This paper introduces the new Family of Ethnic Power Relations (EPR) Datasets, version 2014, which

The global expansion of the Internet is frequently associated with increased government transparency, political rights, and democracy. However, this assumption depends on marginalized groups getting access in the first place. Here we document a strong and persistent political bias in the allocation of Internet coverage across ethnic groups worldwide. Using estimates of Internet penetration obtained through network measurements, we show that politically excluded groups suffer from significantly lower Internet penetration rates compared with those in power, an effect that cannot be explained by economic or geographic factors. Our findings underline one of the central impediments to "liberation technology," which is that governments still play a key role in the allocation of the Internet and can, intentionally or not, sabotage its liberating effects.

A large body of literature claims that oil production increases the risk of civil war. However, a growing number of skeptics argue that the oil–conflict link is not causal, but merely an artifact of flawed research designs. This article re-evaluates whether – and where – oil causes conflict by employing a novel identification strategy based on the geological determinants of hydrocarbon reserves. We employ geospatial data on the location of sedimentary basins as a new spatially disaggregated instrument for petroleum production. Combined with newly collected data on oil field locations, this approach allows investigating the causal effect of oil on conflict at the national and subnational levels. Contrary to the recent criticism, we find that previous work has underestimated the magnitude of the conflict-inducing effect of oil production. Our results indicate that oil has a large and robust effect on the likelihood of secessionist conflict, especially if it is produced in populated areas. In contrast, oil production does not appear to be linked to center-seeking civil wars. Moreover, we find considerable evidence in favor of an ethno-regional explanation of this link. Oil production significantly increases the risk of armed secessionism if it occurs in the settlement areas of ethnic minorities.

Weak state capacity is one of the most important explanations of civil conflict. Yet, current conceptualizations of state capacity typically focus only on the state while ignoring the relational nature of armed conflict. We argue that opportunities for conflict arise where relational state capacity is low, that is, where the state has less control over its subjects than its potential challengers. This occurs in ethnic groups that are poorly accessible from the state capital, but are internally highly interconnected. To test this argument, we digitize detailed African road maps and convert them into a road atlas akin to Google Maps. We measure the accessibility and internal connectedness of groups via travel times obtained from this atlas and simulate road networks for an instrumental variable design. Our findings suggest that low relational state capacity increases the risk of armed conflict in Africa.

Research on ethnic politics and political violence has benefited substantially from the growing availability of cross-national, geo-coded data on ethnic settlement patterns. However, because existing datasets represent ethnic homelands using aggregate polygon features, they lack information on ethnic compositions at the local level. Addressing this gap, this article introduces the Spatially Interpolated Data on Ethnicity (SIDE) dataset, a collection of 253 near-continuous maps of local ethno-linguistic, religious and ethno-religious settlement patterns in 47 low- and middle-income countries. We create these data using spatial interpolation and machine learning methods to generalize the ethnicity-related information in the geo-coded Demographic and Health Surveys (DHS). For each DHS survey we provide the ethnic, religious and ethno-religious compositions of cells on a raster that covers the respective countries at a resolution of 30 arc-seconds. The resulting data are optimized for use with geographic information systems (GIS) software. Comparisons of SIDE with existing categorical datasets and district-level census data from Uganda and Senegal are used to assess the data’s accuracy. Finally, we use the new data to study the effects of local polarization between politically relevant ethnic groups, finding a positive effect on the risk of local violence such as riots and protests. However, local ethno-political polarization is not statistically associated with violent events pertaining to larger-scale processes such as civil wars.