Spatial statistics and voting

In political science, “spatial models” are usually metaphorical, with the “spatial” dimensions representing political ideology (left to right) or positions on issues such as war/peace or racial tolerance. But what about actual spatial dimensions, actual distances on the ground? In some sense, spatial models are used all the time in analyzing political data, since states, counties, Congressional districts, neighborhoods, and so forth are always (or nearly always) spatially contiguous. Along with these political structures, one can also add spatial information in the form of distances between units and then fit so-called geostatistical models.

Drew Thomas has done some work along these lines, fitting spatial-statistical modeling to vote data from the counties in Iowa. (See also a draft of his paper here). Much more could be done here, clearly, but this work might be of interest as a starting point for others who want to play with these sorts of models.