To an economist, a commodity is a good for which there is a demand, and it is fungible—a person can substitute one unit for another, since all units are assumed to be of equal quality. It is convenient for policymakers to treat teachers as a commodity, because then they can determine teacher compensation on a supply-and-demand basis. Teacher compensation could—like that for traders on the financial markets—be set based on the value they contribute, but this would mean that the best teachers would cost way too much—over $300,000 per year according to one study (Chetty et al., 2010). It is convenient for politicians to set a standard for “the qualified teacher,” so that everyone who meets that standard gets in. Teacher compensation can then be determined by supply and demand—how much needs to be paid to get a qualified teacher in every classroom (although in this context, it is worth noting that this is not the basis that politicians tend to use to determine their own compensation!).
The desire of teacher unions to treat all teachers as equally good is understandable, because it generates solidarity among their members, but more important because performance-related pay is in principle impossible to determine fairly. Consider a district that tests its students every year from third through eighth grade and then uses the test score data to work out which teachers have added the most value each year. This looks straightforward, but there is a fatal flaw: no test can capture all that is important for future progress. A fourth-grade teacher who spends a great deal of time developing skills of independent and collaborative learning, who ensures that her students become adept at solving problems, and who develops her students’ abilities at speaking, listening, and writing in addition to teaching reading may find that her students’ scores on the fourth-grade mathematics and reading tests are not as high as those of other teachers in her school who have been emphasizing only what is on the test. And yet, the teacher who inherits this class in fifth grade will look very good when the results of the fifth-grade tests are in, not because of what the fifth-grade teacher has done, but because of the firm foundations that the fourth-grade teacher laid.
In addition, evidence suggests that paying teachers bonuses for the achievement of their students does not raise test scores. Between 2006 and 2009, researchers selected teachers in Nashville, Tennessee, at random and offered bonuses of $15,000 for getting their students’ achievement to match the highest-performing 5 percent of students, with lesser bonuses of $10,000 and $5,000 for matching the highest-performing 10 percent and 20 percent, respectively. An evaluation of the incentives found that the scores of the students taught by teachers offered bonuses were no higher than the scores of those taught by other teachers (Springer et al., 2010).
Such results seem to surprise many economists. They tend to assume that people’s primary motivation is economic reward, and so offering cash incentives for people to try harder must surely increase results. They forget that such incentives work only when people are not already trying as hard as they can. There are, no doubt, some teachers who do not care about how well their students do, and for this small minority of teachers, incentives may work. But the vast majority of teachers are trying everything they can to increase their students’ achievement. There is certainly no evidence that there are teachers who are holding on to a secret proven method for teaching fractions until someone pays them more money. So, performance-related pay is impossible to implement fairly, does not seem to work, and even if it can be made to work, will make a difference only for that small minority of teachers who are not already trying their best.
As noted previously, for many years, researchers and politicians assumed that one teacher was as good as another, providing each was adequately qualified for the job. However, in 1996, William Sanders and June Rivers published a paper based on an analysis of three million records on the achievement of Tennessee’s entire student population from second to eighth grade. Because of the way they collected the data, it was possible to track the progress each individual student made and match that to the teacher who had been teaching them each year. They found that there were differences in how much students learned with different teachers, and that these differences were large. To show how large the differences were, they classified the teachers into five equally sized groups based on how much progress their students had made (low, below average, average, above average, and high). They then examined how an average eight-year-old student would fare, depending on what teachers he or she got. What they found was rather surprising. A student who started second grade at the 50th percentile of achievement would end up at the 90th percentile of achievement after three years with a high-performing teacher but, if assigned to the classes of low-performing teachers for three years, would end up at the 37th percentile of achievement—a difference of over 50 percentile points. They found that increases in teacher quality were most beneficial for lower-achieving students, and the general effects were the same for students from different ethnic backgrounds (Sanders & Rivers, 1996).
Subsequent studies (for example, Rivkin, Hanushek, & Kain, 2005; Rockoff, 2004) confirmed the link between teacher quality and student progress on standardized tests. While different studies have found slightly different results, there is now a clear consensus among researchers that the correlation between teacher quality and student progress is at least 0.1, and may be over 0.2, especially for mathematics, as the data in table 1.1 clearly indicate. A correlation of 0.1 would mean that if a student was taught by an above-average teacher (for example, a teacher who is one standard deviation above the mean), then that student would make 0.1 standard deviations’ more progress in a year than a student taught by an average teacher. Since for most students in these studies, one year’s progress is around 0.4 standard deviations, this would equate to a 25 percent increase in the rate of learning.
Table 1.1: Correlation Between Teacher Quality and Student Progress in Reading and Mathematics
The estimates in table 1.1 are based on the progress made from one year to the next on standardized tests, and these numbers could be very different if we looked at other measures of student achievement. However, there is no evidence that having a good teacher is more important for performance on standardized tests than it is for other measures of performance. As far as we know, having a good teacher makes a difference no matter what the subject, or the age of the student.
One objection to this argument is that teachers may appear to make more progress with their students not because they are better teachers, but because they teach higher-achieving students. There is no doubt that in many school districts, teachers with seniority have influence over the classes they are assigned to teach. To test this explanation, the Measures of Effective Teaching (MET) project, funded by the Bill and Melinda Gates Foundation, identified teachers who had been successful in one school, and reassigned them to teach in another school, often teaching students of different socioeconomic backgrounds. The project found that the teachers who were more successful in one school were more successful in a very different school (Kane, McCaffrey, Miller, & Staiger, 2013). While the circumstances in which teachers work—the time they have to plan instruction, the quality of curriculum with which they are working, the size of classes they teach—undoubtedly have an influence, there is something that successful teachers carry around with them in their heads that makes them more effective wherever they work.
The average correlations for reading and mathematics in table 1.1 are 0.14 and 0.18 respectively, so 0.15 is a reasonable average value for the correlation between teacher quality and student progress. What this means is that an increase of one standard deviation of teacher quality would result in an increase of 0.15 standard deviations in student achievement, equivalent to