Who Are the Liberal Democrats and the Conservative Republicans?

Daniel Lee and I made these graphs showing the income distribution of voters self-classified by ideology (liberal, moderate, or conservative) and party identification (Democrat, Independent, or Republican). We found some surprising patterns:

Each line shows the income distribution for the relevant category of respondents, normalized to the income distribution of all voters. Thus, a flat line would represent a group whose income distribution is identical to that of the voters at large. The height of the line represents the size of the group; thus, for example, there were very few liberal Republicans, especially by 2008.

The most striking patterns to me are:

1. The alignment of income with party identification is close to zero among liberals, moderate among moderates, and huge among conservatives. If you’re conservative, then your income predicts your party identification very well.

2. First focus on Democrats. Liberal Democrats are spread among all income groups, but conservative Democrats are concentrated in the lower brackets.

3. Conservative Republicans–the opposite of liberal Democrats, if you will–are twice as concentrated among the rich than among the poor.

Putting factors 2 and 3 together, we find that ideological partisans (liberal Democrats and conservative Republicans) are not opposites in their income distributions. In particular, richer voters are more prevalent in these groups.

Which might be relevant for the debates over health care, taxes, and other political issues that have a redistributive dimension.

P.S. The 2000 and 2004 data are from the National Annenberg Election Survey; 2008 is from the Pew Research pre-election surveys. We show all three years to indicate the persistence of the general pattern. As a way of showing uncertainty and variation, this is much more effective than displaying standard errors, I think.

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About Andrew Gelman 26 Articles

Affiliation: Columbia University

Andrew Gelman is a professor of statistics and political science and director of the Applied Statistics Center at Columbia University. He has received the Outstanding Statistical Application award from the American Statistical Association, the award for best article published in the American Political Science Review, and the Council of Presidents of Statistical Societies award for outstanding contributions by a person under the age of 40.

His books include Bayesian Data Analysis (with John Carlin, Hal Stern, and Don Rubin), Teaching Statistics: A Bag of Tricks (with Deb Nolan), Data Analysis Using Regression and Multilevel/Hierarchical Models (with Jennifer Hill), and, most recently, Red State, Blue State, Rich State, Poor State: Why Americans Vote the Way They Do (with David Park, Boris Shor, Joe Bafumi, and Jeronimo Cortina).

Andrew has done research on a wide range of topics, including: why it is rational to vote; why campaign polls are so variable when elections are so predictable; why redistricting is good for democracy; reversals of death sentences; police stops in New York City, the statistical challenges of estimating small effects; the probability that your vote will be decisive; seats and votes in Congress; social network structure; arsenic in Bangladesh; radon in your basement; toxicology; medical imaging; and methods in surveys, experimental design, statistical inference, computation, and graphics.

Visit: Andrew Gelman's Website

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