Identification and Inference in First-Price Auctions with Collusion

Identification and Inference in First-Price Auctions with Collusion

Author: Karl Edward Schurter

Publisher:

Published: 2017

Total Pages: 111

ISBN-13: 9780355077759

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This dissertation develops a method to detect collusion and estimate its effect on the seller's revenue in first-price auctions with independent, private valuations. The challenge is that collusion may be difficult to detect because colluders can use a simple and costless strategy to make their bids appear competitive. If the econometrician observes an exogenous shifter of the level of competition in the auction in addition to the winning bids, a statistical test for collusion by a given bidder can be formulated as a test of independence between the exogenous shifter and the valuations that rationalize its bids under the null hypothesis that it is not colluding. Simulations confirm this test performs well even when colluders attempt to disguise their behavior. I then adopt a multiple hypothesis testing framework to simultaneously test for collusion bidder by bidder. By controlling the probability of making one or more type I errors, the set of rejected hypotheses serves as a lower confidence bound on the set of colluders. To produce a lower confidence bound on the cost of collusion, I use consistent estimates of the bidders' valuation distributions to numerically solve for the seller's expected revenues in auctions with and without collusion. To provide an example of this identification strategy, I use exogenous variation in the reserve prices at British Columbia's timber auctions to estimate the extent of collusion in the years preceding a lumber trade dispute between the United States and Canada.


Handbook of Industrial Organization

Handbook of Industrial Organization

Author:

Publisher: Elsevier

Published: 2021-12-09

Total Pages: 784

ISBN-13: 0323988881

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Handbook of Industrial Organization Volume 4 highlights new advances in the field, with this new volume presenting interesting chapters. Each chapter is written by an international board of authors. Part of the renowned Handbooks in Economics series Chapters are contributed by some of the leading experts in their fields A source, reference and teaching supplement for industrial organizations or industrial economists


Collusion Detection in Auctions Using Machine Learning Algorithms

Collusion Detection in Auctions Using Machine Learning Algorithms

Author: Muskan Rathi

Publisher:

Published: 2023

Total Pages: 0

ISBN-13:

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This interdisciplinary honors thesis in Computational Economics investigates the different methods to compute auction equilibria and the impact of collusion on auction outcomes and the effectiveness of various machine learning algorithms in detecting collusive behavior using real-world datasets. We develop a program to analyze the Bayesian Nash equilibrium strategies of bidders in first-price and second-price auctions under scenarios with and without collusion. We further explore the performance of different machine learning algorithms, including Support Vector Machine (SVM), which demonstrates the highest F1 score in detecting collusion among the tested algorithms. The challenges associated with obtaining real-life auction data necessitate the use of synthetic data, providing a valuable resource for developing and validating anti-collusion algorithms in the future.This research contributes to a deeper understanding of auction dynamics and collusion, informing policymakers and regulators in designing robust auction mechanisms, implementing effective anti-collusion measures, and promoting fair and efficient market outcomes.


Inference for First-Price Auctions with Guerre, Perrigne, and Vuong's Estimator

Inference for First-Price Auctions with Guerre, Perrigne, and Vuong's Estimator

Author: Jun Ma

Publisher:

Published: 2016

Total Pages: 61

ISBN-13:

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In this paper, we focus on inference on the probability density function (PDF) of the valuations in the first-price sealed-bid auction models within the independent private value paradigm in the presence of auction-specific heterogeneity. We show the asymptotic normality of the two-step nonparametric estimator of Guerre et al. (2000, GPV), and propose an easily implementable and consistent estimator of the asymptotic variance of the two-step estimator. In addition, we prove the validity of the percentile bootstrap inference with the GPV estimator.


A Study of Collusion in First-Price Auctions

A Study of Collusion in First-Price Auctions

Author: Martin Pesendorfer

Publisher:

Published: 2001

Total Pages: 0

ISBN-13:

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This paper examines the bidding for school milk contracts in Florida and Texas during the 1980s. In both states firms were convicted of bid-rigging. The data and legal evidence suggest that the cartels in the two states allocate contracts in different ways: One cartel divides the market among members, while the other cartel also uses side payments to compensate that both forms of cartel agreements are almost optimal, provided the number of contracts is sufficiently large. In the auction the cartel bidder may face competition from non-cartel bidders. The presence of an optimal cartel induces an asymmetry in the auction. The selected cartel bidder is bidding as a representative of a group and has on average a lower cost than a non-cartel bidder. The data support the predicted equilibrium bidding behaviour in asymmetric auctions in accordance with optimal cartels.


Identification and Estimation of First-Price Auctions Under Ambiguity

Identification and Estimation of First-Price Auctions Under Ambiguity

Author: Serafin Grundl

Publisher:

Published: 2013

Total Pages: 0

ISBN-13:

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This paper studies identification and estimation of first-price auctions if the bidders face ambiguity about the distribution of valuations. Ambiguity is modeled using Gilboa and Schmeidler's (1989) Maxmin Expected Utility preferences. We exploit variation in the number of bidders to identify the essential primitives of the model. The identification result yields a closed form for the inverse bid function, which suggests a two-step estimation procedure. We study asymptotic and finite sample properties of the estimators. We find evidence of ambiguity in USFS timber auctions which leads to aggressive bidding for bidders with high valuations and has important implications for auction design.