Dikaios Tserkezos () (Department of Economics, University of Crete, Greece) Maria Nikoloudaki
Abstract
A 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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Publisher Info
Paper 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 Handle: RePEc:crt:wpaper:0822
Find related papers by JEL classification: C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions 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
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