After this, here’s more, again from exit poll crosstabs that Jared pulled off the CNN website:

Difference in McCain vote share, comparing people in each state with family incomes over and under $50,000 (thus, states that are high on this graph are those where richer people were much more Republican than poorer people):

The same graph, but for whites only (following Larry Bartels’s suggestion):

As before, the states are colored as red or blue where McCain or Obama won by more than 10% of the two-party vote, and purple for the states in between.

Lots of interesting patterns here.

In our book, we discussed how the rich-state, poor-state divide was larger among the rich than the poor–or, to put it another way, how rich people in states such as Mississippi are much more Republican than poor people in Mississippi, but rich people in Connecticut do not vote so differently from poor people in Connecticut.

What happened in 2008? From the exit poll data at the CNN website, we get:

On the logarithmic scale:

The x-positions of these lines are in different places because Mississippi and Connecticut got small samples and CNN didn’t post the percentages for some of the extreme categories which had small n’s.

Here are three states ranging from Texas (strongly Republican) to Florida (battleground) to California (strongly Democratic). Texas actually has a higher per-capita income than Florida, but here are the exit poll data in any case:

The more systematic thing to do is to look at all 50 states. In each, I took McCain’s share of the two-party vote for each income category where we had data, then regressed it on the category numbers (which we originally numbered 1 through 8 and then standardized to have mean 0 and standard deviation 0.5). I then plotted these regression coefficients on a graph along with state income:

The y-scale of the graph roughly represents McCain’s vote share among the rich minus his share among the poor, within the state. We see the familiar pattern from our book, that the association of rich with Republican holds everywhere but is strongest in poor states. The states are colored as red or blue where McCain or Obama won by more than 10% of the two-party vote, and purple for the states in between.

But there’s a potential problem here, as illustrated by the Mississippi-Connecticut pattern above. The data from Mississippi are more at the low end of income, and the data from Connecticut are more at the high end. We already know that the relation between income and Republican voting flattens out at higher incomes, and so maybe Connecticut’s flat slope arises just because we’re taking its numbers from the flatter part of the curve.

To correct for this, for each state we take the regression plotted above, then we fit the same regression to the same range of incomes from the national exit poll, then we add back in the full regression of the national poll using all eight income categories. The result is a quick estimate of what the entire difference between rich and poor would be in the state, if we were to have sufficient data from all eight income categories within each state.

And here’s the result:

A few of the southern states on the left part of the graph have high rich-poor voting differences (even after controlling for the range of incomes where the comparisons were being made), but the overall pattern of rich and poor states isn’t so strong.

Further thoughts:

1. Larry Bartels comments that if you only look at whites, the rich voter, poor voter pattern is similar in rich and in poor states. So one of our main findings from the Red State, Blue State book from the 2000 and 2004 elections did not persist in 2008.

2. Boy do I want the raw exit poll data so I don’t have to screw around with these artificial missing data problems.

3. I also want some pre-election poll data. The exit polls were so screwed up this year, I don’t fully trust anything based on exit poll data alone.

Shivaji Sondhi writes:

I had a question for you about the youth vote. What are its ethnic and red/blue composition? The reason I ask is that I was trying to integrate the apparently growing Democratic dominance in this segment with various other beliefs I have seen expressed, e.g

a) that red states have larger fertility (affordable family formation or whatever)

b) that families have an impact on the political beliefs of children (more than educators, as educators insist – at least at the college level, I haven’t really seen a discussion of school teachers) which would then provide a mechanism for (a) to affect voting share to the right of the spectrum

c) that the minorities form a growing share of the young which would tilt the playing field to the left.

My reply:

1. I don’t yet have raw survey data. The exit polls on the web do break down the vote by age and race. Among blacks, Obama won about the same among all age groups. Among Hispanics, Obama did 8% better among the young than the old, and among whites, Obama did 14% better among the young than the old.

