Data Appendix for
Shared Space: Ethnic Groups, State Accommodation and Localized Conflict
Kathleen Gallagher Cunningham
International Peace Research Institute, Oslo
and
Iowa State University
Nils B. Weidmann
Princeton University
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DATASETS
Two datasets are provided for this article:
(i)
a GIS dataset of first-level administrative units for 1991, and
(ii)
the (non-spatial) dataset containing the variables required to replicate the
regression results reported in the article.
THE ADMINISTRATIVE REGIONS GIS DATASET
The administrative unit dataset contains the first-level administrative regions of
150 countries as of 1991 as vector polygons. The dataset is provided in the ESRI
shapefile format (http://www.esri.com/library/whitepapers/pdfs/shapefile.pdf) in WGS
1984 reference system. It can be used with all standard GIS tools. Some statistical
software also provide basic support for the shapefile format, as for example the R
package.
Our dataset was created from an existing administrative unit dataset provided by
ESRI, which is now freely available at
http://geodata.grid.unep.ch/download/admin98_li_shp.zip
However, this dataset captures the administrative subdivisions of countries for different
points in time. For this reason, we backdated it to reflect the 1991 status. This was done
using the country descriptions and maps given on the Statoids web page
(http://www.statoids.com/).
Apart from the geographic extent, the GIS contains the following variables for
each unit:
 ADMIN_NAME: The name of the unit
 FIPS_CNTRY: The FIPS identifier of the country the unit is part of
 CNTRY_NAME: The name of the country the unit is part of
 COWCODE: The COW identifier of the country the unit is part of
 ADMINID: A unique numeric identifier for the unit
THE REPLICATION DATASET
This dataset is a cross-section of first-level administrative units, as given by our
GIS dataset introduced above. The unit of analysis is the first-level administrative unit in
1991. Newly created or changed units in the 1990s are not included in the data.
Coding information
Ethnic groups coding
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For each administrative unit, the number and relative population of different
ethnic groups were identified using the GREG GIS dataset. See the GREG article
forthcoming in the Journal of Peace Research for an illustration of how this done. The
article is available on the GREG webpage (http://www.icr.ethz.ch/research/greg). We
then rank groups according to their relative size in the unit, and use the difference
between the largest and the second largest group as our indicator of domination. This is a
continuous measure from 0 to 1. Units with a 0 score have multiple ethnic groups with
total parity in population shares. Units with a 1 have only one ethnic group.
Description of variables computed from GREG:
 LUNITPOP: logged total population of a unit
 LCTRPOP: loggeg total country population, computed as the sum of all unit
populations in a country
 DOMINATION: the difference in the population shares between the largest
and the second largest group (or 1 if there is only one group).
Conflict coding
Cases of ethnic conflicts are based on a combination the Cunningham et al (2009)
dataset and the Minorities at Risk (MAR) rebellion coding which were matched to the
GREG group list. The Cunningham et al (2009) data has a 25 battle death threshold, and
includes dyadic data on conflict that encompasses all distinct groups in the dispute. The
MAR data is coded by group and indicates a level of rebellion. All groups that received a
2 or greater were given a positive coding for violence (this is all violence greater than
“banditry/scattered terrorism”). The geocoding of the conflict was done by the authors
using the following process. First, ethnic groups in the GREG list were matched to
parties in conflict in the Cunningham at al (2009) and MAR data. Next, using the
Minorities at Risk profiles and Uppsala conflict profiles, the location of conflict was
determined for each conflict cases. Possible locations included all regional sub-units that
contained the ethnic group in question.
Description of conflict variables:
 LOCALCONF - group was in conflict in 90s in this unit
 INTERCONF - group was in communal conflict in 90s in this unit
 CONF - group was in either civil war violence conflict or communal conflict in
90s in this unit.
Example: map of ethnic group coding and conflict locations
The map in Figure A1 shows our coding of India. For each of the states, the color
shading indicates the level of domination computed for this state. The white dots denote
those states that are coded as having ethnic conflict in the 1990s.
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Figure A1: Map of India, showing the domination scores at the state level as well as our
conflict coding.
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