MARKET POWER AND INFORMATION REVELATION IN DYNAMIC TRADING

We study a strategic model of dynamic trading where agents are asymmetrically informed over common value sources of uncertainty. There is a continuum of buyers and a finite number n of sellers. All buyers are uninformed, while at least one seller is privately informed about the true state of the world. When n = 1, full information revelation never occurs in equilibrium and the only information transmission happens in the first period. With n > 1 the outcome depends both on the structure of the sellers' information and, even more importantly, on the intensity of competition allowed by the existing trading rules. When there is intense competition (absence of clienteles), information is fully and immediately revealed to the buyers in every equilibrium for n large enough, regardless of the number of informed sellers. On the other hand, for trading arrangements characterized by less intense forms of competition (presence of clienteles), for any n we always have equilibria where information is never fully revealed. Moreover, in that case, when only one seller is informed, for many parameter configurations there are no equilibria with full information revelation, even for large n. (JEL: C72, C78, D82, D83)     

Dynamic Matching,Two‐Sided Incomplete Information,and Participation Costs: Existence and Convergence to Perfect Competition

Consider a decentralized, dynamic market with an infinite horizon and participation costs in which both buyers and sellers have private information concerning their values for the indivisible traded good. Time is discrete, each period has length δ, and, each unit of time, continuums of new buyers and sellers consider entry. Traders whose expected utility is negative choose not to enter. Within a period each buyer is matched anonymously with a seller and each seller is matched with zero, one, or more buyers. Every seller runs a first price auction with a reservation price and, if trade occurs, both the seller and the winning buyer exit the market with their realized utility. Traders who fail to trade continue in the market to be rematched. We characterize the steady‐state equilibria that are perfect Bayesian. We show that, as δ converges to zero, equilibrium prices at which trades occur converge to the Walrasian price and the realized allocations converge to the competitive allocation. We also show the existence of equilibria for δ sufficiently small, provided the discount rate is small relative to the participation costs.     

AUCTION DESIGN WITHOUT COMMITMENT

In anonymous platforms like the Internet, committing to honor the outcome of an auction is difficult since the seller can benefit by reauctioning the good. We argue that how information is processed within the auction mechanism is crucially important in such circumstances. In our model, the seller uses an intermediary to extract information from the buyers but is not tied to sell the good with terms that the mechanism proposes. Instead, she may reauction the good again via some other intermediary. There are no restrictions on how many times and through which mechanisms the good can be reauctioned. The buyers may also choose their outside option at any stage of the game. We argue that a sequentially rational seller can only implement a version of the English auction, in particular the popular version where bidders employ proxy bids. This is a consequence of the informational properties of the English action: it reveals just the right information for the seller to be able to commit to the mechanism.     

基于信号博弈的卖方欺诈行为分析

本文主要基于信号博弈的卖方欺诈行为进行研究，假设拍卖中可能存在欺诈型和诚实型两种卖家，其中欺诈行为有概率发生在第二价格拍卖中：欺诈型卖方冒充竞拍者递交仅次于最高价的报价从而获得额外收益。两种卖家根据各自效用选择拍卖形式：第一价格或者第二价格。而竞买者将卖者的选择作为信号，更新对卖方类型的判断，然后制定报价策略。这是一个买卖方信号交叉影响的过程。考虑到拍卖过程中买方价值相关性，本文在建立模型中参考了关联价值原理。针对该模型进行分析，得出了不同情况下的买卖方策略，并且研究了买方报价、买方判断、卖方收益三者之间的关系。文中利用贝叶斯公式对双方的策略选择问题进行预测，与单纯的概率分布方法相比，更具实践价值。     

Reverse Auctions with Multiple Reinforcement Learning Agents*

Reverse auctions in business‐to‐business (B2B) exchanges provide numerous benefits to participants. Arguably the most notable benefit is that of lowered prices driven by increased competition in such auctions. The competition between sellers in reverse auctions has been analyzed using a game‐theoretic framework and equilibria have been established for several scenarios. One finding of note is that, in a setting in which sellers can meet total demand with the highest‐bidding seller being able to sell only a fraction of the total capacity, the sellers resort to a mixed‐strategy equilibrium. Although price randomization in industrial bidding is an accepted norm, one might argue that in reality managers do not utilize advanced game theory calculations in placing bids. More likely, managers adopt simple learning strategies. In this situation, it remains an open question as to whether the bid prices converge to the theoretical equilibrium over time. To address this question, we model reverse‐auction bidding behavior by artificial agents as both two‐player and n‐player games in a simulation environment. The agents begin the game with a minimal understanding of the environment but over time analyze wins and losses for use in determining future bids. To test for convergence, the agents explore the price space and exploit prices where profits are higher, given varying cost and capacity scenarios. In the two‐player case, the agents do indeed converge toward the theoretical equilibrium. The n‐player case provides results that reinforce our understanding of the theoretical equilibria. These results are promising enough to further consider the use of artificial learning mechanisms in reverse auctions and other electronic market transactions, especially as more sophisticated mechanisms are developed to tackle real‐life complexities. We also develop the analytical results when one agent does not behave strategically while the other agent does and show that our simulations for this environment also result in convergence toward the theoretical equilibrium. Because the nature of the best response in the new setting is very different (pure strategy as opposed to mixed), it indicates the robustness of the devised algorithm. The use of artificial agents can also overcome the limitations in rationality demonstrated by human managers. The results thus have interesting implications for designing artificial agents in automating bid responses for large numbers of bids where human intervention might not always be possible.     

