Quarterly Journal of Political Science > Vol 2 > Issue 4

Rich State, Poor State, Red State, Blue State: What's the Matter with Connecticut?

Andrew Gelman, Department of Statistics and Department of Political Science, Columbia University, USA, gelman@stat.columbia.edu Boris Shor, Harris School of Public Policy Studies, University of Chicago, USA, Joseph Bafumi, Department of Government, Dartmouth College, USA, David Park, Department of Political Science, George Washington University, USA,
Suggested Citation
Andrew Gelman, Boris Shor, Joseph Bafumi and David Park (2008), "Rich State, Poor State, Red State, Blue State: What's the Matter with Connecticut?", Quarterly Journal of Political Science: Vol. 2: No. 4, pp 345-367. http://dx.doi.org/10.1561/100.00006026

Published: 31 Jan 2008
© 2007 A. Gelman, B. Shor, J. Bafumi and D. Park
Public opinion,  Voting behavior,  Presidential politics
Availability heuristicEcological fallacyHierarchical modelIncome and votingMultilevel modelPresidential electionsPublic opinionSecret weaponVarying-slope model

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In this article:
Democrats and Republicans, Rich, and Poor: Two Perspectives
Studying the Relation Between Income and Vote Preferences
Modeling State-Level Differences in Individual-Level Patterns


For decades, the Democrats have been viewed as the party of the poor, with the Republicans representing the rich. Recent presidential elections, however, have shown a reverse pattern, with Democrats performing well in the richer blue states in the northeast and coasts, and Republicans dominating in the red states in the middle of the country and the south. Through multilevel modeling of individuallevel survey data and county- and state-level demographic and electoral data, we reconcile these patterns.

Furthermore, we find that income matters more in red America than in blue America. In poor states, rich people are much more likely than poor people to vote for the Republican presidential candidate, but in rich states (such as Connecticut), income has a very low correlation with vote preference.

Key methods used in this research are: (1) plots of repeated cross-sectional analyses, (2) varying-intercept, varying-slope multilevel models, and (3) a graph that simultaneously shows within-group and between-group patterns in a multilevel model. These statistical tools help us understand patterns of variation within and between states in a way that would not be possible from classical regressions or by looking at tables of coefficient estimates.