Download or read book Nonparametric Estimation of First price Auctions written by Emmanuel Guerre and published by . This book was released on 1995 with total page 38 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Nonparametric Estimation of First price Auctions written by Emmanuel Guerre and published by . This book was released on 1995 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Nonparametric Identification and Semi nonparametric Estimation of First price Auctions written by Hosin Song and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Empirical Implementation of Nonparametric First Price Auction Models written by Daniel J. Henderson and published by . This book was released on 2011 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: Nonparametric estimators provide a flexible means of uncovering salient features of auction data. Although these estimators are popular in the literature, many key features necessary for proper implementation have yet to be uncovered. Here we provide several suggestions for nonparamteric estimation of first-price auction models. Specifically, we show how to impose monotonicity of the equilibrium bidding strategy; a key property of structural auction models not guaranteed in standard nonparametric estimation. We further develop methods for automatic bandwidth selection. Finally, we discuss how to impose monotonicity in auctions with differering number of bidders, reserve prices, and auction-specific characteristics. Finite sample performance is examined using simulated data as well as experimental auction data.

Download or read book Empirical implementation of nonparametric first price auction models written by Daniel J. Henderson and published by . This book was released on 2011 with total page 27 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: Nonparametric estimators provide a flexible means of uncovering salient features of auction data. Although these estimators are popular in the literature, many key features necessary for proper implementation have yet to be uncovered. Here we provide several suggestions for nonparamteric estimation of first-price auction models. Specifically, we show how to impose monotonicity of the equilibrium bidding strategy; a key property of structural auction models not guaranteed in standard nonparametric estimation. We further develop methods for automatic bandwidth selection. Finally, we discuss how to impose monotonicity in auctions with differering number of bidders, reserve prices, and auction-specific characteristics. Finite sample performance is examined using simulated data as well as experimental auction data.

Download or read book Nonparametric Identication and Structural Estimation of Auction Models written by Ming He and published by . This book was released on 2016 with total page 115 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation contributes to the structural auction literature in two different auction models, namely the pure common value model and the affiliated private value model. The goal of structural analysis of auction data is to recover the model primitives and to provide policy guidance for welfare analysis. In Chapter 1, we study identification in the first-price and the second-price sealed-bid auctions within the pure common value framework. In Chapter 2, we apply the identification results and estimation method in Chapter 1 to analyze the U.S. Outer Continental Shelf (OCS) wildcat auction data and provide policy guidance for welfare analysis. In Chapter 3, we develop identification and partial identification results for the first-price and the second-price sealed-bid auction models with affiliated private values and incomplete sets of bids. Chapter 1: In this chapter, we establish novel identification results for both the first-price and the second-price sealed-bid auction models within the pure common value framework. We show that the policy parameters, including the expected total welfare, the seller's expected revenue, and the bidders' expected surplus under any reserve price are identified for a general nonparametric class of latent joint distributions when the ex-post common value is unobserved. Moreover, we establish that these policy parameters are nonparametric identified without normalization assumption when the ex-post common value is observed. We propose a semiparametric estimation method and establish consistency of the estimator. Results from Monte Carlo experiments reveal good finite sample performance of the estimator. Chapter 2: In this chapter, we employ the identification strategy and estimation method in Chapter 1 to analyze data from the U.S. Outer Continental Shelf (OCS) wildcat auctions in the pure common value framework. We study the welfare implication of different counterfactual reserve prices, focusing on the cases with two and three bidders. The empirical results suggest that if the U.S. government had set reserve prices optimally using the newly-developed econometric method in Chapter 1, its expected revenue can be increased by around $34\%$ and $30\%$ for these two cases, respectively. Lastly, we compare our results with those estimated under the affiliated private value framework, and find that the estimated welfare curves under the two different frameworks are very different. Chapter 3: In this chapter, we address the identification issue in the first-price sealed-bid affiliated private value model when an incomplete set of bids is observed. In the simple case with symmetric bidders and non-binding reserve price, we establish identification or partial identification results in two scenarios of practical interest. First, when the two highest bids are observed, we achieve identification of the joint distribution function of private values by assuming the copula function of private values to be a nonparametric Archimedean copula with weak requirement. Second, when only the highest bid is observed, we establish partial identification for the quantile function of private value and several policy parameters by parameterizing the copula function. Further, we extend the identification/partial identification results to the cases with asymmetric bidders and/or binding reserve price. We also extend our identification/partial identification results to the second-price sealed-bid auction.

