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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
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
We study the problem of testing the error distribution in a multivariate linear regression (MLR) model. The tests are functions of appropriately standardized multivariate least squares residuals whose distribution is invariant to the unknown cross-equation error covariance matrix. Empirical...
Persistent link: https://www.econbiz.de/10005133089
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
In this paper, we propose exact inference procedures for asset pricing models that can be formulated in the framework of a multivariate linear regression (CAPM), allowing for stable error distributions. The normality assumption on the distribution of stock returns is usually rejected in...
Persistent link: https://www.econbiz.de/10005100963
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/10005688554