bootstrap versions of the tests have much better properties in this respect. In other words, the bootstrap can be used to size …

bootstrap resampling technique. The method is illustrated on S&P 500 index data. …

use quantities derived from the parameters to disentangle the relationships between the variables. Bootstrap methods are … often used for inference on the derived quantities. Alternative bootstrap methods for this purpose are discussed, some …

often not provided. If confidence intervals are given they are often based on bootstrap methods with poor theoretical …

fixed link functions. In this paper we consider a bootstrap specification test that detects nonparametric deviations of the … link function. The bootstrap is used with the aim to find a more accurate distribution under the null than the normal … we show that the bootstrap is able to capture the negative bias and the skewness of the test statistic. It yields better …

define also an adjusted-for-chance version, although we advise that, whenever feasible, bootstrap replications should be …

of portfolio return, 2. by using a bootstrap method in a nonparametric framework. The Empirical exercise is implemented …

-tests based on a variety of standard errors, confidence intervals, bootstrap resampling, and likelihood-ratio-type tests. In their … signed root tests and z-tests based on the empirical sandwich and the empirical bootstrap standard errors perform best in …

estimating the standard error of poverty measures when th e poverty line is estimated from survey data. Based on bootstrap …