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 Supplement to Quantile Based Nonparametric Inference for First Price Auctions written by Vadim Marmer and published by . This book was released on 2009 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper contains supplemental materials for Marmer and Shneyerov (2009) "Quantile-Based Nonparametric Inference for First-Price Auctions."
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 Structural Econometric Modeling in Industrial Organization and Quantitative Marketing written by Ali Hortaçsu and published by Princeton University Press. This book was released on 2023-10-24 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: A concise and rigorous introduction to widely used approaches in structural econometric modeling Structural econometric modeling specifies the structure of an economic model and estimates the model’s parameters from real-world data. Structural econometric modeling enables better economic theory–based predictions and policy counterfactuals. This book offers a primer on recent developments in these modeling techniques, which are used widely in empirical industrial organization, quantitative marketing, and related fields. It covers such topics as discrete choice modeling, demand modes, estimation of the firm entry models with strategic interactions, consumer search, and theory/empirics of auctions. The book makes highly technical material accessible to graduate students, describing key insights succinctly but without sacrificing rigor. • Concise overview of the most widely used structural econometric models • Rigorous and systematic treatment of the topics, emphasizing key insights • Coverage of demand estimation, estimation of static and dynamic game theoretic models, consumer search, and auctions • Focus on econometric models while providing concise reviews of relevant theoretical models
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 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 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 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 A Simple Nonparametric Approach for Estimation and Inference of Conditional Quantile Functions written by Zheng Fang and published by . This book was released on 2018 with total page 53 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper we present a new nonparametric method for estimating a conditional quantile function and develop its weak convergence theory. The proposed estimator is computationally easy-to-implement, and automatically ensures quantile monotonicity by construction. For inference, we propose to use a residual bootstrap method. The Monte Carlo simulations show that our new estimator compares well with the checkfunction-based estimator in terms of estimation mean squared error (MSE), and the bootstrap confidence bands give adequate coverage probabilities. An empirical example considering a dataset from Canadian high school graduate earnings illustrates that the proposed method delivers a more reasonable quantile estimate than the check-function counterpart.
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 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 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 Robust Inference in First price Auctions written by Serafin Grundl and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
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 Shape restricted Problems in Econometrics written by Brandon Scott Reeves and published by . This book was released on 2019 with total page 201 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many econometric models restrict the set of parameters consistent with the underlying model theory or observable data. These restrictions may come from a priori beliefs about the model-such as monotonicity of demand curves-or from statistical or economic theory-such as non-crossing quantile functions or first-price auction models which restrict the set of observable bids. When these restrictions are binding or close to binding, standard asymptotic theory provides poor approximations to the finite-sample behavior of the restricted estimator. This dissertation concerns the construction of estimators and inference procedures for shape-restricted models. The first chapter proposes a uniformly valid inference method for a parameter vector satisfying certain shape-restrictions. The method applies generally to a range of finite dimensional and nonparametric problems, such as regressions or instrumental variable estimation, to both kernel or series estimators, and to many shape restrictions. The bands are asymptotically equivalent to standard, unrestricted confidence bands if the true parameter strictly satisfies all shape restrictions, but they can be much smaller if some of the shape restrictions are binding or close to binding. We illustrate these sizable width gains in Monte Carlo simulations and in an empirical application. The second chapter proposes a general method for constructing asymptotically normally distributed estimators from shape-restricted estimators which applies in both parametric and nonparametric settings. Due to the asymptotically normality, our estimator avoids the non-standard distribution of shape-restricted estimators. Consequently, our resulting confidence sets are easy to obtain and simple to report. As our main application of interest, we provide low-level assumptions under which our method applies to the estimation of first-price auctions with independent, private valuations. In this context, our method provides the first inference result in the literature which allows for the construction of confidence sets for a general class of functions. Simulations suggest our estimator and inference procedure perform well, as our confidence sets have empirical coverage near nominal levels and the mean squared error of our estimator compares favorably against alternative estimators in the literature. We demonstrate the empirical usefulness of our approach in an application to timber auctions conducted by the US Forest Service.
Download or read book Nonparametric Identification of First Price Auctions With Non Separable Unobserved Heterogeneity written by David McAdams 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 novel methodology for nonparametric identification of first-price auction models with independent private values, which allows for one-dimensional auction-specific unobserved heterogeneity, based on recent results from the econometric literature on nonclassical measurement error in Hu and Schennach (2008). Our approach can accommodate a wide variety of applications in which some location of the conditional distribution of bids (e.g. min or max of the support, mean, etc.) is increasing in the unobserved heterogeneity. This includes settings in which the econometrician fails to observe the reserve price, the cost of bidding, the number of bidders, or some factor (“quality”) with a non-linear effect on bidder values.
Download or read book Applied Nonparametric Econometrics written by Daniel J. Henderson and published by Cambridge University Press. This book was released on 2015-01-12 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 ignore 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.
