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We study the impact of an innovative program in the Indian state of Bihar that aimed to reduce the gender gap in secondary school enrollment by providing girls who continued to secondary school with a bicycle that would improve access to school. Using data from a large representative household survey, we employ a triple difference approach (using boys and the neighboring state of Jharkhand as comparison groups) and find that being in a cohort that was exposed to the Cycle program increased girls' age-appropriate enrollment in secondary school by 32 percent and reduced the corresponding gender gap by 40 percent. We also find an 18 percent increase in the number of girls who appear for the high-stakes secondary school certificate exam, and a 12 percent increase in the number of girls who pass it. Parametric and non-parametric decompositions of the triple-difference estimate as a function of distance to the nearest secondary school show that the increases in enrollment mostly took place in villages that were further away from a secondary school, suggesting that the mechanism of impact was the reduction in the time and safety cost of school attendance made possible by the bicycle. We also find that the Cycle program was much more cost effective at increasing girls' secondary school enrollment than comparable conditional cash transfer programs in South Asia.

We present experimental evidence on the impact of a school choice program in the Indian state of Andhra Pradesh that provided students with a voucher to finance attending a private school of their choice. The study design featured a unique two-stage lottery-based allocation of vouchers that created both student-level and market-level experiments, which allows us to study the individual and the aggregate effects of school choice (including spillovers). After two and four years of the program, we find no difference between test scores of lottery winners and losers on Telugu (native language), math, English, and science/social studies, suggesting that the large cross-sectional differences in test scores across public and private schools mostly reflect omitted variables. However, private schools also teach Hindi, which is not taught by the public schools, and lottery winners have much higher test scores in Hindi. Furthermore, the mean cost per student in the private schools in our sample was less than a third of the cost in public schools. Thus, private schools in this setting deliver slightly better test score gains than their public counterparts (better on Hindi and same in other subjects), and do so at a substantially lower cost per student. Finally, we find no evidence of spillovers on public school students who do not apply for the voucher, or on private school students, suggesting that the positive effects on voucher winners did not come at the expense of other students.

We study the impact of a personalized technology-aided after-school instruction program in middle-school grades in urban India using a lottery that provided winners with free access to the program. Lottery winners scored 0.37 σ higher in math and 0.23 σ higher in Hindi over just a 4.5-month period. IV estimates suggest that attending the program for 90 days would increase math and Hindi test scores by 0.6 σ and 0.39 σ respectively. We find similar absolute test score gains for all students, but much greater relative gains for academically-weaker students. Our results suggest that well-designed, technology-aided instruction programs can sharply improve productivity in delivering education.

We present results from a randomized evaluation of a teacher performance pay program implemented across a large representative sample of government-run rural primary schools in the Indian state of Andhra Pradesh. At the end of 2 years of the program, students in incentive schools performed significantly better than those in control schools by 0.27 and 0.17 standard deviations in math and language tests, respectively. We find no evidence of any adverse consequences of the program. The program was highly cost effective, and incentive schools performed significantly better than other randomly chosen schools that received additional schooling inputs of a similar value.

We present unique audit-study evidence on health care quality in rural India, and find that most private providers lacked medical qualifications, but completed more checklist items than public providers and recommended correct treatments equally often. Among doctors with public and private practices, all quality metrics were higher in their private clinics. Market prices are positively correlated with checklist completion and correct treatment, but also with unnecessary treatments. However, public sector salaries are uncorrelated with quality. A simple model helps interpret our findings: Where public-sector effort is low, the benefits of higher diagnostic effort among private providers may outweigh costs of potential overtreatment.

Antipoverty programs in developing countries are often difficult to implement; in particular, many governments lack the capacity to deliver payments securely to targeted beneficiaries. We evaluate the impact of biometrically authenticated payments infrastructure (\"Smartcards\") on beneficiaries of employment (NREGS) and pension (SSP) programs in the Indian state of Andhra Pradesh, using a large-scale experiment that randomized the rollout of Smartcards over 157 subdistricts and 19 million people. We find that, while incompletely implemented, the new system delivered a faster, more predictable, and less corrupt NREGS payments process without adversely affecting program access. For each of these outcomes, treatment group distributions first-order stochastically dominated those of the control group. The investment was cost-effective, as time savings to NREGS beneficiaries alone were equal to the cost of the intervention, and there was also a significant reduction in the \"leakage \"of funds between the government and beneficiaries in both NREGS and SSP programs. Beneficiaries overwhelmingly preferred the new system for both programs. Overall, our results suggest that investing in secure payments infrastructure can significantly enhance \"state capacity\" to implement welfare programs in developing countries.

We present results from a large-scale randomized experiment across 350 schools in Tanzania that studied the impact of providing schools with (i) unconditional grants, (ii) teacher incentives based on student performance, and (iii) both of the above. After two years, we find (i) no impact on student test scores from providing school grants, (ii) some evidence of positive effects from teacher incentives, and (iii) significant positive effects from providing both programs. Most important, we find strong evidence of complementarities between the programs, with the effect of joint provision being significantly greater than the sum of the individual effects. Our results suggest that combining spending on school inputs (the default policy) with improved teacher incentives could substantially increase the cost-effectiveness of public spending on education.

How does a large unconditional increase in salary affect the performance of incumbent employees in the public sector? We present experimental evidence on this question in the context of a policy change in Indonesia that led to a permanent doubling of teacher base salaries. Using a large-scale randomized experiment across a representative sample of Indonesian schools that accelerated this pay increase for teachers in treated schools, we find that the large pay increase significantly improved teachers’ satisfaction with their income, reduced the incidence of teachers holding outside jobs, and reduced self-reported financial stress. Nevertheless, after two and three years, the increase in pay led to no improvement in student learning outcomes. The effects are precisely estimated, and we can rule out even modest positive impacts on test scores. Our results suggest that unconditional pay increases are unlikely to be an effective policy option for improving the effort and productivity of incumbent employees in public-sector settings.

Metastatic breast cancers are still incurable. Characterizing the evolutionary landscape of these cancers, including the role of metastatic axillary lymph nodes (ALNs) in seeding distant organ metastasis, can provide a rational basis for effective treatments. Here, we have described the genomic analyses of the primary tumors and metastatic lesions from 99 samples obtained from 20 patients with breast cancer. Our evolutionary analyses revealed diverse spreading and seeding patterns that govern tumor progression. Although linear evolution to successive metastatic sites was common, parallel evolution from the primary tumor to multiple distant sites was also evident. Metastatic spreading was frequently coupled with polyclonal seeding, in which multiple metastatic subclones originated from the primary tumor and/or other distant metastases. Synchronous ALN metastasis, a well-established prognosticator of breast cancer, was not involved in seeding the distant metastasis, suggesting a hematogenous route for cancer dissemination. Clonal evolution coincided frequently with emerging driver alterations and evolving mutational processes, notably an increase in apolipoprotein B mRNA-editing enzyme, catalytic polypeptide-like-associated (APOBEC-associated) mutagenesis. Our data provide genomic evidence for a role of ALN metastasis in seeding distant organ metastasis and elucidate the evolving mutational landscape during cancer progression.