CRS ICT4D Conference

This paper uses a spatial analytical approach in locating and explaining conflict in Nepal. Human casualties that occurred during the 10 years of conflict in the districts is the dependent variable to be explained. Moran’s I is used to test the spatial dependence of conflict in the districts. A highly significant lambda confirms spatial dependence, forming geographic clusters of high- and low-casualty districts. Further, local Moran’s I results show that high-conflict districts have higher socioeconomic problems. The results show that lower life expectancy, lower per capita income, low literacy, low employment, low scores on gender equality, and a weak infrastructure base in the districts are associated with higher conflict, possibly reflecting greater level of grievances against the government and intensification of conflict. A spatial lag model shows that illiteracy, landholding size, poor infrastructure base, and unequal share of women’s income are factors associated with conflict. The presence of spatial dependence suggests that any program and policy targeted for peace and stability should be focused at the regional level as the effect of any intervention may go beyond a district’s boundary.