Record Details

Reporting of Non-Fatal Conflict Events

Harvard Dataverse (Africa Rice Center, Bioversity International, CCAFS, CIAT, IFPRI, IRRI and WorldFish)

View Archive Info
 
 
Field Value
 
Title Reporting of Non-Fatal Conflict Events
 
Identifier https://doi.org/10.7910/DVN/AI4P1G
 
Creator Mihai Croicu
Kristine Eck
 
Publisher Harvard Dataverse
 
Description Temporally and spatial disaggregated datasets are commonly used to study political violence. Researchers are increasingly studying the data generation process itself to understand the selection processes by which conflict events are included in conflict datasets. This work has focused on conflict fatalities. In this research note, we explore how non-fatal conflict events are reported upon and enter into datasets of armed conflict. To do so, we compare reported non-fatal conflict events with the population of events in two direct observation datasets, collected using a boots-on-the-ground strategy: mass abductions in Nepal (1996–2006) and troop movements in Darfur. We show that at the appropriate level of aggregation media reporting on abductions in Nepal largely mirrors the “true” population of abductions, but at more disaggregated levels of temporal or spatial analysis, the match is poor. We also show that there is no overlap between a media-driven conflict dataset and directly-observed data on troop movements in Sudan. These empirics indicate that non-fatal data can suffer from serious underreporting and that this is particularly the case for events lacking elements of coercion. These findings are indicative of selection problems in regards to the reporting on non-fatal conflict events.
 
Subject Social Sciences
conflict
Reporting bias
Non-violence
event data
data
 
Contributor Interactions, International