Mixed Mechanisms for Auctioning Ranked Items

This paper deals with the problem of designing and choosing auctioning mechanisms for multiple commonly ranked objects as, for instance, keyword auctions in search engines on Internet. We shall adopt the point of view of the auctioneer who has to select the auction mechanism to be implemented not only considering its expected revenue, but also its associated risk. In order to do this, we consider a wide parametric family of auction mechanisms which contains the generalizations of discriminatory-price auction, uniform-price auction and Vickrey auction. For completeness, we also analyze the Generalized Second Price (GSP) auction which is not in the family. The main results are: (1) all members of the family satisfy the four basic properties of fairness, no over-payment, optimality and efficiency, (2) the Bayesian Nash equilibrium and the corresponding value at risk for the auctioneer are obtained for the considered auctions, (3) the GSP and all auctions in the family provide the same expected revenue, (4) there are new interesting auction mechanisms in the family which have a lower value at risk than the GSP and the classical auctions. Therefore, a window opens to apply new auction mechanisms that can reduce the risk to be assumed by auctioneers.

Discriminatory price auctions with resale and optimal quantity caps

We present a model of a discriminatory price auction in which a large bidder competes against many small bidders, followed by a post‐auction resale stage in which the large bidder is endogenously determined to be a buyer or a seller. We extend results on first‐price auctions with resale to this setting and use these results to give a tractable characterization of equilibrium behavior. We use this characterization to study the policy of capping the amount that may be won by large bidders in the auction, a policy that has received little attention in the auction literature. Our analysis shows that the trade‐offs involved when adjusting these quantity caps can be understood in terms familiar to students of asymmetric first‐price single‐unit auctions. Furthermore, whether one seeks to maximize welfare or revenue can have contradictory implications for the choice of cap.

Ride with Me - Ethnic Discrimination, Social Markets and the Sharing Economy

We study ethnic discrimination in the sharing economy using the example of online carpooling marketplaces. Based on a unique dataset of 16,624 real rides from Germany, we estimate the effects of drivers’ perceived name origins on the demand for rides. The results show sizable ethnic discrimination – a discriminatory price premium of about 32% of the average market price. Further analyses suggest that additional information about actors in this market decreases the magnitude of ethnic discrimination. Our findings broaden the perspective of ethnic discrimination by shedding light on subtle, everyday forms of discrimination in social markets; inform ongoing discussions about ways to address discrimination in an era in which markets gradually move online; and respond to increasingly recognized limitations of experimental approaches to study discrimination.

Discriminatory Pricing and Spatial Competition in Two-Sided Media Markets

This study describes a spatial model of price discrimination in two-sided media markets. Given that media platforms offer a uniform price for consumers and either a uniform or discriminatory price for advertisers, we compare a platform’s profit and welfare under these two different pricing schemes. In contrast to the well-known result that price discrimination based on a consumer’s location leads to lower profits, if consumers have a strong aversion to advertising, we show that a platform’s profit is better off under price discrimination. In addition, if consumers rather dislike advertising, we show that price discrimination is detrimental to both a platform’s profit and the consumer’s welfare.