NJ 2019 General Election Early/Absentee Vote Report
About This Data
In order to make the 2019 early vote data easier to understand, we’ve broken down the individual vote history by demographics so it’s clear how the electoral demographics have shifted from 2015 and 2017 to 2019. This data comes from TargetSmart analysis of data that has been released by individual state election officials. While it’s important to keep an eye on 2017, the most relevant comparison is to 2015 as it matches the same point in the four year election cycle. For each of the following demographic data points, we’ve broken down the electorate by vote share as well as turnout. More information about these metrics can be found below as well as a few notes about the variables we’ve included.
Race: Where self-reported race is not available, a TargetSmart model is used. The “Uncoded” category indicates that the TargetSmart race model is not confident enough to make a prediction.
Gender: Where self-reported gender is not available, a TargetSmart model is used.
Voter Score: Quintiles of voting frequency in general or primaries going back to 2000 for registrants that have voted in at least one of these elections. Calculated at the county level.
Party Rollup: Party registration is not available in every state. In states where it is not available, all voters will be labeled as ‘Unaffiliated’.
Urbanicity: A TargetSmart-specific measure that describes how densely developed an area is based on population, employees, businesses, traffic counts and other factors. The urbanicity measure is broken down into 6 classifications: Rural 1, Rural 2, Suburban 3, Suburban 4, Urban 5, and Urban 6. For this site, they’ve been summarized further to Rural, Suburban, and Urban.
National Summary: An aggregate of the states specified as available in the map above. Until vote history is available in all 51 states plus DC, it won’t be a complete national summary.
Race with Education: This divides Caucasian voters into those with and without a college degree. Recent research has shown that these groups exhibit quite different voting patterns.
State Senate Districts: In some states, such as Virginia, districts may have changed since the 2015 election. In these cases, we have made our best effort to apply current district boundaries to the 2015 and 2017 data, but it’s important to note that these may be imperfect and are for comparison purposes only.
Please note that in some states, it takes multiple data updates to obtain the full, individual-level vote history. We include states in the analysis on this site once our data represents 90% of the ballots that were cast in the election.
Transparency in Coverage: This link leads to the machine-readable files that are made available in response to the federal Transparency in Coverage Rule and includes negotiated service rates and out-of-network allowed amounts between health plans and healthcare providers. The machine readable files are formatted to allow researchers, regulators, and application developers to more easily access and analyze data.