Randomized Controlled Trials (RCTs) enroll hundreds of millions of subjects and involve many human lives. To improve subjects’ welfare, I propose a design of RCTs that I call Experiment-as-Market (EXAM). EXAM produces a Pareto efficient allocation of treatment assignment probabilities, is asymptotically incentive compatible for preference elicitation, and unbiasedly estimates any causal effect estimable with standard RCTs. I quantify these properties by applying EXAM to a water cleaning experiment in Kenya (Kremer et al., 2011). In this empirical setting, compared to standard RCTs, EXAM improves subjects’ predicted well-being while reaching similar treatment effect estimates with similar precision.

Subsidy programs are typically accompanied by large costs due to the difficulty of screening those who should receive the program from those who would have purchased the good anyway. We design and implement a platform intended to increase the take-up of improved sanitation services by targeting the poorest households for subsidies and using purchases by the wealthy households to increase available subsidies to the poor. We develop a theoretical model designed to isolate the key factors of concern in designing the pricing system. The field project then proceeds in two stages: we first create a demand model based on market data and a demand elicitation experiment, and use the model to predict prices that will maximize take-up subject to an expected budget constraint. We then test the modeled prices on a new sample of households. The treatment led to an increase in market share of mechanical desludging of 4.4 percentage points. The decreased probability of purchasing a manual desludging among those with the largest subsidies was 7.6-8.2 percentage points leading to a market share increase of mechanical desludging of 7.9-9.6 percentage points in that group. The health impacts among neighborhoods with many poor households were large: a 10% increase in the number of poor households in a treatment neighborhood meant that there was a 2.2 percentage point larger decrease in diarrhea. We compare the outcomes of the pricing treatment with alternative targeting methods and pricing structures and show that the pricing treatment outperforms proxy means testing, auctions with perfect pass-through of costs, and straight subsidies on the basis of take-up and/or budget sustainability.

We study a setting in which dynamically arriving items are assigned to waiting agents, who have heterogeneous values for distinct items and heterogeneous outside options. An ideal match would both target items to agents with the worst outside options, and match them to items for which they have high value. Our first finding is that two common approaches – using independent lotteries for each item, and using a waitlist in which agents lose priority when they reject an offer – lead to identical outcomes in equilibrium. Both approaches encourage agents to accept items that are marginal fits. We show that the quality of the match can be improved by using a common lottery for all items. If participation costs are negligible, a common lottery is equivalent to several other mechanisms, such as limiting participants to a single lottery, using a waitlist in which offers can be rejected without punishment, or using artificial currency. However, when there are many agents with low need, there is an unavoidable tradeoff between matching and targeting. In this case, utilitarian welfare may be maximized by focusing on good matching (if the outside option distribution is light-tailed) or good targeting (if it is heavy-tailed). Using a common lottery achieves near-optimal matching, while introducing participation costs achieves near-optimal targeting.