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Missing observations in ARIMA models: Skipping approach versus additive outlier approach

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  • Gomez, Victor
  • Maravall, Agustin
  • Pena, Daniel

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  • Gomez, Victor & Maravall, Agustin & Pena, Daniel, 1998. "Missing observations in ARIMA models: Skipping approach versus additive outlier approach," Journal of Econometrics, Elsevier, vol. 88(2), pages 341-363, November.
    • Handle: RePEc:eee:econom:v:88:y:1998:i:2:p:341-363
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    1. S. R. Brubacher & G. Tunnicliffe Wilson, 1976. "Interpolating Time Series with Application to the Estimation of Holiday Effects on Electricity Demand," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 25(2), pages 107-116, June.
    2. Sargan, J D & Drettakis, E G, 1974. "Missing Data in an Autoregressive Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 15(1), pages 39-58, February.
    3. Maravall, Agustín, 1992. "Missing observations and additive outliers in time series models," UC3M Working papers. Economics 2888, Universidad Carlos III de Madrid. Departamento de Economía.
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    Cited by:

    1. Qian, Hang, 2012. "Essays on statistical inference with imperfectly observed data," ISU General Staff Papers 201201010800003618, Iowa State University, Department of Economics.
    2. Carlos Carrillo‐Tudela & Ludo Visschers, 2023. "Unemployment and Endogenous Reallocation Over the Business Cycle," Econometrica, Econometric Society, vol. 91(3), pages 1119-1153, May.
    3. Doornik, Jurgen A. & Ooms, Marius, 2008. "Multimodality in GARCH regression models," International Journal of Forecasting, Elsevier, vol. 24(3), pages 432-448.
    4. Brunhes-Lesage, V. & Darné, O., 2008. "Why calculate a business sentiment indicator for services?," Quarterly selection of articles - Bulletin de la Banque de France, Banque de France, issue 13, pages 21-30, Autumn.
    5. Gianluca Caporello & Agustín Maravall & Fernando J. Sánchez, 2001. "Program TSW Reference Manual," Working Papers 0112, Banco de España.
    6. Andy Lee & John Yick & Yer Van Hui, 2001. "Sensitivity of the portmanteau statistic in time series modeling," Journal of Applied Statistics, Taylor & Francis Journals, vol. 28(6), pages 691-702.
    7. Alonso, Andres M. & Sipols, Ana E., 2008. "A time series bootstrap procedure for interpolation intervals," Computational Statistics & Data Analysis, Elsevier, vol. 52(4), pages 1792-1805, January.
    8. Shigeru Fujita & Christopher J. Nekarda & Garey Ramey, 2007. "The cyclicality of worker flows: new evidence from the SIPP," Working Papers 07-5, Federal Reserve Bank of Philadelphia.
    9. Zudi Lu & Y. Hui, 2003. "L 1 linear interpolator for missing values in time series," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 55(1), pages 197-216, March.
    10. Maravall, Agustin, 2006. "An application of the TRAMO-SEATS automatic procedure; direct versus indirect adjustment," Computational Statistics & Data Analysis, Elsevier, vol. 50(9), pages 2167-2190, May.
    11. Andrés Alonso & Ana Sipols & Silvia Quintas, 2013. "A single-index model procedure for interpolation intervals in time series," Computational Statistics, Springer, vol. 28(4), pages 1463-1484, August.

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