Search Results - subject:"m out of n bootstrap"

Robust nonparametric analysis of dynamic profits, prices and productivity : an application to French meat-processing firms

Ang, Frederic; Kerstens, Pieter Jan - In: European review of agricultural economics 50 (2023) 2, pp. 771-809

Persistent link: https://www.econbiz.de/10014313285

Bootstrapping the Stein-rule estimators

Namba, Akio - In: Journal of quantitative economics 19 (2021), pp. 219-237

Persistent link: https://www.econbiz.de/10013441719

Bootstrapping Sample Quantiles of Discrete Data

Jentsch, Carsten; Leucht, Anne - 2014

Sample quantiles are consistent estimators for the true quantile and satisfy central limit theorems (CLTs) if the underlying distribution is continuous. If the distribution is discrete, the situation is much more delicate. In this case, sample quantiles are known to be not even consistent in...

Persistent link: https://www.econbiz.de/10011441851

Bootstrapping Sample Quantiles of Discrete Data

Jentsch, Carsten; Leucht, Anne - Abteilung für Volkswirtschaftslehre, Universität Mannheim - 2014

Persistent link: https://www.econbiz.de/10010833246

Bootstrapping sample quantiles of discrete data

Jentsch, Carsten; Leucht, Anne - 2014

Persistent link: https://www.econbiz.de/10011490510

Bootstrap-based Bandwidth Selection for Semiparametric Generalized Regression Estimators

Goh, Chuan - University of Toronto, Department of Economics - 2009

This paper considers the problem of implementing semiparametric extremum estimators of a generalized regression model with an unknown link function. The class of estimator under consideration includes as special cases the semiparametric least-squares estimator of Ichimura (1993) as well as the...

Persistent link: https://www.econbiz.de/10008506897

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

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 … bootstrap, m out of n bootstrap, and subsampling do lead to uniformly asymptotically valid confidence sets in moment inequality …

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

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

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

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

Bandwidth Selection for Semiparametric Estimators Using the m-out-of-n Bootstrap

Goh, Chuan - University of Toronto, Department of Economics - 2007

This paper considers a class of semiparametric estimators that take the form of density-weighted averages. These arise naturally in a consideration of semiparametric methods for the estimation of index and sample-selection models involving preliminary kernel density estimates. The question...

Persistent link: https://www.econbiz.de/10005827255