Measuring change in source of leader support

The CHISOLS dataset

Bibliographic Data

ID3917113
AuthorsMichaela Mattes (0000-0002-1566-7479, University of California, Berkeley), Brett Ashley Leeds (0000-0002-4598-3528, Rice University, corresponding author), Naoko Matsumura (0000-0002-5879-4339, Hitotsubashi University)
Year2016
Volume53
Issue2
Pages259-267
Publication date2016-03-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueJournal of Peace Research (JOURNAL)
Journal identifiersISSN: 0022-3433 • E-ISSN: 1460-3578
PublisherSAGE Publications Inc (PUBLISHER)
DOI10.1177/0022343315625760
OpenAlexW2319484893
LanguageEN
Citations received57
References cited21

This article introduces the CHISOLS (Change in Source of Leader Support) dataset, which identifies which leadership changes within countries bring to power a new leader whose primary support is drawn from different societal groups than those who supported her predecessor. The dataset covers all countries of the world with populations greater than 500,000 from 1919 to 2008. We discuss the underlying rationale of our data collection, provide some brief information about the coding rules and procedures, and share some descriptive statistics. We find that changes in sources of leader support are more common in democracies than non-democracies, but also that changes in sources of leader support often occur without irregular leader transitions or large institutional changes, even within non-democracies. CHISOLS can be productively combined with other datasets like POLITY, Archigos, and DPI that provide information about political institutions, modes of leader transition, and placement on a left-right policy continuum, but CHISOLS also provides something new that was not previously available. These data allow researchers to study the extent to which different types of policy change are associated with all leader transitions, with changes in political institutions, or with changes in the set of interests that leaders most closely represent; CHISOLS facilitates comparing the effect of leaders, interests, and institutions on policy change across a wide spatial temporal domain

Coding (social sciences) · Descriptive statistics · Political science · Politics · Polity · Public relations · Set (abstract data type) · Social science · Sociology · Statistics · Computer Science · Electoral Systems and Political Participation · Law · Mathematics · Political Conflict and Governance · Social Policy and Reform Studies

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