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Testing for the appropriate level of clustering in linear regression models

MacKinnon, James G.; Nielsen, Morten Ørregaard; Webb, … - 2020

prove the asymptotic validity of a wild bootstrap implementation. The proposed tests work for a null hypothesis of either no … determine the appropriate level of clustering. Simulations suggest that the bootstrap tests perform very well under the null …

Persistent link: https://www.econbiz.de/10012201366

A bootstrap test for instrument validity in heterogeneous treatment effect models

Kitagawa, Toru - 2013

bootstrap algorithm to implement the proposed test and show its asymptotic validity. The proposed test procedure can apply to …

Persistent link: https://www.econbiz.de/10010190476

Change point estimation in panel data without boundary issue

Peštová, Barbora; Pešta, Michal - In: Risks : open access journal 5 (2017) 1, pp. 1-22

Panel data of our interest consist of a moderate number of panels, while the panels contain a small number of observations. An estimator of common breaks in panel means without a boundary issue for this kind of scenario is proposed. In particular, the novel estimator is able to detect a common...

Persistent link: https://www.econbiz.de/10011636497

Improved inference on the rank of a matrix

Chen, Qihui; Fang, Zheng - In: Quantitative economics : QE ; journal of the … 10 (2019) 4, pp. 1787-1824

under are highly nonstandard due to the inherent irregular natures of the problem, and then construct bootstrap critical …

Persistent link: https://www.econbiz.de/10012202917

The Romano-Wolf multiple hypothesis correction in Stata

Clarke, Damian; Romano, Joseph P.; Wolf, Michael - 2019

When considering multiple hypothesis tests simultaneously, standard statistical techniques will lead to over-rejection of null hypotheses unless the multiplicity of the testing framework is explicitly considered. In this paper we discuss the Romano-Wolf multiple hypothesis correction, and...

Persistent link: https://www.econbiz.de/10012147332

Small sample adjustment for hypotheses testing on cointegrating vectors

Canepa, Alessandra - In: Journal of time series econometrics 14 (2022) 1, pp. 51-85

Persistent link: https://www.econbiz.de/10013260145

Heteroskedasticity-and-autocorrelation-consistent bootstrapping

Davidson, Russell; Monticini, Andrea - 2014

disturbances,where the heteroskedasticity and autocorrelation are of unknown form. A particular version of the wild bootstrap can … dependent wild bootstrap. Here, we extend this new method, and link it to the well-known HAC covariance estimator, in much the … same way as one can link the wild bootstrap to the HCCME. It works very well even with sample sizes smaller than 50, and …

Persistent link: https://www.econbiz.de/10011774249

Testing mean-variance efficiency in CAPM with possibly non-gaussian errors : an exact simulation-based approach

Beaulieu, Marie-Claude; Dufour, Jean-Marie; Khalaf, Lynda - 2003

In this paper we propose exact likelihood-based mean-variance efficiency tests of the market portfolio in the context of Capital Asset Pricing Model (CAPM), allowing for a wide class of error distributions which include normality as a special case. These tests are developed in the framework of...

Persistent link: https://www.econbiz.de/10001731828

Maximum Likelihood Estimation and Uniform Inference with Sporadic Identification Failure

Andrews, Donald W. K.; Cheng, Xu - 2011

This paper analyzes the properties of a class of estimators, tests, and confidence sets (CS's) when the parameters are not identified in parts of the parameter space. Specifically, we consider estimator criterion functions that are sample averages and are smooth functions of a parameter theta....

Persistent link: https://www.econbiz.de/10014176550

Inference for Parameters Defined by Moment Inequalities : A Recommended Moment Selection Procedure

Andrews, Donald W. K.; Jia, Panle - 2011

methods (i.e., the asymptotic distribution versus the bootstrap) have been proposed. In this paper, we compare these methods …

Persistent link: https://www.econbiz.de/10014179349