Predictability, Real Time Estimation, and the Formulation of Unobserved Components Models

25 Pages Posted: 22 Mar 2019

See all articles by Tommaso Proietti

Tommaso Proietti

University of Rome II - Department of Economics and Finance

Date Written: March 22, 2019

Abstract

The formulation of unobserved components models raises some relevant interpretative issues, owing to the existence of alternative observationally equivalent specifi cations, differing for the timing of the disturbances and their covariance matrix. We illustrate them with reference to unobserved components models with ARMA(m;m) reduced form, performing the decomposition of the series into an ARMA(m; q) signal, q m, and a noise component. We provide a characterization of the set of covariance structures that are observationally equivalent, when the models are formulated both in the future and the contemporaneous forms. Hence, we show that, while the point predictions and the contemporaneous real time estimates are invariant to the specifi cation of the disturbances covariance matrix, the reliability cannot be identi fied, except for special cases requiring q < m - 1.

Keywords: ARMA models. Steady State Kalman lter. Correlated Components. Nonfundamentalness.

JEL Classification: C22, C51, C53

Suggested Citation

Proietti, Tommaso, Predictability, Real Time Estimation, and the Formulation of Unobserved Components Models (March 22, 2019). CEIS Working Paper No. 455. Available at SSRN: https://ssrn.com/abstract=3358467 or http://dx.doi.org/10.2139/ssrn.3358467

Tommaso Proietti (Contact Author)

University of Rome II - Department of Economics and Finance ( email )

Via Columbia, 2
Rome, 00133
Italy

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
21
Abstract Views
217
PlumX Metrics