The global linear trend with autocorrelated disturbances is a surprising omission from the M1 competition. This approach to forecasting is therefore evaluated using the 51 non-seasonal series from the competition. It is contrasted with a fully optimized version of Holts trend corrected...

A class of nonlinear processes which have a root that is not constant, but is stochastic, and varying around unity is introduced. Th eprocess can be stationary for some periods, and mildly explosive for others.

In this paper we have estimated Vector Autoregression (VAR), Bayesian VAR and Vector Error Correction models (VECMs) using annual time series data of SOuth Korea for 1950-1994. We find evidence supporting the view that growth of real per capita income has been aided by income, investment and...

In this paper we analyze the sensitivity of unit root inference to nonlinear transformations through Bayesian techniques. We make joint inference about the Box-Cox transformation, which includes the cases yt and log(yt), and the unit root. When we apply our method to the fourteen Nelson-Plosser...

In a nonlinear framework the magnitude of temporal dependence may depend on the transformation applied to time series. The aim of this paper is to examine in detail various forms of persistence and the corresponding transformations. For multivariate series the persistence analysis is used to...

This study analyzes the size and power of tests of the null of stationarity against the unit root alternative. Existing evidence is limited to processes with roots between 0 and 0.7. In sharp contrast, virtually all applications of economic interest involve null hypotheses much closer to 1. We...