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An exact multivariate model-based structural decomposition

dc.contributor.authorCasals Carro, José
dc.contributor.authorJerez Méndez, Miguel
dc.contributor.authorSotoca López, Sonia
dc.date.accessioned2023-06-21T01:38:36Z
dc.date.available2023-06-21T01:38:36Z
dc.date.issued2000
dc.description.abstractWe describe a simple procedure for decomposing a vector of time series into trend, cycle, seasonal and irregular components. Contrary to common practice, we do not assume these components to be orthogonal conditional on their past. However, the state-space representation employed assures that their smoothed estimates converge to exact values, with null variances and covariances. Among ather implications, this means that the components are not revised when the sample increases. The practical application of the method is illustrated both with simulated and real data.
dc.description.facultyFac. de Ciencias Económicas y Empresariales
dc.description.facultyInstituto Complutense de Análisis Económico (ICAE)
dc.description.refereedTRUE
dc.description.statuspub
dc.eprint.idhttps://eprints.ucm.es/id/eprint/29230
dc.identifier.relatedurlhttp://www.ucm.es/icae
dc.identifier.urihttps://hdl.handle.net/20.500.14352/64235
dc.issue.number06
dc.language.isoeng
dc.page.total40
dc.publication.placeMadrid
dc.publisherFacultad de Ciencias Económicas y Empresariales. Instituto Complutense de Análisis Económico (ICAE)
dc.relation.ispartofseriesDocumentos de Trabajo del Instituto Complutense de Análisis Económico (ICAE)
dc.rightsAtribución-NoComercial-CompartirIgual 3.0 España
dc.rights.accessRightsopen access
dc.rights.urihttps://creativecommons.org/licenses/by-nc-sa/3.0/es/
dc.subject.keywordState-space models
dc.subject.keywordSeasonal adjustment
dc.subject.keywordTrends
dc.subject.keywordUnobserved components.
dc.subject.ucmAnálisis Multivariante
dc.subject.unesco1209.09 Análisis Multivariante
dc.titleAn exact multivariate model-based structural decomposition
dc.typetechnical report
dc.volume.number2000
dcterms.referencesAnderson, B.D.O. and J.B. Moore (1979). Optimal Filtering, Prentice-Hall, Englewood Cliffs, NJ. Aoki, M. (1990). State Space Modeling of Time Series, Springer-Verlag, Heidelberg. Bell, W.R. (1984). "Signal Extraction for Non-Stationary Time Series," Annals of Statistics, 12, 646-664. Bell, W.R. and S.C. Hillmer (1984). "Issues Involved with the Seasonal Adjustment of Economic Time Series," Journal of Business and Economic Statistics, 2, 291-320. Box, G.E.P., S.C. Hillmer and G.C. Tiao (1978). "Analysis and Modeling of Seasonal Time Series," in A Zellner (ed.), Seasonal Analysis of Time Series, Bureau of the Census (Washington, D.C.). Box, G.E.P., D.A Pierce and P. Newbold (1987). "Estimating Trend and Growth Rates Analysis in Seasonal Time Series," Journal of The American Statistical Association, 82, 397, 276-282. Burman, J.P. (1980). "Seasonal Adjustment by Signal Extraction," Journal of the Royal Statistical Society, series A, 143, 321-337. Casals, J., Sotoca, S. y Jerez, M. (1999). "A Fast and Stable Method to Compute the Likelihood of Time Invariant State-Space Models," Economics Letters, 65, 329-337. Casals, J., M. Jerez and S. Sotoca (2000). "Exact Smoothing for Stationary and Nonstationary Time Series," Internatfonal Journal of Forecasting, 16, 1, 59-69. De Souza, C.E., M.R. Gevers and G.C. Goodwin (1986). "Riccati Equations in Optimal Filtering of Nonstabilizable Systems having Singular State Transition Matrices," IEEE Transactions on Automatic Control, Vol AC-31, 9, 831-838. Engle, R.F. (1978). "Estimating Structural Models