Add to ORKGAutocorrelation 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
This paper concerns the problem of assessing autocorrelation of multivariate (i.e. system wise) mode...
This paper concerns the problem of assessing autocorrelation of multivariate (i.e. systemwise) model...
Using the power kernels of Phillips, Sun and Jin (2006, 2007), we examine the large sample asymptoti...
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 ...
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...
Testing restrictions on regression coefficients in linear models often requires correcting the conve...
We complement the theory developed in Preinerstorfer and Pötscher (2016) with further finite sample ...
This paper concerns the problem of assessing autocorrelation of multivariate (i.e. system wise) mode...
This paper concerns the problem of assessing autocorrelation of multivariate (i.e. systemwise) model...
Using the power kernels of Phillips, Sun and Jin (2006, 2007), we examine the large sample asymptoti...
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 ...
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...
Testing restrictions on regression coefficients in linear models often requires correcting the conve...
We complement the theory developed in Preinerstorfer and Pötscher (2016) with further finite sample ...
This paper concerns the problem of assessing autocorrelation of multivariate (i.e. system wise) mode...
This paper concerns the problem of assessing autocorrelation of multivariate (i.e. systemwise) model...
Using the power kernels of Phillips, Sun and Jin (2006, 2007), we examine the large sample asymptoti...