Sometimes statistics just make sense. For instance, the revelation that spending more on education is correlated with a more highly educated workforce is hardly a surprise. To be sure correlation is not causation, but as more states look to cut corners on education spending, it is important to remember the relationship between spending and results.
Using the 2014 State New Economy Index’s workforce education score (a weighted score of the educational attainment of the workforce), there is a significant positive correlation of 0.46 between the education levels of a state’s workforce and the state’s current spending on education per student.
Of course, with a simple correlation it is impossible to attribute any directional causality. Part of the correlation could derive from higher incomes earned by a more educated workforce. Much of education spending comes from property taxes, so wealthy areas where land is more valuable tend to have higher education spending. For instance, education spending is highest in Northeastern states, led by New York ($19,552), where schools spent over three times as much per student as in Utah ($6,206). Resource rich Alaska and Wyoming also spent heavily, though they both had middling scores on the work-force education metric.
In fact, a few states were able to significantly outperform workforce education predictions given their low expenditures on education. In particular, Colorado, Utah, and Virginia all have highly educated workforces despite below-average educational spending. There are at least three explanations for this disparity. First, these states are magnets for highly-skilled workers from elsewhere to relocate to (both Virginia and Colorado rank in the top 10 on the New Economy Index scores of education levels of domestic migrants). Second, these states may have fine-tuned education systems that have figured out how to achieve excellent results for less. Finally, changes in the quality of education would take a while to have an impact on the economies and workforce compositions of each state. It’s possible that a lack of spending now will have repercussions on these states years in the future once students grow and join the workforce.
The opposite is also true- states with less educated workforces who are now spending more than the national average money educating their students have a chance in moving up the economic latter. For example, Louisiana and West Virginia both rank above average in education spending, though both scoring in the bottom three in workforce education.
Interestingly, the correlation intensifies when considering specific educational outcomes, especially relating to science, technology, engineering, and mathematics (STEM) education. The number of high school students taking AP Statistics and Computer Science tests in 2013 is an even better predictor of the education levels of a state’s workforce than is overall spending, with a correlation of 0.59. This result confirms that the results above do not constitute a recommendation to throw money blindly at school systems. In fact, the extent to which school spending varies is a testament not only to how socio-economically diverse state populations are, but that some state education systems function in ways to get more bang for the buck. As ITIF has written, innovation in education itself is critically important. However, it does show that a focus on promoting positive educational outcomes helps produce a workforce capable of meeting the challenges presented by a global economy.