Abstract
Age is among the strongest predictors of political participation, yet it is also among the least well understood. We oer a probability model of participation in the U.S. voter registration system - the rst step in the voting process. In this model, people have a constant probability of registering to vote at any given time and a constant probability of moving. A strong relationship between age and participation arises simply as a byproduct of the rules of the registration system, namely that participation is voluntary and that it is residentially based. Specically, the probability that someone is registered increases over time (and thus with age) even when the probability of becoming registered is constant. A new, national random sample of 1.8 million voter registration records is employed to test the model. The model provides a theoretical foundation for the relationship between age and participation, identies the functional
Highlights
Age is among the strongest predictors of political participation, yet it is among the least well understood
Our model presents an alternative explanation of the correlation between age and registration that poses a broad challenge to more common social-psychological explanations of political participation
We propose a stochastic model of a population in which people enter, exit upon moving, and can reenter
Summary
Let s be the rate of stabilty (non-movement) in the population, assumed constant and the same for all people in the basic model but allowed to vary in extensions. This is the flow parameter of registration. We assume constant r, it is useful to begin with a general accounting identity that characterizes the proportion of age cohort t who are registered, the stock of registrants of age t: Rt = Rt−1st + (1 − Rt−1)strt + (1 − st)rt. As people age their propensity to participate is not affected by aging or factors correlated with age, such as knowledge, social network density, education, or experience with the political system This assumption is consistent with data on registration (see Figure 1 below). We show that the empirical patterns of registration fit best the model in which r is constant and s varies over the life cycle, but the data are fit exceptionally well by the simplest model in which r and s are both constant
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