Innovation Incentives for Information Goods

Abstract

Innovations can often be targeted to be more valuable for some consumers than others. This is especially true for digital information goods. We show that the traditional price system not only results in significant deadweight loss, but also provides incorrect incentives to the creators of these innovations. In contrast, we propose and analyze a profit-maximizing mechanism for bundles of digital goods which is more efficient and more accurately provides innovation incentives for information goods. Our “statistical couponing mechanism” does not rely on the universal excludability of information goods, which creates substantial deadweight loss, but instead estimates social value created from new goods and innovations by offering coupons to a relatively small sample of representative consumers. We find that the statistical couponing mechanism can operate with less than 0.1% of the deadweight loss of the traditional price-based system, while more accurately aligning incentives with social value.