This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

Structural Time Series Models and the Kalman Filter: a concise review

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Jalles, Joao Tovar

Additional information is available for the following registered author(s):

Abstract

The continued increase in availability of economic data in recent years and, more impor- tantly, 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 di¤erent stages, from initialisation to parameter?s estimation. JEL codes: C10, C22, C32

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://fesrvsd.fe.unl.pt/WPFEUNL/WP2009/wp541.pdf
File Format:
File Function:
Download Restriction: no

Publisher Info
Paper provided by Universidade Nova de Lisboa, Faculdade de Economia in its series FEUNL Working Paper Series with number wp541.

Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Length: 30 pages
Date of creation: 2009
Date of revision:
Handle: RePEc:unl:unlfep:wp541

Contact details of provider:
Web page: http://www.fe.unl.pt

For technical questions regarding this item, or to correct its listing, contact: (Lourdes Gouveia).

Related research
Keywords:

This paper has been announced in the following NEP Reports:

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Harvey, Andrew C & Koopman, Siem Jan, 1992. "Diagnostic Checking of Unobserved-Components Time Series Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(4), pages 377-89, October.
  2. Andrew C Harvey & Andrew Scott, 1994. "Seasonality in Dynamic Regression Models," CEP Discussion Papers dp0184, Centre for Economic Performance, LSE.
    Other versions:
  3. Harvey, Andrew & Koopman, Siem Jan & Riani, Marco, 1997. "The Modeling and Seasonal Adjustment of Weekly Observations," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(3), pages 354-68, July.
  4. Hannan, E J & Terrell, R D & Tuckwell, N E, 1970. "The Seasonal Adjustment of Economic Time Series," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 11(1), pages 24-52, February. [Downloadable!] (restricted)
Full references

Statistics
Access and download statistics

Did you know? IDEAS uses the data collected within the RePEc project, the largest online bibliographic database in Economics.

This page was last updated on 2009-11-30.


This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.