nep-des New Economics Papers
on Economic Design
Issue of 2018‒04‒09
four papers chosen by
Guillaume Haeringer, Baruch College and Alex Teytelboym, University of Oxford

  1. Dynamic Refugee Matching By Andersson, Tommy; Ehlers, Lars; Martinello, Alessandro
  2. A Note on Manipulability in School Choice with Reciprocal Preferences By Claus-Jochen Haake; Nadja Stroh-Maraun
  3. Do Better Informed Investors Always Do Better? A Buyback Puzzle By Glenn Boyle; Gerald Ward
  4. Number of bidders and the winner’s curse By Ronald Peeters; Anastas P. Tenev

  1. By: Andersson, Tommy (Department of Economics, Lund University); Ehlers, Lars (Département de sciences économiques, Université de Montréal); Martinello, Alessandro (Department of Economics, Lund University)
    Abstract: Asylum seekers are often assigned to a locality in their host country directly upon arrival based on some type of uninformed dynamic matching system which does not take the background of the asylum seekers into consideration. This paper proposes an informed, intuitive, easy-to-implement and computationally efficient dynamic mechanism for matching asylum seekers to localities. This mechanism can be adopted in any dynamic refugee matching problem given locality-specific quotas and that asylum seekers can be classified into specific types. We demonstrate that any matching selected by the proposed mechanism is Pareto efficient and that envy between localities is bounded by a single asylum seeker. Via simulation, we evaluate the performance of the proposed mechanism in settings that resemble the US and the Swedish situations, and show that our mechanism outperforms uninformed mechanisms even in presence of severe misclassification error in the estimation of asylum seeker types.
    Keywords: forced migration; market design; refugee matching; dynamics; envy; efficiency
    JEL: C71 C78 D71 D78 F22
    Date: 2018–03–27
  2. By: Claus-Jochen Haake (Paderborn University); Nadja Stroh-Maraun (Paderborn University)
    Abstract: We show that the Boston school choice mechanism (BM), the student proposing deferred acceptance algorithm (DA) and the top trading cycles algorithm (TTC) generate the same outcome when the colleges’ priorities are modified according to students’ preferences in a “first preferences first” manner. This outcome coincides with the BM outcome under original priorities. As a result, the DA and TTC mechanism that are non-manipulable under original priorities become vulnerable to strategic behavior.
    Date: 2018–01
  3. By: Glenn Boyle (University of Canterbury); Gerald Ward
    Abstract: We explore the value of private investment information using data from a singular source: auctions of yearling racehorses. Horse breeders possess superior information about their own horses and have strong financial incentives to buy the best of these back at auction. However, those they repurchase subsequently perform significantly worse on average, earning 30% less at the racetrack than horses purchased by out-siders. Moreover, this underperformance is concentrated in male horses, despite these being purchased exclusively for racing purposes. These puzzling findings can-not be explained by differences in horse risk or breeder abilities, or by non-financial objectives, or by behavioral or selection biases.
    Keywords: Auctions; racehorses; buybacks
    JEL: G02 G11 G14 L83 D44
    Date: 2018–04–01
  4. By: Ronald Peeters (Department of Economics, University of Otago, New Zealand); Anastas P. Tenev (Department of Economics, Maastricht University)
    Abstract: Within an affiliated value auction setting, we study the relationship between the number of bidders and the winner’s curse in terms of its occurrence and its expected harm. From a design perspective, we find that both the number of bidders and the level of affiliation are instrumental when choosing an auction format and whether to encourage or discourage bidder participation.
    Keywords: Winner’s curse; number of bidders; affiliated value auctions
    JEL: D44 D82 H57
    Date: 2018–01

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