Structural Time Series Models and the Kalman Filter: A Concise Review

FEUNL Working Paper No. 541

30 Pages Posted: 20 Nov 2009

See all articles by João Tovar Jalles

João Tovar Jalles

University of Lisbon; International Monetary Fund (IMF); Technical University of Lisbon (UTL) - Research Unit on Complexity and Economics (UECE)

Date Written: June 19, 2009

Abstract

The continued increase in availability of economic data in recent years and, more importantly, the possibility to construct larger frequency time series, have fostered the use (and development) of statistical and econometric techniques to treat them more accurately. This paper presents an exposition of structural time series models by which a time series can be decomposed as the sum of a trend, seasonal and irregular components. In addition to a detailled analysis of univariate speci…cations we also address the SUTSE multivariate case and the issue of cointegration. Finally, the recursive estimation and smoothing by means of the Kalman …lter algorithm is described taking into account its different stages, from initialisation to parameter's estimation.

Keywords: SUTSE, cointegration, ARIMA, smoothing, likelihood

JEL Classification: C10, C22, C32

Suggested Citation

Jalles, João Tovar, Structural Time Series Models and the Kalman Filter: A Concise Review (June 19, 2009). FEUNL Working Paper No. 541, Available at SSRN: https://ssrn.com/abstract=1496864 or http://dx.doi.org/10.2139/ssrn.1496864

João Tovar Jalles (Contact Author)

University of Lisbon ( email )

R. Branca Edmée Marques
Dept. Plant Biology
Lisboa, 1600-276
Portugal

International Monetary Fund (IMF) ( email )

700 19th Street, N.W.
Washington, DC 20431
United States

Technical University of Lisbon (UTL) - Research Unit on Complexity and Economics (UECE)

Rua Miguel Lupi, 20
Lisboa, 1200-781
Portugal

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