Common Value Auctions Research Articles

Returns from herding as a function of the social network of agents: a simulation study

PurposeThis study combines different perspectives on herding, viewing it as a social network heuristic in comparison to other heuristics. The purpose is to use the heuristic view of herding as found in early literature and test it on grounds of efficiency and payoff, in essence, combining the heuristic and rational agent view of herding. The simulated double auction setting includes agents embedded in a social network, allowing for an examination of herding alongside rational behaviour and imperfect signals.Design/methodology/approachIn each round of the simulation, levels of homophily, density and fractions of types of agents is set and agents are allowed to follow their respective heuristics under those conditions. Characteristics of the social network, such as the size, levels of different homophilies, density and fractions of different types of agents are varied randomly to gauge their effect on the performance of herders vis-à-vis others and the overall market efficiency through simulation based approach. The data used for the study has been developed in Python and linear models are estimated using R.FindingsHerding decreases total surplus in private value double auctions, but herders are not worse off than other agents and perform equally in common value auctions. Further, herders and random offerers reduce payoffs of other agents as well, and herding effects the surplus per transaction and not the quantum.Research limitations/implicationsThis study explores herding as a strategic behaviour coexisting with rationality and other strategies in specific circumstances. It presents intriguing findings on the impact of herding on individual outcomes and market efficiency, raising new avenues for future research. Implication to research includes a dent on the “sieve” argument of markets rooting out irrationality and from it, a policy implication that follows is the need for corrective measures as markets cannot self-correct this, given herders do not perform worse than others.Originality/valueThe study links the phenomenon of herding to the dynamics of social networks and heuristic-based learning mechanisms that sets apart this research from the majority of existing literature, which predominantly conceptualizes herding as an outcome derived from a perfect Bayesian Equilibrium and a rational learning process.

The Common-Probability Auction Puzzle

This paper presents a puzzle in the behavior of experimental subjects in what we call common-probability auctions. In common-value auctions, uncertainty is defined over values, while in common-probability auctions, uncertainty is defined over probabilities. We find that in contrast to the substantial overbidding found in common-value auctions, bidding in strategically equivalent common-probability auctions is consistent with Nash equilibrium. To explain our results, we run treatments to identify whether this difference stems from the way subjects estimate the good’s value in a competitive environment rather than the way they bid conditional on these valuations. We conclude it is the former. (JEL C70, C90, D44, D81)

The Winner’s Curse in Dynamic Forecasting of Auction Data: Empirical Evidence from eBay

Problem definition: Dynamic forecasting models in auctions have fallen short on two dimensions: (i) the lack of an equilibrium model for final bids and (ii) the lack of a winner’s curse (i.e., a tendency to overpay conditional on winning the auction) adjustment to allow bidders to account for a common value component in the auction item. In this paper, we develop a methodology to accurately predict equilibrium stage bids from the initial bidding dynamics and quantify the impact of the winner’s curse. This methodology allows us to conduct policy simulations to optimize auction design parameters. Methodology/Results: Dynamic auctions typically have a stage of high exploratory activity, followed by an inactivity period, and then an equilibrium stage of last-minute bids with sharp jumps. With a Kalman filter approach, we use exploratory stage bids to predict an auction item’s valuation distribution. We feed this prediction into an equilibrium model and apply item-specific adjustments for winner’s curse, bidder heterogeneity, and inactivity period. We use the resulting equilibrium model to predict the equilibrium stage bids. Our methodology improves the forecast of equilibrium stage bids by 11.33%, on average, compared with a state-of-the-art benchmark. This improvement is even higher (18.99%) for common value auctions. We also find that (i) significantly more (respectively, fewer) bidders internalize the winner’s curse in common value (respectively, private value) auctions; (ii) bidders in common value auctions decrease their bids by 6.03% because of the winner’s curse; and (iii) the inactivity period has a lesser impact on the equilibrium stage bids in private value auctions. Managerial implications: Our proposed methodology is intended to facilitate the need in academia and practice for real-time bid predictions that encompass different levels of the common value component in auctions. Using our methodology, auction platforms can support their choice of minimum bid increment policies and decide how to allocate resources across different auctions to mitigate the adverse effects of the winner’s curse. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2022.1165 .

