Add to ORKGWe propose a quantile-based nonparametric approach to inference on the probability density function (PDF) of the private values in first-price sealed-bid auctions with independent private values. Our method of inference is based on a fully nonparametric kernel-based estimator of the quantiles and PDF of observable bids. Our estimator attains the optimal rate of Guerre, Perrigne, and Vuong (2000), and is also asymptotically normal with the appropriate choice of the bandwidth. As an application, we consider the problem of inference on the optimal reserve price
The first novelty of this paper is that we show global identification of the private values distribu...
Until now the optimal reserve price in the independent private value paradigm has been expressed as...
This dissertation is divided into three chapters. In Chapter 1, I propose a nonparametric estimator ...
We propose a quantile-based nonparametric approach to inference on the probability density function ...
We propose a quantile-based nonparametric approach to inference on the probability density function ...
We propose a quantile-based nonparametric approach to inference on the probability density function ...
In a classical model of the first-price sealed-bid auction with independent private values, we devel...
This paper proposes a semiparametric estimation procedure of the first-price auction model with risk...
The paper proposes a sieve quantile regression approach for first-price auctions with symmetric risk...
This paper proposes a semiparametric estimation procedure of the first-price auc-tion model with ris...
The first novelty of this paper is that we show global identification of the private values distribu...
PhDThe goal of this thesis is to propose a new quantile regression approach to identify and estimat...
Within the independent private-values paradigm, we demonstrate nonparametric identification of Dutch...
Monotonicity of the equilibrium bidding strategy is a key property of structural auction models. Tra...
We develop tests for common values at first-price sealed-bid auctions. Our tests are nonparametric, r...
The first novelty of this paper is that we show global identification of the private values distribu...
Until now the optimal reserve price in the independent private value paradigm has been expressed as...
This dissertation is divided into three chapters. In Chapter 1, I propose a nonparametric estimator ...
We propose a quantile-based nonparametric approach to inference on the probability density function ...
We propose a quantile-based nonparametric approach to inference on the probability density function ...
We propose a quantile-based nonparametric approach to inference on the probability density function ...
In a classical model of the first-price sealed-bid auction with independent private values, we devel...
This paper proposes a semiparametric estimation procedure of the first-price auction model with risk...
The paper proposes a sieve quantile regression approach for first-price auctions with symmetric risk...
This paper proposes a semiparametric estimation procedure of the first-price auc-tion model with ris...
The first novelty of this paper is that we show global identification of the private values distribu...
PhDThe goal of this thesis is to propose a new quantile regression approach to identify and estimat...
Within the independent private-values paradigm, we demonstrate nonparametric identification of Dutch...
Monotonicity of the equilibrium bidding strategy is a key property of structural auction models. Tra...
We develop tests for common values at first-price sealed-bid auctions. Our tests are nonparametric, r...
The first novelty of this paper is that we show global identification of the private values distribu...
Until now the optimal reserve price in the independent private value paradigm has been expressed as...
This dissertation is divided into three chapters. In Chapter 1, I propose a nonparametric estimator ...