This paper reports on the results of a dynamic pricing experiment that compares the performance of three popular pricing programs–hourly pricing, critical peak pricing, and critical peak-pricing with a rebate–for a representative sample from the population of households in the District of Columbia. The sampled households differ in terms of their income levels, electricityusing appliance holdings and whether they own a smart thermostat. Using a nonparametric conditional mean estimation framework that allows for customer-specific fixed effects and hourof- sample fixed effects, I find that customers on all of the dynamic pricing programs substantially reduce their electricity consumption during high-priced periods. The hourly average treatment effects associated with each of these dynamic pricing plans are larger in absolute value for households with all-electric heating and households with smart thermostats. Low-income households have significantly larger hourly average treatment effects than higher income households on the same dynamic-pricing tariff. The results of these experiments are also used to investigate two hypotheses about differences in the customer-level demand response to the three dynamic pricing tariffs. Specifically, I find that for roughly the same marginal price during a critical peak period, critical peak pricing yields a larger hourly average demand reduction than critical peak pricing with a rebate. I also find that the demand reduction associated with higher hourly prices is very similar to the predicted demand reduction associated with the same price increase under critical peak pricing.