: 10.1177/00223433221088712
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