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Time-scale transformations of discrete time processes

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  • Oscar Jordà
  • Massimiliano Marcellino

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 are 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. Copyright 2004 Blackwell Publishing Ltd.

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Bibliographic Info

Article provided by Wiley Blackwell in its journal Journal of Time Series Analysis.

Volume (Year): 25 (2004)
Issue (Month): 6 (November)
Pages: 873-894

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Handle: RePEc:bla:jtsera:v:25:y:2004:i:6:p:873-894

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References

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  1. Ricardo J. Caballero & Eduardo M.R.A. Engel, 1992. "Microeconomic Adjustment Hazards and Aggregate Dynamics," NBER Working Papers 4090, National Bureau of Economic Research, Inc.
  2. Stock, James H, 1987. "Measuring Business Cycle Time," Journal of Political Economy, University of Chicago Press, University of Chicago Press, vol. 95(6), pages 1240-61, December.
  3. Hannan, E J, 1971. "The Identification Problem for Multiple Equation Systems with Moving Average Errors," Econometrica, Econometric Society, Econometric Society, vol. 39(5), pages 751-65, September.
  4. Marcellino, Massimiliano, 1999. "Some Consequences of Temporal Aggregation in Empirical Analysis," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 17(1), pages 129-36, January.
  5. Hinich, Melvin J., 1999. "Sampling Dynamical Systems," Macroeconomic Dynamics, Cambridge University Press, Cambridge University Press, vol. 3(04), pages 602-609, December.
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  7. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, Econometric Society, vol. 57(2), pages 357-84, March.
  8. Oscar Jorda, . "Random-Time Aggregation In Partial Ajustment Models," Department of Economics, California Davis - Department of Economics 97-32, California Davis - Department of Economics.
  9. Rothenberg, Thomas J, 1971. "Identification in Parametric Models," Econometrica, Econometric Society, Econometric Society, vol. 39(3), pages 577-91, May.
  10. Stock, James H., 1987. "Measuring Business Cycle Time," Scholarly Articles 3425950, Harvard University Department of Economics.
  11. Weiss, Andrew A., 1984. "Systematic sampling and temporal aggregation in time series models," Journal of Econometrics, Elsevier, Elsevier, vol. 26(3), pages 271-281, December.
  12. 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, American Statistical Association, vol. 12(3), pages 279-88, July.
  13. Robert F. Engle & Jeffrey R. Russell, 1998. "Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data," Econometrica, Econometric Society, Econometric Society, vol. 66(5), pages 1127-1162, September.
  14. Brewer, K. R. W., 1973. "Some consequences of temporal aggregation and systematic sampling for ARMA and ARMAX models," Journal of Econometrics, Elsevier, Elsevier, vol. 1(2), pages 133-154, June.
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Cited by:
  1. Shigeru Fujita & Garey Ramey, 2006. "The cyclicality of job loss and hiring," Working Papers 06-17, Federal Reserve Bank of Philadelphia.
  2. Andrea, SILVESTRINI, 2005. "Temporal aggregaton of univariate linear time series models," Discussion Papers (ECON - Département des Sciences Economiques), Université catholique de Louvain, Département des Sciences Economiques 2005044, Université catholique de Louvain, Département des Sciences Economiques.

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