Asymptotics of unit root tests under sequential sampling via diffusion approximation
نویسندگان
چکیده
منابع مشابه
Seasonal Unit Root Tests Under Structural Breaks
In this paper, several seasonal unit root tests are analysed in the context of structural breaks at known time and a new break corrected test is suggested. We show that the widely used HEGY test as well as an LM variant thereof are asymptotically robust to seasonal mean shifts of finite magnitude. In finite samples, however, experiments reveal that such tests suffer from severe size distortions...
متن کاملBootstrap Unit Root Tests
We consider the bootstrap unit root tests based on finite order autoregressive integrated models driven by iid innovations, with or without deterministic time trends. A general methodology is developed to approximate asymptotic distributions for the models driven by integrated time series, and used to obtain asymptotic expansions for the Dickey–Fuller unit root tests. The second-order terms in ...
متن کاملPanel Unit Root Tests under Cross-sectional Dependence: an Overview
The increasing availability of new datasets where the time-series dimension and the cross-section dimension are of the same order of magnitude asks for new techniques for the analysis of this peculiar kind of data. In the panel unit root test framework, two generations of tests have been developed: a first generation whose main limit is the assumption of cross-sectional independence across unit...
متن کاملPanel Unit Root Tests Under Cross Sectional Dependence
In this paper alternative approaches for testing the unit root hypothesis in panel data are considered. First, a robust version of the Dickey-Fuller t-statistic under contemporaneous correlated errors is suggested. Second, the GLS t-statistic is considered, which is based on the t-statistic of the transformed model. The asymptotic power of both tests against a sequence of local alternatives is ...
متن کاملDifferencing and Unit Root Tests
e d In the Box-Jenkins approach to analyzing time series, a key question is whether to difference th ata, i.e., to replace the raw data {y } by the differenced series {y −y }. Experience indicates that m t t t −1 ost economic time series tend to wander and are not stationary, but that differencing often yields a e r stationary result. A key example, which often provides a fairly good descriptio...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Теория вероятностей и ее применения
سال: 2010
ISSN: 0040-361X
DOI: 10.4213/tvp4255