with Niclas Moneke and Ana Radu
Population censuses constitute the basis of public resource allocation and political representation globally. This paper shows that census forms commonly generate incentives for enumerators to disproportionately omit members of larger households. Using microdata from 254 censuses, we estimate that this leads to undercounting in at least 60% of censuses. Omission is concentrated in poor countries where 0.6% of the population is missing. Within countries, poor households are missing three times as many members as rich ones, leading to larger undercounts in poorer regions. We illustrate how this translates into systematic underfunding of public services and political underrepresentation in poor regions. [paper]
with Nitin Bharti, David Blakeslee, Samreen Malik and Talha Naeem
Poor air quality causes substantial health issues and cognitive harm, particularly to the young. We conducted an RCT providing air purifiers to grade-2 classrooms in Lahore, Pakistan. The intervention initially reduced indoor PM2.5 concentrations by 25%, from a base of 191μg/m3; and caused large gains in test scores (0.15 SD) three weeks after installation, accompanied by improvements in classroom behavior. Gains are concentrated in math and fluid intelligence, with no improvement in English or crystallized intelligence. However, six weeks later, the treatment becomes ineffective, ceasing to improve air quality and resulting in no detectable gains in test scores. [paper]
with Niclas Moneke
This paper examines how incentives for data collectors shape the selection of sampling units. We provide causal evidence that data collectors respond to variation in effort cost across survey subjects by excluding high-cost subjects, thereby breaching protocol. Exploiting the random assignment of eligibility for individual interviews across 3.4 million households in 181 surveys worldwide, we find that in 110 (39) surveys at least 5% (10%) of eligible subjects are missing from the sample. Selection out of sample is systematic: missing subjects disproportionately come from marginalised populations. Using three applications, we illustrate how this selection undermines microeconomic and macroeconomic analysis alike. [paper]
with Niclas Moneke
Economists have long studied the underprovision of public goods. Electrification is highly positively correlated with economic development. However, causal evidence points to modest average effects of recent electrification programs in low- and middle-income countries at best. This paper unveils stark differences in the impact of grid access across locations underlying these average effects. First, we document that in rural Sub-Saharan Africa, the world’s least electrified region, most locations with grid access have either near zero or almost full electricity adoption. In other words, modest average connection rates mask a bimodal distribution across locations. Second, we empirically test for a potential determinant of successful electrification identified prominently in historical accounts and modern engineering plans: the productive use of electricity. Exploiting a large-scale, country-wide rural electrification program in Zambia, we provide three findings. First, the aggregate effects of rural electrification are mixed at best, confirming existing evidence. Second, locations with pre-existing productive uses experience almost full household electrification in contrast to near zero adoption elsewhere. Third, any development effects of rural electrification are confined to these same locations. We interpret the bimodal adoption and development pattern as reflective of the high fixed cost of the local electric network, and provide suggestive evidence that productive users help overcome the resulting ‘last mile problem’. [paper] [policy brief]
with Michael Kremer, Ofir Reich, Zhengyun Sun, Sam van Herwaarden, Habtamu Yesigat, Elias Nure and Temesgen Gebeyehu
We identified and tested potential modifications to a digital agricultural extension system using farmer focus groups, surveys, funnel analysis of system data to map points of high user attrition, and iterative A/B tests. Among the modifications tested, reducing information requests from farmers generated the largest reductions in user attrition and increases in information delivery. For example, removing a multi-step user registration process increased access to agricultural advice by 18% without sacrificing valuable user information. The revealed excess data collection, beyond what is needed to maximize the quality of services to users, is consistent with strategic motivations by the government, for example Scott’s (2020) view that states systematically extract information to maintain control, or the view often articulated by economists that governments require citizens to fill out unnecessary forms as an “ordeal mechanism” to ration public services. Indeed, rather than implementing the modifications immediately, the government asked for multiple trials and testing of alternatives to reducing data collection. However, it ultimately eliminated counterproductive data collection, suggesting that tendencies for governments to ask citizens for excessive information are responsive to data analytics identifying “sludge”, in line with Sunstein (2022). [paper]
with Guthrie Gray-Lobe and Sarah Kabay
Hardware requirements are a barrier to widespread adoption of digital learning software among low-income populations. We investigate the demand among smallholder-farming households for a simple, adaptive math learning tool that can be accessed by “brick” phones, and its effect on educational outcomes. Over a quarter of invited households used the tool, with greater demand among households lacking electricity, radios, or televisions, and greater usage when schools were out of session. Engagement lapses without regular reminders to use the service. Using random variation in access to the service, we find some evidence that the platform increased test scores, school attendance, and grade attainment. Interpretation of these estimates is complicated by potentially endogenous outcome observation. [paper] [blog post]
This paper examines the allocation of teachers across public primary schools and assesses its relevance for aggregate learning levels. Harmonizing administrative data on the universe of public primary schools from 85 countries, I build a new global school-level data set that comprises nearly two million schools across 27,691 administrative units. I document that pupil-teacher ratios (PTRs) in high-income countries are low on aggregate and vary little between schools. In contrast, in poor countries aggregate PTRs are high and differences in PTRs between schools are large. Even at the local level, within second-tier administrative units, differences are substantial. Moreover, PTRs are only weakly negatively correlated with local levels of population density, wealth and education. To assess the implications of these facts for aggregate educational outcomes, I leverage data from an experiment in Kenya that assigned an extra teacher to randomly selected primary schools. I show that the effect of adding a teacher on test scores is larger at schools with higher baseline PTRs, thus suggesting that reallocating teachers from low- to high-PTR schools could not only reduce inequality of opportunity but also increase aggregate learning. [Old version available here: STICERD Working Paper No. EOPP 70]
Seasonality and Structural Transformation (with Niclas Moneke and Lixia Ren)
Seasonal Consumption and Development (with Niclas Moneke, Lixia Ren and Kevishen Valeyatheepillay)
The Social Returns to Electrification (with Niclas Moneke and Likun Tian)