Results 1  10
of
83
Consistent Specification Testing With Nuisance Parameters Present Only Under The Alternative
, 1995
"... . The nonparametric and the nuisance parameter approaches to consistently testing statistical models are both attempts to estimate topological measures of distance between a parametric and a nonparametric fit, and neither dominates in experiments. This topological unification allows us to greatly ex ..."
Abstract

Cited by 92 (13 self)
 Add to MetaCart
. The nonparametric and the nuisance parameter approaches to consistently testing statistical models are both attempts to estimate topological measures of distance between a parametric and a nonparametric fit, and neither dominates in experiments. This topological unification allows us to greatly extend the nuisance parameter approach. How and why the nuisance parameter approach works and how it can be extended bears closely on recent developments in artificial neural networks. Statistical content is provided by viewing specification tests with nuisance parameters as tests of hypotheses about Banachvalued random elements and applying the Banach Central Limit Theorem and Law of Iterated Logarithm, leading to simple procedures that can be used as a guide to when computationally more elaborate procedures may be warranted. 1. Introduction In testing whether or not a parametric statistical model is correctly specified, there are a number of apparently distinct approaches one might take. T...
Identification and Estimation in Highway Procurement Auctions under Unobserved Auction Heterogeneity
, 2004
"... The accurate assessment of participants’ private information may critically affect policy recommendations in auction markets. In many auction environments estimation of the private information distribution may be complicated by the presence of unobserved heterogeneity. This problem arises when some ..."
Abstract

Cited by 47 (1 self)
 Add to MetaCart
The accurate assessment of participants’ private information may critically affect policy recommendations in auction markets. In many auction environments estimation of the private information distribution may be complicated by the presence of unobserved heterogeneity. This problem arises when some of the information available to all bidders at the time of the auction is subsequently not observed by the researcher. This paper develops a semiparametric method that allows a researcher to uncover the distribution of bidders’ private information in a standard FirstPrice procurement auction when unobserved auction heterogeneity is present. Sufficient identification conditions are derived and a twostage estimation procedure to recover bidders’ private information is developed. The procedure is applied to data from Michigan highway procurement auctions and compared to the estimation procedures traditionally used in the context of highway procurement auctions. The estimation results suggest that ignoring unobserved auction heterogeneity is likely to result in substantially biased estimates and may lead to erroneous policy recommendations.
BROWNIAN DISTANCE COVARIANCE
"... Distance correlation is a new class of multivariate dependence coefficients applicable to random vectors of arbitrary and not necessarily equal dimension. Distance covariance and distance correlation are analogous to productmoment covariance and correlation, but generalize and extend these classica ..."
Abstract

Cited by 34 (1 self)
 Add to MetaCart
(Show Context)
Distance correlation is a new class of multivariate dependence coefficients applicable to random vectors of arbitrary and not necessarily equal dimension. Distance covariance and distance correlation are analogous to productmoment covariance and correlation, but generalize and extend these classical bivariate measures of dependence. Distance correlation characterizes independence: it is zero if and only if the random vectors are independent. The notion of covariance with respect to a stochastic process is introduced, and it is shown that population distance covariance coincides with the covariance with respect to Brownian motion; thus, both can be called Brownian distance covariance. In the bivariate case, Brownian covariance is the natural extension of productmoment covariance, as we obtain Pearson productmoment covariance by replacing the Brownian motion in the definition with identity. The corresponding statistic has an elegantly simple computing formula. Advantages of applying Brownian covariance and correlation vs the classical Pearson covariance and correlation are discussed and illustrated. 1. Introduction. The
Modeling Multivariate Distributions with Continuous Margins Using the copula R Package
 URL http: //www.jstatsoft.org/v34/i09
, 2010
"... The copulabased modeling of multivariate distributions with continuous margins is presented as a succession of rankbased tests: a multivariate test of randomness followed by a test of mutual independence and a series of goodnessoffit tests. All the tests under consideration are based on the empi ..."
Abstract

Cited by 27 (4 self)
 Add to MetaCart
The copulabased modeling of multivariate distributions with continuous margins is presented as a succession of rankbased tests: a multivariate test of randomness followed by a test of mutual independence and a series of goodnessoffit tests. All the tests under consideration are based on the empirical copula, which is a nonparametric rankbased estimator of the true unknown copula. The principles of the tests are recalled and their implementation in the copula R package is briefly described. Their use in the construction of a copula model from data is thoroughly illustrated on real insurance and financial data.
Structural Estimation of the Affiliated Private Value Auction Model
, 1999
"... This paper considers the structural estimation of the affiliated private value (APV) model in firstprice sealedbid auctions. The model allows for bidders' individual efficiencies and opportunity costs, while permiting dependence among bidders' private values through affiliation. We estab ..."
Abstract

