On the solution of linear stochastic time-varying rational expectations models

Author

Carravetta, Francesco

Author_Institution

Istituto di Analisi dei Sistemi ed Inf., CNR, Rome, Italy

Volume

1

fYear

1996

fDate

11-13 Dec 1996

Firstpage

55

Abstract

For a general vector rational expectations (RE) model, it is shown that there exists always a solution having the nice property of being the closest, in mean square, to the state motion of the autoregressive model governing the “ideal” behaviour of the economic system. Moreover, a recursive algorithm (based upon Kalman filtering theory) giving the rational expectation term (hence, the solution) and the optimal filtering estimate is presented

Keywords

Kalman filters; autoregressive processes; economic cybernetics; filtering theory; least mean squares methods; optimisation; statistical analysis; stochastic systems; Kalman filtering theory; autoregressive model; economic system; linear stochastic time-varying rational expectations models; mean square; optimal filtering estimate; recursive algorithm; state motion; vector rational expectations model; Econometrics; Equations; Filtering algorithms; Filtering theory; Kalman filters; Nonlinear filters; Random sequences; Stochastic processes; Vectors; Yttrium;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 1996., Proceedings of the 35th IEEE Conference on

Conference_Location

Kobe

ISSN

0191-2216

Print_ISBN

0-7803-3590-2

Type

conf

DOI

10.1109/CDC.1996.574251

Filename

574251