Standard experimental designs are geared toward point estimation and hypothesis testing, while bandit algorithms are geared toward in‐sample outcomes. Here, we instead consider treatment assignment in an experiment with several waves for choosing the best among a set of possible policies (treatments) at the end of the experiment. We propose a computationally tractable assignment algorithm that we call “exploration sampling,” where assignment probabilities in each wave are an increasing concave function of the posterior probabilities that each treatment is optimal. We prove an asymptotic optimality result for this algorithm and demonstrate improvements in welfare in calibrated simulations over both non‐adaptive designs and bandit algorithms. An application to selecting between six different recruitment strategies for an agricultural extension service in India demonstrates practical feasibility.

Incentivized experiments are often used to identify the time preferences of households in developing countries. We argue theoretically and empirically that experimental measures may not identify preference parameters, but are a useful tool for understanding financial shocks and constraints. Using data from an experiment in Mali, we find that subject responses vary with savings and financial shocks, meaning they provide information about credit constraints and can be used to test models of risk sharing.

Progress on child mortality requires better curative care, but common policies to improve access risk reducing underuse incompletely or creating overuse. In an RCT of 1,768 children in Mali we analyze how subsidized care and community health worker (CHW) visits affect the targeting of acute care, using nine weeks of daily health data to measure demand conditional on need for care per WHO standards. Parents are five times more likely to seek care when medically indicated. Subsidies increase utilization by over 250%, significantly reducing underuse with moderate effects on overuse. CHW do not improve efficient health care utilization on average.