Cited by 26 (1 self)
 Add to MetaCart
This paper considers the structural estimation of the affiliated private value (APV) model in firstprice sealedbid auctions. The model allows for bidders' individual efficiencies and opportunity costs, while permiting dependence among bidders' private values through affiliation. We establish the nonparametric identification of the APV model, characterize its theoretical restrictions, and propose a computationally convenient and consistent twostep nonparametric estimation procedure for estimating the joint private value distribution from observed bids. Using simulated bid data we provide a step by step guide on how to implement our procedure and show the good behavior of our estimator in small samples.
Asymmetry in FirstPrice Auctions with Affiliated Private Values
 Journal of Applied Econometrics
, 2001
"... The existence of collusion and heterogeneity across firms is known to introduce some asymmetry in bidding games. A major difficulty when considering asymmetric auctions is that the equilibrium strategies are solutions of an intractable system of differential equations. This paper proposes a simple m ..."
Abstract

Cited by 20 (2 self)
 Add to MetaCart
The existence of collusion and heterogeneity across firms is known to introduce some asymmetry in bidding games. A major difficulty when considering asymmetric auctions is that the equilibrium strategies are solutions of an intractable system of differential equations. This paper proposes a simple method for estimating asymmetric firstprice auctions within the affiliated private values (APV) paradigm. Specifically, we consider two types of bidders and derive the differential equations characterizing the Bayesian Nash equilibrium strategies. We show that these differential equations can be rewritten using the distribution of observed bids.
Empirical process of the squared residuals of an ARCH sequence
 The Annals of Statistics
, 2001
"... this paper we consider the ARCH(p) model defined by the equations y t = oe t " t # oe ..."
Abstract

Cited by 20 (5 self)
 Add to MetaCart
this paper we consider the ARCH(p) model defined by the equations y t = oe t " t # oe
Testing serial independence using the sample distribution function
 Journal of Time Series Analysis
, 1996
"... Abstract _ This paper presents and discusses a nonparametric test for detecting serial dependence. We consider a Cram~rv.Mises statistic based on the difference between the joint sample distribution and the product of the marginals. Exact critical values can be approximated from the asymptotic null ..."
Abstract

Cited by 18 (1 self)
 Add to MetaCart
Abstract _ This paper presents and discusses a nonparametric test for detecting serial dependence. We consider a Cram~rv.Mises statistic based on the difference between the joint sample distribution and the product of the marginals. Exact critical values can be approximated from the asymptotic null distribution or by resampling, randomly permuting the original series. The approximation based on resampling is more accurate and the corresponding test enjoys, like other bootstrap based procedures, excellent level accuracy, with level error of order 1'"312. A Monte Carlo experiment illustrates the test performance with small and moderate sample sizes. The paper also includes an application, testing the random walk hypothesis of exchange rate returns for several currencies. Key Words Serial independence test; Multivariate sample distribution; HoeffdingBlumKieferRosenblatt empirical process; Random permutation test; Ergodic alternatives.Departamento de Estadfstica y Econometrfa. Universidad Carlos III de Madrid. This article is based on research supported by the Spanish Direcci6n General de Investigaci6n Cientffica y Tecnica (DGICYT), reference number: PB92Q247. 1.
Statistical problems involving permutations with restricted positions
 IMS Lecture Notes Monogr. Ser
, 1999
"... The rich world of permutation tests can be supplemented by a variety of applications where only some permutations are permitted. We consider two examples: testing independence with truncated data and testing extrasensory perception with feedback. We review relevant literature on permanents, rook po ..."
Abstract

Cited by 18 (3 self)
 Add to MetaCart
The rich world of permutation tests can be supplemented by a variety of applications where only some permutations are permitted. We consider two examples: testing independence with truncated data and testing extrasensory perception with feedback. We review relevant literature on permanents, rook polynomials and complexity. The statistical applications call for new limit theorems. We prove a few of these and o er an approach to the rest via Stein's method. Tools from the proof of van der Waerden's permanent conjecture are applied to prove a natural monotonicity conjecture. 1
Consistent Nonparametric Tests of Independence
, 2009
"... Three simple and explicit procedures for testing the independence of two multidimensional random variables are described. Two of the associated test statistics (L1, loglikelihood) are defined when the empirical distribution of the variables is restricted to finite partitions. A third test statist ..."
Abstract

Cited by 16 (5 self)
 Add to MetaCart
Three simple and explicit procedures for testing the independence of two multidimensional random variables are described. Two of the associated test statistics (L1, loglikelihood) are defined when the empirical distribution of the variables is restricted to finite partitions. A third test statistic is defined as a kernelbased independence measure. Two kinds of tests are provided. Distributionfree strong consistent tests are derived on the basis of large deviation bounds on the test statistcs: these tests make almost surely no Type I or Type II error after a random sample size. Asymptotically αlevel tests are obtained from the limiting distribution of the test statistics. For the latter tests, the Type I error converges to a fixed nonzero value α, and the Type II error drops to zero, for increasing sample size. All tests reject the null hypothesis of independence if the test statistics become large. The performance of the tests is evaluated experimentally on benchmark data.