Temporal Aggregation Effects In Choosing The Optimal Lag Order In Stable Arma Models. Some Monte Carlo Results
AbstractA crucial aspect of empirical research based on ARIMA(p,q) model is the choice of the appropriate lag order. Several criteria have been used in order to identify the appropriate order of a ARIMA(p,q) process. In this paper we investigate the effects of using a variation of selection criteria under different temporal aggregation levels. We don�t spend our attention in determining the appropriate order but on the effects of using the above selection criteria on the dynamic characteristics (impulse responses) and the forecasting properties of the ARIMA(p,q) process. The conducted Monte Carlo simulation experiments show that the use of temporally aggregated data can affect seriously the impulse responses and the forecasting properties of the ARIMA model.
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Bibliographic InfoPaper provided by University of Crete, Department of Economics in its series Working Papers with number 0822.
Length: 12 pages
Date of creation: 01 Jan 2005
Date of revision:
Publication status: Published in IWA International Conference on Water Economics, Statistics, and Finance
Stable ARMA process; temporal aggregation and stochastic simulation;
Find related papers by JEL classification:
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple 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
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Granger, C. W. J. & Siklos, Pierre L., 1995.
"Systematic sampling, temporal aggregation, seasonal adjustment, and cointegration theory and evidence,"
Journal of Econometrics,
Elsevier, vol. 66(1-2), pages 357-369.
- Granger, C.W.J. & Siklos, P.L., 1993. "Systematic Sampling, Temporal Aggregation, Seasonal Adjustment, and Cointegration: Theory and Evidence," Working Papers 93001, Wilfrid Laurier University, Department of Economics.
- Ng, Serena, 1995. "Testing for unit roots in flow data sampled at different frequencies," Economics Letters, Elsevier, vol. 47(3-4), pages 237-242, March.
- Wei, William W. S., 1978. "The effect of temporal aggregation on parameter estimation in distributed lag model," Journal of Econometrics, Elsevier, vol. 8(2), pages 237-246, October.
- Zellner, Arnold & Montmarquette, Claude, 1971. "A Study of Some Aspects of Temporal Aggregation Problems in Econometric Analyses," The Review of Economics and Statistics, MIT Press, vol. 53(4), pages 335-42, November.
- 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.
- Drost, F.C. & Nijman, T.E., 1990.
"Temporal aggregation of GARCH processes,"
1990-66, Tilburg University, Center for Economic Research.
- Drost, F.C. & Nijman, T.E., 1993. "Temporal aggregation of GARCH processes," Open Access publications from Tilburg University urn:nbn:nl:ui:12-153273, Tilburg University.
- Drost, F.C. & Nijman, T.E., 1990. "Temporal Aggregation Of Garch Processes," Papers 9066, Tilburg - Center for Economic Research.
- Drost, F.C. & Nijman, T.E., 1992. "Temporal aggregation of GARCH processes," Discussion Paper 1992-40, Tilburg University, Center for Economic Research.
- Drost, F.C. & Nijman, T.E., 1992. "Temporal Aggregation of Garch Processes," Papers 9240, Tilburg - Center for Economic Research.
- Otero, Jesus & Smith, Jeremy, 2000. "Testing for cointegration: power versus frequency of observation -- further Monte Carlo results," Economics Letters, Elsevier, vol. 67(1), pages 5-9, April.
- Weiss, Andrew A., 1984. "Systematic sampling and temporal aggregation in time series models," Journal of Econometrics, Elsevier, vol. 26(3), pages 271-281, December.
- Dikaios Tserkezos, E., 1992. "Forecasting residential electricity consumption in Greece using monthly and quarterly data," Energy Economics, Elsevier, vol. 14(3), pages 226-232, July.
- 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.
- Pierse, R. G. & Snell, A. J., 1995. "Temporal aggregation and the power of tests for a unit root," Journal of Econometrics, Elsevier, vol. 65(2), pages 333-345, February.
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