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Time-Scale Transformations of Discrete-Time Processes

Author

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  • Oscar Jorda
  • Massimiliano Marcellino

    (Department of Economics, University of California Davis)

Abstract

This paper investigates the effects of temporal aggregation when the aggregation frequency is variable and possibly stochastic. The results that we report include, as a particular case, the well-known results on fixed-interval aggregation, such as when monthly data is aggregated into quarters. A variable aggregation frequency implies that the aggregated process will exhibit time-varying parameters and non-spherical disturbances, even when these characteristics are absent from the original model. Consequently, we develop methods for specification and estimation of the aggregate models and show with an example how these methods perform in practice.

Suggested Citation

  • Oscar Jorda & Massimiliano Marcellino, 2003. "Time-Scale Transformations of Discrete-Time Processes," Working Papers 32, University of California, Davis, Department of Economics.
  • Handle: RePEc:cda:wpaper:03-2
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    File URL: http://wp.econ.ucdavis.edu/03-2.pdf
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    References listed on IDEAS

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    1. Weiss, Andrew A., 1984. "Systematic sampling and temporal aggregation in time series models," Journal of Econometrics, Elsevier, vol. 26(3), pages 271-281, December.
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    4. Marcellino, M., 1997. "Temporal Disaggregation, Missing Observations, Outliers, and Forecasting: A Unifying Non-Model Based Procedures," Economics Working Papers eco97/30, European University Institute.
    5. Jorda, Oscar, 1999. "Random-Time Aggregation in Partial Adjustment Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(3), pages 382-395, July.
    6. White,Halbert, 1996. "Estimation, Inference and Specification Analysis," Cambridge Books, Cambridge University Press, number 9780521574464.
    7. Stock, James H, 1987. "Measuring Business Cycle Time," Journal of Political Economy, University of Chicago Press, vol. 95(6), pages 1240-1261, December.
    8. Rothenberg, Thomas J, 1971. "Identification in Parametric Models," Econometrica, Econometric Society, vol. 39(3), pages 577-591, May.
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    10. Arthur F. Burns & Wesley C. Mitchell, 1946. "Measuring Business Cycles," NBER Books, National Bureau of Economic Research, Inc, number burn46-1.
    11. Marcellino, Massimiliano, 1999. "Some Consequences of Temporal Aggregation in Empirical Analysis," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(1), pages 129-136, January.
    12. Brewer, K. R. W., 1973. "Some consequences of temporal aggregation and systematic sampling for ARMA and ARMAX models," Journal of Econometrics, Elsevier, vol. 1(2), pages 133-154, June.
    13. Durland, J Michael & McCurdy, Thomas H, 1994. "Duration-Dependent Transitions in a Markov Model of U.S. GNP Growth," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 279-288, July.
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    Citations

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    Cited by:

    1. SILVESTRINI, Andrea & VEREDAS, David, 2005. "Temporal aggregation of univariate linear time series models," CORE Discussion Papers 2005059, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Robert Kunst & Philip Franses, 2015. "Asymmetric time aggregation and its potential benefits for forecasting annual data," Empirical Economics, Springer, vol. 49(1), pages 363-387, August.
    3. Ramey, Garey & Shigeru Fujita, 2006. "The Cyclicality of Job Loss and Hiring," University of California at San Diego, Economics Working Paper Series qt4nz8p839, Department of Economics, UC San Diego.

    More about this item

    Keywords

    time aggregation; time-scale transformation; irregularly spaced data; autoregressive conditional intensity model.;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • F31 - International Economics - - International Finance - - - Foreign Exchange

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