An Experimental Analysis of Parallel Multiple Auctions

At online auction platforms we often observed that substitutable goods are auctioned concurrently with auctions ending at the same time. I introduce an experimental setup of three sellers and four buyers in an ascending second price auction environment where every seller runs one auction with a homogeneous good and the buyers are confronted with single unit demand. I find that sellers revenue is significantly lower than theory predicts due to the fact that some auctions did not receive bids whereas other auctions concentrated the bids of all bidders. Moreover, I observe a statistically higher revenue of sellers setting the minimum starting price. Furthermore, my study shows that the buyers submit bids which are significantly lower than the private valuation every buyer receives. Comparing the efficiency of the parallel multiple auction setup to a double auction control experiment, I find a significant lower efficiency in parallel multiple auctions due to the coordination failure of the buyers.simultaneous auctions, internet auctions, market design, electronic business

Learning optimization models in the presence of unknown relations

In a sequential auction with multiple bidding agents, it is highly challenging to determine the ordering of the items to sell in order to maximize the revenue due to the fact that the autonomy and private information of the agents heavily influence the outcome of the auction. The main contribution of this paper is two-fold. First, we demonstrate how to apply machine learning techniques to solve the optimal ordering problem in sequential auctions. We learn regression models from historical auctions, which are subsequently used to predict the expected value of orderings for new auctions. Given the learned models, we propose two types of optimization methods: a black-box best-first search approach, and a novel white-box approach that maps learned models to integer linear programs (ILP) which can then be solved by any ILP-solver. Although the studied auction design problem is hard, our proposed optimization methods obtain good orderings with high revenues. Our second main contribution is the insight that the internal structure of regression models can be efficiently evaluated inside an ILP solver for optimization purposes. To this end, we provide efficient encodings of regression trees and linear regression models as ILP constraints. This new way of using learned models for optimization is promising. As the experimental results show, it significantly outperforms the black-box best-first search in nearly all settings.Comment: 37 pages. Working pape

Just a small delay? Bidding Behavior and Efficiency in overlapping multiple auctions

Online auction platforms like eBay provide a wide range of auctions containing substitutable goods. Some of these auctions exhibit parallel elements which means that two or more auctions run side by side for a certain time. Experiments have shown that multiple auctions ending at the same time, result in significantly lower efficiency due to the coordination failure of the buyers. I introduce an experimental setup with three sellers and four buyers in an overlapping multiple second price auction environment, where every seller runs one auction with a homogeneous good and the buyers are confronted with single unit demand. Furthermore, I vary the degree of the overlap between the successive auctions. One main result is that sellers revenue is significantly higher in overlapping multiple auctions than in parallel multiple auctions. Moreover, I observe a lower coordination failure of the buyers in overlapping auctions than in parallel multiple auctions. Due to these results, efficiency in overlapping multiple auctions is higher compared to the efficiency in parallel multiple auctions.internet auctions, cross bidding, market design, electronic business

An Experimental Analysis of Parallel Multiple Auctions

At online auction platforms we often observed that substitutable goods are auctioned concurrently with auctions ending at the same time. I introduce an experimental setup of three sellers and four buyers in an ascending second price auction environment where every seller runs one auction with a homogeneous good and the buyers are confronted with single unit demand. I find that sellers revenue is significantly lower than theory predicts due to the fact that some auctions did not receive bids whereas other auctions concentrated the bids of all bidders. Moreover, I observe a statistically higher revenue of sellers setting the minimum starting price. Furthermore, my study shows that the buyers submit bids which are significantly lower than the private valuation every buyer receives. Comparing the efficiency of the parallel multiple auction setup to a double auction control experiment, I find a significant lower efficiency in parallel multiple auctions due to the coordination failure of the buyers

Essays on Bidding Behavior in Auctions

The following thesis presents the results of three experimental studies that investigate how changes in the auction environment or auction rules affect bidding behavior and the auction outcome in a variety of auctions. The first study is concerned with the impact of ambiguity about one’s competitiveness. In particular, bidders are either informed or not informed about the upper limit of the support of a uniform distribution from which their competitors’ bids are drawn. Their relative bid is found to decrease under ambiguity – an effect, which is not predicted by standard ambiguity theories alone. A combination of smooth ambiguity and nonlinear probability weighting is shown to organize the experimental results. The second study investigates how two forms of favoritism affect the auction outcome. In one of the treatments, an ex ante preferred bidder is given the right of first refusal. In the other treatment, the seller elicits the preferred bidder’s valuation with an incentive compatible transfer. The good is then sold to the non-preferred bidder(s) via an auction with a reserve price that optimizes the expected joint payoff of the seller and the preferred bidder. The formal analysis for risk-neutral bidders is based to a great extend on Burguet and Perry (2009). Observed behavior partly deviates from the theoretical predictions. In particular, the auction with an optimal reserve price does not maximize the joint payoff of the seller and the preferred bidder. Most of the deviations can be explained by accounting for risk aversion. The third study is concerned with multi-unit uniform-price auctions in the context of emission trading. It investigates the impact of auction frequency on the ability of the secondary market to achieve cost-efficient emission reduction. In the experiment, frequent auctioning does not increase the allocative efficiency (due to better information in later trading periods) but leads to higher price variability and thus higher total abatement costs

