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Socioeconomic segregation is often decried for denying poorer children the benefits of positive 'peer effects'. Yet standard, linear-in-means models of peer effects (a) implicitly assume that segregation is zero sum, with gains and losses to rich and poor perfectly offsetting, and (b) rule out theories of 'social distance' whereby peer effects are strongest among similar pairings. The paper exploits the random assignment of pupils between classes to identify more general peer effects in Argentine test-score data. Estimates violate both assumptions (a) and (b), and provide micro foundations for the correlations between school segregation, average test-scores, and test-score inequality in municipality-level data.

Economic Segregation --- Education --- Education For All --- Peer-Group Effects --- Primary Education --- Secondary Education --- Social development --- Teaching and Learning --- Tertiary Education --- Test Scores

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This paper presents the results of a large-scale randomized experiment conducted across 1,496 public primary schools in Mexico. The experiment identifies the impact on schools' managerial capacity and student test scores of providing schools with: (a) cash grants, (b) managerial training for school principals, or (c) both. The school principals' managerial training focused on improving principals' capacities to collect and use data to monitor students' basic numeracy and literacy skills and provide feedback to teachers on their instruction and pedagogical practices. After two years of implementing these interventions, the study finds that: (a) the cash grant had no impact on the student's test scores or the management capacity of school principals; (b) the managerial training improved school principals' managerial capacity but had no impact on students' test scores; and (c) the combination of cash grants and managerial training amplified the effect on the school principals' managerial capacity and had a positive but statistically insignificant impact on students' test scores.

Economics of Education --- Education --- Education Grants --- Education Quality --- Education Reform and Management --- Effective Schools and Teachers --- Managerial Training --- Primary Education --- Principals --- School Management --- Student Learning --- Test Scores

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The Oaxaca-Blinder technique was originally used in labor economics to decompose earnings gaps and to estimate the level of discrimination. It has been applied since in other social issues, including education, where it can be used to assess how much of a gap is due to differences in characteristics (explained variation) and how much is due to policy or system changes (unexplained variation). The authors apply the decomposition technique in an effort to analyze the increase in Indonesia's score in PISA mathematics. Between 2003 and 2006, Indonesia's score increased by 30 points, or 0.3 of a standard deviation. The test score increase is assessed in relation to family, student, school and institutional characteristics. The gap over time is decomposed into its constituent components based on the estimation of cognitive achievement production functions. The decomposition results suggest that almost the entire test score increase is explained by the returns to characteristics, mostly related to student age. However, the authors find that the adequate supply of teachers also plays a role in test score changes.

Education --- Education For All --- Indonesia --- Macroeconomics and Economic Growth --- Pisa --- Primary Education --- Secondary Education --- Teaching and Learning --- Tertiary Education --- Test Scores

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Low student learning is a common finding in much of the developing world. This paper uses a relatively unique dataset of five semiannual rounds of standardized test data to characterize and explain the short-term changes in student learning. The data are collected as part of the quality assurance system for a public-private partnership program that offers public subsidies conditional on minimum learning levels to low-cost private schools in Pakistan. Apart from a large positive distributional shift in learning between the first two test rounds, the learning distributions over test rounds show little progress. Schools are ejected from the program if they fail to achieve a minimum pass rate in the test in two consecutive attempts, making the test high stakes. Sharp regression discontinuity estimates show that the threat of program exit on schools that barely failed the test for the first time induces large learning gains. The large change in learning between the first two test rounds is likely attributable to this accountability pressure given that a large share of new program entrants failed in the first test round. Schools also qualify for substantial annual teacher bonuses if they achieve a minimum score in a composite measure of student test participation and mean test score. Sharp regression discontinuity estimates do not show that the prospect of future teacher bonus rewards induces learning gains for schools that barely did not qualify for the bonus.

Education --- Education For All --- Learning --- Learning levels --- Learning outcomes --- Pass rate --- Primary Education --- Private school --- Quality assurance --- Quality standards --- Secondary Education --- Standardized tests --- Student learning --- Teaching and Learning --- Tertiary Education --- Test scores

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Social scientists frequently rely on the cardinal comparability of test scores to assess achievement gaps between population subgroups and their evolution over time. This approach has been criticized due to the ordinal nature of test scores and the sensibility of results to order-preserving transformations, which are theoretically plausible. Bond and Lang (2013) document the sensitivity of measured ability to scaling choices and develop a method to assess the robustness of changes in ability over time to scaling choices. This paper presents the scale transformation command, which expands the Bond and Lang method to more general cases and optimizes their algorithm to work with large data sets. The program assesses the robustness of an achievement gap between two subgroups to any arbitrary choice of scale by finding bounds for the original gap estimation. Additionally, the program finds scale transformations that are very likely and unlikely to benchmark against the results obtained. Finally, the program also allows the user to measure how much gap growth coefficients change when including controls in their specifications.

Ability --- Achievement Gaps --- Education --- Education For All --- Educational Sciences --- Effective Schools and Teachers --- Measurement --- Psychometrics --- Public Examination System --- Scale Transformation --- Science and Technology Development --- STATA --- Statistical and Mathematical Sciences --- Student Achievement --- Test Scores