GIS in Locating and Explaining Conflict Hotspots in Nepal

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1 GIS in Locating and Explaining Conflict Hotspots in Nepal Lila Kumar Khatiwada Notre Dame Initiative for Global Development 1

2 Outline Brief background Use of GIS in conflict study Data source Findings and recommendations 2

3 Background Nepal conflict ( ) claimed over 15,000 lives and displaced thousands Originated in western hill in 1996, by 2004 most of Nepal districts were affected Conflict experts: Spatial-horizontal inequality in the districts best explains origin and expansion of conflict 3

4 Patterns of conflict High casualties in some districts: They were clustered together Low casualties in some districts: They were also clustered together Presence of spatial dependence 4

5 Data sources UNDP Nepal Human Development Report Central Bureau of Statistics, Nepal INSEC- human rights violation data UNSTAT- country boundary file 5

6 Use of GIS Visualizing, seeing the patterns Combining data: combined data derived from three different sources Mapping the casualties Testing autocorrelation, Morans I Building models, spatial error, lag models 6

7 Software use ArcMap Geoda Excel 7

8 Population killed in the districts 8

9 Why spatial dependence in conflict? Conflict is contagious: conflict of one place depends on its neighbor (autocorrelation) Geographically proximate units are similar to each other; conflict might spill over from one location to the next Population flows help in diffusion by facilitating the spread of arms, combatants, and ideologies conducive to conflict 9

10 Spatial dependence Underlying socio-economic process has led to clustered distribution of variable values Grouping processes grouping of similar people in localized areas Spatial interaction processes people near each other more likely to interact, share Diffusion processes Neighbors learn from each other Dispersal processes People move, but tend to be short distances, take their knowledge with them Spatial hierarchies Economic influences that bind people together 10

11 Moran s I A measure of autocorrelation similar in interpretation to the Pearson's correlation for independent samples, in that both statistics range between -1.0 and 1.0 Local Moran s I decomposes a global measure into each unit s contribution 11

12 Scatterplot 12

13 Moran s I results of high-high and low-low districts and their comparison Development indicators Low-low districts (averages) National Average High-high districts (averages) Life expectancy at birth, yrs Adult literacy rate Percent population without safe drinking water Female life expectancy, yrs Female literacy rate Percent women in administrative jobs Infant mortality rate Percent electrified households Land inequality Percent population with access to credit Percent population in nonagriculture

14 Local Moran s I 14

15 Spatial lag model Spatial lag model deals with questions of how the interaction between socioeconomic agents can lead to emergent collective behavior and aggregate patterns It is used to estimate the effect of various socioeconomic factors present in the districts on conflict It includes the mean of the dependent variable in neighboring areas (i.e., spatial lag) as an extra explanatory variable 15

16 Dependent variable District level fatalities: both govt. army, rebel side and common people Death rate is standardized based on district population 16

17 Regression results Variables Coefficient Std. Error Constant * Per capita GDP in PPP$ Adult literacy rate * Women s share of income ** Average landholding size ** Electrified households * Infant mortality rate Percent in non-agriculture Percent household with radio ** R Log Likelihood Rho 0.398*** 17

18 Findings Conflict is not independent of location and is not random but is a function of regional spatial effects A spatial lag model shows that districts with higher death rate had higher illiteracy, lower landholding size, poor infrastructure base, and unequal share of women s income 18

19 Findings It calls for addressing inequality issues in the districts Program and policy targeted for post reconstruction should be focused at the regional level the effect of any intervention may go beyond a district s boundary 19

20 Methodological contribution GIS can be used to locate the high conflict places Modeling with available spatial approach can answer many questions that are not possible from other methods 20

21 Thanks! 21

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