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...

In approximating the small sample distribution of the least squares estimator of the coefficient in a non-circular autoregression the saddlepoint method is complicated by the presence of a branch point of the integrand within the natural contour of integration. Some new approximations are given...

This paper extends earlier results, which were reported in [7], to include non null distributions. As in [7], attention is concentrated on the Wald statistic for testing general linear restrictions on the coefficients in the multivariate linear model. The results of the present paper encompass...

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...

Fisher's equation for the determination of the real rate of interest is studied from a fresh econometric perspective. Some new methods of data description for nonstationary time series are introduced. The methods provide a nonparametric mechanism for modelling the spatial densities of a time...

One of the more obvious empirical characteristics of macroeconomic time series is their tendency to grow, or trend, over time. Dealing with this trendnonstationarity in models of multiple time series has been a major agenda of econometric research for much of the last decade and has produced an...