Poster #23 - Digging for Conflict Patterns: Understanding the Relationship Between Mining and Conflict in Central Asia’s Ferghana Valley

• In Event: Saturday Poster Luncheon

Abstract

This study examines the relationship between mining and conflict in Central Asia’s densely populated Ferghana Valley, a particularly under-studied region with significant mineral resources, geopolitical tensions, ethnic and cultural diversity, and a history of dispute. We combine remotely sensed data with information on mining activity, borders, land use, water resources, and conflict events across highly disaggregated hexagonal grid cells covering the valley and its surrounding environs. Mining activity is strongly linked to conflict. In any given year, the probability of conflict increases the closer a grid cell is to a mine. For example, moving from a distance of 50 km to 5 km from a mine is associated with a 0.92 percentage-point increase in the likelihood of conflict, representing a 163% increase relative to the mean probability of conflict across grids. We show that the underlying mechanisms driving this relationship are unique to Ferghana. Specifically, mining in the region appears to exacerbate conflict through its effect on already constrained land and water resources, operating through property-rights and environmental and resource-externality channels. Furthermore, this association is particularly pronounced along the region’s complex and contentious borders. We support these quantitative findings with a qualitative analysis of conflict-event narratives. Prior research examining the relationship between mining and conflict has mostly focused on Africa and South America, raising questions about the generalizability of previously observed mining–conflict mechanisms. Unlike in many other contexts, we find only weak evidence that conflict is sensitive to price fluctuations or that it is being fueled by fighting over the control of mineral resources and the profitability of mining projects.

Note: This paper does not include public or formerly public data that was recently embargoed or taken offline.

Author

• Elisa Yoshiara, RAND Corporation
  Presenting Author