THE LONG-TERM IMPACTS OF TEACHERS

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TEACHER VALUE-ADDED AND STUDENT OUTCOMES IN ADULTHOOD

Many policy makers advocate increasing the quality of teaching, but there is considerable debate about the best way to measure and improve teacher quality. One method is to evaluate teachers based on their impacts on students’ test scores, commonly termed the “value-added” (VA) approach. A teacher’s value-added is defined as the average test-score gain for his or her students, adjusted for differences across classrooms in student characteristics such as prior scores. School districts from Washington D.C. to Los Angeles have begun to use VA to evaluate teachers. Proponents argue that using VA can improve student achievement (e.g. Hanushek 2009), while critics argue that test score gains are poor proxies for a teacher’s true quality (e.g. Baker et al. 2010).

The debate about VA stems from two fundamental questions. First, does VA accurately measure teachers’ impacts on scores or does it unfairly penalize teachers who may systematically be assigned lower achieving students? Second, do high VA teachers improve their students’ long-term outcomes or are they simply better at teaching to the test? Researchers have not reached a consensus about the accuracy and long-term impacts of VA because of data and methodological limitations.

In this paper the authors address these two questions by tracking one million children from a large urban school district from 4th grade to adulthood. They evaluate the accuracy of standard VA measures using several methods, including natural experiments that arise from changes in teaching staff.

The study finds that when a high VA teacher joins a school, test scores rise immediately in the grade taught by that teacher; when a high VA teacher leaves, test scores fall. Test scores change only in the subject taught by that teacher, and the size of the change in scores matches what we predict based on the teacher’s VA. These results establish that VA accurately captures teachers’ impacts on students’ academic achievement and thereby reconcile the conflicting conclusions of Kane and Staiger (2008) and Rothstein (2010). These methods provide a simple yet powerful method to estimate the bias of value-added models in any district; interested readers can download computer code to implement these tests from this link.

In the second part of the study, the authors analyze whether high VA teachers also improve students’ long-term outcomes. They find that students assigned to higher VA teachers are more successful in many dimensions. They are more likely to attend college, earn higher salaries, live in better neighborhoods, and save more for retirement. They are also less likely to have children as teenagers.

Teachers’ impacts on students are substantial. Replacing a teacher whose true VA is in the bottom 5% with a teacher of average quality would generate lifetime earnings gains worth more than $250,000 for the average classroom. VA estimates are less reliable when they are based on data from a small number of classes. However, even after observing teachers’ impacts on test scores for one year, estimates of VA are reliable enough that such personnel changes would yield large gains on average.

Teachers have large impacts in all the grades analyzed (4 to 8), implying that the returns to education remain large well beyond early childhood. Teachers’ impacts on earnings are also similar in percentage terms for students from low and high income families. As a rough guideline, parents should be willing to pay about 25% of their child’s income at age 28 to switch their child from a below-average (25th percentile) to an above-average (75th percentile) teacher. For example, parents whose children will earn around $40,000 in their late 20s should be willing to pay $10,000 to switch from a below-average to an above-average teacher for one grade, based on the expected increase in their child’s lifetime earnings.

Overall, this study shows that great teachers create great value – perhaps several times their annual salaries – and that test score impacts are helpful in identifying such teachers. Improving the quality of teaching – whether using value-added or other tools – is likely to have large economic and social returns.

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