But . . . if you believe the exit polls (which I don’t, completely), there was an interaction between age and race: many more of the young voters were ethnic minorities. Among blacks and Hispanics, there were three times as many under-30’s as over-65’s. (By comparison, among whites, there were more old voters than young voters.)

So the age effect partly arose from lots of young ethnic minorities coming out to vote.

2. People do tend to vote like their parents–children of Republicans are, on average, more likely to vote Republican–but cohort effects go on top of this. The recent economy and George W. Bush’s approval ratings aren’t likely to make the Republican Party popular with young people–especially those who are ethnic minorities. Any differences in birth rates between states are small compared to these big political swings, which are not just about Obama; see this graph from 2006:

Ben Lauderdale writes:

I [Ben] had this map [see below] on my door for the last week. Based on exactly the same calculation using constant 95% black support and census-proportional representation. The white counties are the ones whose census names didn’t match properly with the names used in the library(maps) package in R, I was too lazy to fix them.

Cool. I’d only suggest using light gray rather than heavy black lines between counties; the map as it is overemphasizes the county borders, I think. But I respect his laziness; there’s always time later to fix the details.

Ben continues:

[Below are] the state-by-state county share plots for the lower 49, Obama vote share as a function of black population share. V.O. Key’s observation that whites who live near blacks in southern states are less positively inclined towards them is *still* visible in several states.

The circle areas are proportional to county voter turnout. (The biggest circle is L.A. county in California, and so forth.)

Ben also had this comment about his map:

It reminded me of something Bob Putnam would say every time someone presented an empirical talk in our Center for the Study of Democratic Politics series during the year he was a fellow here at Princeton: “You should include miles to the Canadian border as a variable in your regression, it is the most important proxy for political culture in America!” At least in the eastern half of the country, he has a point.

Except for New Hampshire and Vermont, I think.

P.S. Further discussion here of graphing possibilities.

Jeremy Teigen (link from John Sides) says the answer is pretty much No. Here’s Teigen:

I [Teigen] examined contested House races from 2000-2006 to see if candidates’ previous military service helped them garner a higher share of the vote. . . . the effect of being a Democratic veteran or a Republican veteran on vote share, controlling for presidential vote share in the district, gender, incumbency, campaign spending, and other relevant factors. . . .

In general, veteran status has small effects that are not statistically distinguishable from 0. Democratic vets did better than their nonveteran peers in 2002, but did no better in 2006. That election was the year that Joe Sestak, Tammy Duckworth, and others constituted the “Fighting Dems,” a year when you would expect Democratic vets to do well, but instead Republican veterans were helped by a martial past. . . . In 2006 Democratic veterans actually did a little bit worse than Democrats without a service record. This result may have occurred because Democrats were overzealous in their attempts to attract veterans as candidates, leading them to select veterans over higher quality challengers (14% of Democratic challengers were vets in 2002, compared to 28% in 2006). Republican vets running that year performed a little better than nonveteran Republican candidates, as they had been doing in the previous three elections, but the advantage just slipped above statistical significance. Overall, the effect of veteran status is very small.

It would be interesting to see data from other years and comparisons to other occupations (community organizers? small-town mayors? POW’s?).

Teigen continues:

Nevertheless, this does not seem to deter veterans from running for office and promoting their service during their campaign. Despite the allegedly “tinny ring” of military values, some candidates make their military service the key element of their campaign narrative (e.g., Craig Williams). To me, this behavior and the continued emergence of veteran candidacies says that our candidate selection mechanisms still value military service even if the general election yield is inconstant and small.

I actually disagree with this bit, or at least I’m not yet convinced by the evidence. Every candidate has some strength. If you’re a veteran, you can make a big deal about that. If you’re a trial lawyer and won cases for sick kids, you can advertise that. If you’ve been a community organizer, ditto. The lack of any special advantage for veterans does not at all imply that it’s silly for veterans to promote their service during their campaigns.

P.S.

Some technical comments: I don’t think it’s a good idea to control for campaign spending. That’s an intermediate outcome (see, for example, chapter 9).

