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Researchers today have access to an unprecedented amount of geo-referenced, disaggregated data on political conflict. Because these new data sources use disparate event typologies and units of analysis, findings are rarely comparable across studies. As a result, we are unable to answer basic questions like 'what does conflict A tell us about conflict B?' This article introduces xSub – a 'database of databases' for disaggregated research on political conflict ( www.x-sub.org ). xSub reduces barriers to comparative subnational research, by empowering researchers to quickly construct custom, analysis-ready datasets. xSub currently features subnational data on conflict in 156 countries, from 21 sources, including large data collections and data from individual scholars. To facilitate comparisons across countries and sources, xSub organizes these data into consistent event categories, actors, spatial units (country, province, district, grid cell, electoral constituency), and time units (year, month, week, and day). This article introduces xSub and illustrates its potential, by investigating the impact of repression on dissent across thousands of subnational datasets.

Counterinsurgency, state repression and other forms of coercion have multiple adverse effects. Although a state's use of threats and force should deter an opposition group, these measures often stimulate resistance. And although state-led coercion aims to influence an opposition group, coercive practices have social, economic and political consequences for civilians. This dissertation studies the efficacy and effects of coercive policies in the context of the Israel-Palestine conflict. The four composite essays investigate the impact of Israel's practice of house demolition and construction of a separation barrier on Palestinians' conflict preferences and use of violence, as well as the broader consequences of these policies for Palestinian communities. Essay I questions the conventional wisdom that the selective targeting of militants can be an effective counterinsurgency strategy. Through a survey of Palestinians, it demonstrates that house demolition can generate opposition to peace when it is perceived as indiscriminate in its targeting, even if it is selective by design. Essay II distinguishes between the mechanisms of collective threat and personal fear in state repression. In a longitudinal study of administrative demolition orders, it finds that orders issued against communal structures increase preferences for violence and militant political parties, suggesting that collective threats backfire. Essay III quantifies the economic consequences of counterinsurgency by measuring the separation barrier's impact on Palestinian employment and wages. It further shows that this economic impact increases the rate of Israeli conflict fatalities, demonstrating that economic consequences of coercion can stimulate violent resistance. Essay IV conceptualises a state's separation and exclusion of particular population groups as a general phenomenon and form of state repression. It draws on historical cases worldwide and presents the enclosure of Palestinian communities in special zones of the separation barrier as a contemporary example. The essays are empirical studies which use survey methods, quantitative analysis, principles of experimental design, qualitative sources and field work as a basis for description and explanation. As a whole, the dissertation contributes to the study of coercion by calling attention to understudied forms of coercion and identifying particular mechanisms by which threats and force can result in adverse effects.

AbstractTheoretical units of interest often do not align with the spatial units at which data are available. This problem is pervasive in political science, particularly in subnational empirical research that requires integrating data across incompatible geographic units (e.g., administrative areas, electoral constituencies, and grid cells). Overcoming this challenge requires researchers not only to align the scale of empirical and theoretical units, but also to understand the consequences of this change of support for measurement error and statistical inference. We show how the accuracy of transformed values and the estimation of regression coefficients depend on the degree of nesting (i.e., whether units fall completely and neatly inside each other) and on the relative scale of source and destination units (i.e., aggregation, disaggregation, and hybrid). We introduce simple, nonparametric measures of relative nesting and scale, asex anteindicators of spatial transformation complexity and error susceptibility. Using election data and Monte Carlo simulations, we show that these measures are strongly predictive of transformation quality across multiple change-of-support methods. We propose several validation procedures and provide open-source software to make transformation options more accessible, customizable, and intuitive.