One of the difficulties with assessing how compensation for public school teachers compares to that of teachers in the private sector is that the former outnumber the latter by a wide margin. To get a sense of how teachers are compensated, studies have tended to compare teachers to non-teachers with similar levels of experience and educational attainment, e.g., comparing teachers with post-graduate degrees to other professionals with post-graduate degrees. One obvious difficulty is that not all post-graduate degrees are the same. Matthew Slaughter has observed that U.S. workers with MDs, JDs, and MBAs have pulled far ahead of workers with other masters degrees. Moreover, two people might have the same qualification, yet one might have other unobserved qualities that make her* more productive. It’s easy to imagine that a worker who is particularly industrious might gravitate towards firms that offer incentive-based compensation while a worker who is less industrious might prefer employment in an organization that imposes a rigid pay scale tied to seniority.

In a recent study, Andrew Biggs of AEI and Jason Richwine of the Heritage Foundation have attempted to sort through this difficult tangle of issues to give us a clearer picture of how teachers are compensated relative to non-teachers with similar skills. Part of what Biggs and Richwine do is give a more complete accounting of how to understand teacher compensation, e.g., they try to account for job security, retiree health benefits, and the role of public-sector accounting practices in increasing the value of public pension guarantees.

In addition, they compare teachers and non-teachers by using an objective measure of cognitive ability rather than years of education and look at what happens when non-teachers become teachers and when teachers become non-teachers. By correcting for differences in cognitive ability, the wage gap disappears. When non-teachers become teachers, they tend to experience a wage increase while teachers who become non-teachers tend to experience a wage decrease.

The following is drawn from the paper:

Table 2 shows how teacher salaries change depending on whether education or AFQT is included in the regression. The first row is the “standard” regression based on our CPS analysis in the previous section: Years of education are controlled for, but AFQT is not. The standard regression shows a teacher salary penalty of 12.6 percent.
The second row includes both education and AFQT in the same regression. The impact on teacher wages is small: The penalty decreases by less than two percentage points. The third row again includes AFQT but now omits education. With this specification, the change is dramatic: The teaching penalty is gone, replaced by a statistically insignificant premium.

And also:

Years of education, in particular, is a misleading measure of teacher skill, both within the teaching profession and between teaching and non-teaching occupations. The field of education is less challenging than other academic concentrations, and teacher education has little measurable effect on classroom performance. Furthermore, teachers have significantly lower cognitive ability, on average, than non-teachers with the same level of education. Removing education from a wage regression and replacing it with a measure of raw cognitive ability appears to erase the teacher salary penalty. Clearly, the standard regression masks important facts about teacher skills.

Biggs and Richwine won’t be the last word on this subject, but they’ve moved the ball forward.