Sunshine Hillygus has been awarded two large grants from the National Science Foundation for her work in political science. Hillygus serves as both the director of the Duke Initiative on Survey Methodology (DISM) at the Social Science Research Institute (SSRI) and as an SSRI faculty affiliate. She's published widely on the topics of American political behavior, campaigns and elections, survey methods, public opinion, and information technology and politics.
For details of her two new grants, see below. To learn more about survey methods and design, see DISM's fall schedule of workshops.
Voter turnout among young people is dismally low in the United States, often 20-30 percentage points lower than that of older Americans. This project evaluates potential education and electoral policies to increase youth turnout.
The researchers contend that increasing youth turnout requires not only lowering registration barriers for young citizens but also helping them to develop the skills, especially the so-called noncognitive skills, needed to follow through and overcome the obstacles and distractions that get in the way of voting.
Building on an existing partnership with the Wake County Public School System, this project brings together for the first time:
These combined datasets will allow for a more comprehensive and rigorous evaluation of existing civic education and electoral policies to better inform the development of new reforms designed to promote voter turnout.
Modern surveys have seen steep declines in response rates. These declines threaten the validity of secondary analyses based on those incomplete data. This research project will develop methods and practical tools for leveraging the information from other data sources, such as administrative records and databases gathered by private-sector data aggregators, to adjust for nonresponse in surveys.
The methodological developments to be addressed in this project will focus on the following question: How can survey organizations take advantage of information about the marginal distributions of survey variables that are available in auxiliary data sources when adjusting for nonresponse?
The project will train two Ph.D. students from underrepresented groups, one in statistical science and one in political science and engage two undergraduate students in a data science summer research experience.
An open-source package will be developed and made widely available via the Comprehensive R Archive Network. This package will enable agencies and other users to take advantage of the methodological advances.
The project will fuse features of Bayesian modeling and classical survey-weighted estimation to ensure imputations account for complex survey designs. The methodology will be illustrated on an application examining voter turnout among subgroups of the population in the Current Population Survey (CPS). The application will use population-based auxiliary data from government election statistics available in the United States Elections Project and voter files available from Catalist, a leading national vendor of voter registration data.
The information in the auxiliary margins will be used to adjust the CPS data for nonresponse with a more reasonable set of assumptions than previous analyses of voter turnout based on the CPS. The CPS voter turnout application will inform scholars and policy makers about inequalities in electoral participation and provides insights about possible policy alternatives for improving voter turnout.