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We study the impact of reforms that introduced more stringent, biometric ID requirements into India's largest social protection program, using large-scale randomized and natural experiments. Corruption fell but with substantial costs to legitimate beneficiaries, 1.5-2 million of whom lost access to benefits at some point during the reforms. At the same time, adverse effects appear to have been driven primarily by decisions about the way the transition was managed, illustrating both the risks of rapid reforms, and how the impacts of promising new technologies can be highly sensitive to the protocols governing their use.

We use a near-representative household panel survey of ∼19,000 primary-school-aged children in rural Tamil Nadu to study the extent of ‘learning loss’ after COVID-19 school closures, the pace of recovery in the months after schools reopened, and the role of a flagship compensatory intervention introduced by the state government. Students tested in December 2021, after 18 months of school closures, displayed severe deficits in learning of about 0.7 standard deviations (σ) in math and 0.34σ in language compared to identically-aged students in the same villages in 2019. Using multiple rounds of in-person testing, we find that two-thirds of this deficit was made up in the 6 months after school reopening. Using value-added models, we attribute ∼24% of the cohort-level recovery to a government-run after-school remediation program which improved test scores for attendees by 0.17σ in math and 0.09σ in Tamil after 3-4 months. Further, while learning loss was regressive, the recovery was progressive, likely reflecting (in part) the greater take up of the remediation program by more socioeconomically disadvantaged students. These positive results from a state-wide program delivered at scale by the government may provide a useful template for both recovery from COVID-19 learning losses, and bridging learning gaps more generally in low-and-middle-income countries.

This 18th India Policy Forum 2021 Volume comprises papers and highlights of the discussions at the India Policy Forum (IPF) held virtually on July 12–15, 2021, due to the persistence of the Coronavirus pandemic. The IPF is organized by NCAER, the National Council of Applied Economic Research, India’s oldest and largest, independent, non-profit, economic think-tank. The IPF promotes original economic policy and empirical research on India. The IPF Editors commission both empirical research papers and policy-focused expert reviews, the latter also based on robust, original research. It provides a unique combination of intense scholarship and policymaker engagement at the annual IPF Conference that reviews this research.

Improving “ last-mile” public service delivery is a recurring challenge in developing countries. Could the widespread adoption of mobile phones provide a scalable, cost-effective means for improvement? We use a large-scale experiment to evaluate the impact of phone-based monitoring on a program that transferred nearly a billion dollars to 5.7 million Indian farmers. In randomly selected jurisdictions, officials were informed that program implementation would be measured via calls with beneficiaries. This led to a 7.8 percent reduction in the number of farmers who did not receive their transfers. The program was highly cost-effective, costing 3.6 cents for each additional dollar delivered. (JEL O13, O33, Q12, Q18)

This paper uses new data to study school management and productivity in India. We report four main results. First, management quality in public schools is low, and ~2σ below high-income countries with comparable data. Second, private schools have higher management quality, driven by much stronger people management. Third, people management quality is correlated with both independent measures of teaching practice, as well as school productivity measured by student value added. Fourth, private school teacher pay is positively correlated with teacher effectiveness, and better managed private schools are more likely to retain more effective teachers. Neither pattern is seen in public schools.

We use a large-scale randomized experiment to study the impact of augmenting staffing in the world’s largest public early childhood program: India’s Integrated Child Development Services (ICDS). Adding a half-time worker doubled net preschool instructional time and led to 0.29σ and 0.46σ increases in math and language test scores after 18 months for children who remained enrolled in the program. Rates of stunting and severe malnutrition were also lower in the treatment group. A cost-benefit analysis suggests that the benefits of augmenting ICDS staffing are likely to significantly exceed its costs even under conservative assumptions.

