Last month our home state of North Carolina was named “America’s Top State for Business” by CNBC (see the full ranking here). It wasn’t long after when some commentators pointed out that Oxfam had named N.C. the worst state for workers in its most recent rankings.1 The extreme juxtaposition of rankings made me wonder if this was a coincidence or if there are systematic factors that make states good for businesses and bad for workers. Perhaps “right-to-work” laws, lax worker protection regulation or regional wage differences attract businesses looking to take advantage of areas with weak labor bargaining power. This in turn leads to business growth and thus job migration to states that are less desirable for individual workers. At the end of the day, economic planning should have the best interest of residents in mind when crafting business policy, so it seems worth unpacking what drives the rankings.
The Kenan Institute research team collected the detailed rankings data so I could take a closer look. The graph below is a scatter plot of the CNBC and Oxfam rankings. If it looks to you like a paper target hit by a shotgun from 100 feet, you are not alone — there is little correlation between the attractiveness of a state for business and the quality of work at the state level. The dashed line is a best fit to the data and shows just a slight negative relation — that is, a state that is attractive for business is associated with just slightly worse quality of work overall.
In some ways, this result seems like good news insofar as it doesn’t suggest businesses are evaluating the quality of states based primarily on poor conditions for workers. It does, however, leave open the possibility that businesses might be partial to certain characteristics that determine the quality of work. To investigate this possibility, I examined how the CNBC Top States for Business rankings correlated with the three factors going into the Oxfam rankings (wage policies, worker protection and right to organize). Here again, I found no significant relationship between a state’s desirability as a place to do business and the Oxfam subcomponents.2
So, then, what is driving the CNBC business rankings? They measure 10 characteristics in their process. I examined how important each of these 10 factors is along with the Oxfam factors.3 As it turns out, three factors are very important for the CNBC rankings (in order of importance):
It’s interesting that life, health and inclusion is so important (and more so given N.C. ranks below average on this) because it seems to relate closely to the overall quality of life of people in the state. CNBC describes this characteristic as “livability factors like per capita crime rates and environmental quality … inclusiveness in state laws, including protections against discrimination of all kinds, as well as voting rights.” Of course, “cost of doing business” is going to include wages, so there is an apparent balance between quality of life and the wages workers receive. One interpretation would be that businesses especially like cheap, nice places to live — which seems entirely logical.
Interestingly, none of the Oxfam characteristics show up as significantly positively or negatively related to the CNBC rankings. However, the Oxfam ratings are negatively related to the CNBC ranking of cost of living as well as positively related to the CNBC ranking of life, health and inclusion. This suggests that Oxfam rankings may be confounding wages with quality of life. In other words, places with a high cost of living are likely to be expensive (in part because people want to live there given the high quality of life). Again, this is entirely logical and what economists would expect to happen in equilibrium.
Overall, it seems safe to conclude that, at least according to these rankings, there isn’t a strong force drawing businesses into states with poor quality labor markets. But admittedly, this analysis just scratches the surface of what are very complex issues for businesses, workers and policymakers.
2 I estimated an ordinary least squares regression of the CNBC rankings on the three Oxfam factors. None of the factors were statistically significant explanatory variables, and the R-squared of the regression was close to zero (0.04).
3 I again estimated an ordinary least squares regression, this time with all 10 CNBC factors and the Oxfam factors as explanatory variables.