Results 41 to 50 of about 1,180 (135)
The Wild Bootstrap, Tamed at Last [PDF]
Various versions of the wild bootstrap are studied as applied to regression models with heteroskedastic errors. We develop formal Edgeworth expansions for the error in the rejection probability (ERP) of wild bootstrap tests based on asymptotic t ...
Russell Davidson, Emmanuel Flachaire
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A new approach to bootstrap inference in functional coefficient models [PDF]
We introduce a new, factor based bootstrap approach which is robust under heteroskedastic error terms for inference in functional coefficient models. Modeling the functional coefficient parametrically, the bootstrap approximation of an F statistic is ...
Herwartz, Helmut, Xu, Fang
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Bootstrap tests for simple structures in nonparametric time series regression. [PDF]
This paper concerns statistical tests for simple structures such as parametric models, lower order models and additivity in a general nonparametric autoregression setting.
Yao, Qiwei +2 more
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A better way to bootstrap pairs [PDF]
In this paper we are interested in heteroskedastic regression models, for which an appropriate bootstrap method is bootstrapping pairs, proposed by Freedman (1981).
Emmanuel Flachaire
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Bootstrap-Based Improvements for Inference with Clustered Errors [PDF]
Researchers have increasingly realized the need to account for within-group dependence in estimating standard errors of regression parameter estimates. The usual solution is to calculate cluster-robust standard errors that permit heteroskedasticity and ...
Douglas L. Miller +2 more
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Energy Substitutability in Canadian Manufacturing: Econometric Estimation with Bootstrap Confidence Intervals [PDF]
This study provides estimates of the price and Morishima substitution elasticities between energy and non-energy inputs in two Canadian energy-intensive manufacturing industries: Primary Metal and Cement.
Yazid Dissou, Reza Ghazal
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Are analysts' loss functions asymmetric? [PDF]
, 2005 Recent research by Gu and Wu (2003) and Basu and Markov (2004) suggests that the well-known optimism bias in analysts’ earnings forecasts is attributable to analysts minimizing symmetric, linear loss functions when the distribution of forecast errors is ...
Mark A. Clatworthy +5 more
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Computationally efficient approximation for the double bootstrap mean bias correction [PDF]
We propose a computationally efficient approximation for the double bootstrap bias adjustment factor without using the inner bootstrap loop. The approximation converges in probability to the population bias correction factor.
Rachida Ouysse
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A parametric bootstrap for heavytailed distributions [PDF]
It is known that Efron's resampling bootstrap of the mean of random variables with common distribution in the domain of attraction of the stable laws with infinite variance is not consistent, in the sense that the limiting distribution of the bootstrap ...
Russell Davidson, Adriana Cornea
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Bootstraping econometric models [PDF]
The bootstrap is a statistical technique used more and more widely in econometrics. While it is capable of yielding very reliable inference, some precautions should be taken in order to ensure this.
Russell Davidson
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