Oregon, unemployment, and college

Once I get on a run, I tend to run with it.
Especially if it is something that I have data on, and can just cut and paste to different documents.
In the nation, there isn't much relation between college and unemployment, so lets look at the same data in Oregon.
(BTW, for those of you who don't know, I am an Oregonian. Mostly. Also, Oregon gives a good cross section of demographics.)Overall, there isn't a lot of direction in this diagram, although the four urban counties with most of the educated people and where much of the work goes on, are all grouped together in the middle.
So, again, another inconclusive result.

Oh, and also: 2010 is going to happen soon. It already did in London.
2010 means a number of things, including a CENSUS. However, the census results won't be out for two years, or so.

The same thing, with Oregon:

So, to make up for my terrible downturn in daily updating, and because I got interested,

I decided to look at the last plot I did, but for Oregon and its counties. Luckily, the census has growth figures by county, and the Department of Labor has a handy tool for looking at county level data

So the same graph for Oregon gives us:
There is a little bit more shape to this, but admittedly, not much. And again, although its not very clear, there is the same 5/6th pattern as we had last time: the only area where we don't see any points is high-growth, low-unemployment. Hood River and Benton Counties come close, though!
Another problem with this, as I have said for my Oregon diagrams before, is that bit all Oregon counties are equal in population. Especially noticeable in this, with Harney County, population 8,000, just sitting down there in the corner. I am tempted to do this graph with, for example, only the 10 or 15 most populous counties, and see what results I get from that.

Unemployment versus growth: once again, the easy explanation isn't the best one.

One piece of obvious conventional wisdom that I had been carrying around was that unemployment was higher in areas with high growth: that areas with high unemployment were areas with large influxes of population, and they therefore had high frictional unemployment, or had "oversold" themselves to potential workers. It seems like a good argument, and there are certainly a few data points to support it.
But you, my astute readers, know about "seems like a good argument" and "a few data points to support it". The actual scatter plot of the data is, as could be expected, scattered.
And, as is also often the case, there is a "three quarters" effect in here, although not a distinct one. Actually, It would be more a "five-sextet" effect. If we divide unemployment into high, medium and low, and growth into high and low...all of the five sextiles are occupied, except for "high-growth, low-unemployment". Utah, Texas and Colorado have high growth and medium unemployment, but there is nothing to the left of them.
Of course, in a normal economy, this graph might look different. So lets hope that we have a normal economy so I can find out! Also, I will have a job, and might not have time to scatterplot.
Incidentally, I found out this data several weeks ago, and just didn't bother to make a graph and post it. I actually have lots of stuff like that that I am sitting on!

Content unrelated:

Now I am breaking down the sanctity of my scatterplot blog, just so I can post this image, and link from it for elsewhere.

But really, isn't it relevant?
Because aren't the data we mine out of the earth, the earth being random census documents, a secret to everyone? Like the money that rebellion-minded spear throwing dogs give to us?

Oregon is not Ohio. Neither is Washington.

After finding out that Ohio does indeed have a long pattern of following the nation's political trends, I decided to look at the same data for Oregon.
One thing to remember is that the electorate has been realigned many times since 1860 (which is as far back as I am going with these). Prohibition? Steel tarriffs? Vietnam? Female suffrage? The political and social and demographic issues that divide people have changed quite a bit over the years.
Which only makes it more important when a state does match up so closely with the nation. Whatever the political or social issue that divided the nation...Ohio somehow managed to feel pretty much the same way about it, since 1860.
I can't quite pin down a pattern to Oregon, though. Since 1980, it has been consistently more Democratic than the nation. Before that, it seemed to jump around, in a way that my knowledge of Oregon's demographics don't quite explain.
To wit:
Although, even with the fact that Oregon lines up less than Ohio does, there are still no major surprises here. While there are clusters of dots in the upper left and lower right quadrants, which represent not voting with the country, those dots are also pretty close to the origin, meaning that even though Oregon swung the other way (giggles), it didn't do so by a lot.
Along with that, I wanted to look at two states that would correlate with each other: Oregon and Washington. As expected,Oregon and Washington, going back to 1892, correlate pretty well. The major differences I think come from times when Washington was becoming industrialized, unionized and ethnicized before Oregon was, which gave it different demographics.

Way to go Ohio...

One of the often quoted maxims of US politics is that the candidate that wins Ohio wins the nation. Of course, using modern technology, we can look at that a bit closer.
As can be seen, those numbers pretty much add up. They add up not just with the true/false test, but with the amount of the vote, as well. The exceptions are in a few landslide years, when Ohio doesn't always swing quite as wildly as the nation. But on the whole, it is true.
(This also explains the one exception to the rule: 1960, when Nixon won Ohio, but Kennedy won the nation. Nixon's victory in Ohio was small, as was Kennedy's victory overall).
According to the formula that shall not be named, there is quite a bit of correlation, and I bet that Ohio would indeed have a higher correlation than another other state, besides maybe Missouri.

I didn't need to snort all that GABA, anyway

I was e-Mailing with Dr. Stephen Wu, one of the authors of the "happiest states" reports, and I am happy to report that most of the spin put on the reports is due to the media, not to his research, which is much more modest in its claims.