Bootstrap hypothesis testing in regression models
The paper investigates how the particular choice of residuals used in a bootstrap-based testing procedure affects the properties of the test. The properties of the tests are investigated both under the null and under the alternative. It is shown that for non-pivotal test statistics, the method used to obtain residuals largely affects the power behavior of the tests. For instance, imposing the null hypothesis in the residual estimation step--although it does not affect the behavior of the test if the null is true--it leads to a loss of power under the alternative as compared to tests based on resampling unrestricted residuals. Residuals obtained using a parameter estimator which minimizes their variance maximizes the power of the corresponding bootstrap-based tests. In this context, studentizing makes the tests more robust to such residual effects.
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Volume (Year): 74 (2005)
Issue (Month): 4 (October)
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References listed on IDEAS
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- Nankervis, John C & Savin, N E, 1996. "The Level and Power of the Bootstrap t Test in the AR(1) Model with Trend," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(2), pages 161-68, April.
- Park, Joon, 2002.
"Bootstrap Unit Root Tests,"
2003-04, Rice University, Department of Economics.
- Joon Y. Park, 2000. "Bootstrap Unit Root Tests," Econometric Society World Congress 2000 Contributed Papers 1587, Econometric Society.
- Horowitz, Joel L., 1994. "Bootstrap-based critical values for the information matrix test," Journal of Econometrics, Elsevier, vol. 61(2), pages 395-411, April.
- Anders Rygh Swensen, 2003. "Bootstrapping unit root tests for integrated processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(1), pages 99-126, 01.
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