Despite growing interest in improving early-childhood education in developing countries, there is little evidence on cost-effective ways of doing so at scale. We use a large-scale randomized experiment to study the impact of adding an extra worker focused on pre-school education (for children aged 3-5) in the world’s largest public early-childhood program: India’s Integrated Child Development Services (ICDS). Adding a worker doubled net instructional time and led to 0.29 and 0.46 standard deviation increases in math and language test scores after 18 months for children who remained enrolled in the program. Rates of stunting and severe malnutrition were also lower in the treatment group, likely reflecting the effect of freeing up time of the incumbent worker to focus more on nutrition-related tasks. A cost-benefit analysis suggests that the benefits of the program are likely to significantly exceed its costs even under conservative assumptions. Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

Author(s): Arcidiacono, Peter; Muralidharan, Karthik; Shim, Eun-young; Singleton, John D. | Abstract: In this paper, we use a unique two-stage experiment that randomized access to school vouchers across both markets and students in rural India to estimate the revealed preference value of school choice. In the first step of the research design, we develop an empirical model of school choice subject to liquidity and credit constraints that is estimated using data from only the control markets. Based on this exercise, we estimate that the voucher generated welfare gains exceeding four times the average private school's annual tuition on average to the students induced into private schooling. The second step of the research design will validate the estimated welfare impacts by comparing model predictions for a simulated voucher program in control markets with the data from the treatment group. The results in this paper are based on the first step (using only control data) and this draft serves as a pre-commitment to the model estimates and predictions before examining the experimental data.

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.

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. (JEL I21, I26, I28, J24, O15)

Gains in schooling must be translated into gains in learning

This paper uses new data to study school management and productivity in India. We report four main results. First, management quality in public schools is low, and ~2σ below high-income countries with comparable data. Second, private schools have higher management quality, driven by much stronger people management. Third, people management quality is correlated with both independent measures of teaching practice, as well as school productivity measured by student value added. Fourth, private school teacher pay is positively correlated with teacher effectiveness, and better managed private schools are more likely to retain more effective teachers. Neither pattern is seen in public schools.

This paper uses new data to study school management and productivity in India. We report four main results. First, management quality in public schools is low, and ~2σ below high-income countries with comparable data. Second, private schools have higher management quality, driven by much stronger people management. Third, people management quality is correlated with both independent measures of teaching practice, as well as school productivity measured by student value added. Fourth, private school teacher pay is positively correlated with teacher effectiveness, and better-managed private schools are more likely to retain more effective teachers. Neither pattern is seen in public schools. Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

We present results from a large-scale experimental evaluation of an ambitious attempt to improve management quality in Indian schools (implemented in 1,774 randomly-selected schools). The intervention featured several global “best practices” including comprehensive assessments, detailed school ratings, and customized school improvement plans. It did not, however, change accountability or incentives. We find that the assessments were near-universally completed, and that the ratings were informative, but the intervention had no impact on either school functioning or student outcomes. Yet, the program was perceived to be successful and scaled up to cover over 600,000 schools nationally. We find using a matched-pair design that the scaled-up program continued to be ineffective at improving student learning in the state we study. We also conduct detailed qualitative interviews with frontline officials and find that the main impact of the program on the ground was to increase required reporting and paperwork. Our results illustrate how ostensibly well-designed programs, that appear effective based on administrative measures of compliance, may be ineffective in practice.

We present results from a large-scale experimental evaluation of an ambitious attempt to improve management quality in Indian schools (implemented in 1,774 randomly-selected schools). The intervention featured several global “best practices” including comprehensive assessments, detailed school ratings, and customized school improvement plans. It did not, however, change accountability or incentives. We find that the assessments were near-universally completed, and that the ratings were informative, but the intervention had no impact on either school functioning or student outcomes. Yet, the program was perceived to be successful and scaled up to cover over 600,000 schools nationally. We find using a matched-pair design that the scaled-up program continued to be ineffective at improving student learning in the state we study. We also conduct detailed qualitative interviews with frontline officials and find that the main impact of the program on the ground was to increase required reporting and paperwork. Our results illustrate how ostensibly well-designed programs, that appear effective based on administrative measures of compliance, may be ineffective in practice.

