systematic reviews demonstrate.<sup>1</sup> In particular, our findings help in understanding both the effect sizes of interventions shown to raise students’ test scores, and the reasons why some well-intentioned policy experiments have not significantly impacted learning outcomes. At the core is the interdependence between teacher effort, ability, and skills in generating high quality education. For example, interventions that focus on increasing one component—say, low teacher effort—may not have as high an impact as expected if teachers’ knowledge of the subject they teach is too low. For the same reason, formal teacher education and training do not explain much of the variation in test scores across students in our data, even though their subject and pedagogical knowledge are superior, because those with more formal training tend to teach less.

Most importantly, we argue that the stylized facts presented here can help guide the next generation of policy experiments and reforms. For example, we document substantial shortcomings in teacher knowledge and skills, and show, using quasi-experimental variation, that teacher subject knowledge and teacher pedagogy knowledge and skills are important determinants of student test scores. As of yet, however, we know relatively little about effective ways to raise these aspects of teacher competencies.

We proceed by first providing a brief background of the research program (Service Delivery Indicators) followed by a short description of measured student learning in the seven countries surveyed (sections 2 and 3). The subsequent three sections (4, 5, and 6) aim to answer the main questions outlined above: How much do teachers teach? What do teachers know? How well do teachers teach? Sections 7 and 8 exploit the data to account for the variation in teacher effort, knowledge, and skills across schools, and to account for and explain the variation in student learning. Section 9 compares teachers in public and private schools. Finally, in a concluding

> 1 Kremer, Brannen, and Glennerster (2013), drawing on a set of RCT studies, argue that interventions that match teaching to student learning levels, contract teachers, and interventions improving access to schooling are the most effective. Krishnaratne, White, and Carpenter (2013) – a meta-analysis of 69 RCT and quasi-experimental studies – argue that the most compelling evidence of what works is computer-assisted learning tools. McEwan (2014) – a meta-analysis of 77 RCT – finds the largest effects for interventions involving computer-assisted learning. Murnane and Ganimian (2014) – a narrative review drawing on 115 RCT and quasi-experimental studies – conclude that the strongest evidence (unconditionally) of impact comes from studies providing information about school quality and returns to schooling. Conn (2014) – a meta-analysis based on 56 studies conducted in Sub-Saharan Africa – finds that pedagogical interventions (changes in instructional techniques) have the highest effect size on achievement outcomes, and Glewwe and Muralidharan (2015) – employing a voting counting approach based on 118 studies (of which 80 RCTs) – conclude that teaching at the right level (remedial programs), and teacher performance and accountability interventions are the most promising.  Evans and Popova (2015) provide a review of these reviews to assess which findings are consistent, and which divergent, across these studies and conclude that there are three areas where interventions tend to be most consistently impactful: pedagogical interventions (including computer-assisted learning) that tailor teaching to student skills; repeated teacher training interventions, often linked to another pedagogical intervention; and improving accountability through contracts or performance incentives, at least in certain contexts.

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