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A strategy is obviously dominant if, for any deviation, at any information set where both strategies first diverge, the best outcome under the deviation is no better than the worst outcome under the dominant strategy. A mechanism is obviously strategy-proof (OSP) if it has an equilibrium in obviously dominant strategies. This has a behavioral interpretation: a strategy is obviously dominant if and only if a cognitively limited agent can recognize it as weakly dominant. It also has a classical interpretation: a choice rule is OSP-implementable if and only if it can be carried out by a social planner under a particular regime of partial commitment.

The high-frequency trading arms race is a symptom of flawed market design. Instead of the continuous limit order book market design that is currently predominant, we argue that financial exchanges should use frequent batch auctions: uniform price double auctions conducted, for example, every tenth of a second. That is, time should be treated as discrete instead of continuous, and orders should be processed in a batch auction instead of serially. Our argument has three parts. First, we use millisecond-level direct-feed data from exchanges to document a series of stylized facts about how the continuous market works at high-frequency time horizons: (i) correlations completely break down; which (ii) leads to obvious mechanical arbitrage opportunities; and (iii) competition has not affected the size or frequency of the arbitrage opportunities, it has only raised the bar for how fast one has to be to capture them. Second, we introduce a simple theory model which is motivated by and helps explain the empirical facts. The key insight is that obvious mechanical arbitrage opportunities, like those observed in the data, are built into the market design—continuous-time serial-processing implies that even symmetrically observed public information creates arbitrage rents. These rents harm liquidity provision and induce a never-ending socially wasteful arms race for speed. Last, we show that frequent batch auctions directly address the flaws of the continuous limit order book. Discrete time reduces the value of tiny speed advantages, and the auction transforms competition on speed into competition on price. Consequently, frequent batch auctions eliminate the mechanical arbitrage rents, enhance liquidity for investors, and stop the high-frequency trading arms race.

We run a regression discontinuity design analysis to document the causal effect of increasing buyers’ discretion on procurement outcomes in a large database for public works in Italy. Works with a value above a given threshold have to be awarded through an open auction. Works below this threshold can be more easily awarded through a restricted auction, where the buyer has some discretion in terms of who (not) to invite to bid. Our main result is that discretion increases the probability that the same firm wins repeatedly, and it does not deteriorate (and may improve) the procurement outcomes we observe. The effects of discretion persist when we repeat the analysis controlling for the geographical location, corruption, social capital, and judicial efficiency in the region of the public buyers running the auctions. Data and the online appendix are available at https://doi.org/10.1287/mnsc.2016.2628 . This paper was accepted by John List, behavioral economics.

Online peer-to-peer lending (P2P lending) has emerged as an appealing new channel of financing in recent years. A fundamental but largely unanswered question in this nascent industry is the choice of market mechanisms, i.e., how the supply and demand of funds are matched, and the terms (price) at which transactions will occur. Two of the most popular mechanisms are auctions (where the “crowd” determines the price of the transaction through an auction process) and posted prices (where the platform determines the price). While P2P lending platforms typically use one or the other, there is little systematic research on the implications of such choices for market participants, transaction outcomes, and social welfare. We address this question both theoretically and empirically. We first develop a game-theoretic model that yields empirically testable hypotheses, taking into account the incentive of the platform. We then test these hypotheses by exploiting a regime change from auctions to posted prices on one of the largest P2P lending platforms. Consistent with our hypotheses, we find that under platform-mandated posted prices, loans are funded with higher probability, but the preset interest rates are higher than borrowers’ starting interest rates and contract interest rates in auctions. More important, all else equal, loans funded under posted prices are more likely to default, thereby undermining lenders’ returns on investment and their surplus. Although platform-mandated posted prices may be faster in originating loans, auctions that rely on the crowd to discover prices are not necessarily inferior in terms of overall social welfare. This paper was accepted by Chris Forman, information systems .

We study the role of limited commitment in a standard auction environment. In each period, the seller can commit to an auction with a reserve price but not to future reserve prices. We characterize the set of equilibrium profits attainable for the seller as the period length vanishes. An immediate sale by efficient auction is optimal when there are at least three buyers. For many natural distributions two buyers is enough. Otherwise, we give conditions under which the maximal profit is attained through continuously declining reserve prices.

The presence of hypothetical bias (HB) associated with stated preference methods has garnered frequent attention in the broad literature trying to describe and understand human behavior, often seen in environmental valuation, marketing studies, transportation choices, medical research, and others. This study presents an updated meta-analysis to explore the source of HB and methods to mitigate it. While previous meta-analysis on this topic often involves a few dozen articles, this analysis includes 131 studies after reviewing over 500 published and unpublished articles. This enables the inclusion of several important factors that have not been investigated before. These include relatively recent willingness to pay elicitation methods such as choice experiments and the Turnbull lower bound estimator. Newly emerged HB reduction techniques such as consequentiality and certainty follow-up treatments are also included. For explanatory variables that have been examined in previous studies, this analysis does not always report consistent findings. In particular, holding everything constant and contrary to commonlyheld beliefs, the method of auction does not offer much reduction to HB compared to more conventional methods such as a referendum vote. However, choice experiment, cheap talk, consequentiality and certainty follow-up all significantly contributed to explaining and mitigating the magnitude of HB. These results help practitioners to understand HB’s presence and choose appropriate methods for amelioration. The framework established through this study also enables future analyses targeted at understanding variations built upon one or multiple HB mitigation techniques.

In online advertising markets, advertisers often purchase ad placements through bidding in repeated auctions based on realized viewer information. We study how budget-constrained advertisers may compete in such sequential auctions in the presence of uncertainty about future bidding opportunities and competition. We formulate this problem as a sequential game of incomplete information, in which bidders know neither their own valuation distribution nor the budgets and valuation distributions of their competitors. We introduce a family of practical bidding strategies we refer to as adaptive pacing strategies, in which advertisers adjust their bids according to the sample path of expenditures they exhibit, and analyze the performance of these strategies in different competitive settings. We establish the asymptotic optimality of these strategies when competitors’ bids are independent and identically distributed over auctions, but also when competing bids are arbitrary. When all the bidders adopt these strategies, we establish the convergence of the induced dynamics and characterize a regime (well motivated in the context of online advertising markets) under which these strategies constitute an approximate Nash equilibrium in dynamic strategies: the benefit from unilaterally deviating to other strategies, including ones with access to complete information, becomes negligible as the number of auctions and competitors grows large. This establishes a connection between regret minimization and market stability, by which advertisers can essentially follow approximate equilibrium bidding strategies that also ensure the best performance that can be guaranteed off equilibrium. This paper was accepted by Noah Gans, stochastic models and simulation.

Oligopoly models of price competition predict that strategic firms exercise market power and generate inefficiencies. However, heterogeneity in firms’ strategic ability also generates inefficiencies. We study the Texas electricity market where firms exhibit significant heterogeneity in how they deviate from Nash equilibrium bidding. These deviations, in turn, increase the cost of production. To explain this heterogeneity, we embed a cognitive hierarchy model into a structural model of bidding and estimate firms’ strategic sophistication. We find that firm size and manager education affect sophistication. Using the model, we show that mergers which increase sophistication can increase efficiency despite increasing market concentration.