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Alternative seasonal adjustment methods for aggregate Irish macroeconomic data

Author

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  • Colm McCarthy
  • John Lawlor

Abstract

Three distinct strands can be identified in the literature on seasonality. Economists have long been interested in removing high-frequency "noise" from individual economic time series, or "deseasonalizing the data" in common parlance. The second strand, on which an extensive technical literature has been developed over recent decades, treats seasonality as just one element to be encompassed in multivariate dynamic time series modeling, while a final strand seeks to model the economics of seasonality as the outcome of maximizing behavior by producing and consuming agents. Direct and indirect approaches have been compared to the seasonal adjustment of Irish macroeconomic series published by the Central Statistics Office. The presumption in the literature is that the indirect method is likely to be preferred in most real-world situations, but it is an empirical question whether it makes any great practical difference. The results indicate that it makes a very big difference indeed, with one-period growth rates frequently changing sign.

Suggested Citation

  • Colm McCarthy & John Lawlor, 2005. "Alternative seasonal adjustment methods for aggregate Irish macroeconomic data," Open Access publications 10197/566, School of Economics, University College Dublin.
  • Handle: RePEc:ucn:oapubs:10197/566
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    File URL: http://hdl.handle.net/10197/566
    File Function: Open Access version, 2005
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    References listed on IDEAS

    as
    1. Alberto Cabrero, 2000. "Seasonal Adjustment in Economic Time Series: the Experience of the Banco de España (with the model-based method)," Working Papers 0002, Banco de España.
    2. Agustín Maravall, 2002. "An Application of TRAMO-SEATS: Automatic Procedure and Sectoral Aggregation," Working Papers 0207, Banco de España.
    Full references (including those not matched with items on IDEAS)

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