Misbehavior in Common Value Auctions: Bidding Rings and Shills

We characterize the optimal misbehavior by bidding rings or an auctioneer in the ascending English auction with common values. We also show, in an extended game, that in equilibrium potential members join and truthfully reveal their signals. Under a separability assumption, behavior does not change if nonring bidders are informed about the ring’s existence. In general, misbehavior in dynamic settings is more profitable than in outcome-equivalent static settings. However, under a stronger separability assumption, the ring can do no better in the dynamic English format than in the outcome-equivalent, static Sophi format. (JEL D44, D82)

Secret vs Public Rings in Common Value Auctions

Secret vs Public Rings in Common Value Auctions

Revisiting the convergence theorem for competitive bidding in common value auctions

Revisiting the convergence theorem for competitive bidding in common value auctions

Cultural Algorithms as a Framework for the Design of Trustable Evolutionary Algorithms

One of the major challenges facing Artificial Intelligence in the future is the design of trustworthy algorithms. The development of trustworthy algorithms will be a key challenge in Artificial Intelligence for years to come. Cultural Algorithms (CAs) are viewed as one framework that can be employed to produce a trustable evolutionary algorithm. They contain features to support both sustainable and explainable computation that satisfy requirements for trustworthy algorithms proposed by Cox [Nine experts on the single biggest obstacle facing AI and algorithms in the next five years, Emerging Tech Brew, January 22, 2021]. Here, two different configurations of CAs are described and compared in terms of their ability to support sustainable solutions over the complete range of dynamic environments, from static to linear to nonlinear and finally chaotic. The Wisdom of the Crowds method was selected for the one configuration since it has been observed to work in both simple and complex environments and requires little long-term memory. The Common Value Auction (CVA) configuration was selected to represent those mechanisms that were more data centric and required more long-term memory content. Both approaches were found to provide sustainable performance across all the dynamic environments tested from static to chaotic. Based upon the information collected in the Belief Space, they produced this behavior in different ways. First, the topologies that they employed differed in terms of the “in degree” for different complexities. The CVA approach tended to favor reduced “indegree/outdegree”, while the WM exhibited a higher indegree/outdegree in the best topology for a given environment. These differences reflected the fact the CVA had more information available for the agents about the network in the Belief Space, whereas the agents in the WM had access to less available knowledge. It therefore needed to spread the knowledge that it currently had more widely throughout the population.

A Dichotomy of Sport Sponsorships: Does the Nature of Competition Among Sponsors Matter?

In this paper, the authors argue that the firm value implications of sport sponsorships for sponsors may depend on the competitive environment during the bidding process for different types of sponsorships. More specifically, the authors contend that the bidding environment for professional football (soccer) kit sponsorships represents a form of common value auction, while the bidding environment for corporate logo sponsorships on teams’ shirts does not. As common value auctions are prone to winner’s curse, the firm value implications should be different for kit sponsorship announcements than for shirt sponsorship announcements. Our results suggest that shareholders indeed perceive the value derived from kit and shirt sponsorships differently, resulting in the predicted distinction in their impact on sponsors’ firm value. This study sheds light on conflicting results on firm value implications of sport sponsorships in the prior literature and provides rich areas for future research.

Peaches, lemons, and cookies: Designing auction markets with dispersed information

We study how ex ante information asymmetries affect revenue in common-value second-price auctions, motivated by online advertising auctions where “cookies” inform individual advertisers about advertising opportunities. We distinguish information structures in which cookies identify “lemons” (low-value impressions) from those in which cookies identify “peaches” (high-value impressions). As this setting features multiple Nash equilibria, we introduce a new refinement, “tremble robust equilibrium” (TRE) and characterize the unique TRE in first-price and second-price common-value auctions with two bidders who each receive a binary signal. We find that common-value second-price auction revenues are vulnerable to ex ante information asymmetry if relatively rare cookies identify lemons, but not if they identify peaches. First-price auction revenues are substantially higher than second-price auction revenues under these conditions. Extensions show that these insights are robust.

Reference-Dependent Preferences and Overbidding in Private and Common Value Auctions

This paper proposes a model of reference dependent preferences to explain overbidding in private and common value auctions. It is assumed that the reference point is proportional to the value of the object and that losses are weighed more heavily than gains in the utility function. Equilibrium bidding strategies are derived for first- and second-price private and common value auctions. I find that this model fits the data of all experiments analyzed, both private and common value, better in terms of the Bayesian Information Criterion than a standard risk neutral model; moreover, it explains overbidding in all private value and some common value auctions better than other alternative models. These results suggest that reference dependence, among other factors, might play a role in the widespread tendency of subjects to overbid in most experimental auctions.

