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Wednesday, August 12, 2009
Today I combined some Census data with 2008 election results (thanks Cosma). Though Barack Obama won the vote last fall, he lost the Non-Hispanic white vote. It stands to reason then that the whiter and less Hispanic a county is, the more likely it would be to tilt McCain. I was curious as to geographic variation within this general rule-of-thumb. So I plotted the % who voted for Obama in a county vs. the % who were Non-Hispanic whites (according to the 2000 Census*). I then generated a line of best fit via loess, and used the deviations from the trend to generate a map shaded proportionately. In other words, the bluer a county is the more it voted for Obama above expectation based on the overall relationship of the % white Non-Hispanic within a county and vote for Obama (the converse for red naturally). Again, click the map for the larger image.
I also decided to constrain the data set to those counties which were at minimum 80% Non-Hispanic white. Mostly because the "Black Belt" counties are showing up on the above map.
Finally, a shaded map of the results.
1) Don't mess with Texas Obama. Despite Obama winning the Hispanic counties in the South, those counties are always underperforming relative to other majority-minority districts. Since some of those counties are 90% Hispanic it probably isn't just Non-Hispanic white swing in the other direction.
2) Though Obama lost much of the rural North and East, he overperformed when you use the whole nation as a reference point, in particular rural areas in the West and South.
3) Pennsylvania kind of does look like Pittsburgh + Philadelphia, with Alabama in the middle.
4) Obama did well in Greater New England. Less well in the Butternut Region of the southern Midwest settled from the South.
Here are a list of the 200 counties furthest from the trendlines. The first 100 are the most pro-Obama above expectation when the predictor is Non-Hispanic white %. The last 100 the most pro-McCain.
Deviation From Trend Line | % For Obama | County & State | 0.4 | 0.78 | Marin, California | 0.39 | 0.77 | Multnomah, Imbler | 0.38 | 0.78 | Santa Cruz, California | 0.38 | 0.77 | San Miguel, Colorado | 0.36 | 0.74 | Sonoma, California | 0.36 | 0.75 | Dukes, Massachusetts | 0.35 | 0.75 | Berkshire, Massachusetts | 0.35 | 0.74 | Pitkin, Colorado | 0.34 | 0.73 | Dane, Wisconsin | 0.34 | 0.72 | Orange, North Carolina | 0.34 | 0.72 | Boulder, Colorado | 0.33 | 0.73 | Windham, Vermont | 0.33 | 0.73 | Franklin, Massachusetts | 0.33 | 0.72 | Hampshire, Massachusetts | 0.32 | 0.7 | Washtenaw, Michigan | 0.32 | 0.7 | Mendocino, California | 0.32 | 0.7 | King, Washington | 0.31 | 0.71 | Lamoille, Vermont | 0.31 | 0.84 | San Francisco, California | 0.31 | 0.7 | New Castle, Delaware | 0.31 | 0.7 | Johnson, Iowa | 0.31 | 0.69 | Tompkins, New York | 0.3 | 0.7 | Washington, Vermont | 0.3 | 0.7 | San Juan, Washington | 0.3 | 0.69 | Imbler, Wisconsin | 0.3 | 0.77 | Suffolk, Massachusetts | 0.3 | 0.83 | Philadelphia, Pennsylvania | 0.3 | 0.72 | Arlington, Virginia | 0.3 | 0.69 | Windsor, Vermont | 0.29 | 0.69 | Addison, Vermont | 0.29 | 0.69 | Silver Bow, Montana | 0.29 | 0.68 | Nantucket, Massachusetts | 0.29 | 0.72 | Montgomery, Maryland | 0.29 | 0.69 | Cuyahoga, Ohio | 0.28 | 0.68 | Chittenden, Vermont | 0.28 | 0.66 | Ingham, Michigan | 0.28 | 0.66 | Ramsey, Minnesota | 0.28 | 0.75 | Denver, Colorado | 0.28 | 0.67 | Iowa, Wisconsin | 0.28 | 0.67 | Camden, New Jersey | 0.27 | 0.67 | Deer Lodge, Montana | 0.27 | 0.66 | Summit, Colorado | 0.27 | 0.66 | Blaine, Idaho | 0.27 | 0.65 | Lucas, Ohio | 0.27 | 0.65 | Genesee, Michigan | 0.27 | 0.65 | Hartford, Connecticut | 0.27 | 0.66 | Monroe, Indiana | 0.27 | 0.66 | Jefferson, Washington | 0.27 | 0.66 | Bennington, Vermont | 0.26 | 0.66 | Athens, Ohio | 0.26 | 0.76 | Durham, North Carolina | 0.26 | 0.66 | Douglas, Wisconsin | 0.26 | 0.68 | Milwaukee, Wisconsin | 0.26 | 0.67 | Mercer, New Jersey | 0.26 | 0.65 | Benton, Oregon | 0.26 | 0.76 | Cook, Illinois | 0.26 | 0.64 | Hennepin, Minnesota | 0.26 | 0.64 | Muskegon, Michigan | 0.26 | 0.65 | Napa, California | 0.26 | 0.64 | Middlesex, Massachusetts | 0.26 | 0.64 | Douglas, Kansas | 0.26 | 0.77 | Santa Fe, New Mexico | 0.26 | 0.74 | Wayne, Michigan | 0.26 | 0.65 | Orange, Vermont | 0.26 | 0.74 | San Mateo, California | 0.25 | 0.65 | St. Louis, Minnesota | 0.25 | 0.64 | Hood River, Oregon | 0.25 | 0.63 | Humboldt, California | 0.25 | 0.63 | Albany, New York | 0.25 | 0.64 | Bayfield, Wisconsin | 0.25 | 0.64 | Marion, Indiana | 0.25 | 0.64 | Rock, Wisconsin | 0.25 | 0.67 | Lake, Indiana | 0.25 | 0.79 | Alameda, California | 0.24 | 0.64 | Cumberland, Maine | 0.24 | 0.68 | Contra Costa, California | 0.24 | 0.83 | Clayton, Georgia | 0.24 | 0.62 | Mahoning, Ohio | 0.24 | 0.62 | Rock Island, Illinois | 0.24 | 0.62 | Hampden, Massachusetts | 0.24 | 0.63 | Lane, Oregon | 0.24 | 0.63 | Trempealeau, Wisconsin | 0.24 | 0.63 | Carlton, Minnesota | 0.24 | 0.63 | Cheshire, New Hampshire | 0.24 | 0.63 | Grand Isle, Vermont | 0.23 | 0.63 | Crawford, Wisconsin | 0.23 | 0.63 | Orleans, Vermont | 0.23 | 0.63 | Gunnison, Colorado | 0.23 | 0.63 | Lackawanna, Pennsylvania | 0.23 | 0.63 | Grafton, New Hampshire | 0.23 | 0.63 | Portage, Wisconsin | 0.23 | 0.63 | Routt, Colorado | 0.23 | 0.67 | Broward, Florida | 0.23 | 0.65 | Clarke, Georgia | 0.23 | 0.62 | Palm Beach, Florida | 0.23 | 0.61 | New Haven, Connecticut | 0.23 | 0.61 | Eagle, Colorado | 0.23 | 0.62 | Howard, Iowa | 0.23 | 0.62 | Jackson, Iowa | 0.23 | 0.62 | Green, Wisconsin |
