Teach For America (TFA) Teach For America (TFA) recruits and selects graduates from some of the most selective colleges and universities across the country to teach in the nation's most challenging KϪ12 schools throughout the nation. TFA has grown significantly since its inception in 1990, when it received 2,500 applicants and selected and placed 500 teachers. In 2005, it received over 17,000 applicants and selected and placed a little over 2,000 new teachers, and the program anticipates expanding to over 4,000 placements in 2010. In total, the program has affected the lives of nearly 3 million students.The growth of the program suggests that TFA is helping to address the crucial need to staff the nation's schools, a particularly acute need in high-poverty schools, but TFA is not without its critics. The criticisms tend to fall into two categories. The first is that most TFA teachers have not received traditional teacher training and therefore are not as prepared for the demands of the classroom as traditionally trained teachers. TFA corps members participate in an intensive five-week summer national institute and a two-week local orientation and induction program prior to their first teaching assignment.1 The second criticism is that TFA requires only a two-year teaching commitment, and the majority of corps members leave at the end of that commitment. The short tenure of TFA teachers is troubling because research shows that new teachers are generally less effective than more experienced teachers (Rivkin, Hanushek, & Kain, 2005;Rockoff, 2004).The research reported here investigates the relative effectiveness (in terms of student tested achievement) of TFA teachers and examines the validity of the criticisms of TFA. Specifically, we look at TFA teachers in high schools, and especially in math and science, where considerable program growth is planned over the next few years. To the best of our knowledge, this is the first study of TFA at the high school level. Using individual-level student data linked to teacher data in North Carolina, we estimate the effects of having a TFA teacher compared to a traditional teacher on student performance. The North Carolina data we employ are uniquely suited for this type of analysis because it includes end-of-course (EOC) testing for students across multiple subjects. This allows us to employ statistical methods that attempt to account for the nonrandom nature of student assignments to classes and teachers, which have been shown to lead to biased estimates of the impact of teacher credentials (Clotfelter, Ladd, & Vigdor, 2010;Goldhaber, 2007). Making a Difference? The Effects of Teach For America in High SchoolThe findings show that TFA teachers are in general more effective, as measured by student exam performance, than traditional teachers. Moreover, they suggest that the TFA effect, at least in the grades and subjects investigated, offsets or exceeds the impact of additional years of experience, implying that TFA teachers are at least as effective as experienced hi...

Using student-level microdata from 2000-2001 to 2004-2005 from Florida and North Carolina, we compare the effectiveness of teachers in schools serving primarily students from low-income families (>70% free-and-reduced-price-lunch students) with teachers in schools serving more advantaged students. The results show that the average effectiveness of teachers in high poverty schools is in general less than teachers in other schools and there is significantly greater variation in teacher quality among high poverty schools. These differences are largely driven by less productive teachers at the bottom of the teacher effectiveness distribution in highpoverty schools. The bulk of the quality differential is due to differences in the unmeasured characteristics of teachers. We find that the gain in productivity to more experienced teachers from additional experience is much stronger in lower-poverty schools. The lower return to experience in high-poverty schools does not appear to be a result of differences in the quality of teachers who leave teaching or who switch schools, however. Our findings suggest that measures that induce highly effective teachers to move to high-poverty schools and which promote an environment in which teachers' skills will improve over time are more likely to be successful.

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a b s t r a c tUsing student-level microdata from 2000-2001 to 2004-2005 from Florida and North Carolina, we compare the effectiveness of teachers in schools serving primarily students from low-income families (>70% free-and-reduced-price-lunch students) with teachers in schools serving more advantaged students. The results show that the average effectiveness of teachers in high poverty schools is in general less than teachers in other schools and there is significantly greater variation in teacher quality among high poverty schools. These differences are largely driven by less productive teachers at the bottom of the teacher effectiveness distribution in high-poverty schools. The bulk of the quality differential is due to differences in the unmeasured characteristics of teachers. We find that the gain in productivity to more experienced teachers from additional experience is much stronger in lower-poverty schools. The lower return to experience in high-poverty schools does not appear to be a result of differences in the quality of teachers who leave teaching or who switch schools, however. Our findings suggest that measures that induce highly effective teachers to move to high-poverty schools and which promote an environment in which teachers' skills will improve over time are more likely to be successful.

This paper provides practical guidance for researchers who are designing and analyzing studies that randomize schools—which comprise three levels of clustering (students in classrooms in schools)—to measure intervention effects on student academic outcomes when information on the middle level (classrooms) is missing. This situation arises frequently in practice because many available data sets identify the schools that students attend but not the classrooms in which they are taught. Do studies conducted under these circumstances yield results that are substantially different from what they would have been if this information had been available? The paper first considers this problem in the context of planning a school randomized study based on preexisting two-level information about how academic outcomes for students vary across schools and across students within schools (but not across classrooms in schools). The paper next considers this issue in the context of estimating intervention effects from school-randomized studies. Findings are based on empirical analyses of four multisite data sets using academic outcomes for students within classrooms within schools. The results indicate that in almost all situations one will obtain nearly identical results whether or not the classroom or middle level is omitted when designing or analyzing studies.