The Winner's Curse in Dynamic Forecasting of Auction Data: Empirical Evidence from eBay

Problem definition: Dynamic forecasting models in auctions have fallen short on two dimensions: (i) the lack of an equilibrium model for final stage bids and (ii) the lack of a winner's curse (i.e., a tendency to overpay conditional on winning the auction) adjustment to allow bidders to account for a common value component in the auction item. In this paper, we develop a methodology to accurately predict final stage bids from the initial bidding dynamics and quantify the impact of the winner's curse. This methodology allows us to conduct policy simulations to optimize auction design parameters. Methodology: Dynamic auctions typically have a stage of high exploratory activity, followed by an inactivity period, and then a final stage of last-minute bids with sharp jumps. With a Kalman filter approach, we use exploratory stage bids to predict an auction item's valuation distribution. We feed this prediction into an equilibrium model and apply item-specific adjustments for winner's curse, bidder heterogeneity, and inactivity period. We use the resulting equilibrium model to predict the final stage bids. Results: Our methodology improves the forecast of final stage bids by 15.84%, on average, compared to a state-of-the-art benchmark. This improvement is even higher (22.44%) for common value auctions. We also find that: (i) significantly more (resp., fewer) bidders internalize the winner's curse in common value (resp., private value) auctions, (ii) bidders in common value (resp., private value) auctions decrease their bids by 6.69% (resp., 3.51%) due to the winner's curse, and (iii) the inactivity period has a lesser impact on the final stage bids in private value auctions. Managerial Implications: Our proposed methodology is intended to facilitate the need in academia and practice for real-time bid predictions that encompass different levels of the common value component in auctions. Using our methodology, auction platforms can support their choice of minimum bid increment policies and decide how to allocate resources across different auctions to mitigate the adverse effects of the winner's curse.

Information Asymmetries in Common-Value Auctions with Discrete Signals

We consider common-value hybrid auctions among two asymmetrically informed bidders, in which the winning bidder pays his bid with some positive probability κ and the losing bid otherwise. Under the assumption of discrete and affiliated signals, we give an explicit characterization of the (unique) equilibrium based on a simple recurrence relation, which gives rise to a linear-time algorithm for explicitly computing the equilibrium. By analyzing the execution of the algorithm, we derive several insights about the equilibrium structure. First, we show that equilibrium revenue is decreasing in κ and that the limit second-price equilibrium selected as κ → 0 has the highest revenue, in stark contrast to the revenue collapse of the second-price auction predicted by the trembling-hand equilibrium selection proposed in prior work. We further show that the linkage principle can fail to hold even in a pure first-price auction with binary signals: public revelation of a signal to both bidders may decrease the auctioneer’s revenue. Finally, we analyze the effects of public acquisition of additional information on bidder utilities and exhibit cases in which both bidders strictly prefer for a specific bidder to receive additional information.

Private and common value auctions with ambiguity over correlation

We analyze auctions when individuals have ambiguity over the joint information structures generating the valuations and signals of players. We analyze how two standard auction effects interact with the ambiguity of bidders over correlation structures. First, a “competition effect” arises when different beliefs about the correlation between bidders' valuations imply different likelihoods of facing competitive bids. Second, a “winner's value effect” arises when different beliefs imply different inferences about the winner's value. In the private values case, only the first effect exists and this implies that the distribution of bids first order stochastically dominates the distribution of bids in the absence of ambiguity. In common value auctions both effects exist and we show that compared to the canonical model, both in the first-price and second-price auctions, these effects combine to imply that the seller's revenue decreases with ambiguity (in contrast with the private values case). We then characterise the optimal auction in both the private and common value cases. A novel feature that arises in the optimal mechanism in the common values case is that the seller only partially insures the high type against ambiguity.

Revenue Enhancement via Asymmetric Signaling in Interdependent-Value Auctions

We consider the problem of designing the information environment for revenue maximization in a sealed-bid second price auction with two bidders. Much of the prior literature has focused on signal design in settings where bidders are symmetrically informed, or on the design of optimal mechanisms under fixed information structures. We study commonand interdependent-value settings where the mechanism is fixed (a second-price auction), but the auctioneer controls the signal structure for bidders. We show that in a standard common-value auction setting, there is no benefit to the auctioneer in terms of expected revenue from sharing information with the bidders, although there are effects on the distribution of revenues. In an interdependent-value model with mixed private- and common-value components, however, we show that asymmetric, information-revealing signals can increase revenue.

Optimistic overconfidence in electronic reverse auctions

Abstract Optimistic overconfidence, the overly optimistic view of uncertain events, can significantly impact bidding behavior in auctions. This bias so far has been mainly seen as a cause for the winner’s curse in common value auctions. In the present paper, we experimentally study overconfidence in the context of electronic reverse auctions. Here, overconfidence might lead to misperceptions of the bidder’s own cost situation, and of the probability of winning. We also study interactions of overconfidence with other psychometric properties of the bidder, and the format of information presentation. Both factors could mitigate the impact of overconfidence. Our results indicate that overconfidence leads to a more optimistic view of winning the auction and to more aggressive bidding. Its effect can be mitigated if bidders have a high risk literacy, but possibilities to influence it by better information representation are limited.

