It seems obvious: places with poorer schools also have lower incomes. The chart above shows this pattern for different types of local authority areas in England and Wales. The further down the chart you go, the lower the incomes and poorer the schools (as measured by the share of secondary pupils in schools rated “Inadequate or “Requires improvement” by Ofsted).
Economists have little difficulty explaining the potential causal pathways for such a pattern. Most importantly, poorer schools would tend to lead to poorer skills among the working population. This would particularly be the case if it meant that fewer students went on to higher education and if the best pupils were likely to move out. A lower level of human capital would typically be expected to reduce employment (as a share of total population) and wages (due to the lower productivity of lower-skilled workers), and hence incomes.
However, such a narrative is not really sufficient to explain the pattern seen in the graph above. Why? Well, look at the years for the data: I have chosen to display the latest available information on the two variables (gross disposable household income per head for 2018; and the share of secondary school pupils that are in schools that Ofsted has rated “Inadequate” or “Requires improvement” in 2020). Since those secondary school pupils are not yet in the workforce, the quality of their scools cannot be having a direct impact on current incomes.
Now, it’s entirely plausible that past school quality — which would have an impact on the current level of human capital — is strongly associated, or even causally implicated, in today’s school quality. [I only have the data easily available for 2018 and 2020, and at the local authority level, they are strongly, but by no means perfectly, correlated (R-squared of 52%). This doesn’t say much, however, because the average age of a person in the workforce in 2020 was 42. That means that, on average, they left school around 25 years ago, so would have been in secondary school around the early 1990s. I have assumed people on average left school when they were 18, based on this fascinating ONS article.]
What I am interested in, then, is the reverse causality. Why is the quality of schools in lower-income areas apparently so much worse? Again, it is not difficult to think of explanations. For example, maybe these places are less able to attract and retain the best teachers. Parents in these places probably invest less (in absolute terms) in their childrens’ education (e.g., by way of equipment or tutoring). People’s expectations, aspirations and priorities may be different to more prosperous areas. In fact, this paper from 2004 is quite a good summary of the evidence.
Such two-way causation (over several generations) is likely at the heart of some of the UK’s (and, indeed, any country’s) regional inequalities. While many, many factors contributing to local incomes are likely interrelated (see e.g., #16 here) — ranging from schools to higher education to entrepreneurship to business investment to innovation to exports to employment to management quality to productivity to wages to incomes to consumption to health—the one way this vicious cycle could surely be broken is by improving school quality.
I’m not going to claim that it is easy; nor that the results could be seen soon. But if we want to avoid having the same conversation about “left behind” places in another 25 years, then applying the best brains to solving this system-level problem should surely be a priority.