Linking Ethnic Data from Africa (LEDA)
| Author | Nils-Christian Bormann,Carl Müller-Crepon,Yannick Pengl |
| DOI | 10.1177/00223433211016528 |
| Published date | 01 May 2022 |
| Date | 01 May 2022 |
| Subject Matter | Special Data Features |
Special Data Features
Linking Ethnic Data from Africa (LEDA)
Carl Mu
¨ller-Crepon
Department of Politics and International Relations, University of Oxford
Yannick Pengl
Center for International Studies, ETH Zurich
Nils-Christian Bormann
Department of Philosophy, Politics, and Economics, Witten/Herdecke University
Abstract
Social scientists in general and conflict researchers in particular increasingly combine multiple datasets to study ethnic
politics and conflict in Africa. We facilitate these efforts by systematically linking over 8,100 ethnic categories from
11 databases, including surveys, geographic data, and expert-coded lists. Exploiting the linguistic tree from the
Ethnologue database, we propose a systematic solution to the grouping problem of ethnicity. An analysis of political
exclusion, mistrust of state leaders, and ethnic grievances highlights different ways of linking ethnic categories from
multiple datasets. The LEDA open-source software package allows researchers to link ethnic groups from any
database with explicit rules and to add their own data on ethnic groups.
Keywords
Africa, data, ethnicity
Introduction
Ethnic identityconstitutes one of the mostsalient political
cleavages in developing countries, in particular in sub-
Saharan Africa. Not surprisingly, social scientists investi-
gate the effect of ethnic differences on outcomes such as
national identification (Robinson, 2014), trust (Nunn &
Wantchekon, 2011), voting (Huber, 2012), and distribu-
tive politics (De Luca et al., 2018). Ethnic groups and
their attributes have been especially relevant to the study
of civil war (Cederman, Gleditsch & Buhaug, 2013;
Horowitz, 1985; Østby, 2008; Stewart, 2008) and com-
munal violence (Fjelde & von Uexkull, 2012; Fjelde &
Østby, 2014; Hillesund et al., 2018), but also one-sided
violence (Fjelde & Hultman, 2014) and international
dynamics of ethnic civil wars (Cederman et al., 2013).
Combining meso- and micro-level datasets, scholars
explore the effects of ethnic group-level characteristics
on individual outcomes (Franck & Rainer, 2012),
measure group-level attributes through micro-data
(Cederman, Weidmann & Bormann, 2015), or enrich
one meso-level dataset with information from another
(Wig, 2016; Wig & Kromrey, 2018).
When studying questions related to ethnicity, it is
inherently difficult to link ethnic categories from two
datasets to each other.
1
Due to the socially constructed
nature of ethnic identities and different conceptual
approaches, we lack a common definition of the uni-
verse of ethnic groups in Africa. Thus, any social scien-
tist faces the ‘grouping problem’ of ethnic identities
(Posner, 2004a: 850–851). Put differently, each dataset
comes with its own list and resolution of ethnic cate-
gories. Some, for example the Ethnic Power Relations
data (EPR; Vogt et al., 2015), focus on a theoretically
Corresponding author:
carl.muller-crepon@politics.ox.ac.uk
1
The terms ‘linking’ and ‘matching’ interchangeably denote the
process of connecting any two ethnic categories from different data
sources.
Journal of Peace Research
2022, Vol. 59(3) 425–435
ªThe Author(s) 2021
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DOI: 10.1177/00223433211016528
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