IDEAS home Printed from https://ideas.repec.org/a/bla/jtsera/v14y1993i3p261-269.html
   My bibliography  Save this article

The Effect Of Aggregation On Prediction In Autoregressive Integrated Moving‐Average Models

Author

Listed:
  • L. K. Hotta
  • J. Cardosc Neto

Abstract

. Let xt be a time series generated by an autoregressive integrated moving‐average process ARIMA(p, d, q). The non‐overlapping aggregate series also follows an ARIMA process. Thus, the prediction of the aggregated observations could be done by either the disaggregate model or the aggregate model. We derive the efficiency of the predictors for two important disaggregate models, ARIMA(0, 1, 1) and ARIMA(0, 2, 2), when the models are assumed known. When the models are not known we estimate the efficiency through simulation with the models being selected using Akaike's information criterion.

Suggested Citation

  • L. K. Hotta & J. Cardosc Neto, 1993. "The Effect Of Aggregation On Prediction In Autoregressive Integrated Moving‐Average Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 14(3), pages 261-269, May.
    • Handle: RePEc:bla:jtsera:v:14:y:1993:i:3:p:261-269
    DOI: 10.1111/j.1467-9892.1993.tb00143.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1467-9892.1993.tb00143.x
    Download Restriction: no
    File URL: https://libkey.io/10.1111/j.1467-9892.1993.tb00143.x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jože Martin Rožanec & Blaž Fortuna & Dunja Mladenić, 2022. "Reframing Demand Forecasting: A Two-Fold Approach for Lumpy and Intermittent Demand," Sustainability, MDPI, vol. 14(15), pages 1-21, July.
    2. SILVESTRINI, Andrea & VEREDAS, David, 2005. "Temporal aggregation of univariate linear time series models," LIDAM Discussion Papers CORE 2005059, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. Athanasopoulos, George & Hyndman, Rob J. & Kourentzes, Nikolaos & Petropoulos, Fotios, 2017. "Forecasting with temporal hierarchies," European Journal of Operational Research, Elsevier, vol. 262(1), pages 60-74.
    4. Souza, Leonardo Rocha, 2003. "The aliasing effect, the Fejer Kernel and temporally aggregated long memory processes," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 470, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    5. George Athanasopoulos & Puwasala Gamakumara & Anastasios Panagiotelis & Rob J Hyndman & Mohamed Affan, 2019. "Hierarchical Forecasting," Monash Econometrics and Business Statistics Working Papers 2/19, Monash University, Department of Econometrics and Business Statistics.
    6. Ferrara, Laurent & Marsilli, Clément & Ortega, Juan-Pablo, 2014. "Forecasting growth during the Great Recession: is financial volatility the missing ingredient?," Economic Modelling, Elsevier, vol. 36(C), pages 44-50.
    7. George Athanasopoulos & Rob J Hyndman & Nikolaos Kourentzes & Anastasios Panagiotelis, 2023. "Forecast Reconciliation: A Review," Monash Econometrics and Business Statistics Working Papers 8/23, Monash University, Department of Econometrics and Business Statistics.
    8. Luiz Hotta & Pedro Pereira & Rissa Ota, 2004. "Effect of outliers on forecasting temporally aggregated flow variables," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 13(2), pages 371-402, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:jtsera:v:14:y:1993:i:3:p:261-269. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0143-9782 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.