Diarrhea is the second leading cause of death for children in low- and middle-income countries (LMICs). This is true despite the fact that nearly all such deaths could be prevented with a simple and inexpensive solution: oral rehydration salts (ORS). Private health care providers, who treat the majority of childhood illness in LMICs, are particularly unlikely to dispense ORS to children with diarrhea. Instead, providers often dispense antibiotics inappropriately. In order to improve prescribing practices, it is essential that we first have a good understanding of the key drivers of underprescription of ORS and overprescription of antibiotics in the private sector. In this study, we examine several leading explanations for poor quality of care for child diarrhea in the private sector. First, patient preferences for ORS alternatives (e.g., an antibiotic) could be driving underprescription of ORS. We will identify the causal effect of patient preferences by having anonymous standardized patients (SPs) pose as caretakers of children with diarrhea and express different (randomly assigned) preferences for treatment (ask for ORS, ask for antibiotics, or let provider decide). Second, private providers could be responding to financial incentives to sell more profitable alternatives to ORS (e.g., an antibiotic). To estimate the causal effect of financial incentives, we will instruct a subset of SPs to inform providers that they can get discounted treatments at a relative’s drug shop. This eliminates the provider’s financial incentive to recommend a given treatment and allows us to estimate the effect of such incentives. Finally, private providers might not directly distribute ORS or could have frequent stock-outs. To estimate the causal effect of stock-outs, we will randomly assign half of the providers to receive a three-month supply of ORS. This generates exogenous variation in stock outs and thus enables us to isolate the causal effect of stock outs on ORS and antibiotic prescribing. Combining, (a) causal estimates of the impact of each factor on prescribing, and (b) population estimates of the prevalence of each factor, will allow us to estimate the population level impact of implementing interventions that address each factor. The results of this study will inform the design of interventions aimed at increasing ORS dispensing and reducing antibiotic dispensing. If such interventions are targeted appropriately, millions of young lives could be saved.