eprintid: 10072972
rev_number: 22
eprint_status: archive
userid: 608
dir: disk0/10/07/29/72
datestamp: 2019-06-27 17:32:30
lastmod: 2020-06-01 06:10:30
status_changed: 2019-06-27 17:32:30
type: thesis
metadata_visibility: show
creators_name: Marra, Marleen Renske
title: Essays on the structural analysis of auction markets
ispublished: In preparation
divisions: UCL
divisions: A01
divisions: B03
divisions: C03
divisions: F24
note: Copyright © The Author 2019. Original content in this thesis is licensed under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) Licence (https://creativecommons.org/licenses/by/4.0/). Any third-party copyright material present remains the property of its respective owner(s) and is licensed under its existing terms. Access may initially be restricted at the author’s request.
abstract: This thesis presents new results that make significant contributions to the structural analysis of auction markets. One chapter develops a methodology to study welfare and revenue impacts of fees in auction platforms. The impacts of fees are theoretically ambiguous as the platform faces a ``two-sided market'' with network effects; increased seller entry raises its value to bidders, and vice versa. The chapter develops and solves a structural model with endogenous bidder and seller entry, seller selection, and costly listing inspection. It also exploits an original dataset with 15 months of wine auctions to study these issues. Relevant model primitives are shown to be identified in the auction platform model from observed variation in reserve prices, transaction prices, and the number of bidders. The proposed estimation strategy combines methods from the auction and discrete choice literatures. Model estimates reveal significant network effects, and it is shown with counterfactual policy simulations that fee structures that subsidize bidders make all parties better off. Implications for competition policy are discussed as well. Another chapter focuses on nonparametric identification in English auctions with absentee bidding, in which the number of bidders is unknown. The chapter exploits additional identifying variation from drop-out values of absentee bidders and develops a novel nonparametric identification approach based on the stochastic spacing of order statistics. In combination with a shape restriction the method delivers bounds on both the latent valuation distribution and expected consumer surplus. The value of the proposed method is highlighted by showing that it identifies informative bounds on policy-relevant model primitives in a sample of traditional English auctions collected from the online bidding portal of Sotheby's, which does not contain the number of bidders and their final bids. The thesis ends by providing directions for future research.
date: 2019-05-28
date_type: published
oa_status: green
full_text_type: other
thesis_class: doctoral_open
thesis_award: Ph.D
language: eng
thesis_view: UCL_Thesis
primo: open
primo_central: open_green
verified: verified_manual
elements_id: 1651430
lyricists_name: Marra, Marleen
lyricists_id: MARRA91
actors_name: Marra, Marleen
actors_id: MARRA91
actors_role: owner
full_text_status: public
pages: 158
event_title: UCL (University College London)
institution: UCL (University College London)
department: Economics
thesis_type: Doctoral
editors_name: Chesher, A
editors_name: Nesheim, L
citation:        Marra, Marleen Renske;      (2019)    Essays on the structural analysis of auction markets.                   Doctoral thesis  (Ph.D), UCL (University College London).     Green open access   
 
document_url: https://discovery.ucl.ac.uk/id/eprint/10072972/1/Marra%20dissertation%20final%20copy.pdf