Our goals are to accurately identify the various determinants of waiting times Election Day and to identify if, and to what extent, different types of voting technology contribute to overall wait times. We will also evaluate the public contracts between elections machine manufacturers and state elections departments to determine a scale of cost-effectiveness (defined as “cost per vote”) for various voting machine technologies.

Methods

On February 5, 2008, our data gatherers will record 1) voter arrival rate, 2) the exact time every 5th voter checks in, enters and leaves the voting booth, and 3) the frequency and point of origin of lines. Our analysis will focus on select precincts in Alameda, Napa, and San Mateo counties (each county representing a different technology).¹ We will use a regression model to examine relationships between characteristics of interest and wait times. We will also update elections queuing models with more reliable baseline data to predict wait times under simulated parameters. Finally, we will generate cost-effectiveness estimates of variable elections components, particularly voting technology.

Results

Our results will help policy-makers maximize voter convenience by selecting the optimal voting systems and procedures for their counties.