Redistributive Peak Load Pricing
Abstract
This article studies peak-load pricing in essential-goods markets such as electricity, transport, and network industries, when consumers have private information about their willingness to pay, belong to observable categories, and a market designer has redistributive objectives. I characterize the optimal mechanism and answer the following: who benefits from capacity expansion, and how redistributive preferences shape the optimal allocation. I derive structural conditions under which the consumers who gain or lose from the mechanism do not coincide with redistributive priorities. This occurs because allocating to one type propagates to others through informational rents and capacity scarcity, and these effects are evaluated at different social values. The same mechanism governs three policy results. First, I characterize the optimal tagging rule for peak-load pricing and show how observable categories should be ranked by capacity allocation and budget contribution. Second, in contrast to the utilitarian case, I establish a new peak-load investment rule in which the distortion from private information and redistribution persists at the optimum. Third, I further discuss the optimal nonlinear tariff that implements the mechanism, showing that spot pricing fails and that optimal block tariffs are generically neither increasing nor decreasing for consumers with strong redistributive priority.
Leopold Monjoie
Working paper
2026