Two Essays in Competitive Price Formation in Auctions

In this work, I look at two competitive auction settings where a profit maximizing seller chooses auctions as a vehicle to sell to strategic bidders. In both essays, the auctioneer's problem is the selection of the optimal auction format. In the first essay, the auctioneer has a single item to sell while in the second essay, there are two items. In this work, I use game theoretic methods to derive the best course of action for the buyer and use this to arrive at the best course of action for the auctioneer. In essay 1, I consider a hybrid (between English outcry and second price sealed bid) auction format where at any point in time, the identity of the highest bidder and the second highest price is known to all. I show that this format would generate higher revenues than the English outcry format if the bidders' valuations are interdependent. This is because of lesser risk of overpayment and winner's curse for the bidders in the hybrid auction and consequently, they are better off bidding their valuations earlier. Such behavior results in a quicker convergence of the outstanding price to the final price realized as the bidders can update their valuations with certainty. I test this claim by comparing objects auctioned in Yahoo! and eBay as eBay follows the hybrid action format while Yahoo! follows the English outcry format and do find that with interdependent object valuations revenue from the hybrid auction format is higher.In the second essay, I consider an auctioneer who has two items to sell. These could be complements or substitutes or independent products. Given a pool of strategic bidders, I investigate whether he is better off auctioning the items sequentially or as a bundle. To do so, I first solve the bidders' optimization problem and use the solution to arrive at the implications for the seller. I find that with a moderate number of bidders (N>4), it is optimal to bundle strong complements only. On the other hand, I find that bundling is optimal when the number of bidders is less than four

Just a small delay? Bidding Behavior and Efficiency in overlapping multiple auctions

Online auction platforms like eBay provide a wide range of auctions containing substitutable goods. Some of these auctions exhibit parallel elements which means that two or more auctions run side by side for a certain time. Experiments have shown that multiple auctions ending at the same time, result in significantly lower efficiency due to the coordination failure of the buyers. I introduce an experimental setup with three sellers and four buyers in an overlapping multiple second price auction environment, where every seller runs one auction with a homogeneous good and the buyers are confronted with single unit demand. Furthermore, I vary the degree of the overlap between the successive auctions. One main result is that sellers revenue is significantly higher in overlapping multiple auctions than in parallel multiple auctions. Moreover, I observe a lower coordination failure of the buyers in overlapping auctions than in parallel multiple auctions. Due to these results, efficiency in overlapping multiple auctions is higher compared to the efficiency in parallel multiple auctions

Advancing Ad Auction Realism: Practical Insights & Modeling Implications

This paper proposes a learning model of online ad auctions that allows for the following four key realistic characteristics of contemporary online auctions: (1) ad slots can have different values and click-through rates depending on users' search queries, (2) the number and identity of competing advertisers are unobserved and change with each auction, (3) advertisers only receive partial, aggregated feedback, and (4) payment rules are only partially specified. We model advertisers as agents governed by an adversarial bandit algorithm, independent of auction mechanism intricacies. Our objective is to simulate the behavior of advertisers for counterfactual analysis, prediction, and inference purposes. Our findings reveal that, in such richer environments, "soft floors" can enhance key performance metrics even when bidders are drawn from the same population. We further demonstrate how to infer advertiser value distributions from observed bids, thereby affirming the practical efficacy of our approach even in a more realistic auction setting

Structural Econometric Methods in Auctions: A Guide to the Literature

Auction models have proved to be attractive to structural econometricians who, since the late 1980s, have made substantial progress in identifying and estimating these rich game-theoretic models of bidder behavior. We provide a guide to the literature in which we contrast the various informational structures (paradigms) commonly assumed by researchers and uncover the evolution of the eld. We highlight major contributions within each paradigm and benchmark modi cations and extensions to these core models. Lastly, we discuss special topics that have received substantial attention among auction researchers in recent years, including auctions formultiple objects, auctions with risk averse bidders, testing between common and private value paradigms, unobserved auction-speci c heterogeneity, and accounting for an unobserved number of bidders as well as endogenous entry