How should recipients of publicly-provided goods and services prove their identity in order to access these benefits? The core design challenge is managing the tradeoff between Type-II errors of inclusion (including corruption) against Type-I errors of exclusion whereby legitimate beneficiaries are denied benefits. We use a large-scale experiment randomized across 15 million beneficiaries to evaluate the effects of more stringent ID requirements based on biometric authentication on the delivery of India's largest social protection program (subsidized food) in the state of Jharkhand. By itself, requiring biometric authentication to transact did not reduce leakage, slightly increased transaction costs for the average beneficiary, and reduced benefits received by the subset of beneficiaries who had not previously registered an ID by 10%. Subsequent reforms that made use of authenticated transaction data to determine allocations to the program coincided with large reductions in leakage, but also significant reductions in benefits received. Our results highlight that attempts to reduce corruption in welfare programs can also generate non-trivial costs in terms of exclusion and inconvenience to genuine beneficiaries.

Factorial designs are widely used to study multiple treatments in one experiment. While t-tests using a fully-saturated “long” model provide valid inferences, “short” model t-tests (that ignore interactions) yield higher power if interactions are zero, but incorrect inferences otherwise. Of 27 factorial experiments published in top-5 journals (2007–2017), 19 use the short model. After including interactions, over half of their results lose significance. Based on recent econometric advances, we show that power improvements over the long model are possible. We provide practical guidance for the design of new experiments and the analysis of completed experiments.

How does a large unconditional increase in salary affect the performance of incumbent employees in the public sector? This paper presents experimental evidence on this question in the context of a policy change in Indonesia that led to a permanent doubling of teachers' base salaries. The analysis uses a large-scale, randomized experiment across a representative sample of Indonesian schools that accelerated this pay increase for teachers in treated schools. The findings show 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, making it possible to rule out even modest positive impacts on test scores. The 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.

This paper makes the case for greater use of randomized experiments “at scale.” We review various critiques of experimental program evaluation in developing countries, and discuss how experimenting at scale along three specific dimensions—the size of the sampling frame, the number of units treated, and the size of the unit of randomization— can help alleviate the concerns raised. We find that program-evaluation randomized controlled trials published over the last 15 years have typically been “small” in these senses, but also identify a number of examples—including from our own work— demonstrating that experimentation at much larger scales is both feasible and valuable.

Factorial designs are widely used for studying multiple treatments in one experiment. While “long” model t-tests provide valid inferences, “short” model t-tests (ignoring interactions) yield higher power if interactions are zero, but incorrect inferences otherwise. Of 27 factorial experiments published in top-5 journals (2007–2017), 19 use the short model. After including all interactions, over half their results lose significance. Modest local power improvements over the long model are possible, but with lower power for most values of the interaction. If interactions are not of interest, leaving the interaction cells empty yields valid inferences and global power improvements.

We visited 1519 villages across 19 Indian states in 2009 to (a) count all health care providers and (b) elicit their quality as measured through tests of medical knowledge. We document three main findings. First, 75% of villages have at least one health care provider and 64% of care is sought in villages with 3 or more providers. Most providers are in the private sector (86%) and, within the private sector, the majority are 'informal providers' without any formal medical training. Our estimates suggest that such informal providers account for 68% of the total provider population in rural India. Second, there is considerable variation in quality across states and formal qualifications are a poor predictor of quality. For instance, the medical knowledge of informal providers in Tamil Nadu and Karnataka is higher than that of fully trained doctors in Bihar and Uttar Pradesh. Surprisingly, the share of informal providers does not decline with socioeconomic status. Instead, their quality, along with the quality of doctors in the private and public sector, increases sharply. Third, India is divided into two nations not just by quality of health care providers, but also by costs: Better performing states provide higher quality at lower per-visit costs, suggesting that they are on a different production possibility frontier. These patterns are consistent with significant variation across states in the availability and quality of medical education. Our results highlight the complex structure of health care markets, the large share of private informal providers, and the substantial variation in the quality and cost of care across and within markets in rural India. Measuring and accounting for this complexity is essential for health care policy in India.

