nep-des New Economics Papers
on Economic Design
Issue of 2020‒01‒27
five papers chosen by
Alex Teytelboym
University of Oxford

  1. Matching Platforms By Masaki Aoyagi; Seung Han Yoo
  2. Robust Bidding and Revenue in Descending Price Auctions By Sarah Auster; Christian Kellner
  3. Incumbent and entrant bidding in scoring rule auctions: A study on Italian canteen services By Riccardo Camboni; Paola Valbonesi
  4. Delegating Learning By Juan Escobar; Qiaoxi Zhang
  5. On the role of electricity storage in capacity remuneration mechanisms By Fraunholz, Christoph; Keles, Dogan; Fichtner, Wolf

  1. By: Masaki Aoyagi; Seung Han Yoo
    Abstract: A platform matches agents from two sides of a market to create a trading opportunity between them. The agents subscribe to the platform by paying subscription fees which are contingent on their reported private types, and then engage in strategic interactions with their matched partner(s). A matching mechanism of the platform specifies the subscription fees as well as the matching rule which determines the probability that each type of agent on one side is matched with each type on the other side. We characterize optimal matching mechanisms which induce truthful reporting from the agents and maximize the subscription revenue. We show that the optimal mechanisms for a one-to-one trading platform match do not necessarily entail assortative matching, and may employ an alternative matching rule that maximizes the extraction of informational rents of the higher type. We then study an auction platform that matches each seller to two agents, and show that the optimal mechanism entails the combination of negative and positive assortative matching.
    Date: 2019–12
    URL: http://d.repec.org/n?u=RePEc:dpr:wpaper:1072&r=all
  2. By: Sarah Auster; Christian Kellner
    Abstract: We study the properties of Dutch auctions in an independent private value setting, where bidders face uncertainty over the type distribution of their opponents and evaluate their payoffs by the worst case from a set of probabilistic scenarios. In contrast to static auction formats, participants in the Dutch auction gradually learn about the valuations of other bidders. We show that the transmitted information can lead to changes in the worst-case distribution and thereby shift a bidder’s payoff maximizing exit price over time. We characterise the equilibrium bidding function in this environment and show that the arriving information leads bidders to exit earlier at higher prices. As a result, the Dutch auction systematically generates more revenue than the first-price auction.
    Keywords: Auctions, Ambiguity, Consistent Planning
    Date: 2020–01
    URL: http://d.repec.org/n?u=RePEc:bon:boncrc:crctr224_2020_146&r=all
  3. By: Riccardo Camboni (DSEA, University of Padova); Paola Valbonesi (DSEA, University of Padova and HSE-NRU, Moscow)
    Abstract: We empirically investigate incumbents' and entrants' bids on an original dataset of 192 scoring rule auctions for canteen services in Italy. Our findings show that winning rebates are lower (i.e., prices paid by the public buyer are higher) when the contract is awarded to the incumbent supplier. This result is not explained by the observable characteristics of the auction and service awarded. We then develop a simple theoretical model that shows that such a result is consistent with a setting in which the buyer distorts the scoring function to increase the probability that the incumbent wins the auction at the cost of a higher purchasing price.
    Keywords: Scoring Rule Auctions, Procurement, Incumbent and Entrant, Auction design
    JEL: D44 D47 H57 L88
    Date: 2019–11
    URL: http://d.repec.org/n?u=RePEc:pad:wpaper:0242&r=all
  4. By: Juan Escobar; Qiaoxi Zhang
    Abstract: Learning is crucial to organizational decision making but often needs be delegated. We examine a dynamic delegation problem where a principal decides on a project with uncertain profitability. A biased agent, who is initially as uninformed as the principal, privately learns the profitability over time and communicates to the principal. We formulate learning delegation as a dynamic mechanism design problem and characterize the optimal delegation scheme. We show that private learning gives rise to the tradeoff between how much information to acquire and how promptly it is reflected in the decision. We discuss implications on learning delegation for distinct organizations. Key words: cheap talk.,commitment,deadlines,delays,delegation,private learning
    Date: 2019
    URL: http://d.repec.org/n?u=RePEc:edj:ceauch:347&r=all
  5. By: Fraunholz, Christoph; Keles, Dogan; Fichtner, Wolf
    Abstract: In electricity markets around the world, the substantial increase of intermittent renewable electricity generation has intensified concerns about generation adequacy, ultimately driving the implementation of capacity remuneration mechanisms. Although formally technology-neutral, substantial barriers often exist in these mechanisms for non-conventional capacity such as electricity storage. In this article, we provide a rigorous theoretical discussion on design parameters and show that the concrete design of a capacity remuneration mechanism always creates a bias towards one technology or the other. In particular, we can identify the bundling of capacity auctions with call options and the definition of the storage capacity credit as essential drivers affecting the future technology mix as well as generation adequacy. In order to illustrate and confirm our theoretical findings, we apply an agent-based electricity market model and run a number of simulations. Our results show that electricity storage has a capacity value and should therefore be allowed to participate in any capacity remuneration mechanism. Moreover, we find the implementation of a capacity remuneration mechanism with call options and a strike price to increase the competitiveness of storages against conventional power plants. However, determining the amount of firm capacity an electricity storage unit can provide remains a challenging task.
    Date: 2019
    URL: http://d.repec.org/n?u=RePEc:zbw:kitiip:37&r=all

This nep-des issue is ©2020 by Alex Teytelboym. It is provided as is without any express or implied warranty. It may be freely redistributed in whole or in part for any purpose. If distributed in part, please include this notice.
General information on the NEP project can be found at http://nep.repec.org. For comments please write to the director of NEP, Marco Novarese at <director@nep.repec.org>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.