Showing 1 - 10 of 12
Multiple time series models with stochastic regressors are considered and primary attention is given to vector autoregressions (VAR's) with trending mechanisms that may be stochastic, deterministic or both. In a Bayesian framework, the data density in such a system implies the existence of a...
Persistent link: https://www.econbiz.de/10005249158
This paper offers an approach to time series modeling that attempts to reconcile classical and Bayesian methods. The central idea put forward to achieve this reconciliation is that the Bayesian approach relies implicitly on a frame of reference for the data generating mechanism that is quite...
Persistent link: https://www.econbiz.de/10005249284
Asymptotic properties of the local Whittle estimator in the nonstationary case (d > 1/2) are explored. For 1/2 < d < 1, the estimator is shown to be consistent, and its limit distribution and the rate of convergence depend on the value of d. For d = 1, the limit distribution is mixed normal. For d > 1 and when the process has a linear trend, the estimator is shown to be inconsistent and to converge in probability to unity.
Persistent link: https://www.econbiz.de/10004990709
This paper develops an asymptotic theory for a first order autoregression with a root near unity. Deviations from the unit root theory are measured through a noncentrality parameter. When this parameter is negative we have a local alternative that is stationary; when it is positive, the local...
Persistent link: https://www.econbiz.de/10004990755
Instrumental variable (IV) estimation methods that allow for certain nonlinear functions of the data as instruments are studied. The context of the discussion is the simple unit root model where certain advantages to the use of nonlinear instruments are revealed. In particular, certain classes...
Persistent link: https://www.econbiz.de/10004990782
Weak convergence of partial sums and multilinear forms in independent random variables and linear processes to stochastic integrals now plays a major role in nonstationary time series and has been central to the development of unit root econometrics. The present paper develops a new and...
Persistent link: https://www.econbiz.de/10004990794
Log periodogram (LP) regression is shown to be consistent and to have a mixed normal limit distribution when the memory parameter d = 1. Gaussian errors are not required. Tests of d = 1 based on LP regression are consistent against d < 1 alternatives but inconsistent against d > 1 alternatives. A test based on a modified LP regression that...</1>
Persistent link: https://www.econbiz.de/10005762562
It is shown that the fully modified ordinary least squares (FM-OLS) estimator of a unit root in time series regression is T^{3/2}-consistent. Relative to FM-OLS, therefore, the least squares and maximum likelihood estimators are infinitely deficient asymptotically. Simulations show that this...
Persistent link: https://www.econbiz.de/10005196030
This paper provides an empirical implementation of some recent work by the author and Werner Ploberger on the development of "Bayes models" for time series. The methods offer a new data-based approach to model selection, to hypothesis testing and to forecast evaluation in the analysis of time...
Persistent link: https://www.econbiz.de/10005593351
This paper reports an empirical application of new Baynesian methodology to Australian data on consumption, income, liquid assets and inflation. The methods involve the use of objective model based reference priors and objective posterior odds test criteria. The paper provides an overview of...
Persistent link: https://www.econbiz.de/10005634716