Munich Personal RePEc Archive

Direct and iterated multistep AR methods for difference stationary processes

Proietti, Tommaso (2008): Direct and iterated multistep AR methods for difference stationary processes.

This is the latest version of this item.

[thumbnail of MPRA_paper_15343.pdf]

Download (466kB) | Preview


The paper focuses on the comparison of the direct and iterated AR predictors for difference stationary processes. In particular, it provides new methods for comparing the efficiency of the two predictors and for extracting the trend from macroeconomic time series using the two methods. The methods are based on an encompassing representation for the two predictors which enables to derive their properties quite easily under a maintained model. The paper provides an analytic expression for the mean square forecast error of the two predictors and derives useful recursive formulae for computing the direct and iterated coefficients. From the empirical standpoint, we propose estimators of the AR coefficients based on the tapered Yule- Walker estimates; we also provide a test of equal forecast accuracy which is very simple to implement and whose critical values are obtained with the bootstrap method.

Available Versions of this Item

Atom RSS 1.0 RSS 2.0

Contact us: mpra@ub.uni-muenchen.de

This repository has been built using EPrints software.

MPRA is a RePEc service hosted by Logo of the University Library LMU Munich.