Stephanie Nail - How Much Will Voters Pay for a “Bit” of Information?
Despite technology decreasing the cost of acquiring information, people are now less knowledgeable about some facts – such as the names of their members of Congress (Jacobson 2015). I argue that cheaper information has not increased voters’ knowledge about individual candidates because voters possess an even cheaper and increasingly informative cue: party id. As parties have become more ideologically distinct, voters have been increasingly able to guess how any given representative voted on a salient bill. Therefore, individuals should be less likely to seek out speciﬁc information about what individual legislators do in Congress. This hypothesis is tested using a decision-theoretic experiment. Participants guess how a candidate voted on a particular bill, and may pay to acquire an informative signal before guessing. I ﬁnd that, in treatments mimicking the informational conditions in 1970-2008, individuals’ willingness to pay for more information when they have the party label has decreased by 33%.
I am a Postdoctoral Research Fellow at Stanford University working with Douglas Rivers, Morris Fiorina, and David Brady. I obtained a PhD in Political Science in July 2019 from the University of California, Merced. I received a Bachelor of Science in Psychology (Mathematics) and Managerial Economics with a minor in Statistics from the University of California, Davis in 2014.
I study how people use information to make decisions with methodology ranging from experimental studies and instrumental variables to spatial models and new measures. My current methodological interests include experiments, survey sampling, design, and analysis, Bayesian statistical inference, mathematical statistics, causal inference, and behavioral game theory. Substantively, my current interests include the study of information, party identification, polarization, judgement and decision-making, political behavior, and legislative politics.
At the undergraduate level, I have taught "Introduction to Judgment and Decision Making," an upper-division course that incorporates the foundations of information processing and biases while applying them to real life situations in political science, cognitive science, economics, and management.