Another thing that I have noticed during data-glancing in the past is that income is not highly correlated with poverty rates. One of the problems with this is that there are many different ways to compute income. Using one criterion (income tax returns), the richest zip code in Oregon also has the 2nd-highest poverty rate.
Median household income is usually a pretty good meter. (In fact, maybe I should do a scatterplot of mean household income versus median household income...hmmm) For the same Oregon communities I have been reporting on lately (and which I should probably move on from), I did a plot of median income versus poverty rates, and:
Unfortunately, I can't lay out some mind-bending statement like "the richer the town, the more poor people). But we do see that as with most social science statistics, the results might not be as obvious as at first guess.
There are actually two different trends. Starting from the richer suburbs (although for the three richest, poverty increases as income goes up), until about halfway through the graph, the trend is obvious and sharp. And then, from the middle of the graph to the right edge, there is a large increase in poverty level among communities without much difference in median income. The differences in income between these cities are probably within the standard error, or a methodological error.
I could have included more data points in this diagram, and reached different conclusions. Portland has a number of "micro-suburbs", whereas these are (mostly) the major suburbs and surrounding communities.
So what to make of this odd curve?