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.

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. (JEL H42, I11, I18, O15)

Public employment programs may affect poverty through both the income they provide and their effects on private labor markets. We estimate both effects, exploiting a large-scale experiment randomized across 157 sub-districts (with an average population of 62,500 each) that improved the implementation of India's national rural employment guarantee scheme. The reform raised low-income households' earnings by 13%, with 90% of this gain coming from non-program earnings, driven by increases in both market wages and private-sector employment. Workers' reservation wages increased and their employment gains were higher in treated areas with more concentrated landholdings, consistent with monopsonistic labor markets. We also find increases in credit, private assets, and longer-term enterprise counts and non-agricultural employment, underscoring the far-reaching market impacts of the initial reform. Overall the results suggest that public employment programs can effectively reduce poverty in developing countries, and may also improve economic efficiency.

The study of education in developing countries has been transformed by the rapid increase in the feasibility and prevalence of field experiments over the past 15 years. This paper comprises three main sections. First, it illustrates the very broad range of research questions regarding education in developing countries that have been addressed using field experiments, and summarizes the most important patterns of findings from this body of research. Second, it discusses some of the limitations of field experiments and strategies for mitigating them through better design. Third, it provides a practical toolkit on design, implementation, measurement and data collection, analysis, and interpretation of field experiments in education. The main goal for this chapter is to serve as a reference for students, researchers, and practitioners by summarizing lessons learned, highlighting key open questions for future research, and providing guidance on how to design and implement high-quality field experiments in education in a way that maximizes what we learn from them.

A 57 years old male who was a known case of type 2 diabetes presented with a swelling over the left lower abdomen and groin. The patient appeared toxic and local examination revealed discoloration of size 8x6 cm over the groin with a 1×0.5 cm sized ulcer over it accompanied by a seropurulent discharge. A clinical diagnosis of necrotizing fasciitis was made and investigations revealed an elevated blood sugar, white count and creatinine with cultures showing a poly-microbial growth. Emergency debridement under IV sedation was done and subsequently patient underwent daily debridement and dressing in addition to antibiotics and adequate glycemic control. This condition is a surgical emergency and early diagnosis is crucial for improved prognosis. Aggressive surgical debridement is the first line treatment followed by specific antibiotic therapy.

A 48 years old man presented to the surgical OPD with a history of multiple painless swellings on his scrotum for 20 years. He had avoided all sexual relations with his wife due to potential embarrassment. A clinical diagnosis of scrotal epidermoid cysts was made. Both testes were normal on ultrasound. Upon surgery, the scrotal skin was thoroughly excised, and primary closure of skin was done. Postoperative period was uneventful. The patient engaged in intercourse with his partner two weeks after surgery. The man and his partner were referred to the psychiatry unit for appropriate counselling. Scrotal epidermoid cysts cause significant psychological handicap. In Asian countries, the taboo of seeking medical assistance for genital conditions still exists. The treatment of scrotal epidermoid cysts requires a team of surgeons, psychologists, and psychiatrists.

Empirical studies of the relationship between school inputs and test scores typically do not account for the fact that households will respond to changes in school inputs. This paper presents a dynamic household optimization model relating test scores to school and household inputs, and tests its predictions in two very different low-income country settings -- Zambia and India. The authors measure household spending changes and student test score gains in response to unanticipated as well as anticipated changes in school funding. Consistent with the optimization model, they find in both settings that households offset anticipated grants more than unanticipated grants. They also find that unanticipated school grants lead to significant improvements in student test scores but anticipated grants have no impact on test scores. The results suggest that naïve estimates of public education spending on learning outcomes that do not account for optimal household responses are likely to be considerably biased if used to estimate parameters of an education production function.

