Showing 1 - 10 of 11
This paper presents a family of simple nonparametric unit root tests indexed by one parameter, d, and containing Breitung's (2002) test as the special case d = 1. It is shown that (i) each member of the family with d 0 is consistent, (ii) the asymptotic distribution depends on d, and thus...
Persistent link: https://www.econbiz.de/10010292072
Persistent link: https://www.econbiz.de/10009464000
This paper presents a family of simple nonparametric unit root tests indexed by one parameter, d, and containing Breitung's (2002) test as the special case d=1. It is shown that (i) each member of the family with d0 is consistent, (ii) the asymptotic distribution depends on d, and thus reflects...
Persistent link: https://www.econbiz.de/10010290321
This paper presents a family of simple nonparametric unit root tests indexed by one parameter, d, and containing Breitung's (2002) test as the special case d = 1. It is shown that (i) each member of the family with d 0 is consistent, (ii) the asymptotic distribution depends on d, and thus...
Persistent link: https://www.econbiz.de/10010290378
Persistent link: https://www.econbiz.de/10012483170
Persistent link: https://www.econbiz.de/10011949753
Via the leading unit root case, the problem of testing on a lagged dependent variable is characterized by a nuisance parameter which is present only under the alternative (see Andrews and Ploberger (1994)). This has proven a barrier to the construction of optimal tests. Moreover, in their...
Persistent link: https://www.econbiz.de/10005328474
A two-stage procedure based on impulse saturation is suggested to distinguish mean and variance shifts. The resulting zero-mean innovation test statistic has a non standard distribution, with a nuisance parameter. Hence, simulation-based critical values are provided for some cases of interest....
Persistent link: https://www.econbiz.de/10005085644
Persistent link: https://www.econbiz.de/10014364694
The technique of Monte Carlo (MC) tests [Dwass (1957), Barnard (1963)] provides an attractive method of building exact tests from statistics whose finite sample distribution is intractable but can be simulated (provided it does not involve nuisance parameters). We extend this method in two ways:...
Persistent link: https://www.econbiz.de/10005100868