Deep Blue, Metropolis, Big Sky, Greater Dixie
There are a lot of old faces leaving Congress, and we can expect many efforts to figure out what the Democratic wave meant. On one level, it may be all about “corruption [and] the Iraq war.” But a recent analysis by Stan Cox suggests some interesting possibilities.
Cox “compiled rankings of the 50 states for a range of characteristics, including wages, taxes, and energy costs from a recent Forbes Magazine’s survey entitled “The Best States for Business,” an environmental policy (“green-capacity”) rating by the Resource Renewal Institute, and government data on median income, income inequality, population size, and the number of Wal-Mart Supercenters relative to population.” He then divided “divergent states” into four categories based on their status: Deep Blue, Metropolis, Big Sky, Greater Dixie. He found that the more Democratic of these (Deep Blue and Metropolis) had median incomes “25% higher than in Big Sky and Greater Dixie.” Big Sky and Greater Dixie states also had far higher “Iraq war deaths per million residents,” lower minimum wages, and worse environmental policies (though they had cleaner environments, largely due to less population density).
I don’t agree with all the ways Cox interprets the data, but his organization of it is interesting. It’s a nice reminder to the MSM that rather than incessant coverage of the “horse race,” it might help to point out the huge disparities “in wages, business and environmental policies, income inequality, population size, racial and ethnic makeup, poverty, and military impact” of different areas. These disparities might explain a lot more about what went on Tuesday than the Limbaugh/Fox, macaca/misogynist, and Kerry “stuck in Iraq” feuds they fixated on.
Photo Credit: Flickr/Poor Yorick (“The 2004 presidential election as represented by population, by Mark Newman, Department of Physics and Center for the Study of Complex Systems, University of Michigan”).
PS: I forgot to mention a certain counterintuitive paper that suggests some legal uses of these results. Anup Malani has suggested that “The value of a law should be judged by the extent to which it raises housing prices and lowers wages. . . . Housing prices go up because more people want to live there. Wages go down because more people want to work there.” This type of data helps correlate things like wages and environmental laws.