The Kentucky Gubernatorial Election

Political observers were shocked when the Republican candidate for governor in Kentucky, Matt Bevin, won a resounding victory over Democrat Jack Conway. Conway, the incumbent Attorney General, had held a small lead in the polls throughout the campaign, about 2.1 percent according to the Huffington Post’s Pollster charts.  That difference translated into an 88 percent chance that Conway was actually ahead in the electorate as a whole.

The actual results were not even close.  Bevin won with 52.5 percent of the ballots cast compared to 43.8 percent for Conway and 3.7 percent for third-party candidate Drew Curtis. Bevin received nearly 218,000 more votes than the Republican candidate in 2011, David Williams, while Conway lost ground winning some 37,000 votes fewer than the total won by the outgoing Democratic governor, Steve Beshear, when he ran in 2011.  In the two largest counties, Jefferson and Fayette, where the Louisville and Lexington metropolitan areas are located, Conway actually won about 10,000 fewer votes in 2015 than he had received when running for Attorney General in 2011.

In 53 of the 120 counties in Kentucky, Bevin’s share of the vote increased by more than twenty percent compared to that won by Williams four years ago.

Following my earlier report on the 2013 Virginia gubernatorial race, here is a simple model based on county-by-county data predicting the vote for Bevin as a function of the vote for Williams in 2011, the proportion of black and Hispanic adults in 2011, and the change in turnout measured as a proportion of the total population aged 19 and older.  (As usual, I have transformed these proportions into their “logits.” )  The voting data comes from the official returns on the site run by the Kentucky Secretary of State.  The demographic data were compiled from Census estimates reported here.  Because of the way the Census groups people by age, my definition of “adults” excludes 18 year-olds.

Ordinary Least Squares; 120 Kentucky Counties
Dependent variable: Republican Vote for Governor, 2015
All variables measured as "logits."

                 coefficient   std. error   t-ratio   p-value 
  const            0.480953     0.116231      4.138    6.70e-05 ***
  Rep Gov 2011     0.646872     0.0354867    18.23     1.04e-35 ***
  Black 2014      −0.0545183    0.0206335    −2.642    0.0094   ***
  Hispanic 2014    0.0132545    0.0328316     0.4037   0.6872  
  Turnout Change   0.322859     0.136171      2.371    0.0194   **

Mean dependent var   0.341255   S.D. dependent var   0.388213
Sum squared resid    3.832535   S.E. of regression   0.182555
R-squared            0.786303   Adjusted R-squared   0.778870

Bevin did less well in counties with higher proportions of blacks, though not Hispanics, even after controlling for the 2011 Republican vote.  He also apparently fared better in counties where turnout increased.

However the turnout effect largely depends on three “outliers,” Cumberland, Elliott, and Menifee Counties, all with adult populations under 7,000. In the first two of these, turnout fell by more than fifteen percent, while in Menifee it rose by about the same amount.  If we exclude these three counties, the effects of turnout change are much more modest:

Ordinary Least Squares; 117 Kentucky Counties
Dependent variable: Republican Vote for Governor, 2015
All variables measured as "logits."

                 coefficient   std. error   t-ratio   p-value 
  const            0.455381     0.118921      3.829    0.0002   ***
  Rep Gov 2011     0.682421     0.0379599    17.98     8.51e-35 ***
  Black 2014      −0.0486127    0.0205614    −2.364    0.0198   **
  Hispanic 2014   −0.00571780   0.0342821    −0.1668   0.8678  
  Turnout Change   0.147086     0.184871      0.7956   0.4279  

Mean dependent var   0.344539   S.D. dependent var   0.383348
Sum squared resid    3.617365   S.E. of regression   0.179716
R-squared            0.787798   Adjusted R-squared   0.780220

The effects for the prior Republican vote and the proportion black and Hispanic remain about the same after these three counties are excluded, but the effect for changes in turnout is about half its prior value and fails to achieve statistical significance.

The Kynect Effect

One of the major issues in the campaign was the “Kynect” program, Kentucky’s implementation of the exchanges provided for under the Affordable Care Act.  Bevin opposed Kynect and first threatened to abolish the program entirely if elected.  He has since relented somewhat agreeing to grandfather all current enrollees but not accept any new applications.  We might thus expect that counties with higher Kynect enrollment rates might show lower levels of support for the Republican.  Using 2014 enrollment data from the Kentucky governor’s site, I find no effect for Kynect enrollment when measured as a proportion of a county’s total population.  When added to the model above, the coefficient is trivially small (-0.014) and statistically insignificant.

It turns out, though, that if we look at the factors influencing Kynect enrollments, we get what might be considered a counter-intuitive result:

Ordinary Least Squares: 120 Kentucky Counties
Dependent variable: Proportion of Total Population Enrolled in Kynect
All variables measured as "logits."

             coefficient   std. error   t-ratio   p-value 
const         −2.88070      0.205054     −14.05    8.61e-27 *** 
Rep Gov 2011   0.147432     0.0639254      2.306   0.0229   ** 
Black 2014    −0.0979391    0.0366472     −2.672   0.0086   *** 
Hispanic 2014 −0.154206     0.0587630     −2.624   0.0099   *** 

Mean dependent var  −1.955458   S.D. dependent var   0.388445 
Sum squared resid    12.62110   S.E. of regression   0.329852 
R-squared            0.297104   Adjusted R-squared   0.278926

Kynect enrollments are higher in counties that voted Republican in 2011 and lower in counties with larger proportions of black or Hispanic citizens.

One possible theory might be that because the ACA was designed to provide insurance to less well-off Americans not already covered by programs like Medicaid, Kynect rates should be higher in counties where Medicaid rates are relatively lower.  This is certainly false.  The bivariate correlation between 2014 Kynect enrollment rates and 2011 Medicaid enrollment rates is 0.89.  Kynect enrollments are highest in counties where Medicaid enrollments are also higher.  The real determinant of Kynect (and Medicaid) coverage rates is whether a county is urban or rural.  If we use total county population as a rough measure of urbanity, then we have this relationship:

Kynect enrollments are higher in the smaller counties.  Not surprisingly, those more rural counties gave a larger share of their votes to Bevin.


However Bevin fared worst in two largest counties where Lexington and Louisville are located.

Many commentators suggested that Bevin’s success came more from his appeal to social and religious conservatives than anything having to do with economics or programs like Kynect.  Kentucky ranks eighth among the states based on weekly church attendance rates, and Bevin appealed directly to religious conservatives with his strong endorsement of Kim Davis, the local official who refused to issue marriage certificates to homosexual couples after the Supreme Court’s decision in June.  It seems much more plausible that Bevin’s victory was powered more by these religious appeals than by anything having to do with his policy stands.