In the empirical analysis, we combine geo-coded conflict-event data from the UCDP Georeferenced Event Dataset (GED) global version 19.1 (Sundberg and Melander, 2013) with information on the birth places of political leaders from the Political Lead-ers’ Affiliation Database (PLAD) (Dreher et al., 2020). Our dataset is based on several further sources that, together with detailed variable definitions and measurements, are listed in the Data appendix. The unit of observation is region-year, whereby
‘region’ refers to the second administrative level of a country provided by the GADM dataset v3.6 (GADM, 2019). Our final sample consists of a panel dataset with 44,025 regions in 2,963 provinces and 172 countries over the years 1989 – 2015 resulting in a total of 1,177,805 observations.
The main explanatory variables are Leader autoc and Leader non-autoc, which are defined as dummy variables that take the value of 1 if a region is the birth region of the current national leader in an autocratic and non-autocratic political regime. In years with a change in office, two regions can be defined as the leader region. We identify the birth regions of national leaders with the PLAD database. Figure 3.1 depicts the leader regions.
Our dependent variables are three different indicators of conflict. Conflict is measured a) as a dummy variable, indicating if there is any conflict event in a given region and year, b) as a dummy variable for conflict events resulting in at least 25 battle-related deaths in a given region and year or c) by the inverse hyperbolic sine function of the number of casualties. The variables are based on the UCDP GED dataset, which offers information on the exact geographical location of conflict events, the involved actors and the corresponding reported number of casualties from 1989 until 2015. In the channel analysis, we subdivide the conflict events based on the UCDP definition into state-based and non-state-based conflicts as well as one-sided violence.
The frequency of conflict, measured by the number of years in which at least one conflict event occurred, is shown in figure 3.2. Conflict events are regionally clustered,
Chapter 3. Political favoritism and conflict
FIGURE3.1: Spatial distribution of leader regions
Note:The figure reports the number of years of being the leader region for each second administrative region over the time period of 1989 – 2015. A leader region is the birth region of the effective leader during the time in office. Sources: Archigos, own data collection.
FIGURE3.2: Spatial distribution of conflict years
Note:The figure reports the number of conflict years for each second administrative region during the sample period 1989 – 2015. A conflict year is a year in which at least one conflict event occurred in the region. Source: UCDP.
with a higher frequency of conflict events in Africa, the Middle East and parts of Asia. Most regions experienced 0 years of conflict, others were exposed to conflict during the entire sample period. The average probability of a region to experience a conflict event in any given year is 2.2% in our sample. On average, 1.45 conflict-related casualties per region and year occur. The average probability of conflict rises to 3.5% (6.37 casualties) for regions in autocracies and drops to 1.9% (0.6 casualties) in non-autocratic countries. In general, leader regions have a higher likelihood to experience conflict (6.24% with an average of 16.06 casualties per year). Similarly, the probability (8.03% vs 5.79%) and intensity (58.02 vs 2.83 casualties) of conflict is higher in autocracies. This unconditional comparison shows a) that autocracies are
more prone to conflict than non-autocracies and b) that leader regions on average experience more conflicts than non-leader regions.
Political favoritism is not only targeted towards the birth regions of national leaders but also towards their ethnic in-groups (De Luca et al., 2018b). We use the information on the ethnic affiliation of national leaders provided by the PLAD dataset in order to link the leaders’ ethnicity to conflict in two different ways. First, we stick to the regional approach and observe the conflict exposure of ethnic homelands based on the GeoEPR2019 dataset (Vogt et al., 2015). Second, we link ethnicity to conflict via (ethnic non-governmental) conflict actors provided by the Geographical Research On War Unified Platform (Growup) database (Girardin et al., 2015). This allows us to observe whether ethnic groups of national leaders are less involved in conflict events while the leaders are in office. To do so, we create dummy variables that indicate the ethnic homelands of the current political leader and identify the conflict actors belonging to the same ethnicity as the current leader. Analogous to the birth regions, we separate by political regime type.
In order to investigate the channels of action, we use geo-localized data from the Afrobarometer rounds 1 to 6. We aggregate the individual survey data at the second administrative level. This provides us with regional measures for the presence of state forces (military or police), trust and evaluated performance of the national leaders, and measurements of corruption. Since the Afrobarometer data is only available for 35 countries and at most 6 years, the sample is reduced to around 7000 observations.
A detailed description of all variables used can be found in the data appendix, and table 3.1 provides the descriptive statistics of the main variables.
Chapter 3. Political favoritism and conflict
TABLE3.1: Summary statistics
Variable Obs Mean SD Min Max
(1) (2) (3) (4) (5)
Regional favoritism
Conflict 1,177,805 0.02 0.15 0 1
Number of casualties 1,177,805 1.47 311.39 0 321,999
Leader region 1,177,805 0.00 0.06 0 1
Autocratic regime 1,177,805 0.13 0.34 0 1
Flood (sum of months) 1,177,805 2.26 2.14 0 12
Drought (sum of months) 1,177,805 2.00 2.03 0 12
Ln(population) 1,177,805 11.83 1.70 0.99 16.76
Oil x ln(price) 1,177,805 0.70 1.45 0 4.65
Gas x ln(price) 1,177,805 0.80 1.67 0 5.19
Ethnic favoritism
Ethnic leader homeland region 14,954 0.16 0.36 0 1
Any conflict per ethnic homeland 14,954 0.26 0.44 0 1
Number of casualties per ethnic homeland 14,954 189.03 6182.72 0 524,477
Ethnicity leader region 15,094 0.16 0.36 0 1
Any conflict per ethnicity 15,094 0.05 0.22 0 1
Number of casualties per ethnicity 15,094 39.16 493.23 0 30,628 Channel analysis
Number of state casualties 1,177,805 0.52 32.53 0 16,060
Number of non-state casualties 1,177,805 0.08 5.77 0 2,494 Number of civilian casualties by gov 1,177,805 0.24 66.14 0 44,310
Polity 2 score 1,157,668 5.52 5.37 -10 10
Nighttime lights 957,939 6.75 12.04 0 63
Army 7,757 0.10 0.26 0 1
Police 7,763 0.32 0.36 0 1
State force 7,763 0.25 0.28 0 1
Trust leader 8,131 1.82 0.67 0 3
Performance leader 8,137 2.82 0.61 1 4
Activism 8,236 0.98 0.59 0 5
Corruption index 8,336 2.42 0.43 1 4
Political corruption 8,190 2.21 0.49 1 4
Police corruption 7,791 2.63 0.47 1 4
Coup 1,177,805 0.14 0.35 0 1
Resource 1,177,805 0.13 0.33 0 1
Ethnic 1,177,805 0.51 0.50 0 1