A large body of work on distributive politics emphasizes that incumbents strategically target spending at voters to achieve electoral ends, with important debates about whether politicians target swing or core voters. Nearly all such work, however, ignores the fact that voters are clustered in space and that much government spending is on club goods that are inherently geographic. These goods, such as schools or clinics, serve communities and cannot be targeted at individual voters; such goods also have spatial externalities because neighboring communities can use them. Our paper has three aims. First, we outline the analytical challenges inherent in taking project locations and their corresponding spatial externalities seriously. Second, we describe some of the empirical challenges associated with attaining project location data, mapping it, combining it with relevant covariates at the appropriate scale and modeling it. Third, we introduce a new dataset that combines over 40,000 projects in Ghana’s districts with fine-grained census tract and polling booth data. To the best of our knowledge, this is the largest data set of its kind. In preliminary analysis of a modest portion of the data, we estimate the role of need, partisanship and spatial externalities in shaping which communities receive government projects.
Funding: This research was supported by AidData at the College of William and Mary and the USAID Global Development Lab through cooperative agreement AID-OAA-A-12-00096.