of Seasonality," in A. Zellner (ed.), Seasonal Analysis of Time Series, Bureau of the Census (Washington, D.C.). Engle, R.F. and S. Kozicki (1993). "Testing for Common Features," Journal of Business and Economic Statistics, 11, 369-380. Espasa, A. and D. Peña (1995). "The Decomposition of Forecast in Seasonal ARIMA Models," Journal of Forecasting, 14, 7, 565-583. Findley, D.B. B.C. Monsell, W.R. Bell, M.C. Otto and E. Chen (1998). "New Capabilities and Methods of the X-12-ARIMA Seasonal-Adjustment Program," Journal of Business and Economic Statistics, 16, 127-177. García-Ferrer, A. and J. del Hoyo (1992). "On Trend Extraction Models: Interpretation, Empirical evidence and Forecasting Performance," Journal of Forecasting, 11, 8, 645-665. García-Ferrer, A. and R. Queralt (1998). "Can Univariate Models Forecast Turning Points in Seasonal Economic Time Series?", International Journal of Forecasting, 14, 433-446. Gómez, V. and A Maravall (1996). "Programs TRAMO and SEATS: Instructions for the User," Working paper 9628, Bank of Spain, Madrid (http://www.bde.es/sen.icio/software/software.htm). Harvey, A.C. (1989). Forecasting, Structural Time Series Models and the Kalman Filter, Cambridge University Press (Cambridge). Harvey, A.C. and N. Shephard (1993). "Structural Time Series Models," in G.S. Maddala, C.R. Rao and H.D. Vinod (eds.), Handbook of Statistics, vol. 11, 261-302, Elsevier Science Publishers, Amsterdam. Hillmer, S.C. and G.C. Tiao (1982). "An ARIMA-Model-Based Approach to Seasonal Adjustment," Journal of the American Statistical Association, 77, 63-70. Hodrick, R.J. and E.C. Prescott (1980). "Post-war U.S. Business Cycles," Carnegie Mellon University Working Paper. Ionescu, V., C. Oara and M. Weiss (1997). "General Matrix Pencil Techniques for the Solution of Algebraic Riccati Equations: A Unified Approach." IEEE Transactions on Automatic Control, 42, 8, 1085-1097. Jenkins, G.M. and A.S. Alavi (1981). "Some Aspects of Modelling and Forecasting Multivariate Time Series," Journal of Time Series Analysis, 2, 1, 1-47. Kohn, R. and Ansley, C.F. (1986). "Estimation, Prediction, and Interpolation for ARIMA Models with Missing Data.," Journal of the American Statistical Association, 81, 751-761. Koopman, S.J., A.C. Harvey, J.A. Doornik and N. Shephard (1995). Stamp 5.0 Structural Time Series Analyser, Modeller and Predictor, Chapman & Hall, London. Petkov, P. Hr., N.D. Christov and M.M. Konstantinov (1991). Computational Methods for linear Control Systems, Prentice-Hall, Englewood Cliffs, New Jersey. Planas, C. (1997). Applied Time Series Analysis: Modeling, Forecasting, Unobserved Components Analysis and the Wiener-Kolmogorov Filter, Eurostat. (This work can be downloaded at http://europa.eu.int/en/comm/eurostat/research/noris4/) Pole, A., M. West and J. Harrison (1994). Applied Bayesian Forecasting and Time Series Analysis, Chapman & Hall, London. Shiskin, J., A.H. Young and J.C. Musgrave (1967). "The X-11 Variant of the Census Method II Seasonal Adjustment Program," Technical Paper, Bureau of the Census (Washington D.C.). Terceiro, J. (1990). Estimation of Dynamic Econometric Models with Errors in Variables. Springer-Verlag, Berlin. West, M. (1997). "Time Series Decomposition and Analysis in a Study of Oxygen Isotope Records," Biometrika, 84, 489-494. Young, P.C. and J. Brenner (1991). MicroCAPTAIN Handbook: Version 2.0, Lancaster University: Centre for Research on Environmental Systems and Statistics, Lancaster, U.K. Young, P., D.J. Pedregal and W. Tych (1999). "Dynamic Harmonic Regression," Journal of Forecasting, 18,369-394.
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