and discuss the use of the bootstrap to improve the properties of asymptotic tests. The theoretical properties of the …

samples than the confidence regions that can be constructed from the smoothed bootstrap method recently suggested by Horowitz …

. Based on adaptive kernel density estimation, we propose an adaptive bootstrap test for multimodality. Our results indicate …

of bootstrap testing. In short, all the algorithms work well and lead to tests with correct or close to correct size …. There is thus little or no reason not to use the bootstrap with error component models. …

than the confidence regions that can be constructed from the smoothed bootstrap method recently suggested by Horowitz (1998). …

There are many bootstrap methods that can be used for econometric analysis. In certain circumstances, such as … regression models with independent and identically distributed error terms, appropriately chosen bootstrap methods generally work … very well. However, there are many other cases, such as regression models with dependent errors, in which bootstrap methods …

bootstrap to achieve valid inference in a time series setting. The test statistics and the estimators are computed using linear …

bootstrap is used to obtain asymptotic refinement of statistical tests. The results in the experiment as well as in the quasi …

classical bootstrap and the robust bootstrap, in terms of accuracy and robustness. These results show that robustness is a key …

appropriate p-value for a test for hysteresis we propose two alternative bootstrap procedures: the first is valid under … homoskedastic errors and the second allows for general heteroskedasticity. We investigate the performance of both bootstrap …