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Temporal aggregation of univariate and multivariate time series models: A survey

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Author Info
Andrea Silvestrini () (Bank of Italy, Economics and International Relations and CORE, Université catholique de Louvain.)
David Veredas () (ECARES, Université Libre de Bruxelles and CORE, Université catholique de Louvain, Belgium)

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Abstract

We present a unified and up-to-date overview of temporal aggregation techniques for univariate and multivariate time series models explaining in detail how these techniques are employed. Some empirical applications illustrate the main issues.

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Paper provided by Bank of Italy, Economic Research Department in its series Temi di discussione (Economic working papers) with number 685.

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Date of creation: Aug 2008
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Handle: RePEc:bdi:wptemi:td_685_08

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Keywords: Temporal aggregation; ARIMA; Seasonality; GARCH; Vector ARMA; Spurious causality; Multivariate GARCH;

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Find related papers by JEL classification:
C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - General
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions
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

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Cited by:
(explanations, 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.)

  1. Helmut Luetkepohl, 2009. "Forecasting Aggregated Time Series Variables: A Survey," Economics Working Papers ECO2009/17, European University Institute. [Downloadable!]
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