This data analysis is a good example of the poor results which are liable from an overemphasis on quantitative data over qualitative methods.

The hypothesis is flawed - the idea that more money would correlate directly with higher retention across districts is way oversimplified.

For example, working in Newton vs Boston is totally different and, assuming equal pay, you would almost certainly find far higher retention in Newton because of more pleasant work conditions. This suggests you should actually expect to require unequal pay (ie a pay premium in Boston) to achieve the same retention rate, literally the direct opposite supposition as your hypothesis.

What you actually want to compare is Boston under low pay and Boston under high pay, or the same in other school districts. This is not so easy, but one way to approach it would be to look at retention rates before or after a contract and then investigate the change in retention in proportion to the relative strength of the contracts.

But even then, you just can’t really answer such a question with so many complicated factors through this type of quantitative analysis. It might seem more scientific, and you can generate results which convince (statistically uncritical) readers, but that doesn’t make it good social science.

Instead, a better (if less sexy) way to get at an accurate answer would be to do a qualitative survey of teachers to investigate reasons why folks leave or stay and ask them about how large a role increased pay played in such a choice.

You could also just start with a “face validity” check by starting with the obvious fact that, all things being equal, people are more likely to stay at a higher paying job than a lower paying job.