nep-des New Economics Papers
on Economic Design
Issue of 2021‒05‒10
six papers chosen by
Alex Teytelboym
University of Oxford

  1. Centralized Matching with Incomplete Information By Fernandez, Marcelo; Rudov, Kirill; Yariv, Leeat
  2. Strong Substitutes: Structural Properties, and a New Algorithm for Competitive Equilibrium Prices By Baldwin, Elizabeth; Bichler, Martin; Fichtl, Maximilian; Klemperer, Paul
  3. Patent Auctions and Bidding Coalitions: Structuring the Sale of Club Goods By Asker, John; Baccara, Mariagiovanna; Lee, SangMok
  4. Credibility in Second-Price Auctions: An Experimental Test By Ahrash Dianat; Mikhail Freer
  5. Detecting bid-rigging coalitions in different countries and auction formats By David Imhof; Hannes Wallimann
  6. Optimal Transport of Information By Cieslak, Anna; Malamud, Semyon; Schrimpf, Andreas

  1. By: Fernandez, Marcelo; Rudov, Kirill; Yariv, Leeat
    Abstract: We study the impacts of incomplete information on centralized one-to-one matching markets. We focus on the commonly used Deferred Acceptance mechanism (Gale and Shapley, 1962). We show that many complete-information results are fragile to a small infusion of uncertainty.
    Keywords: Deferred acceptance; incomplete information; Matching
    JEL: C78 D49 D82
    Date: 2021–03
  2. By: Baldwin, Elizabeth; Bichler, Martin; Fichtl, Maximilian; Klemperer, Paul
    Abstract: We show the Strong Substitutes Product-Mix Auction (SSPMA) bidding language provides an intuitive and geometric interpretation of strong substitutes as Minkowski differences between sets that are easy to identify.We prove that competitive equilibrium prices for agents with strong substitutes preferences can be computed by minimizing the difference between two linear programs for the positive and the negative bids with suitably relaxed resource constraints. This also leads to a new algorithm for computing competitive equilibrium prices which is competitive with standard steepest descent algorithms in extensive experiments.
    Keywords: Algorithms; Auction Theory; Competitive Equilibrium; DC programming; Envy-free prices; Equilibrium computation; indivisible goods; product-mix auction; strong substitutes; Walrasian Equilibrium
    Date: 2021–02
  3. By: Asker, John; Baccara, Mariagiovanna; Lee, SangMok
    Abstract: Auctioneers of patents are observed to allow joint bidding by coalitions of buyers. These auctions are distinguished from standard ones by the patents being non-rivalrous, but still excludable, in consumption--that is, they are club goods. This affects the way coalitional bidding impacts auction performance. We study the implications of coalitions of bidders on second-price (or equivalently, ascending-price) auctions. Although the formation of coalitions per se can benefit the seller, we show that stable coalition profiles tend to consist of excessively large coalitions, to the detriment of both auction revenue and social welfare. We show that limiting the permitted coalition size increases efficiency and confers benefits on the seller. Lastly, we compare the revenues generated by patent auctions and multi-license auctions, and we find that the latter are superior in a large class of environments.
    Keywords: asymmetric auctions; Club goods; Intellectual Property; patents
    JEL: D44 D47 K1 L14
    Date: 2021–01
  4. By: Ahrash Dianat; Mikhail Freer
    Abstract: We provide the first direct test of how the credibility of an auction format affects bidding behavior and final outcomes. To do so, we conduct a series of laboratory experiments where the role of the seller is played by a human subject who receives the revenue from the auction and who (depending on the treatment) has agency to determine the outcome of the auction. We find that a large majority of bids in the non-credible version of the second-price auction lie between the theoretical benchmarks of the first-price auction and the credible second-price auction. While sellers in the non-credible second-price auction often break the rules of the auction and overcharge the winning bidder, they typically do not maximize revenue. We provide a behavioral explanation for our results based on incorrect beliefs (on the part of bidders) and aversion to rule-breaking (on the part of sellers), which is confirmed by revealed preference tests.
    Date: 2021–05
  5. By: David Imhof; Hannes Wallimann
    Abstract: We propose an original application of screening methods using machine learning to detect collusive groups of firms in procurement auctions. As a methodical innovation, we calculate coalition-based screens by forming coalitions of bidders in tenders to flag bid-rigging cartels. Using Swiss, Japanese and Italian procurement data, we investigate the effectiveness of our method in different countries and auction settings, in our cases first-price sealed-bid and mean-price sealed-bid auctions. We correctly classify 90\% of the collusive and competitive coalitions when applying four machine learning algorithms: lasso, support vector machine, random forest, and super learner ensemble method. Finally, we find that coalition-based screens for the variance and the uniformity of bids are in all the cases the most important predictors according the random forest.
    Date: 2021–05
  6. By: Cieslak, Anna; Malamud, Semyon; Schrimpf, Andreas
    Abstract: We study the general problem of Bayesian persuasion (optimal information design) with continuous actions and continuous state space in arbitrary dimensions. First, we show that with a finite signal space, the optimal information design is always given by a partition. Second, we take the limit of an infinite signal space and characterize the solution in terms of a Monge-Kantorovich optimal transport problem with an endogenous information transport cost. We use our novel approach to: 1. Derive necessary and sufficient conditions for optimality based on Bregman divergences for non-convex functions. 2. Compute exact bounds for the Hausdorff dimension of the support of an optimal policy. 3. Derive a non-linear, second-order partial differential equation whose solutions correspond to regular optimal policies. We illustrate the power of our approach by providing explicit solutions to several non-linear, multidimensional Bayesian persuasion problems.
    Keywords: Bayesian persuasion; information design; signalling
    JEL: D82 D83
    Date: 2021–02

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