This paper provides limit theorems for special density matrix estimators and functionals of it for a bivariate co variance stationary process whose spectral density matrix has singularities not only at the origin but possibly at some other frequencies, and thus applies to time series exhibiting...

A multivariate invariance principle is given for dependent processes exhibiting trending variances and other types of global nonstationarity. The limit processes obtained in these results are not Brownian motion, but members of a related class of Gaussian diffusion processes. Also derived is the...

The central limit theorem in Davidson (1992a) is extended to allow cases where the variances of sequence coordinates can be tending to zero. A trade off is demonstrated between the degree of dependence (mixing size) and the rate of degeneration. For the martingale difference case, it is...

In this paper, we argue that measured (RPI) inflation is conceptually mismatched with core inflation: the difference is more than just "measurement error". We propose a technique for measuring core inflation, based on an explicit long-run economic hypothesis. Core inflation is defined as that...

The convergence hypothesis has generated a huge empirical literature: this paper critically reviews some of the earlier key findings, clarifies their implications, and relates them to more recent results. Particular attention is devoted to interpreting convergence empirics. The main findings...

This paper considers unit root regressions in data having simultaneously extensive cross-section and time-series variation. The standard least-squares estimators in such data structures turn out to have an asymptotic distribution that is neither Op(T-1) Dickey-Fuller, nor Op(N-?) normal and...

The score vector for a time series model which fits into the Gaussian state space form can be approximated by numerically differentiating the log-likelihood. If the parameter vector is of length p, this involves the running of p + 1 Kalman filters. This paper shows the score vector can be...

Much of economic analysis presupposes that certain economic time series can be decomposed into trends and cycles. Structural time series models are explicitly set up in terms of such unobserved components. This paper sets up various multivariate structural time series models, shows how they can...