Research

In recent years, there have been increasing calls for marketers to incorporate considerations of fairness into their decision-making. This means that many marketing managers soon will be facing dilemmas between a profit-maximizing action and a fair action. In this paper, I study a particular instance of this trade-off. After recreational cannabis legalization in 2012, Washington state policymakers had to choose whether to allocate retail licenses by lottery (a fair mechanism) or by auction (an efficient mechanism). They chose a lottery. Using the transaction data from the Washington State Liquor and Cannabis Board, I estimate an equilibrium model of competition in the recreational cannabis market and use it to simulate the counterfactual auction allocation of licenses. I find that an auction would have increased the total sales by 5% and reduced prices by 3%. As a result, the state lost $134M over ten years in tax revenue, which amounts to 0.35% of the state's annual budget. From the perspective of fairness, I find that under an auction, Black applicants are on average 21% less likely to receive a retail license and majority-White areas of the state reap disproportionately larger consumer benefits from the auction (20% increase vs 3% increase in consumer surplus for majority-Black areas). The auction increases overall geographic inequality by 3%, as measured by the Gini index.

Should a peer-to-peer platform set prices directly, or should it let sellers set prices while providing price recommendations? A platform can centralize prices and use exclusively available demand information, while price recommendations let sellers compete using their private information. On sharing economy platforms, for example, we observe a myriad of such pricing regimes. We investigate the implications of each pricing regime for the profits of platforms, buyers and sellers. When a platform recommends prices, it effectively plays the role of a sender in a multi-receiver cheap-talk game. Platforms are not always better off by centralizing pricing. When the variance of demand is large, price recommendations can be sustained in equilibrium and are often more profitable for the platform. Otherwise, a price recommendation is not credible. High (low) quality sellers have a stronger (weaker) preference for centralized pricing than the platform. Buyers, in contrast, receive lower surplus when the platform provides price recommendations, and prefer centralized pricing or competition without price recommendations. The results provide tools for platform designers and policy makers to assess the impact of different pricing regimes platforms use. Although price recommendations might seem to encourage lower prices through increased competition, this is not always the case.