| -0.22 | 0.26 | Ector, Texas | -0.22 | 0.18 | Kiowa, Kansas | -0.22 | 0.18 | Sioux, Iowa | -0.22 | 0.18 | Piute, Utah | -0.22 | 0.18 | Cleburne, Alabama | -0.22 | 0.18 | Brantley, Georgia | -0.22 | 0.18 | Campbell, Wyoming | -0.22 | 0.24 | Upton, Texas | -0.22 | 0.27 | Seward, Kansas | -0.22 | 0.16 | Wichita, Kansas | -0.22 | 0.25 | Ward, Texas | -0.22 | 0.17 | Donley, Texas | -0.22 | 0.16 | Morton, Kansas | -0.22 | 0.17 | Alfalfa, Oklahoma | -0.22 | 0.17 | Holmes, Florida | -0.22 | 0.17 | Rock, Nebraska | -0.22 | 0.17 | Leslie, Kentucky | -0.22 | 0.24 | Winkler, Texas | -0.22 | 0.17 | Box Elder, Utah | -0.22 | 0.17 | Hooker, Nebraska | -0.22 | 0.16 | Jack, Texas | -0.22 | 0.17 | Crook, Wyoming | -0.22 | 0.17 | Morgan, Utah | -0.23 | 0.17 | Bear Lake, Idaho | -0.23 | 0.17 | Cullman, Alabama | -0.23 | 0.17 | Archer, Texas | -0.23 | 0.17 | Caribou, Idaho | -0.23 | 0.17 | Sevier, Utah | -0.23 | 0.16 | Kingfisher, Oklahoma | -0.23 | 0.15 | Hutchinson, Texas | -0.23 | 0.37 | Pecos, Texas | -0.23 | 0.16 | Jefferson, Idaho | -0.23 | 0.16 | George, Mississippi | -0.23 | 0.16 | Duchesne, Utah | -0.23 | 0.16 | Sterling, Texas | -0.23 | 0.16 | Millard, Utah | -0.23 | 0.16 | Carter, Montana | -0.23 | 0.16 | Roger Mills, Oklahoma | -0.23 | 0.16 | Dewey, Oklahoma | -0.23 | 0.21 | Garza, Texas | -0.24 | 0.16 | Banks, Georgia | -0.24 | 0.16 | Sioux, Nebraska | -0.24 | 0.16 | Dawson, Georgia | -0.24 | 0.16 | Logan, Kansas | -0.24 | 0.16 | Cameron, Louisiana | -0.24 | 0.16 | Haakon, South Dakota | -0.24 | 0.17 | Clark, Idaho | -0.24 | 0.14 | Gray, Texas | -0.24 | 0.14 | Hemphill, Texas | -0.24 | 0.14 | Wheeler, Texas | -0.24 | 0.15 | Garfield, Montana | -0.24 | 0.15 | Loving, Texas | -0.24 | 0.15 | Glascock, Georgia | -0.24 | 0.15 | Rich, Utah | -0.24 | 0.15 | McPherson, Nebraska | -0.25 | 0.27 | Hale, Texas | -0.25 | 0.15 | Blount, Alabama | -0.25 | 0.15 | Hayes, Nebraska | -0.25 | 0.14 | Uintah, Utah | -0.25 | 0.15 | Scott, Kansas | -0.25 | 0.15 | Arthur, Nebraska | -0.25 | 0.15 | Ellis, Oklahoma | -0.25 | 0.15 | Major, Oklahoma | -0.25 | 0.14 | Sherman, Texas | -0.25 | 0.15 | Banner, Nebraska | -0.25 | 0.15 | Texas, Oklahoma | -0.25 | 0.13 | Hartley, Texas | -0.25 | 0.13 | Stevens, Kansas | -0.25 | 0.22 | Crane, Texas | -0.25 | 0.14 | Blaine, Nebraska | -0.25 | 0.14 | Jackson, Kentucky | -0.25 | 0.14 | Carson, Texas | -0.25 | 0.28 | Dawson, Texas | -0.25 | 0.14 | Shackelford, Texas | -0.26 | 0.14 | Harper, Oklahoma | -0.26 | 0.12 | Lipscomb, Texas | -0.26 | 0.12 | Cimarron, Oklahoma | -0.26 | 0.24 | Sutton, Texas | -0.26 | 0.16 | Gaines, Texas | -0.26 | 0.13 | Thomas, Nebraska | -0.26 | 0.18 | Martin, Texas | -0.27 | 0.13 | Armstrong, Texas | -0.27 | 0.13 | Livingston, Louisiana | -0.27 | 0.11 | Motley, Texas | -0.27 | 0.11 | Oldham, Texas | -0.27 | 0.21 | Moore, Texas | -0.27 | 0.11 | Borden, Texas | -0.28 | 0.12 | Wallace, Kansas | -0.28 | 0.17 | Andrews, Texas | -0.28 | 0.12 | Franklin, Idaho | -0.28 | 0.12 | Madison, Idaho | -0.28 | 0.11 | Beaver, Oklahoma | -0.28 | 0.11 | Grant, Nebraska | -0.29 | 0.11 | Hansford, Texas | -0.29 | 0.26 | Deaf Smith, Texas | -0.3 | 0.19 | Parmer, Texas | -0.3 | 0.09 | Glasscock, Texas | -0.31 | 0.2 | Reagan, Texas | -0.32 | 0.08 | Roberts, Texas | -0.32 | 0.08 | Ochiltree, Texas | -0.34 | 0.05 | King, Texas |
* This is 8 years out of date, but by far the most complete and precise data set until the 2010 Census.Labels: Election 2008
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