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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

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

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

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

On approximating the distributions of goodness-of-fit test statistics based on the empirical distribution function : the case of unknown parameters

Capasso, Marco; Alessi, Lucia; Barigozzi, Matteo; … - 2007

This note discusses some problems possibly arising when approximating via MonteCarlo simulations the distributions of goodness-of-fit test statistics based on the empirical distribution function. We argue that failing to reestimate unknown parameters on each simulated Monte-Carlo sample - and...

Persistent link: https://www.econbiz.de/10003746039

Robust subsampling

Camponovo, Lorenzo (contributor); … - 2006

regression model. Monte Carlo simulations in two settings where the bootstrap fails show the accuracy and robustness of the …

Persistent link: https://www.econbiz.de/10003394379