Emmanuel Guerre

Queen Mary University of London

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Nathalie Gimenes

École Nationale Supérieure des Mines de Paris

Pascal Lavergne

Toulouse School of Economics

Alain Guay

Université du Québec à Montréal

Isabelle Perrigne

Rice University

Quang Vuong

New York University

Hyungsik Roger Moon

University of Southern California

Eduardo Horta

Universidade Federal do Rio Grande do Sul

Jayeeta Bhattacharya

University of Southampton

Sandra Campo

Centre for Automation and Robotics

Marcelo Fernandes

Fundação Getulio Vargas

Cooperative Institutions

Shanghai University of Finance and Economics

Vanderbilt University

Tsinghua University

Federal Reserve Board of Governors

Cornell University

Université Paris Cité

Centre de Recherche en Économie et Statistique

National Bureau of Economic Research

University of Southern California

Centre for Research in Engineering Surface Technology

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Nonparametric Identification of Risk Aversion in First-Price Auctions Under Exclusion Restrictions

Econometrica (2009)

Emmanuel Guerre Isabelle Perrigne Quang Vuong

This paper studies the nonparametric identification of the first-price auction model with risk averse bidders within the private value paradigm. First, we show that the benchmark model is nonindentified from observed bids. We also derive the restrictions imposed by the model on observables and show that these restrictions are weak. Second, we establish the nonparametric identification of the bidders' utility function under exclusion restrictions. Our primary exclusion restriction takes the form of an exogenous bidders' participation, leading to a latent distribution of private values that is independent of the number of bidders. The key idea is to exploit the property that the bid distribution varies with the number of bidders while the private value distribution does not. We then extend these results to endogenous bidders' participation when the exclusion restriction takes the form of instruments that do not affect the bidders' private value distribution. Though derived for a benchmark model, our results extend to more general cases such as a binding reserve price, affiliated private values, and asymmetric bidders. Last, possible estimation methods are proposed.

Identification

Benchmark (surveying)

Structural estimation

Risk Aversion

Value (mathematics)

10.3982/ecta7028

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Citations (171)

Nonparametric identification of an interdependent value model with buyer covariates from first-price auction bids

arXiv (Cornell University) (2019)

Nathalie Gimenes Emmanuel Guerre

This paper introduces a version of the interdependent value model of Milgrom and Weber (1982), where the signals are given by an index gathering signal shifters observed by the econometrician and private ones specific to each bidders. The model primitives are shown to be nonparametrically identified from first-price auction bids under a testable mild rank condition. Identification holds for all possible signal values. This allows to consider a wide range of counterfactuals where this is important, as expected revenue in second-price auction. An estimation procedure is briefly discussed.

Identification

Value (mathematics)

10.48550/arxiv.1910.10646

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Citations (0)

Adaptive Consistent Unit Root Tests Based on Autoregressive Threshold Model

Frédérique Bec Alain Guay Emmanuel Guerre

This paper proposes SupWald tests from a threshold autoregressive model computed with an adaptive set of thresholds. Simple examples of adaptive threshold sets are given. A second contribution of the paper is a general asymptotic null limit theory when the threshold variable is a level variable. We obtain a pivotal null limiting distribution under some simple conditions for bounded or asymptotically unbounded thresholds. Our general approach is flexible enough to allow a choice of the auxiliary threshold model or of the threshold set involved in the test specifically designed for nonlinear stationary alternatives relevant for macroeconomic and financial topics involving arbitrage in presence of transaction costs. A Monte-Carlo study and an application to the interest rates spread for French, German, New-Zealander and US post-1980 monthly data illustrate the ability of the adaptive SupWald tests to reject unit-root when the ADF does not.

Threshold model

Unit root test

Null (SQL)

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Citations (0)

Nonparametric identification of an interdependent value model with buyer covariates from first-price auction bids

Journal of Econometrics (2020)

Nathalie Gimenes Emmanuel Guerre

Identification

Value (mathematics)

Rank (graph theory)

10.1016/j.jeconom.2019.12.018

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Citations (1)

The Limit Distribution of level Crossings of a Random Walk, and a Simple Unit Root Test

Econometric Theory (1996)

Peter Burridge Emmanuel Guerre

We derive the limit distribution of the number of crossings of a level by a random walk with continuously distributed increments, using a Brownian motion local time approximation. This complements the well-known result for the random walk on the integers. Use of the frequency of level crossings to test for a unit root is examined.

