nep-des New Economics Papers
on Economic Design
Issue of 2021‒10‒25
six papers chosen by
Guillaume Haeringer, Baruch College and Alex Teytelboym, University of Oxford


  1. Auction design with ambiguity: Optimality of the first-price and all-pay auctions By Sosung Baik; Sung-Ha Hwang
  2. Getting auctions for transportation capacity to roll By Cherbonnier, Frédéric; Salant, David; Van Der Straeten, Karine
  3. Basic Bidding Formats: Characteristics and Differences By Fritz Helmedag
  4. Dynamic Bipartite Matching Market with Arrivals and Departures By Naonori Kakimura; Donghao Zhu
  5. A Core-partition solution for coalitional rankings with a variable population domain By Sylvain Béal; Sylvain Ferrières; Philippe Solal
  6. Persuasion by Dimension Reduction By Semyon Malamud; Andreas Schrimpf

  1. By: Sosung Baik; Sung-Ha Hwang
    Abstract: We study the optimal auction design problem when bidders' preferences follow the maxmin expected utility model. We suppose that each bidder's set of priors consists of beliefs close to the seller's belief, where "closeness" is defined by a divergence. For a given allocation rule, we identify a class of optimal transfer candidates, named the win-lose dependent transfers, with the following property: each type of bidder's transfer conditional on winning or losing is independent of the competitor's type report. Our result reduces the infinite-dimensional optimal transfer problem to a two-dimensional optimization problem. By solving the reduced problem, we find that: (i) among efficient mechanisms with no premiums for losers, the first-price auction is optimal; and, (ii) among efficient winner-favored mechanisms where each bidder pays smaller amounts when she wins than loses: the all-pay auction is optimal. Under a simplifying assumption, these two auctions remain optimal under the endogenous allocation rule.
    Date: 2021–10
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2110.08563&r=
  2. By: Cherbonnier, Frédéric; Salant, David; Van Der Straeten, Karine
    Abstract: An auction of transport capacity can only roll forward if competitive bidders show up at the start. To characterize bidding behavior, we develop a model with a single incumbent potentially in competition with a single challenger; should the challenger obtain slots, the two firms will engage post-auction in capacity con-strained price competition. We show how the auction structure, that is, whether the slots are auctioned one at a time, and if not, how they are packaged affects the outcome. Our key finding is that the division of the available slots into tranches can significantly affect the outcome of the auction. Absent any set-asides, a single auc-tion for all the slots will almost certainly be won by an incumbent. Set-asides can enable the challenger to win one or more packages of slots. Further, when the slots are split up, and auctioned one-at-a-time or in batches, a challenger’s prospects improve significantly, and no longer rely only on set-asides. The implications of our analysis are (a) the outcome will depend crucially on auction design decisions,(b) set-asides for challengers can help and (c) an auction that results in successful entry by challengers may result in reduced auction revenues and industry profits.
    Keywords: Rail transportation; Open access; Auctions; Regulation
    JEL: D40 L12 L13 L40 L92
    Date: 2021–10–18
    URL: http://d.repec.org/n?u=RePEc:tse:wpaper:126117&r=
  3. By: Fritz Helmedag (Department of Economics, Chemnitz University of Technology)
    Abstract: In standard auction theory, the 'revenue equivalence theorem' asserts that the outcomes of the elementary allocation methods coincide. However, bidding processes differ fundamentally with regard to the decision situation of the participants: Is it at all imperative to take into consideration the number of competitors ('stochastic' strategy) or not ('deterministic' course of action)? Furthermore, established auction theory neglects the operating modes of procurement alternatives under uncertainty. Apart from the lacking knowledge how many rivals have to be beaten, tenderers regularly are ignorant of the buyer's reserve price. Then it is even more tentative to calculate an offer based on probability theory. Consequently, the suppliers' propensity to collude increases.
    Keywords: Auctions, Tendering, Strategic Bidding
    JEL: D44
    Date: 2021–10
    URL: http://d.repec.org/n?u=RePEc:tch:wpaper:cep051&r=
  4. By: Naonori Kakimura; Donghao Zhu
    Abstract: In this paper, we study a matching market model on a bipartite network where agents on each side arrive and depart stochastically by a Poisson process. For such a dynamic model, we design a mechanism that decides not only which agents to match, but also when to match them, to minimize the expected number of unmatched agents. The main contribution of this paper is to achieve theoretical bounds on the performance of local mechanisms with different timing properties. We show that an algorithm that waits to thicken the market, called the $\textit{Patient}$ algorithm, is exponentially better than the $\textit{Greedy}$ algorithm, i.e., an algorithm that matches agents greedily. This means that waiting has substantial benefits on maximizing a matching over a bipartite network. We remark that the Patient algorithm requires the planner to identify agents who are about to leave the market, and, under the requirement, the Patient algorithm is shown to be an optimal algorithm. We also show that, without the requirement, the Greedy algorithm is almost optimal. In addition, we consider the $\textit{1-sided algorithms}$ where only an agent on one side can attempt to match. This models a practical matching market such as a freight exchange market and a labor market where only agents on one side can make a decision. For this setting, we prove that the Greedy and Patient algorithms admit the same performance, that is, waiting to thicken the market is not valuable. This conclusion is in contrast to the case where agents on both sides can make a decision and the non-bipartite case by [Akbarpour et al.,$~\textit{Journal of Political Economy}$, 2020].
    Date: 2021–10
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2110.10824&r=
  5. By: Sylvain Béal (CRESE EA3190, Univ. Bourgogne Franche-Comté, F-25000 Besançon, France); Sylvain Ferrières (Université de Saint-Etienne, CNRS UMR 5824 GATE Lyon Saint-Etienne, France); Philippe Solal (Université de Saint-Etienne, CNRS UMR 5824 GATE Lyon Saint-Etienne, France)
    Abstract: A coalitional ranking problem is described by a weak order on the set of nonempty coalitions of a given agent set. A social ranking is a weak order on the set of agents. We consider social rankings that are consistent with stable/core partitions. A partition is stable if there is no coalition better ranked in the coalitional ranking than the rank of the cell of each of its members in the partition. The core-partition social ranking solution assigns to each coalitional ranking problem the set of social rankings such that there is a core-partition satisfying the following condition: a first agent gets a higer rank than a second agent if and only if the cell to which the first agent belongs is better ranked in the coalitional ranking than the cell to which the second agent belongs in the partition. We provide an axiomatic characterization of the core-partition social ranking and an algorithm to compute the associated social rankings.
    Keywords: Coalitional ranking problem, social ranking, core partition, axiomatic characterization, hedonic games
    JEL: C71
    Date: 2021–10
    URL: http://d.repec.org/n?u=RePEc:crb:wpaper:2021-06&r=
  6. By: Semyon Malamud; Andreas Schrimpf
    Abstract: How should an agent (the sender) observing multi-dimensional data (the state vector) persuade another agent to take the desired action? We show that it is always optimal for the sender to perform a (non-linear) dimension reduction by projecting the state vector onto a lower-dimensional object that we call the "optimal information manifold." We characterize geometric properties of this manifold and link them to the sender's preferences. Optimal policy splits information into "good" and "bad" components. When the sender's marginal utility is linear, revealing the full magnitude of good information is always optimal. In contrast, with concave marginal utility, optimal information design conceals the extreme realizations of good information and only reveals its direction (sign). We illustrate these effects by explicitly solving several multi-dimensional Bayesian persuasion problems.
    Date: 2021–10
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2110.08884&r=

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