The recent wave of randomized trials in development economics has provoked criticisms regarding external validity. We investigate two concerns-heterogeneity across beneficiaries and implementers-in a randomized trial of contract teachers in Kenyan schools. The intervention, previously shown to raise test scores in NGO-led trials in Western Kenya and parts of India, was replicated across all Kenyan provinces by an NGO and the government. Strong effects of shortterm contracts produced in controlled experimental settings are lost in weak public institutions: NGO implementation produces a positive effect on test scores across diverse contexts, while government implementation yields zero effect. The data suggests that the stark contrast in success between the government and NGO arm can be traced back to implementation constraints and political economy forces put in motion as the program went to scale.

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Suppose a policymaker is interested in the impact of an existing social program. Impact estimates using observational data suffer potential bias, while unbiased experimental estimates are often limited to other contexts. This creates a practical trade-off between internal and external validity for evidence-based policymaking. We explore this trade-off empirically for several common policies analyzed in development economics, including microcredit, migration, and education interventions. Based on mean-squared error, non-experimental evidence within context outperforms experimental evidence from another context. This advantage declines, but may not reverse, with experimental replication. We offer four reasons these findings are of general relevance to policy evaluation.

Early reports suggest the fatality rate from COVID-19 varies greatly across countries, but non-random testing and incomplete vital registration systems render it impossible to directly estimate the infection fatality rate (IFR) in many low- and middle-income countries. To fill this gap, we estimate the adjustments required to extrapolate estimates of the IFR from high-income to lower-income regions. Accounting for differences in the distribution of age, sex and relevant comorbidities yields substantial differences in the predicted IFR across 21 world regions, ranging from 0.11% in Western Sub-Saharan Africa to 1.07% for high-income Asia Pacific. However, these predictions must be treated as lower bounds in low- and middle-income countries as they are grounded in fatality rates from countries with advanced health systems. To adjust for health system capacity, we incorporate regional differences in the relative odds of infection fatality from childhood respiratory syncytial virus. This adjustment greatly diminishes but does not entirely erase the demography-based advantage predicted in the lowest income settings, with regional estimates of the predicted COVID-19 IFR ranging from 0.37% in Western Sub-Saharan Africa to 1.45% for Eastern Europe.