The relative return to input-augmentation versus inefficiency-reduction strategies for improving education system performance is a key open question for education policy in low-income countries. Using a new nationally-representative panel dataset of schools across 1297 villages in India, this paper shows that the large investments over the past decade have led to substantial improvements in input-based measures of school quality, but only a modest reduction in inefficiency as measured by teacher absence. In the data, 23.6 percent of teachers were absent during unannounced visits with an associated fiscal cost of $1.5 billion/year. There are two robust correlations in the nationally-representative panel data that corroborate findings from smaller-scale experiments. First, reductions in student-teacher ratios are correlated with increased teacher absence. Second, increases in the frequency of school monitoring are strongly correlated with lower teacher absence. Simulations using these results suggest that investing in better governance by increasing the frequency of monitoring could be over ten times more cost effective at increasing teacher-student contact time (net of teacher absence) than hiring more teachers. Thus, at current margins, policies that decrease the inefficiency of public spending in India are likely to yield substantially higher returns than those that augment inputs.

Improvements in empirical research standards for credible identification of the causal impact of education policies on education outcomes have led to a significant increase in the body of evidence available on improving education outcomes in developing countries. This chapter aims to synthesize this evidence, interpret their results, and discuss the reasons why some interventions appear to be effective and others do not, with the ultimate goal of drawing implications for both research and policy. Interpreting the evidence for generalizable lessons is challenging because of variation across contexts, duration and quality of studies, and the details of specific interventions studied. Nevertheless, some broad patterns do emerge. Demand-side interventions that increase the immediate returns to (or reduce household costs of) school enrollment, or that increase students’ returns to effort, are broadly effective at increasing time in school and learning outcomes, but vary considerably in cost-effectiveness. Many expensive “standard” school inputs are often not very effective at improving outcomes, though some specific inputs (which are often less expensive) are. Interventions that focus on improved pedagogy (especially supplemental instruction to children lagging behind grade level competencies) are particularly effective, and so are interventions that improve school governance and teacher accountability. Our broad policy message is that the evidence points to several promising ways in which the efficiency of education spending in developing countries can be improved by pivoting public expenditure from less cost-effective to more cost-effective ways of achieving the same objectives. We conclude by documenting areas where more research is needed, and offer suggestions on the public goods and standards needed to make it easier for decentralized and uncoordinated research studies to be compared across contexts.

The practical viability of performance-based pay programs for teachers depends critically on the extent of support the idea will receive from teachers. We present evidence on teacher opinions with regard to performance-based pay from teacher interviews conducted in the context of an experimental evaluation of a program that provided performance-based bonuses to teachers in the Indian state of Andhra Pradesh. We report four main findings in this paper: (1) over 80% of teachers had a favorable opinion about the idea of linking a component of pay to measures of performance, (2) exposure to an actual incentive program increased teacher support for the idea, (3) teacher support declines with age, experience, training, and base pay, and (4) the extent of teachers' stated ex-ante support for performance-linked pay (over a series of mean- preserving spreads of pay) is positively correlated with their ex-post performance as measured by estimates of teacher value addition. This suggests that teachers are aware of their own effectiveness and that implementing a performance-linked pay program could not only have broad-based support among teachers but also attract more effective teachers into the teaching profession.

Performance pay for teachers is frequently suggested as a way of improving education outcomes in schools, but the theoretical predictions regarding its effectiveness are ambiguous and the empirical evidence to date is limited and mixed. We present results from a randomized evaluation of a teacher incentive program implemented across a large representative sample of government-run rural primary schools in the Indian state of Andhra Pradesh. The program provided bonus payments to teachers based on the average improvement of their students' test scores in independently administered learning assessments (with a mean bonus of 3% of annual pay). At the end of two years of the program, students in incentive schools performed significantly better than those in control schools by 0.28 and 0.16 standard deviations in math and language tests respectively. They scored significantly higher on "conceptual" as well as "mechanical" components of the tests, suggesting that the gains in test scores represented an actual increase in learning outcomes. Incentive schools also performed better on subjects for which there were no incentives, suggesting positive spillovers. Group and individual incentive schools performed equally well in the first year of the program, but the individual incentive schools outperformed in the second year. Incentive schools performed significantly better than other randomly-chosen schools that received additional schooling inputs of a similar value.

