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

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  • Jalles, Joao Tovar

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

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

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Length: 30 pages
Date of creation: 2009
Date of revision:
Handle: RePEc:unl:unlfep:wp541

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  1. Andrew C Harvey & Andrew Scott, 1994. "Seasonality in Dynamic Regression Models," CEP Discussion Papers dp0184, Centre for Economic Performance, LSE.
  2. 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.
  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. Harvey, A C & Jaeger, A, 1993. "Detrending, Stylized Facts and the Business Cycle," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(3), pages 231-47, July-Sept.
  5. Pierce, David A & Grupe, Michael R & Cleveland, William P, 1984. "Seasonal Adjustment of the Weekly Monetary Aggregates: A Model-based Approach," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(3), pages 260-70, July.
  6. 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.
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Cited by:
  1. A. Bers & Fernando Momo & Irene Schloss & Doris Abele, 2013. "Analysis of trends and sudden changes in long-term environmental data from King George Island (Antarctica): relationships between global climatic oscillations and local system response," Climatic Change, Springer, vol. 116(3), pages 789-803, February.
  2. Dilaver, Zafer & Hunt, Lester C, 2011. "Modelling and forecasting Turkish residential electricity demand," Energy Policy, Elsevier, vol. 39(6), pages 3117-3127, June.
  3. Rude, James & Surry, Yves, 2013. "Canadian Hog Supply Respose: A Provincial Level Analysis," Working Papers 148590, Structure and Performance of Agriculture and Agri-products Industry (SPAA).

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