An Analysis of Scoring and Buyer‐Determined Procurement Auctions

In procurement auctions, the object for sale is a contract, bidders are suppliers, and the bid taker is a buyer. The suppliers bidding for the contract are usually the current supplier (the incumbent) and a group of potential new suppliers (the entrants). As the buyer has an ongoing relationship with the incumbent, he needs to adjust the bids of the entrants to include non‐price attributes, such as the switching costs. The buyer can run a scoring auction, in which suppliers compete on the adjusted bids or scores, or, he can run a buyer‐determined auction, in which suppliers compete on the price, and the buyer adjusts a certain number of the bids with the non‐price attributes after the auction to determine the winner. Unless the incumbent has a significant cost advantage over the entrants, I find that the scoring auction yields a lower average cost for the buyer, if the non‐price attributes are available. If the non‐price attributes are difficult or expensive to obtain, the buyer could run a buyer‐determined auction adjusting only the lowest price bid.     

Waiting for News in the Market for Lemons

We study a dynamic setting in which stochastic information (news) about the value of a privately informed seller's asset is gradually revealed to a market of buyers. We construct an equilibrium that involves periods of no trade or market failure. The no‐trade period ends in one of two ways: either enough good news arrives, restoring confidence and markets reopen, or bad news arrives, making buyers more pessimistic and forcing capitulation that is, a partial sell‐off of low‐value assets. Conditions under which the equilibrium is unique are provided. We analyze welfare and efficiency as they depend on the quality of the news. Higher quality news can lead to more inefficient outcomes. Our model encompasses settings with or without a standard static adverse selection problem—in a dynamic setting with sufficiently informative news, reservation values arise endogenously from the option to sell in the future and the two environments have the same equilibrium structure.     

Valuing Dealers' Informational Advantage: A Study of Canadian Treasury Auctions

In many financial markets, dealers have the advantage of observing the orders of their customers. To quantify the economic benefit that dealers derive from this advantage, we study detailed data from Canadian Treasury auctions, where dealers observe customer bids while preparing their own bids. In this setting, dealers can use information on customer bids to learn about (i) competition, that is, the distribution of competing bids in the auction, and (ii) fundamentals, that is, the ex post value of the security being auctioned. We devise formal hypothesis tests for both sources of informational advantage. In our data, we do not find evidence that dealers are learning about fundamentals. We find that the “information about competition” contained in customer bids accounts for 13–27% of dealers' expected profits.     

Managing Risks in Multiple Online Auctions: An Options Approach*

The scenario of established business sellers utilizing online auction markets to reach consumers and sell new products is becoming increasingly common. We propose a class of risk management tools, loosely based on the concept of financial options that can be employed by such sellers. While conceptually similar to options in financial markets, we empirically demonstrate that option instruments within auction markets cannot be developed employing similar methodologies, because the fundamental tenets of extant option pricing models do not hold within online auction markets. We provide a framework to analyze the value proposition of options to potential sellers, option‐holder behavior implications on auction processes, and seller strategies to write and price options that maximize potential revenues. We then develop an approach that enables a seller to assess the demand for options under different option price and volume scenarios. We compare option prices derived from our approach with those derived from the Black‐Scholes model ( Black & Scholes, 1973 ) and discuss the implications of the price differences. Experiments based on actual auction data suggest that options can provide significant benefits under a variety of option‐holder behavioral patterns.     

Transparency in Buyer‐Determined Auctions: Should Quality be Private or Public?

We study buyer‐determined procurement auctions where both price and non‐price characteristics of bidders matter for being awarded a contract. Although, in scoring auctions bidders perfectly know how price and non‐price attributes determine the awarding of the contract, this remains uncertain in buyer‐determined auctions where the buyer is free to choose once all bids have been submitted. We analyze the impact of information bidders have with respect to the buyer's awarding decision. As we show theoretically whether it is in the buyer's interest to conceal the impact of non‐price characteristics depends on how important the quality aspects of the procured good are to the buyer: The more important quality aspects are, the more interesting concealment becomes. In a counterfactual analysis using data from a large European procurement platform, we analyze the reduction of non‐price information available to the bidders. Confirming our hypothesis, for auction categories where bidders’ non‐price characteristics strongly influence buyers’ decisions concealment of non‐price information leads to an increase in buyers’ surplus of up to 15% due to higher competitive pressure and lower bids. Conversely, for categories where bidders’ non‐price characteristics are of little importance concealment of non‐price information leads to a decrease in buyers’ surplus of up to 6%.     

