Turnout and the local age distribution: examining political participation across space and time
Section snippets
Differences in political and policy views
What kind of political effects might we expect to follow from the generational changes we have been discussing? Much of the significance of generational differences would appear to hinge upon the arriving and departing generations having differing policy views and interests. The fertility and mortality process is surely capable of driving partisan change through differential socialization associated with the events occurring during each generation’s upbringing (Abramson, 1975, Braungart and
Geographic variation in the age distribution
Adding to the fascinating complexity of trying to understand the effects of age cohorts on political behavior is a large and restless population residing in a federal system in which state and local elections are waged as politically distinct battles. To comprehend the political impact of specific age distributions, local information about the geography of these developments is required.
Since our focus is on geographic variation in voter turnout, we must evaluate the relative theoretical
Geographic or spatial structure in turnout rates
There are a number of ways in which we can statistically evaluate the effect of local age distributions in order to document and understand their impact. As a temporal process, addressing the effect of aging on turnout over time obviously makes sense, particularly if the focus is on changes attributable to distinctive generations, as opposed to differences between one group and another attributable to the part of the life-cycle in which they find themselves. Our approach here we will set aside
Alternative hypotheses and data analysis
The Moran’s I statistic, along with the obvious spatial patterns exhibited by the standardized in Fig. 4, strongly suggest that we consider the alternative explanations for turnout that are commonly advanced in political participation research. Indicators that represent these causal influences must be included in any model that hopes to isolate the effects of generational variables. First, we control for the effect of recent migration. Population mobility depresses turnout due to the fact
Results from high and low growth settings: 1980–2000
Little more than a cursory overview of Table 2, Table 3 is needed before one realizes that there are—not surprisingly—striking similarities among these sets of locations regardless of whether they are low growth, high growth or somewhere in between. Variables associated with the conventional SES model (education and income) tend to have a significant impact on turnout regardless of the growth status of the county. Similarly, counties with relatively higher black populations exhibit lower
Results from the pooled cross-sectional analysis
As a last step in our analysis designed to help us summarize our findings and generalize about the impact of our explanatory variables, we pooled our cross-sectional data sets, and controlled for the effect of individual election years with (0, 1) dummy variables. We excluded 1980 for use as the baseline for comparison. We first ran these models without the spatially lagged dependent variable, and the results indicated that there was substantial spatial autocorrelation in the residuals (I=0.51)
Discussion
While all of the points we have made rely upon inferences made from ecological data, we are encouraged that the results we present are not wildly at odds with the large body of survey data on age cohort effects on participation (for example: Rosenstone & Hansen, 1993). Knowing that candidates and parties wage war over turf, and are focused on electorates rather than individuals, our work has tried to extend some of the survey-based generalizations to a geographic level.
What will happen when the
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