It is great that Heritage Foundation pundit Stephen Moore and The University of Ohio economic historian Richard Vedder are talking about economic inequality in the opinion pages of The Wall Street Journal, but they seem to have missed the mark. They correctly note that the states (and the District of Columbia) with the highest economic inequality, at least as measured by the Gini coefficient of income inequality, tend to also be “blue” states (those that tend to elect Democrats). They go on to argue Democratic policies are failing to reduce inequality.
This piece and its underlying data analysis have three fundamental flaws:
- The Gini coefficient they are referencing is of income and does not factor in the effect of taxes or transfers. Thus, the measure they are using explicitly misses the impact of the policies that they claim are ineffective.
- They are suffering from one of the cardinal sins of data analysis: omitted variable bias. More populous areas also tend to have higher inequality, at least in part because higher density allows for higher incomes. Furthermore, cities and urban areas also tend to elect more progressive leaders for a variety of reasons. Thus population density is the omitted variable. They fundamentally misunderstand (or at the very least ignore) the relationship between inequality and population density.
- Finally, they are factually incorrect to say the 1980s and 1990s are emblematic of the very laudable notion that “a rising tide lifts all boats.” As can be seen in the figure below, median hourly compensation has been essentially flat since 1970 despite the fact that per capita economic growth more than doubled over the same period.
It is certainly possible that they made these errors because they are neophytes to the inequality discussion, but it is important to correct them now so that these spurious claims do not propagate. Now that pundits from the Heritage Foundation are dipping their toes into the inequality discussion, I hope that they can bring some new and interesting policy ideas instead of misinformation and boilerplate rhetoric to the discussion.