Brownian excursion

Root (linguistics)

10.1017/s026646660000699x

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Citations (29)

Semiparametric Quantile Models for Ascending Auctions With Asymmetric Bidders

Figshare (2021)

Jayeeta Bhattacharya Nathalie Gimenes Emmanuel Guerre

The article proposes a parsimonious and flexible semiparametric quantile regression specification for asymmetric bidders within the independent private value framework. Asymmetry is parameterized using powers of a parent private value distribution, which is generated by a quantile regression specification. As noted in Cantillon, this covers and extends models used for efficient collusion, joint bidding and mergers among homogeneous bidders. The specification can be estimated for ascending auctions using the winning bids and the winner’s identity. The estimation is in two stage. The asymmetry parameters are estimated from the winner’s identity using a simple maximum likelihood procedure. The parent quantile regression specification can be estimated using simple modifications of Gimenes. Specification testing procedures are also considered. A timber application reveals that weaker bidders have 30% less chances to win the auction than stronger ones. It is also found that increasing participation in an asymmetric ascending auction may not be as beneficial as using an optimal reserve price as would have been expected from a result of Bulow and Klemperer valid under symmetry.

Quantile

10.6084/m9.figshare.14135200

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Citations (0)

A Note on the Nonstationary Binary Choice Logit Model

SSRN Electronic Journal (2002)

Emmanuel Guerre Hyungsik Roger Moon

This paper derives the rate and the asymptotic distribution of the MLE of the parameter of a logit model with a nonstationary covariate when the true parameter is zero. The limit distribution of the t-statistic is also given.

Binary logit model

Mixed logit

10.2139/ssrn.299561

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Smoothing quantile regressions

RePEc: Research Papers in Economics (2017)

Marcelo Fernandes Emmanuel Guerre Eduardo Horta

We propose to smooth the entire objective function, rather than only the check function, in a linear quantile regression context. Not only does the resulting smoothed quantile regression estimator yield a lower mean squared error and a more accurate Bahadur-Kiefer representation than the standard estimator, but it is also asymptotically differentiable. We exploit the latter to propose a quantile density estimator that does not suffer from the curse of dimensionality. This means estimating the conditional density function without worrying about the dimension of the covariate vector. It also allows for two-stage efficient quantile regression estimation. Our asymptotic theory holds uniformly with respect to the bandwidth and quantile level. Finally, we propose a rule of thumb for choosing the smoothing bandwidth that should approximate well the optimal bandwidth. Simulations confirm that our smoothed quantile regression estimator indeed performs very well in finite samples.

Quantile

Quantile regression

Smoothing

Quantile function

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Citations (0)

Nonparametric Identification of First-Price Auction with Unobserved Competition: A Density Discontinuity Framework

arXiv (Cornell University) (2019)

Emmanuel Guerre Yao Luo

We consider nonparametric identification of independent private value first-price auction models, in which the analyst only observes winning bids. Our benchmark model assumes an exogenous number of bidders N. We show that, if the bidders observe N, the resulting discontinuities in the winning bid density can be used to identify the distribution of N. The private value distribution can be nonparametrically identified in a second step. This extends, under testable identification conditions, to the case where N is a number of potential buyers, who bid with some unknown probability. Identification also holds in presence of additive unobserved heterogeneity drawn from some parametric distributions. A last class of extensions deals with cartels which can change size across auctions due to varying bidder cartel membership. Identification still holds if the econometrician observes winner identities and winning bids, provided a (unknown) bidder is always a cartel member. The cartel participation probabilities of other bidders can also be identified. An application to USFS timber auction data illustrates the usefulness of discontinuities to analyze bidder participation.

Identification

Cartel

Bid shading

10.48550/arxiv.1908.05476

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Citations (3)

Quantile regression methods for first-price auctions

arXiv (Cornell University) (2019)

Nathalie Gimenes Emmanuel Guerre

The paper proposes a quantile-regression inference framework for first-price auctions with symmetric risk-neutral bidders under the independent private-value paradigm. It is first shown that a private-value quantile regression generates a quantile regression for the bids. The private-value quantile regression can be easily estimated from the bid quantile regression and its derivative with respect to the quantile level. This also allows to test for various specification or exogeneity null hypothesis using the observed bids in a simple way. A new local polynomial technique is proposed to estimate the latter over the whole quantile level interval. Plug-in estimation of functionals is also considered, as needed for the expected revenue or the case of CRRA risk-averse bidders, which is amenable to our framework. A quantile-regression analysis to USFS timber is found more appropriate than the homogenized-bid methodology and illustrates the contribution of each explanatory variables to the private-value distribution. Linear interactive sieve extensions are proposed and studied in the Appendices.

Quantile regression

Quantile

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Citations (2)