We estimate demand for residential broadband using high-frequency data from subscribers facing a three-part tariff. The three-part tariff makes data usage during the billing cycle a dynamic problem, thus generating variation in the (shadow) price of usage. We provide evidence that subscribers respond to this variation, and we use their dynamic decisions to estimate a flexible distribution of willingness to pay for different plan characteristics. Using the estimates, we simulate demand under alternative pricing and find that usage-based pricing eliminates low-value traffic. Furthermore, we show that the costs associated with investment in fiber-optic networks are likely recoverable in some markets, but that there is a large gap between social and private incentives to invest.

We show that standard winner‐pay auctions are inept fund‐raising mechanisms because of the positive externality bidders forgo if they top another’s high bid. Revenues are suppressed as a result and remain finite even when bidders value a dollar donated the same as a dollar kept. This problem does not occur in lotteries and all‐pay auctions, where bidders pay irrespective of whether they win. We introduce a general class of all‐pay auctions, rank their revenues, and illustrate how they dominate lotteries and winner‐pay formats. The optimal fund‐raising mechanism is an all‐pay auction augmented with an entry fee and reserve price.