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Parente, Paulo M. D. C.; Smith, Richard J. - 2018 - This draft: July 2018

This article introduces and investigates the properties of a new bootstrap method for time-series data, the kernel block bootstrap. The bootstrap method, although akin to, offers an improvement over the tapered block bootstrap of Paparoditis and Politis (2001), admitting kernels with unbounded...

Persistent link: https://www.econbiz.de/10011878210

Robust resampling methods for time series

Camponovo, Lorenzo; Scaillet, Olivier; Trojani, Fabio - 2010 - This version: May 9, 2010

We study the robustness of block resampling procedures for time series. We first derive a set of formulas to … applications. This renders inference based on standard resampling methods useless already in simple estimation and testing settings …. To solve this problem, we introduce a robust fast resampling scheme that is applicable to a wide class of time series …

Persistent link: https://www.econbiz.de/10003971115

Thirty years of heteroskedasticity-robust inference

MacKinnon, James G. - 2011

White (1980) marked the beginning of a new era for inference in econometrics. It introduced the revolutionary idea of inference that is robust to heteroskedasticity of unknown form, an idea that was very soon extended to other forms of robust inference and also led to many new estimation...

Persistent link: https://www.econbiz.de/10009127144

A bootstrap test for instrument validity in heterogeneous treatment effect models

Kitagawa, Toru - 2013

This paper develops a specification test for the instrument validity conditions in the heterogeneous treatment effect model with a binary treatment and a discrete instrument. A necessary testable implication for the joint restriction of instrument exogeneity and instrument monotonicity is given...

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

A test for instrument validity

Kitagawa, Toru - 2014 - This draft: August, 2014

This paper develops a specification test for instrument validity in the heterogeneous treatment effect model with a binary treatment and a discrete instrument. The strongest testable implication for instrument validity is given by the condition for nonnegativity of point-identifiable complier's...

Persistent link: https://www.econbiz.de/10010392075

Inference for functions of partially identified parameters in moment inequality models

Bugni, Federico A.; Canay, Ivan A.; Shi, Xiaoxia - 2014 - Ver. 10.2: May 4, 2014

This paper introduces a bootstrap-based inference method for functions of the parameter vector in a moment (in)equality model. As a special case, our method yields marginal confidence sets for individual coordinates of this parameter vector. Our inference method controls asymptotic size...

Persistent link: https://www.econbiz.de/10010348998

Bootstrap tests of mean-variance efficiency with multiple portfolio groupings

Gungor, Sermin; Luger, Richard - 2014

We propose double bootstrap methods to test the mean-variance efficiency hypothesis when multiple portfolio groupings of the test assets are considered jointly rather than individually. A direct test of the joint null hypothesis may not be possible with standard methods when the total number of...

Persistent link: https://www.econbiz.de/10010429974

Bootstrapping systems cointegration tests with a prior adjustment for deterministic terms

Trenkler, Carsten (contributor) - 2006

In this paper we analyse bootstrap procedures for systems cointegration tests with a prior adjustment for deterministic terms suggested by Saikkonen & Lütkepohl (2000b) and Saikkonen, Lütkepohl & Trenkler (2006). The asymptotic properties of the bootstrap test procedures are derived and their...

Persistent link: https://www.econbiz.de/10003324256

Nested pseudo-likelihood estimation and bootstrap-based inference for structural discrete Markov decision models

Kasahara, Hiroyuki (contributor); … - 2006

This paper analyzes the higher-order properties of nested pseudo-likelihood (NPL) estimators and their practical implementation for parametric discrete Markov decision models in which the probability distribution is defined as a fixed point. We propose a new NPL estimator that can achieve...

Persistent link: https://www.econbiz.de/10003274966

Inference with large clustered datasets

MacKinnon, James G. - 2016

Inference using large datasets is not nearly as straightforward as conventional econometric theory suggests when the disturbances are clustered, even with very small intra-cluster correlations. The information contained in such a dataset grows much more slowly with the sample size than it would...

Persistent link: https://www.econbiz.de/10011528432