Randomization Inference with Natural Experiments: An Analysis of Ballot Effects in the 2003 California Recall Election

Abstract

Since the 2000 U.S. Presidential election, social scientists have rediscovered a long tradition of research that investigates the effects of ballot format on voting. Using a new dataset collected by the New York Times, we investigate the causal effect of being listed on the first ballot page in the 2003 California gubernatorial recall election. California law mandates a complex randomization procedure of ballot order that approximates a classical randomized experiment in a real world setting. The recall election also poses particular statistical challenges with an unprecedented 135 candidates running for the office. We apply (nonparametric) randomization inference based on Fisher's exact test, which incorporates the complex randomization procedure and yields accurate confidence intervals. Conventional asymptotic model-based inferences are found to be highly sensitive to assumptions and model specification. Randomization inference suggests that roughly half of the candidates gained more votes when listed on the first page of the ballot.

Keywords: elections, voting, randomization inference, ballots, causal inference

JEL Classification: C14, C93, D72, K30