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Temporal aggregaton of univariate linear time series models

  • Andrea, SILVESTRINI

In this paper we feature state-of-the-art econometric methodology of temporal aggregation for univariate linear time series, namely ARIMA-GARCH models. We present a unified overview of temporal aggregation techniques for this broad class of processes and we explain in detail, although intuitively, the technical machinery behind the results. An empirical application with Belgian public deficit data illustrates the main issues.

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File URL: http://sites.uclouvain.be/econ/DP/IRES/2005-44.pdf
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Paper provided by Université catholique de Louvain, Département des Sciences Economiques in its series Discussion Papers (ECON - Département des Sciences Economiques) with number 2005044.

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Length: 46
Date of creation: 01 Aug 2005
Date of revision:
Handle: RePEc:ctl:louvec:2005044
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  1. Granger, C. W. J., 1987. "Implications of Aggregation with Common Factors," Econometric Theory, Cambridge University Press, vol. 3(02), pages 208-222, April.
  2. Laurent Moulin & Matteo Sala & Andrea Silvestrini & David Veredas, 2008. "Using intra annual information to forecast the annual state deficit. The case of France," ULB Institutional Repository 2013/136217, ULB -- Universite Libre de Bruxelles.
  3. Yue Fang & Sergio G. Koreisha, 2004. "Updating ARMA predictions for temporal aggregates," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(4), pages 275-296.
  4. Clive Granger & Tae-Hwy Lee, 1999. "The effect of aggregation on nonlinearity," Econometric Reviews, Taylor & Francis Journals, vol. 18(3), pages 259-269.
  5. Tommaso Proietti, 2004. "On the Estimation of Nonlinearly Aggregated Mixed Models," Econometrics 0411012, EconWPA.
  6. Drost, Feike C & Nijman, Theo E, 1993. "Temporal Aggregation of GARCH Processes," Econometrica, Econometric Society, vol. 61(4), pages 909-27, July.
  7. Nijman, T.E. & Palm, F.C., 1984. "Missing observations in the dynamic regression model," Other publications TiSEM 4d689d7c-4d89-4ab6-b8c3-f, Tilburg University, School of Economics and Management.
  8. Drost, F.C. & Werker, B.J.M., 1994. "Closing the GARCH gap : Continuous time GARCH modeling," Discussion Paper 1994-2, Tilburg University, Center for Economic Research.
  9. Nelson, Daniel B., 1990. "ARCH models as diffusion approximations," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 7-38.
  10. Oscar Jordà & Massimiliano Marcellino, 2004. "Time-scale transformations of discrete time processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(6), pages 873-894, November.
  11. BAUWENS, Luc & LAURENT, Sébastien & ROMBOUTS, Jeroen VK, . "Multivariate GARCH models: a survey," CORE Discussion Papers RP 1847, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  12. Nijman, T.E. & Palm, F.C., 1987. "Predictive accuracy gain from disaggregate sampling in ARIMA-models," Research Memorandum FEW 273, Tilburg University, School of Economics and Management.
  13. Hafner, C.M. & Rombouts, J.V.K., 2004. "Estimation of temporally aggregated multivariate GARCH models," Econometric Institute Research Papers EI 2004-30, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  14. Palm, F.C. & Nijman, T.E., 1990. "Parameter identification in ARMA-processes in the presence of regular but incomplete sampling," Other publications TiSEM 69e84dde-44ef-4592-93a8-8, Tilburg University, School of Economics and Management.
  15. Luiz Hotta & Pedro Pereira & Rissa Ota, 2004. "Effect of outliers on forecasting temporally aggregated flow variables," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer, vol. 13(2), pages 371-402, December.
  16. Drost, F.C. & Nijman, T.E., 1993. "Temporal aggregation of GARCH processes," Other publications TiSEM 0642fb61-c7f4-4281-b484-4, Tilburg University, School of Economics and Management.
  17. Lutkepohl, Helmut, 1984. "Forecasting Contemporaneously Aggregated Vector ARMA Processes," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(3), pages 201-14, July.
  18. Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
  19. Christian M. Hafner, 2004. "Temporal aggregation of multivariate GARCH processes," Econometric Society 2004 North American Winter Meetings 538, Econometric Society.
  20. Clive W. J. Granger, 1988. "Aggregation of time series variables-a survey," Discussion Paper / Institute for Empirical Macroeconomics 1, Federal Reserve Bank of Minneapolis.
  21. William W. S. Wei, 1978. "Some Consequences of Temporal Aggregation in Seasonal Time Series Models," NBER Chapters, in: Seasonal Analysis of Economic Time Series, pages 433-448 National Bureau of Economic Research, Inc.
  22. Marcellino, Massimiliano, 1999. "Some Consequences of Temporal Aggregation in Empirical Analysis," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(1), pages 129-36, January.
  23. Granger, C. W. J., 1980. "Long memory relationships and the aggregation of dynamic models," Journal of Econometrics, Elsevier, vol. 14(2), pages 227-238, October.
  24. Weiss, Andrew A., 1984. "Systematic sampling and temporal aggregation in time series models," Journal of Econometrics, Elsevier, vol. 26(3), pages 271-281, December.
  25. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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