Brian Min

Why Do Ethnic Groups Rebel?: New Data and Analysis

Much of the quantitative literature on civil wars and ethnic conflict ignores the role of the state or treats it as a mere arena for political competition among ethnic groups. other studies analyze how the state grants or withholds minority rights and faces ethnic protest and rebellion accordingly, while largely overlooking the ethnic power configurations at the states center. drawing on a new data set on ethnic power relations (EPR ) that identifies all politically relevant ethnic groups and their access to central state power around the world from 1946 through 2005, the authors analyze outbreaks of armed conflict as the result of competing ethnonationalist claims to state power. the findings indicate that representatives of ethnic groups are more likely to initiate conflict with the government (1) the more excluded from state power they are, especially if they have recently lost power, (2) the higher their mobilizational capacity, and (3) the more they have experienced conflict in the past.

Ethnic Politics and Armed Conflict: A Configurational Analysis of a New Global Data Set

Quantitative scholarship on civil wars has long debated whether ethnic diversity breeds armed conflict. We go beyond this debate and show that highly diverse societies are not more conflict prone. Rather, states characterized by certain ethnopolitical configurations of power are more likely to experience violent conflict. First, armed rebellions are more likely to challenge states that exclude large portions of the population on the basis of ethnic background. Second, when a large number of competing elites share power in a segmented state, the risk of violent infighting increases. Third, incohesive states with a short history of direct rule are more likely to experience secessionist conflicts. We test these hypotheses for all independent states since 1945 using the new Ethnic Power Relations (EPR) data set. Cross-national analysis demonstrates that ethnic politics is as powerful and robust in predicting civil wars as is a countrys level of economic development. Using multinomial logit regression, we show that rebellion, infighting, and secession result from high degrees of exclusion, segmentation, and incohesion, respectively. More diverse states, on the other hand, are not more likely to suffer from violent conflict.

From Empire to Nation-State: Explaining Wars in the Modern World, 1816–2001

The existing quantitative literature on war takes the independent nation-state as the self-evident unit of analysis and largely excludes other political types from consideration. In contrast, the authors argue that the change in the institutional form of states is itself a major cause for war. The rise of empires and the global spread of the nation-state are the most important institutional transformations in the modern age. To test this hypothesis, the authors introduce a new data set that records the outbreak of war in fixed geographic territories from 1816 to 2001, independent of the political entity in control of a territory. Analysis of this data set demonstrates that wars are much more likely during and because of these two transformations. For the transformation to the modern nation-state, the authors confirm this hypothesis further with logit regressions that control for variables that have been robustly significant in previous research. The results provide support for the main mechanisms that explain this time dependency. Modern nation-states are ruled in the name of a nationally defined people, in contrast to empires, which govern to spread a faith across the world, to bring civilization to backward people, or to advance the world revolutionary cause. The institution of the nation-state thus introduces incentives for political elites to privilege members of the national majority over ethnic minorities, and for minority elites to mobilize against such political discrimination. The resulting power struggles over the ethno-national character of the state may escalate into civil wars. Interstate wars can result from attempts to protect co-nationals who are politically excluded in neighboring states. The reported research thus provides a corrective to mainstream approaches, which exclude ethnic and nationalist politics as factors that would help understanding the dynamics of war.

Baghdad Nights: Evaluating the US Military ‘Surge’ Using Nighttime Light Signatures

Baghdad Nights: Evaluating the US Military ‘Surge’ Using Nighttime Light Signatures John Agnew Thomas W. Gillespie Jorge Gonzalez Brian Min CCPR-064-08 December 2008 Latest Revised: December 2008 California Center for Population Research On-Line Working Paper Series

Detection of rural electrification in Africa using DMSP-OLS night lights imagery

We report on the first systematic ground-based validation of the US Air Force Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) night lights imagery to detect rural electrification in the developing world. Drawing upon a unique survey of villages in Senegal and Mali, this study compares night-time light output from the DMSP-OLS against ground-based survey data on electricity use in 232 electrified villages and additional administrative data on 899 unelectrified villages. The analysis reveals that electrified villages are consistently brighter than unelectrified villages across annual composites, monthly composites, and a time series of nightly imagery. Electrified villages appear brighter because of the presence of streetlights, and brighter villages tend to have more streetlights. By contrast, the correlation of light output with household electricity use and access is low. We further demonstrate that a detection algorithm using data on night-time light output and the geographic location of settlements can accurately classify electrified villages. This research highlights the potential to use night lights imagery for the planning and monitoring of ongoing efforts to connect the 1.4 billion people who lack electricity around the world.

The Location and Purpose of Wars Around the World: A New Global Dataset, 1816–2001

A critical question in the quantitative study of war is how to choose appropriate units of analysis. While most studies link wars to the sovereign states that fight them, several authors have recently offered alternative perspectives, focusing on the the properties of rebel organizations and armies or tracking events in fine-grained geographic spaces. We contribute to these developments by introducing a new dataset of wars fought from 1816–2001 on fixed territorial units of observation that conform to the grid of states in 2001. Compared to standard datasets, we expand the geographic purview to include states not recognized by the international system. We provide location codes that identify the territories on which conflicts are fought, which is especially important for the analysis of imperial wars and colonial rebellions. We also introduce a new typology of wars based upon the aims of warring parties rather than their status in the state system. This dataset is uniquely suited to explore new questions that cannot be addressed with other datasets. To illustrate, we test an institutionalist theory of war and show empirically that the types of wars fought in a territory depend on whether it is governed as a modern nation-state, an imperial dependency, or the center of an empire.

Tracking Electrification in Vietnam Using Nighttime Lights

The authors report on a systematic ground-based validation of DMSP-OLS night lights imagery to detect rural electrification in Vietnam. Based on an original survey of village-level units in Vietnam, this study compares nighttime light output from the U.S. Air Force Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) against ground-based survey data on electrical infrastructure and electricity use in 200 electrified villages. Monthly and annual composites record a one-point increase in brightness along DMSP-OLS’s 63-point brightness scale for every 60–70 additional street lights or 240–270 electrified homes. Using a time series of 90 nightly images, the data show a one-point increase in brightness for every 125–200 additional streetlights, or 550–700 additional electrified homes. The results highlight the potential to use night lights imagery to support efforts to connect the 1.2 billion people who lack electricity around the world.