The unprecedented and largely unanticipated election of Republican candidate Donald Trump as president of the United States in 2016 set off intense debates about how his victory was achieved and which factors mattered most in determining the outcome. …
For this project, we developed original turnout and support estimates by combining a multitude of publicly available data sources including the American Communities Survey (ACS), the November supplement of the Current Population Survey (CPS), the American National Election Study (ANES), the Cooperative Congressional Election Survey (CCES), our own post-election polling, and voter files from several states.
We used this approach to help address what we believe are systematic problems with some of the most widely available and most frequently cited pieces of data about elections—mainly, that some of the most reliable sources of data we have on demographics do not fit well together with the best data we have on turnout rates, leading to results that vary from the actual levels of turnout seen on Election Day. Furthermore, if we combine those data with the best data we have on vote choice, we get election results that do not line up with reality. This is not due to any one source of information being particularly biased; rather, each particular source has points of weakness. To overcome this, we created a new method for combining these data in ways that fit with known outcomes. CONT.
Rob Griffin, Ruy Teixeira & John Halpin, Center for American Progress