The Effect of Registration Laws on Voter Turnout
After the drastic relaxation of voter registration requirements in the 1960s, do present state laws keep people away from the polls? More specifically, which provisions have how much effect on what kinds of people? We have answered these questions with data from the Current Population Survey conducted by the Census Bureau in November 1972. State registration laws reduced turnout in the 1972 presidential election by about nine percentage points. The impact of the laws was heaviest in the South and on less educated people of both races. Early deadlines for registration and limited registration office hours were the biggest impediments to turnout. Contrary to expectations, changing these requirements would not substantially alter the character of the electorate. The voting population would be faintly less affluent and educated; the biggest difference would be a matter of one or two percentage points. In strictly political terms, the change would be even fainter–a gain for the Democrats of less than half a percent.
Improving Ecological Inference by Predicting Individual Ethnicity from Voter Registration Records
In both political behavior research and voting rights litigation, turnout and vote choice for different racial groups are often inferred using aggregate election results and racial composition. Over the past several decades, many statistical methods have been proposed to address this ecological inference problem. We propose an alternative method to reduce aggregation bias by predicting individual-level ethnicity from voter registration records. Building on the existing methodological literature, we use Bayes's rule to combine the Census Bureau's Surname List with various information from geocoded voter registration records. We evaluate the performance of the proposed methodology using approximately nine million voter registration records from Florida, where self-reported ethnicity is available. We find that it is possible to reduce the false positive rate among Black and Latino voters to 6% and 3%, respectively, while maintaining the true positive rate above 80%. Moreover, we use our predictions to estimate turnout by race and find that our estimates yields substantially less amounts of bias and root mean squared error than standard ecological inference estimates. We provide open-source software to implement the proposed methodology.
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