基于可变供给量的可分离物品拍卖及其应用

本文对统一价格下可分离物品的拍卖问题进行了研究。首先,在买者报价连续、买者和卖者风险中立、卖者采取可变供给量(将供给量看成价格的函数)的策略下,设计了一个新的基于可变供给量的可分离物品统一价格拍卖机制,研究了其信息激励性和分配的有效性,给出了卖者的最佳供给策略和买者的均衡报价策略。然后,将拍卖机制推广到风险中立、风险爱好和风险厌恶三类风险买者共存的情形,并给出了相应的均衡结论,该结论与现有的一些成果相比更具一般性。最后,给出了拍卖机制在环境规划中应用。具体地,结合"十一五"期间获得的"1+8武汉城市圈"环境规划中有关污染物允许排放总量分配数据和统计申报资料,利用拍卖模型来分析和评价了免费分配方案的有效性程度,并据此给出了关于目前排污申报制度和免费分配方法的若干结论和建议。     

Repurposing Materials and Waste through Online Exchanges: Overcoming the Last Hurdle

Online material and waste exchanges (OMWEs) provide online channels to repurpose by‐products, unused materials and waste from industrial and commercial facilities. Unfortunately, OMWE's also have challenges. First, sellers may have access to other disposal options and, as a result, may not fully commit to the exchange. Second, buyers can face high uncertainty about the product exchanged and the transaction being undertaken. Overcoming these challenges is the “last hurdle” to making OMWEs successful. This study investigates the factors that reduce the buyers' uncertainty and increase the sellers' commitment to the OMWE. We analyze novel transaction‐level data from an online exchange (MNExchange.org) combined with other archival public records on county‐level repurposing and disposal statistics. First, we find that regional repurposing policies and alternatives have a complementary effect on sellers' commitment toward OMWEs, resulting in increased OMWE exchanges. However, regional disposal policies and alternatives have a substitution effect on sellers' commitment, resulting in reduced exchange success. Further, greater product and transaction information reduce the buyer's uncertainty and increase exchange success. Finally, the analysis shows that users' (buyers and sellers) heavily rely on their prior experience with OMWEs. Specifically, higher familiarity between the buyer–seller pair and familiarity with the OMWE system leads to higher likelihood of exchange success. This study lays the foundation for understanding OMWEs and has important implications for developing policies and operations to increase online transactions of by‐products, materials and wastes.     

Efficient Multi‐Attribute Multi‐Unit Auctions for B2B E‐Commerce Logistics

This study is the first proposing allocatively efficient multi‐attribute auctions for the procurement of multiple items. In the B2B e‐commerce logistics problem (ELP), the e‐commerce platform is the shipper generating a large number of online orders between product sellers and buyers, and third‐party logistics (3PL) providers are carriers that can deliver these online orders. This study focuses on the ELP with multiple attributes (ELP‐MA), which is generally the problem of matching the shipper's online orders and 3PL providers given that price and other attributes are jointly evaluated. We develop a one‐sided Vickrey–Clarke–Groves (O‐VCG) auction for the ELP‐MA. The O‐VCG auction leads to incentive compatibility (on the sell side), allocative efficiency, budget balance, and individual rationality. We next introduce the concept of universally unsatisfied set to construct a primal‐dual algorithm, also called the primal‐dual Vickrey (PDV) auction. We prove that the O‐VCG auction can be viewed as a single‐attribute multi‐unit forward Vickrey (SA‐MFV) auction. Both PDV and SA‐MFV auctions realize VCG payments and truthful bidding for general valuations. This result reveals the underlying link not only between single‐attribute and multi‐attribute auctions, but between static and dynamic auctions in a multi‐attribute setting.     

First‐Price Auctions With General Information Structures: Implications for Bidding and Revenue

We explore the impact of private information in sealed‐bid first‐price auctions. For a given symmetric and arbitrarily correlated prior distribution over values, we characterize the lowest winning‐bid distribution that can arise across all information structures and equilibria. The information and equilibrium attaining this minimum leave bidders indifferent between their equilibrium bids and all higher bids. Our results provide lower bounds for bids and revenue with asymmetric distributions over values. We also report further characterizations of revenue and bidder surplus including upper bounds on revenue. Our work has implications for the identification of value distributions from data on winning bids and for the informationally robust comparison of alternative auction mechanisms.     

