We’re used to thinking of politics as the messiest of human activities: a subject fit for Greek tragedy, not computer modeling. Political scientists, though, are trying to change that. Jonathan Bendor, Daniel Diermeier, David Siegel, and Michael Ting have found a way to model elections, parties, and voter turnout using computer programs -- their new book, A Behavioral Theory of Elections, even comes with a website where you can download them.
Economists have been using computer models to make sense of markets for decades -- models are useful for making predictions, but also for evaluating and improving theories. Political scientists, though, have found their subject harder to model. The problem is that a model is based, necessarily, on rules. Voters and politicians, meanwhile, are doing something so complicated that figuring out what rules they might be following has been extraordinarily hard. When a voter chooses one candidate over another, she could be doing it for any number of reasons: economic self-interest, for example, but also party loyalty. How can you possibly boil those kinds of decisions down to a set of rules?
Bendor, Diermeier, et. al. make a start by drawing on the field of behavioral economics. Behavioral economists focus on the shortcuts we use to make sense of situations that are too hard to figure out step-by-step. Often, they argue, we make those kinds of decisions in a “boundedly rational” way -- we constrain the complexity of a decision by choosing an arbitrary waypoint and then orienting ourselves towards it. (Think of the way you might look at a huge dinner menu and then decide that, since you’re by the seashore, you’ll choose only from the seafood entrées.) The same process, they argue, is at work in politics. With each election, voters and politicians try out new ways of constraining their own decisions. They concentrate on only a few aspects of politics at a time, selecting new waypoints and abandoning old ones -- “adapting,” the authors write, “by aspiration-based trial and error.” Computer models based on this idea produce realist-looking simulated elections.
You can’t use insights like these to predict the outcomes of an election, of course. (Political science has a few more years of work ahead of it on that front.) But work like this highlights an interesting element of political life: the way that it revolves around the proposal and rejection of aspirations. Politicians and voters are in a constant conversation about which aspects of political life need to be emphasized, and which need to be set aside. From year to year, we change our minds about what matters. That’s why we keep ordering different dishes from the same menu.
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