A note on bootstraps and robustness
In this note we consider several versions of the bootstrap and argue that it is helpful in explaining and thinking about such procedures to use an explicit representation of the random resampling process. To illustrate the point we give such explicit representations and use them to produce some results about bootstrapping linear models that are, apparently, not widely known. Among these are a demonstration of the equivalence, to order n-1 of the covariance matrix of the bootstrap distribution of the least squares estimator and the Eicker(1967)/White(1980) heteroscedasticity robust covariance matrix estimate. And we examine the precise relations between an Efron(1979) bootstrap procedure and the Bayesian bootstrap of Rubin(1981) and show that their covariance matrices are identical to O(1/n).
|Date of creation:||Feb 2006|
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References listed on IDEAS
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877R, Cowles Foundation for Research in Economics, Yale University, revised Jul 1989.
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SFB 373 Discussion Papers
2003,31, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
- Oliver Linton & Esfandiar Maasoumi & Yoon-Jae Whang, 2005. "Consistent Testing for Stochastic Dominance under General Sampling Schemes," Review of Economic Studies, Oxford University Press, vol. 72(3), pages 735-765.
- Oliver Linton & Esfandiar Maasoumi & Yoon-Jae Whang, 2003. "Consistent testing for stochastic dominance under general sampling schemes," LSE Research Online Documents on Economics 2208, London School of Economics and Political Science, LSE Library.
- Robert M. De Jong & James Davidson, 2000.
"Consistency of Kernel Estimators of Heteroscedastic and Autocorrelated Covariance Matrices,"
Econometric Society, vol. 68(2), pages 407-424, March.
- de Jong, R.M. & Davidson, J., 1996. "Consistency of Kernel Estimators of Heteroscedastic and Autocorrelated Covariance Matrices," Discussion Paper 1996-52, Tilburg University, Center for Economic Research.
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