Download or read book Nonparametric Identification and Estimation of K Double Auctions written by Huihui Li and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation consists of two chapters on nonparametrically identifying and estimating the sealed-bid k-double auction models between single buyer and single seller.Chapter 1: Nonparametric Identification and Estimation of k-Double Auctions Using Bid DataThis chapter studies the nonparametric identification and estimation of double auctions with one buyer and one seller. This model assumes that both bidders submit their own sealed bids, and the transaction price is determined by a weighted average between the submitted bids when the buyers offer is higher than the sellers ask. It captures the bargaining process between two parties. Working within this double auction model, we first establish the nonparametric identification of both the buyers and the sellers private value distributions in two bid data scenarios; from the ideal situation in which all bids are available, to a more realistic setting in which only the transacted bids are available. Specifically, we can identify both private value distributions when all of the bids are observed. However, we can only partially identify the private value distributions on the support with positive (conditional) probability of trade when only the transacted bids are available in the data. Second, we estimate double auctions with bargaining using a two-step procedure that incorporates bias correction. We then show that our value density estimator achieves the same uniform convergence rate as Guerre, Perrigne, and Vuong (2000) for one-sided auctions. Monte Carlo experiments show that, in finite samples, our estimation procedure works well on the whole support and significantly reduces the large bias of the standard estimator without bias correction in both interior and boundary regions.Chapter 2: Nonparametric Identification of k-Double Auctions Using Price DataThis chapter studies the model identification problem of k-double auctions between one buyer and one seller when the transaction price, rather than the traders bids, can be observed. Given that only the price data is available, I explore an identification strategy that utilizes the double auctions with extreme pricing weight (k=1 or 0) and exclusive covariates that shift only one traders value distribution to identify both the buyers and the sellers value distributions nonparametrically. First, as each exclusive covariate can take at least two values, the buyers and the sellers value distributions are partially identified from the price distribution for k=1 or k=0. The identified set is sharp and can be easily computed. I provide a set of sufficient conditions under which the traders value distributions are point identified. Second, when the exclusive covariates are continuous, it is shown that the buyers and the sellers value distributions will be uniquely determined by a partial differential equation that only depends on the price distribution, provided that the value distributions are known for at least one value of the exclusive covariates.

Download or read book Are Estimates of Asymmetric First Price Auctions Credible Semi Nonparametric Analyses written by Kirill Chernomaz and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This online appendix contains the plots and supplemental descriptions for "Are Estimates of Asymmetric First-Price Auctions Credible? Semi- & Nonparametric Analyses."The paper "Are Estimates of Asymmetric First-Price Auctions Credible? Semi- & Nonparametric Analyses" to which this Supplement applies is available at the following URL: "http://ssrn.com/abstract=2394832" http://ssrn.com/abstract=2394832.

Download or read book Inference for First Price Auctions with Guerre Perrigne and Vuong s Estimator written by Jun Ma and published by . This book was released on 2016 with total page 61 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Nonparametric Tests for Common Values at First price Sealed Bid Auctions written by Philip A. Haile and published by . This book was released on 2003 with total page 41 pages. Available in PDF, EPUB and Kindle. Book excerpt: We develop tests for common values at first-price sealed-bid auctions. Our tests are nonparametric, require observation only of the bids submitted at each auction, and are based on the fact that the winner's curse' arises only in common values auctions. The tests build on recently developed methods for using observed bids to estimate each bidder's conditional expectation of the value of winning the auction. Equilibrium behavior implies that in a private values auction these expectations are invariant to the number of opponents each bidder faces, while with common values they are decreasing in the number of opponents. This distinction forms the basis of our tests. We consider both exogenous and endogenous variation in the number of bidders. Monte Carlo experiments show that our tests can perform well in samples of moderate sizes. We apply our tests to two different types of U.S. Forest Service timber auctions. For unit-price ( scaled') sales often argued to fit a private values model, our tests consistently fail to find evidence of common values. For lumpsum' sales, where a priori arguments for common values appear stronger, our tests yield mixed evidence against the private values hypothesis.