On the plus side, I agree that it makes sense to analyze House races (larger N than just analyzing presidential contests), and I’m glad to see vote share rather than win/loss used as an outcome.

I said I wouldn’t do more posts on the election, but . . . Eric Rauchway merged our provisional county data with Census numbers on %black and made some graphs, which I played with a little to get the following:

Percent black acts as a floor on Obama’s vote share; beyond that, it predicts his vote better in some regions than others.

But really there are two things going on. First, Obama’s getting nearly all the black vote; second, depending on the region, whites are voting differently in places with more or fewer African Americans.

Then I had a thought. Obama got 96% of the black vote. If he got 96% in every county–which can’t be far from the truth–then we can use simple algebra to figure out his share of the non-black vote in every county. If B is the proportion black in the county and X is the (unknown) Obama vote share among non-blacks, then, for each county,

obama.vote = 0.96*B + X*(1-B)

And so

X = (obama.vote – .96*B) / (1 – B)

This is only an approximation–for one thing, it assumes turnout rates are the same among blacks and others–but it can’t be too far off, I think. And it leads to the following graph:

(Lowess lines are shown in blue.) None of this is a huge surprise: outside the south, places with more African Americans tend to be liberal urban areas where people of other ethnicities also vote for Democrats; in the south, many African Americans live in counties where the whites are very conservative.

Notes:
1. These graphs are non-blacks, not whites. Some of the variation has to be explainable by the presence of other minority groups.
2. For a few of the southern counties, our estimates of X are negative; that just means that Obama got less than 96% of the black vote there, or there was differential turnout, or some combination of these.

P.S. More graphs here (from Ben Lauderdale).

John Kastellec made this graph of seats and votes in 2006 and 2008. For each year, the dot is what actually happened and the line is our estimated seats-votes curve based on modeling from the previous election year.

The Democrats did well in both years, but they didn’t get as many seats as we would’ve expected, given their vote share. As I’ve already discussed, the Democrats’ 56% share of the average district vote was pretty impressive, a 5.7 percentage point gain since 2004:

But the Democrats performed less well than expected in converting votes to seats. This explains to me why Charlie Cook et al. felt that the Democrats’ performance was disappointing. At the level of voters, however (and of public opinion), the party did fine in congressional voting.

Michael Herron sent me this article-in-progress by Jonathan Chapman, Jeffrey Lewis, and himself on residual votes in the 2008 Minnesota Senate race. They conclude:

In the Minnesota Senate case there is no doubt that the number of residual votes dwarfs the margin that separates Coleman from Franken. We show using a combination of precinct voting returns from the 2006 and 2008 General Elections that patterns in Senate race residual votes are consistent with, one, the presence of a large number of Democratic-leaning voters, in particular African-American voters, who appear to have deliberately skipped voting in the Coleman-Franken Senate contest and, two, the presence of a smaller number of Democratic-leaning voters who almost certainly intended to vote validly in the Senate race but for some reason did not do so. . . . At present, though, the data available suggest that the recount will uncover many of the former and that, of the latter, a majority will likely prove to be supportive of Franken.

In a discussion of the historic nature of Barack Obama’s election, Christopher Hitchens writes, “there were not a few elected black American representatives 40 years ago.”

This claim surprised me, so I looked it up. In 1968, there were 5 African Americans in the House of Representatives and 1 in the Senate. This sounds like only “a few” to me! Was Hitchens just confused here, or am I missing something?

P.S. Somebody pointed out that there were black state and local officeholders as well. I guess it all turns on what is meant by “not a few.” Blacks were certainly a very low percentage of all U.S. elected officials back then.

People sometimes ask why I don’t include Alaska and Hawaii on my maps. I could, I guess; it would just make things look a little messier. And since Alaska and Hawaii aren’t swing states (and they’re not even included in many national opinion polls), I don’t bother with them. I don’t include D.C. either. I do include AK and HI in scatterplots, though (when I have data for them).