How does a large unconditional increase in salary affect employee performance in the public sector? We present the first experimental evidence on this question in the context of a unique policy change in Indonesia that led to a permanent doubling of base teacher salaries. Using a large-scale randomized experiment across a representative sample of Indonesian schools that accelerated this doubling of pay for teachers in treatment schools, we find that the doubling of pay significantly improved teacher 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 doubling in pay led to no improvements in measures of teacher effort, and had no impact whatsoever on student learning outcomes. Thus, contrary to the predictions of various efficiency wage models of employee behavior (including gift-exchange, reciprocity, and reduced shirking), as well as those of a model where effort on pro-social tasks is a normal good with a positive income elasticity, we find that large unconditional increases in salaries of incumbent teachers had no meaningful positive impact on student learning.Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

This paper presents direct evidence on the quality of health care in low-income settings using a unique and original set of audit studies, where standardized patients were presented to a nearly representative sample of rural public and private primary care providers in the Indian state of Madhya Pradesh. Three main findings are reported. First, private providers are mostly unqualified, but they spent more time with patients and completed more items on a checklist of essential history and examination items than public providers, while being no different in their diagnostic and treatment accuracy. Second, the private practices of qualified public sector doctors were identified and the same doctors exerted higher effort and were more likely to provide correct treatment in their private practices. Third, there is a strong positive correlation between provider effort and prices charged in the private sector, whereas there is no correlation between effort and wages in the public sector. The results suggest that market-based accountability in the unregulated private sector may be providing better incentives for provider effort than administrative accountability in the public sector in this setting. While the overall quality of care is low both sectors, the differences in provider effort may partly explain the dominant market share of fee-charging private providers even in the presence of a system of free public healthcare.

In this paper, we report results from surveys in which enumerators made unannounced visits to primary schools and health clinics in Bangladesh, Ecuador, India, Indonesia, Peru and Uganda and recorded whether they found teachers and health workers in the facilities. Averaging across the countries, about 19 percent of teachers and 35 percent of health workers were absent. The survey focused on whether providers were present in their facilities, but since many providers who were at their facilities were not working, even these figures may present too favorable a picture. For example, in India, one-quarter of government primary school teachers were absent from school, but only about one-half of the teachers were actually teaching when enumerators arrived at the schools. We will provide background on education and health care systems in developing; analyze the high absence rates across sectors and countries; investigate the correlates, efficiency, and political economy of teacher and health worker absence; and consider implications for policy.

A high rate of absence of teachers from their posts is a serious obstacle to delivery of education in many developing countries, but hard evidence on the problem has been scarce. This study, carried out as part of a new multi-country survey project, is the first systematic investigation in Peru into the extent and causes of teachers’ absence from schools. Data from our nationally representative survey of public primary schools, based on unannounced visits and direct observation of teachers, reveals that public school teachers in Peru are absent from their posts 11 percent of the time. While this overall absence rate is low compared with those of other survey countries, the absence rates in Peru’s poorest and remotest communities are much higher—16 and 21 percent, respectively. In our multivariate analysis of the causes of public school teacher absence, we identify several important variables that are associated with increased absence: poor working conditions, such as poorer communities and infrastructure; teachers with fewer ties to the school’s community; contract teaching; and, perhaps, an absence of private competition. By contrast, proxies for more vigorous top-down and bottom-up monitoring are not associated with lower absence. These results, together with the relatively high overall public school teacher attendance rates in an environment where financial incentives for performance are weak, suggest that non-pecuniary incentives are important determinants of teacher performance.