Please use this identifier to cite or link to this item:
Type: Artigo de periódico
Title: Effect of outliers on forecasting temporally aggregated flow variables
Author: Hotta, LK
Pereira, PLV
Ota, R
Abstract: Economic time series are of two types: stock and flows, and may be available at different levels of aggregation (for instance, monthly or quarterly). The economist., in many situations, is interested in forecasting the aggregated observations. The forecast function, in this case, can be based either on the disaggregated series or the aggregated series. The forecasts based on the disaggregated data are at least as efficient, in terms of mean squared forecast errors, as the forecasts based on temporally aggregated observations when the data generating process (DGP) is a known ARIMA process. However, the effect of outliers on both forecast functions is not known. In this paper, we consider the effect of additive and innovation outliers on forecasting aggregated values based on aggregated and disaggregated models when the DGP is a known ARIMA process and the presence of the outliers is ignored. Results when the model is not known and tests applied for the detection of outliers are derived through simulation.
Subject: additive outliers
innovation outliers
temporal aggregation
Country: Espanha
Editor: Sociedad Estadistica Investigacion Operativa
Rights: fechado
Identifier DOI: 10.1007/BF02595778
Date Issue: 2004
Appears in Collections:Unicamp - Artigos e Outros Documentos

Files in This Item:
File Description SizeFormat 
WOS000225996400005.pdf1.38 MBAdobe PDFView/Open

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.