About the Society
Papers, Posters, Syllabi
Submit an Item
Polmeth Mailing List
Below results based on the criteria 'geography'
Total number of records returned: 3
Issue Voting and Ecological Inference
Thomsen, Soren R.
This article proposes a unifying framework for individual and aggregate voting behavior. The proposed individual level model is a version of the multinomial logit model that applies to both issue voting, ideological voting and normative voting providing a close fit to survey data. The aggregate model is derived by using the binary logit model as an approximation to the multinomial logit model. The aggregate model is useful for modeling electoral change and for identification of homogenous political regions. Further, the unifying framework derives a method for ecological inference that applies to large tables and gives estimates of voter transitions close to survery results.
Is It Worth Going the Extra Mile to Improve Causal Inference? Understanding Voting in Los Angeles County
Brady, Henry E.
Two seemingly unrelated approaches to quantitative analysis have recently become more popular in social science applications. The first approach is the explicit consideration of counterfactuals in causal inference and the development of various matching techniques to choose control cases comparable to treated cases in terms of some predefined characteristics. To be useful, these methods require the identification of important characteristics that are likely to ensure that a statistical condition called “conditional independence” is met. The second trend is the increased attention given to geography and the use of spatial statistics. Although these two approaches have found their ways into the social science research separately, we think that they can be fruitfully combined. Geography and Geographic Information Systems (GIS) can improve matching and causal inference. Geography can be conceptualized in terms of “distance” and “place” which can provide guidance about potentially important characteristics that can be used to improve matching. After developing a conceptual framework that shows how this can be done, we present two empirical examples which combine counterfactual thinking with geographical ideas. The first example looks at the cost of voting and demonstrates the utility of matching using zip codes and distance to polling place. The second example looks at the performance of the InkaVote voting system in Los Angeles by matching precincts in LA with geographically adjacent precincts in surrounding counties. This example demonstrates the strengths and weaknesses of geographic proximity as a matching variable. In pursuing these examples, we also show how recent progress in GIS techniques provides tools that can deepen researchers’ understanding of their idea.
Tobler's Law, Urbanization, and Electoral Bias: Why Compact, Contiguous Districts are Bad for the Democrats
When one of the major parties in the United States wins a substantially larger share of the seats than its vote share would seem to warrant, the conventional explanation lies in manipulation of maps by the party that controls the redistricting process. Yet this paper uses a unique data set from Florida to demonstrate a common mechanism through which substantial partisan bias can emerge purely from residential patterns. When partisan preferences are spatially dependent and partisanship is highly correlated with population density, any districting scheme that generates relatively compact, contiguous districts will tend to produce bias against the urban party. In order to demonstrate this empirically, we apply automated districting algorithms driven solely by compactness and contiguity parameters, building winner-take-all districts out of the precinct-level results of the tied Florida presidential election of 2000. The simulation results demonstrate that with 50 percent of the votes statewide, the Republicans can expect to win around 59 percent of the seats without any "intentional" gerrymandering. This occurs because urban districts tend to be homogeneous and Democratic while suburban and rural districts tend to be moderately Republican. Thus in Florida and other states where Democrats are highly concentrated in cities, the seemingly apolitical practice of requiring compact, contiguous districts will produce systematic pro-Republican electoral bias.