Abstract: Difficulties with inference in predictive regressions are generally attributed to strong persistence in the predictor series. We show that the major source of the problem is actually the nuisance intercept parameter and propose basing inference on the Restricted Likelihood, which is...

Difficulties with inference in predictive regressions are generally attributed tostrong persistence in the predictor series. We show that the major source of the problem is actually the nuisance intercept parameter and propose basing inference on the Restricted Likelihood,which is free of such...

For long-memory time series, we show that the Toeplitz system sect;n(f)x = b can be solved inO(n log5=2 n) operations using a well-known version of the preconditioned conjugate gradient method, where sect;n(f) is the npound;n covariance matrix, f is the spectral density and b is a known vector....

We consider a common components model for multivariate fractional cointegration, in which the s cedil; 1 components have different memory parameters. The cointegrating rank is allowed to exceed 1. The true cointegrating vectors can be decomposed into orthogonal fractional cointegrating subspaces...

We study the small sample behaviour of two goodness-of-fit tests for time series models whichhave been proposed recently in the literature. Both tests are generalizations of the popular Box-Ljung-Pierce portmanteau test, one in the time domain and the other in the frequency domain.The tests are...