Wednesday, December 9, 2015

County Level Unemployment and Determining Cause from Correlation

(A bit of data/mapping ADHD, we're going to go through a lot of maps, very fast!)

Someone pointed out to me that the Kansas side of the KC metro area currently has its lowest unemployment rate in 15 years.  Though this is interesting and positive,  it started me down a path that led to far too many mappings, and a tie into potentially spurious voting correlations.

JOHNSON V WYANDOTTE

If you have spent much time in the Kansas side of the Kansas city metro, you know it's the tale of two counties: white; affluent Johnson County, and a mixed, poor Wyandotte County.  Here's how the two counties compare on selected metrics:


Huge differences between these adjacent counties, but I wondered how that played out in terms of unemployment rate (disclaimer: unemployment rate isn't a great metric for a variety of reasons, but works in this scenario).  Luckily the Bureau of Labor Statistics offers county-level unemployment statistics.  Here's a map of unemployment rates I created for northeast Kansas (2014, annualized):




This is close to what might be expected, Johnson county has the lowest rate in northeast Kansas, Wyandotte county has the highest, and the margin between them (3.1%) is striking.  But while I have this data on my desktop, why don't we look at the entire state. 
 

Three things struck me about this map:
  • There's a huge urban-rural divide (not surprising, very rural, agricultural areas can have very low unemployment rates for multiple reasons).
  • Southeast Kansas is a rural area with high unemployment rate.  This is also not surprising, as this is has been a high-poverty rural area for the past few decades.
  • This looks a little like another map I made.  Specifically this one: 



What is that map?  A map of percent of voters voting for Sam Brownback by county.  Interesting.  I wondered if there might be a correlation.  Two charts proved that there is a fairly significant correlation.







Significant correlation! Low unemployment led to Brownback's win in Kansas! .. probably not..

People say "correlation is not causation" so often that it annoys me.  But this is a great case for explanation.  My thoughts:
  • A priori. One way people debug the correlation/causation is by looking at a priori or functional theory.  This roughly means that we can develop a reasonable theory for the causal mechanisms underlying the correlation.  In this case, we have a pretty clear (and compelling) a priori theory: people in low unemployment counties view the economy as performing well, tend to prefer status quo (incumbent candidates).
  • Covariates: A "gotcha" in the correlation/causation is outside factors simultaneously causing or impacting both correlating variables (this is likely what is occurring here):
    • Other variables: The counties with low unemployment have other things in common, (example: agricultural, more conservative, whiter, more rural).  All of these things lead to supporting more conservative candidates independent of county level unemployment rate. 
    • Pre-existing preferences: The counties with lower unemployment rates voted for Brownback in 2010, before he had any impact on those rates, before a incumbency bias would have been established.
There's another factor at hand though, which *could* have an effect.  Areas with lower unemployment rates could be more conservative generally, due to rational benefits.  The argument here is that low unemployment leads to lower political demand for social services, which are generally considered a liberal policy.  In this case unemployment rates could be at play, but more broadly as a general indicator of well being, and not a preference for an individual candidate.

CONCLUSION

Obviously this post has been a bit ADHD, but a few takeaways:
  • The Kansas side of the KC metro region may have historically low unemployment rates, but that is in no way homogeneous across the region.
  • There is a significant correlation between unemployment rate and propensity to vote for Sam Brownback.  Brownback won counties with < 3% unemployment with nearly 70% of the vote.
  • It's unlikely that the low unemployment rates in counties are directly responsible for Brownback's support, but alternatively, counties with lower demand for social services, may have more conservative preferences.

And a few more maps, unemployment rates over time:

1990

2000

2010 (height of recession)







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