Add to ORKGThe Breusch-Godfrey’s LM test is one of the most popular tests for autocorrelation. However, it has been shown that the LM test may be erroneous when there exist heteroskedastic errors in regression model. Some remedies recently have been proposed by Godfrey and Tremayne (2005) and Shim et al. (2006). This paper suggests wild-bootstrapped variance ratio test for autocorrelation in the presence of heteroskedasticity. We show through a Monte Carlo simulation that our wild-bootstrapped VR test has better small sample properties and is robust to the structure of heteroskedasticity
Département de sciences économiques Faculte ́ des arts et des sciences Rapport présente ́ a ̀ la ...
In this paper we consider several modified wild bootstrap methods that, additionally to heteroskedas...
In a recent paper Cavaliere et al. (2012) develop bootstrap implementations of the (pseudo-) likelih...
International audienceIn regression models, appropriate bootstrap methods for inference robust to he...
We propose a wild bootstrap procedure for linear regression models estimated by instrumental variabl...
Standard asymptotic and residual-based bootstrap tests for error autocorrela- tion are unreliable i...
This paper proposes a heteroskedasticity-robust Breusch–Pagan test of the null hypothesis of zero cr...
This article extends and generalizes the variance-ratio (VR) statistic by employing an estimator of ...
The wild bootstrap is studied in the context of regression models with heteroskedastic disturbances....
We propose a wild bootstrap procedure for linear regression models estimated by instrumental variabl...
Autocorrelation problem causes unduly effects on the variance of Ordinary Least Squares (OLS) estima...
In many, if not most, econometric applications, it is impossible to estimate consistently the elemen...
International audienceRecent results of Cribari-Neto and Zarkos (1999) show that bootstrap methods c...
Département de sciences économiques Faculte ́ des arts et des sciences Rapport présente ́ a ̀ la ...
In this paper we consider several modified wild bootstrap methods that, additionally to heteroskedas...
In a recent paper Cavaliere et al. (2012) develop bootstrap implementations of the (pseudo-) likelih...
International audienceIn regression models, appropriate bootstrap methods for inference robust to he...
We propose a wild bootstrap procedure for linear regression models estimated by instrumental variabl...
Standard asymptotic and residual-based bootstrap tests for error autocorrela- tion are unreliable i...
This paper proposes a heteroskedasticity-robust Breusch–Pagan test of the null hypothesis of zero cr...
This article extends and generalizes the variance-ratio (VR) statistic by employing an estimator of ...
The wild bootstrap is studied in the context of regression models with heteroskedastic disturbances....
We propose a wild bootstrap procedure for linear regression models estimated by instrumental variabl...
Autocorrelation problem causes unduly effects on the variance of Ordinary Least Squares (OLS) estima...
In many, if not most, econometric applications, it is impossible to estimate consistently the elemen...
International audienceRecent results of Cribari-Neto and Zarkos (1999) show that bootstrap methods c...
Département de sciences économiques Faculte ́ des arts et des sciences Rapport présente ́ a ̀ la ...
In this paper we consider several modified wild bootstrap methods that, additionally to heteroskedas...
In a recent paper Cavaliere et al. (2012) develop bootstrap implementations of the (pseudo-) likelih...