International audienceRecent results of Cribari-Neto and Zarkos (1999) show that bootstrap methods can be successfully used to estimate a heteroskedasticity robust covariance matrix estimator. In this paper, we show that the wild bootstrap estimator can be calculated directly, without simulations, as it is just a more traditional estimator. Their experimental results seem to conflict with those of MacKinnon and White (1985); we reconcile these two results
We propose bootstrap methods for statistics that are a function of multivariate high frequency retur...
White (1980) marked the beginning of a new era for inference in econometrics. It introduced the revo...
White (1980) marked the beginning of a new era for inference in econometrics. It introduced the revo...
International audienceRecent results of Cribari-Neto and Zarkos (1999) show that bootstrap methods c...
Recent results of Cribari-Neto and Zarkos (1999) show that bootstrap methods can be successfully use...
The wild bootstrap is studied in the context of regression models with heteroskedastic disturbances....
It is well-known that use of ordinary least squares for estimation of linear regression model with h...
International audienceIn regression models, appropriate bootstrap methods for inference robust to he...
Nowadays bootstrap techniques are used for data analysis in many other fields like engineering, phys...
In many, if not most, econometric applications, it is impossible to estimate consistently the elemen...
This paper uses the wild bootstrap technique in the estimation of a heteroscedastic partially linear...
Bootstrap techniques are widely used today in many other fields such as economics, Business Administ...
Heteroscedastic consistent covariance matrix (HCCM) estimators provide ways for testing hypotheses a...
We propose a wild bootstrap procedure for linear regression models estimated by instrumental variabl...
In this note we consider several versions of the bootstrap and ar-gue that it can be helpful in expl...
We propose bootstrap methods for statistics that are a function of multivariate high frequency retur...
White (1980) marked the beginning of a new era for inference in econometrics. It introduced the revo...
White (1980) marked the beginning of a new era for inference in econometrics. It introduced the revo...
International audienceRecent results of Cribari-Neto and Zarkos (1999) show that bootstrap methods c...
Recent results of Cribari-Neto and Zarkos (1999) show that bootstrap methods can be successfully use...
The wild bootstrap is studied in the context of regression models with heteroskedastic disturbances....
It is well-known that use of ordinary least squares for estimation of linear regression model with h...
International audienceIn regression models, appropriate bootstrap methods for inference robust to he...
Nowadays bootstrap techniques are used for data analysis in many other fields like engineering, phys...
In many, if not most, econometric applications, it is impossible to estimate consistently the elemen...
This paper uses the wild bootstrap technique in the estimation of a heteroscedastic partially linear...
Bootstrap techniques are widely used today in many other fields such as economics, Business Administ...
Heteroscedastic consistent covariance matrix (HCCM) estimators provide ways for testing hypotheses a...
We propose a wild bootstrap procedure for linear regression models estimated by instrumental variabl...
In this note we consider several versions of the bootstrap and ar-gue that it can be helpful in expl...
We propose bootstrap methods for statistics that are a function of multivariate high frequency retur...
White (1980) marked the beginning of a new era for inference in econometrics. It introduced the revo...
White (1980) marked the beginning of a new era for inference in econometrics. It introduced the revo...
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