Download or read book Nonparametric Econometrics written by Qi Li and published by Princeton University Press. This book was released on 2023-07-18 with total page 768 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive, up-to-date textbook on nonparametric methods for students and researchers Until now, students and researchers in nonparametric and semiparametric statistics and econometrics have had to turn to the latest journal articles to keep pace with these emerging methods of economic analysis. Nonparametric Econometrics fills a major gap by gathering together the most up-to-date theory and techniques and presenting them in a remarkably straightforward and accessible format. The empirical tests, data, and exercises included in this textbook help make it the ideal introduction for graduate students and an indispensable resource for researchers. Nonparametric and semiparametric methods have attracted a great deal of attention from statisticians in recent decades. While the majority of existing books on the subject operate from the presumption that the underlying data is strictly continuous in nature, more often than not social scientists deal with categorical data—nominal and ordinal—in applied settings. The conventional nonparametric approach to dealing with the presence of discrete variables is acknowledged to be unsatisfactory. This book is tailored to the needs of applied econometricians and social scientists. Qi Li and Jeffrey Racine emphasize nonparametric techniques suited to the rich array of data types—continuous, nominal, and ordinal—within one coherent framework. They also emphasize the properties of nonparametric estimators in the presence of potentially irrelevant variables. Nonparametric Econometrics covers all the material necessary to understand and apply nonparametric methods for real-world problems.

Download or read book Quantile Based Nonparametric Inference for First Price Auctions written by Vadim Marmer and published by . This book was released on 2010 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: We 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 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.

Download or read book Nonparametric Estimation of an EBay Auction Model with an Unknown Number of Bidders written by and published by . This book was released on 2004 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Applied Nonparametric Econometrics written by Daniel J. Henderson and published by Cambridge University Press. This book was released on 2015-01-19 with total page 381 pages. Available in PDF, EPUB and Kindle. Book excerpt: The majority of empirical research in economics ignores the potential benefits of nonparametric methods, while the majority of advances in nonparametric theory ignores the problems faced in applied econometrics. This book helps bridge this gap between applied economists and theoretical nonparametric econometricians. It discusses in depth, and in terms that someone with only one year of graduate econometrics can understand, basic to advanced nonparametric methods. The analysis starts with density estimation and motivates the procedures through methods that should be familiar to the reader. It then moves on to kernel regression, estimation with discrete data, and advanced methods such as estimation with panel data and instrumental variables models. The book pays close attention to the issues that arise with programming, computing speed, and application. In each chapter, the methods discussed are applied to actual data, paying attention to presentation of results and potential pitfalls.

Download or read book Nonparametric identification and estimation of multi unit sequential oral ascending price auctions with asymmetric bidders written by Bjarne Brendstrup and published by . This book was released on 2004 with total page 35 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book A Nonparametric Test for Comparing Valuation Distributions in First Price Auctions written by Nianqing Liu and published by . This book was released on 2017 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This article proposes a nonparametric test for comparing valuation distributions in first-price auctions. Our test is motivated by the fact that two valuation distributions are the same if and only if their integrated quantile functions are the same. Our method avoids estimating unobserved valuations and does not require smooth estimation of bid density. We show that our test is consistent against all fixed alternatives and has nontrivial power against root-N local alternatives. Monte Carlo experiments show that our test performs well in finite samples. We implement our method on data from U.S. Forest Service timber auctions.

Download or read book Identification Estimation and Testing of Auction Models written by Jie Wei and published by . This book was released on 2014 with total page 73 pages. Available in PDF, EPUB and Kindle. Book excerpt: The third chapter shows nonparametric identification and estimation of private value distribution and density functions in first-price auctions with endogenous entry. In the model, symmetric bidders face a nontrivial entry cost and a binding reserve price. We identify latent structures by solving a two stage game, and estimate density functions (point-wisely) by using and comparing two different methods. Monte Carlo experiments show good performance of our estimators.