ON THE POSSIBILITY OF INFORMATIONALLY EFFICIENT MARKETS

This paper presents conditions for a resolution of the Grossman–Stiglitz paradox of informationally efficient markets. We display a market with asymmetric information where a privately revealing equilibrium obtains in a competitive framework and where incentives to acquire information are preserved as long as the correlation in traders’ valuations is not too large. The equilibrium is efficient, and the problems associated with fully revealing rational expectations equilibria are precluded without resorting necessarily to noise traders. The robustness of the results to general information structures is established and the effect of market power is examined in a large market approximation to the competitive economy. The model is applied to explain changes in bidding behavior in central bank liquidity auctions in the crisis period. (JEL: D82, D84, G14, E59)     

Precautionary Bidding in Auctions

We analyze bidding behavior in auctions when risk‐averse buyers bid for a good whose value is risky. We show that when the risk in the valuations increases, DARA bidders will reduce their bids by more than the appropriate increase in the risk premium. Ceteris paribus, buyers will be better off bidding for a more risky object in first price, second price, and English auctions with affiliated common (interdependent) values. This “precautionary bidding” effect arises because the expected marginal utility of income increases with risk, so buyers are reluctant to bid so highly. We also show that precautionary bidding behavior can make DARA bidders prefer bidding in a common values setting to bidding in a private values one when risk‐neutral or CARA bidders would be indifferent. Thus the potential for a “winner's curse” can be a blessing for rational DARA bidders.     

Group Buying,Buyer Heterogeneity,and Sellers' Bargaining Power*

Group buying enables collective bargaining opportunity that individual buyers lack to negotiate prices with sellers. This potential negotiation capability has two opposing effects. On the one hand, the prospect of the group being able to negotiate price with its rival forces each seller to lower its price offer, as too high a price will induce the group to give its rival an opportunity to undercut its price via negotiation, likely taking away all the buyers. On the other hand, the potential negotiation opportunity may also discourage sellers from competing aggressively in their price offers, as the benefit of charging a low price could be offset by competitors in negotiation, thus yielding overall higher prices for the buyers. In this study, we find that compared to individual purchase, buyers benefit from collective bargaining opportunity by group buying only if sellers’ bargaining power relative to the buyer group is low and/or buyers’ preferences toward the sellers are sufficiently differentiated. Given buyers’ strategic choice of group purchase, sellers may be worse off with a further increase in bargaining power, and so may social welfare.     

双边市场中平台企业搭售行为分析

搭售是现实中双边平台企业常用的促销策略之一。通过构建一个两阶段完全信息动态博弈模型,将买方分为搭售喜好型和搭售无差异型,从垄断和竞争两种情形研究了双边平台企业采取搭售策略时,具有不同搭售偏好的买方对最优均衡解的影响以及相应的社会福利变化。研究发现:不论是垄断情形还是竞争情形,搭售对买卖双方均衡进入价格的影响都不确定,而搭售产品的定价则按照传统单边市场的定价方式制定;垄断情形下,搭售能增加买方数量、卖方数量及双边平台企业的利润,而竞争情形下,搭售产品成本较小的双边平台企业将获得较大买方数量、卖方数量及利润。在两种情形下的买方总效用、卖方总效用以及社会总福利均随搭售喜好型买方数量的增加而增加。     

Level‐k Auctions: Can a Nonequilibrium Model of Strategic Thinking Explain the Winner's Curse and Overbidding in Private‐Value Auctions?

This paper proposes a structural nonequilibrium model of initial responses to incomplete‐information games based on “level‐k” thinking, which describes behavior in many experiments with complete‐information games. We derive the model's implications in first‐ and second‐price auctions with general information structures, compare them to equilibrium and Eyster and Rabin's (2005) “cursed equilibrium,” and evaluate the model's potential to explain nonequilibrium bidding in auction experiments. The level‐k model generalizes many insights from equilibrium auction theory. It allows a unified explanation of the winner's curse in common‐value auctions and overbidding in those independent‐private‐value auctions without the uniform value distributions used in most experiments.     

Estimation of a Dynamic Auction Game

This paper proposes an estimation method for a repeated auction game under the presence of capacity constraints. The estimation strategy is computationally simple as it does not require solving for the equilibrium of the game. It uses a two stage approach. In the first stage the distribution of bids conditional on state variables is estimated using data on bids, bidder characteristics, and contract characteristics. In the second stage, an expression of the expected sum of future profits based on the distribution of bids is obtained, and costs are inferred based on the first order condition of optimal bids. We apply the estimation method to repeated highway construction procurement auctions in the state of California between May 1996 and May 1999. In this market, previously won uncompleted contracts reduce the probability of winning further contracts. We quantify the effect of intertemporal constraints on bidders' costs and on bids. Due to the intertemporal effect and also to bidder asymmetry, the auction can be inefficient. Based on the estimates of costs, we quantify efficiency losses.