When Do the Rich Win

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Authors J. Alexander Branham, Stuart Soroka, Christopher Wlezien
Paper Category
Paper Abstract There is growing interest in the influence of economic “haves” and “have-nots” on public policy. In a widely referenced article, Gilens and Page (2014) compare the influence of upper and middle-income citizens and find that the preferences of the former are all that matter for policy. Here, we reconsider this possibility, examining how often the rich win and the kinds of policies they get. We find that the rich and middle almost always agree and, when they disagree, the rich win only slightly more often. Even when the rich do win, resulting policies do not lean point systematically in a conservative direction. Incorporating the preferences of the poor produces similar results; though the poor do not fare as well, their preferences are not completely dominated by those of the rich or middle. Based on our results, it appears that inequalities in policy representation across income groups are limited. The rich still do matter, seemingly more than they should, and this may have substantial consequences for policy, particularly as effects cumulate over time. It also may be that income does not matter very much, and that other divisions in the electorate or other actors are more relevant for policy. A major theoretical justification for representative democracy is that it puts power in the hands of the people. Political scientists have tested whether this actually is true by assessing the degree to which policy reflects citizens’ preferences. Recent work finds that public policy is frequently responsive to the will of the people, but that there is significant variation across policy domains.1 There may be variation in responsiveness to people as well. Indeed, recent work * Previous versions of this paper was presented at the 2016 annual meetings of the Southern Political Science Association, the Midwest Political Science Association, and the American Association for Public Opinion Research. The authors would like to thank Peter Enns, Stephen Jessee, Frederick Solt, James Stimson, the anonymous reviewers and journal editor for helpful comments. Code and data to reproduce these analyses are available on the Harvard Dataverse: http://dx.doi.org/10.7910/DVN/UZSQTV
Date of publication 2017
Code Programming Language R

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