Autocorrelation robust tests are notorious for suffering from size distortions and power problems. We investigate under which conditions the size of autocorrelation robust tests can be controlled by an appropriate choice of critical value.SCOPUS: ar.jDecretOANoAutActifinfo:eu-repo/semantics/publishe
Testing restrictions on regression coefficients in linear models often requires correcting the conve...
This paper concerns the problem of assessing autocorrelation of multivariate (i.e. systemwise) model...
This paper considers the exact finite sample powers of five popular tests for AR(1) disturbances whe...
Autocorrelation robust tests are notorious for suffering from size distortions and power problems. W...
Autocorrelation robust tests are notorious for suffering from size distortions and power problems. W...
Autocorrelation robust tests are notorious for suffering from size distortions and power problems. W...
Autocorrelation robust tests are notorious for suffering from size distortions and power problems. W...
We complement the theory developed in Preinerstorfer and Pötscher (2016) with further finite sample ...
We complement the theory developed in Preinerstorfer and Pötscher (2016) with further finite sample ...
We complement the theory developed in Preinerstorfer and Pötscher (2016) with further finite sample ...
We complement the theory developed in Preinerstorfer and Pötscher (2016) with further finite sample ...
We complement the theory developed in Preinerstorfer and Pötscher (2016) with further finite sample ...
Using the power kernels of Phillips, Sun, and Jin (2006, 2007), we examine the large sample asymptot...
This paper concerns the problem of assessing autocorrelation of multivariate (i.e. system wise) mode...
Testing restrictions on regression coefficients in linear models often requires correcting the conve...
Testing restrictions on regression coefficients in linear models often requires correcting the conve...
This paper concerns the problem of assessing autocorrelation of multivariate (i.e. systemwise) model...
This paper considers the exact finite sample powers of five popular tests for AR(1) disturbances whe...
Autocorrelation robust tests are notorious for suffering from size distortions and power problems. W...
Autocorrelation robust tests are notorious for suffering from size distortions and power problems. W...
Autocorrelation robust tests are notorious for suffering from size distortions and power problems. W...
Autocorrelation robust tests are notorious for suffering from size distortions and power problems. W...
We complement the theory developed in Preinerstorfer and Pötscher (2016) with further finite sample ...
We complement the theory developed in Preinerstorfer and Pötscher (2016) with further finite sample ...
We complement the theory developed in Preinerstorfer and Pötscher (2016) with further finite sample ...
We complement the theory developed in Preinerstorfer and Pötscher (2016) with further finite sample ...
We complement the theory developed in Preinerstorfer and Pötscher (2016) with further finite sample ...
Using the power kernels of Phillips, Sun, and Jin (2006, 2007), we examine the large sample asymptot...
This paper concerns the problem of assessing autocorrelation of multivariate (i.e. system wise) mode...
Testing restrictions on regression coefficients in linear models often requires correcting the conve...
Testing restrictions on regression coefficients in linear models often requires correcting the conve...
This paper concerns the problem of assessing autocorrelation of multivariate (i.e. systemwise) model...
This paper considers the exact finite sample powers of five popular tests for AR(1) disturbances whe...