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Asymptotic Optimality of Generalized C_{L}, Cross-Validation, and Generalized Cross-Validation in Regression with Heteroskedastic Errors

Andrews, Donald W.K. - Cowles Foundation for Research in Economics, Yale University - 1989

The problem considered here is that of using a data-driven procedure to select a good estimate from a class of linear estimates indexed by a discrete parameter. In contrast to other papers on this subject, we consider models with heteroskedastic errors. The results apply to model selection...

Persistent link: https://www.econbiz.de/10005634704

Invalidity of the Bootstrap and the m Out of n Bootstrap for Interval Endpoints Defined by Moment Inequalities

Andrews, Donald W.K.; Han, Sukjin - Cowles Foundation for Research in Economics, Yale University - 2008

bootstrap, m out of n bootstrap, and subsampling do lead to uniformly asymptotically valid confidence sets in moment inequality …This paper analyzes the finite-sample and asymptotic properties of several bootstrap and m out of n bootstrap methods … the bootstrap nor the m out of n bootstrap is valid in finite samples or in a uniform asymptotic sense in general when …

Persistent link: https://www.econbiz.de/10005039556

An Improved Bootstrap Test of Stochastic Dominance

Linton, Oliver; Song, Kyungchul; Whang, Yoon-Jae - Cowles Foundation for Research in Economics, Yale University - 2009

We propose a new method of testing stochastic dominance that improves on existing tests based on the standard bootstrap … or subsampling. The method admits prospects involving infinite as well as finite dimensional unknown parameters, so that … the variables are allowed to be residuals from nonparametric and semiparametric models. The proposed bootstrap tests have …

Persistent link: https://www.econbiz.de/10005011842

Inference for Parameters Defined by Moment Inequalities Using Generalized Moment Selection

Andrews, Donald W.K.; Soares, Gustavo - Cowles Foundation for Research in Economics, Yale University - 2007

to be asymptotically conservative. The power of GMS tests is compared to that of subsampling, m out of n bootstrap, and … to have asymptotic power that dominates that of subsampling, m out of n bootstrap, and PA tests. Subsampling and m out of … n bootstrap tests are shown to have asymptotic power that dominates that of PA tests. …

Persistent link: https://www.econbiz.de/10005464003

Validity of Subsampling and "Plug-in Asymptotic" Inference for Parameters Defined by Moment Inequalities

Andrews, Donald W.K.; Guggenberger, Patrik - Cowles Foundation for Research in Economics, Yale University - 2007

identified. For a specified class of test statistics, this paper establishes the uniform asymptotic validity of subsampling, m … out of n bootstrap, and "plug-in asymptotic" tests and confidence intervals for such parameters. Establishing uniform …

Persistent link: https://www.econbiz.de/10005593497

An Improved Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimator

Andrews, Donald W.K.; Monahan, Christopher J. - Cowles Foundation for Research in Economics, Yale University - 1990

This paper considers a new class of heteroskedasticity and autocorrelation consistent (HAC) covariance matrix estimators. The estimators considered are prewhitened kernel estimators with vector autoregressions employed in the prewhitening stage. The paper establishes consistency, rate of...

Persistent link: https://www.econbiz.de/10005762589

Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation

Andrews, Donald W.K. - Cowles Foundation for Research in Economics, Yale University - 1988

This paper is concerned with the estimation of covariance matrices in the presence of heteroskedasticity and autocorrelation of unknown forms. Currently available estimators that are designed for this context depend upon the choice of a lag truncation parameter and a weighting scheme. No results...

Persistent link: https://www.econbiz.de/10005762692

Fact-Free Learning

Aragones, Enriqueta; Gilboa, Itzhak; Postlewaite, Andrew; … - Cowles Foundation for Research in Economics, Yale University - 2004

People may be surprised by noticing certain regularities that hold in existing knowledge they have had for some time. That is, they may learn without getting new factual information. We argue that this can be partly explained by computational complexity. We show that, given a database, finding a...

Persistent link: https://www.econbiz.de/10005093944

On the Performance of Least Squares in Linear Regression with Undefined Error Means

Andrews, Donald W.K. - Cowles Foundation for Research in Economics, Yale University - 1986

This paper considers the linear regression model with multiple stochastic regressors, intercept, and errors that have undefined means. This model is of interest from a robustness perspective as a polar case. Generally, least squares estimators are inconsistent in this context. It is shown,...

Persistent link: https://www.econbiz.de/10005249278

Unit Root Model Selection

Phillips, Peter C.B. - Cowles Foundation for Research in Economics, Yale University - 2008

Some limit properties for information based model selection criteria are given in the context of unit root evaluation and various assumptions about initial conditions. Allowing for a nonparametric short memory component, standard information criteria are shown to be weakly consistent for a unit...

Persistent link: https://www.econbiz.de/10005463847