Hypothetical thinking and the winner’s curse: an experimental investigation

There is evidence that bidders fall prey to the winner’s curse because they fail to extract information from hypothetical events—like winning an auction. This paper investigates experimentally whether bidders in a common value auction perform better when the requirements for this cognitive issue—also denoted by contingent reasoning—are relaxed, leaving all other parameters unchanged. For my underlying research question, I used a lab experiment with two stages. In stage I, the subjects participate in a non-standard common value auction, called the wallet game, in which a naive bidding strategy can lead to both winner’s curse and loser’s curse. In stage II, the subjects in the treatment group learn whether their initial bid was the winning bid or not and they get the opportunity to change this bid. In this sense, the bidders face the same decision problems as in stage I again, but the need for hypothetical thinking is reduced in stage II. The overall pattern of the data suggests that the problem of irrational over- and underbidding can be weakened by giving the subjects ex ante feedback about their bid, but unlike related studies I also find negative effects of additional information.

Hypothetical Thinking and the Winner's Curse: An Experimental Investigation

There is evidence that bidders fall prey to the winner's curse because they fail to extract information from hypothetical events - like winning an auction. This paper investigates experimentally whether bidders in a common value auction perform better when the requirements for this cognitive issue - also denoted by contingent reasoning - are relaxed, leaving all other parameters unchanged. The overall pattern of the data suggests that the problem of irrational over - and underbidding can be weakened by giving the subjects ex ante feedback about their bid, but unlike related studies I also find negative effects of additional information.

An experimental study of estimation and bidding in common-value auctions with public information

We study how subjects with identical public data first make estimates and then bid in common-value environments. The data presented rows of numbers and values associated with them by our (undisclosed) rule. Subjects were asked to estimate the missing value in the last row with only the numbers given, and then bid for that value in a second-price auction. There is no presumption of commonly-known distributions, yet we derive necessary conditions for equilibrium. The strong winner's curse that we observe in our data results from the dispersion of the value estimates and the poorly-chosen bid-strategies. We find that bidding is lower when bidders are more uncertain about the estimates they have made. Finally, the k-nearest-neighbor method does well in explaining the estimates of the (common) value.

Knowing me, imagining you: Projection and overbidding in auctions

Overbidding in auctions has been attributed to e.g. risk aversion, loser regret, level-k, and cursedness, relying on varying identifying assumptions. I argue that “type projection” organizes these findings and largely captures observed behavior. Type projection formally models that people tend to believe others have object values similar to their own—a robust psychological phenomenon that naturally applies to auctions. First, I show that type projection generates the main behavioral phenomena observed in auctions, including increased sense of competition (“loser regret”) and broken Bayesian updating (“cursedness”). Second, re-analyzing data from seven experiments, I show that type projection explains the stylized facts of behavior across private and common value auctions. Third, in a structural analysis relaxing the identifying assumptions made in earlier studies, type projection consistently captures behavior best, in-sample and out-of-sample. The results reconcile bidding patterns across conditions and have implications for behavioral and empirical analyses as well as policy.

Reducing Social Welfare by Making Financial Markets More Complete: Implications for the 2008 Crisis

In the two decades leading up to the 2008 financial crisis, numerous significant changes in federal law greatly reduced transactions costs in financial markets and made possible new types of trading in new types of financial instruments. The driving policy assumption behind these and similar regulatory changes was that making financial markets more complete would increase social welfare by moving financial markets closer toward Arrow-Debreu. In this paper, we present a model that can explain why, contrary to this policy assumption, regulatory changes that made financial markets more complete in the years leading up to 2008 seemed to produce the opposite effect. Our model shows how when agents have heterogeneous expectations, making financial markets more complete can reduce social welfare by increasing aggregate risk; reducing aggregate returns; and skewing perceptions of wealth in ways that inefficiently distort aggregate consumption decisions, causing agents to over-consume in some periods so that they are forced to cut back consumption sub-optimally in subsequent periods. The intuition underlying our model is that when agents have heterogeneous expectations, making markets for financial instruments more complete amplifies the magnitude of the “winner’s curse” observed in many common-value auctions with the detrimental welfare effects we describe. This paper remains in draft form because of the untimely death of the first author. The second author is posting it to honor her memory and to share what is some of her last work. She will be missed.