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Seasonal Adjustment Methods and Real Time Trend-Cycle Estimation pp 61–78Cite as

Seasonal Adjustment: Meaning, Purpose, and Methods

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Part of the book series: Statistics for Social and Behavioral Sciences ((SSBS))

Abstract

This chapter deals with the causes and characteristics of seasonality. For gradual changes in seasonality whether of a stochastic or a deterministic type, various models have been proposed that can be grouped into two broad categories: (1) models that assume that the generating process of seasonality varies only in amplitude and (2) models that assume that the generating process varies in both amplitude and phase. The basic assumptions of both groups of models are studied with particular reference to the two seasonal adjustment methods officially adopted by statistical agencies, the X12ARIMA and TRAMO-SEATS. The economic significance of seasonality and the need for seasonal adjustment are also discussed. Since seasonality ultimately results mainly from noneconomic forces (climatic and institutional factors), external to the economic system, its impact on the economy as a whole cannot be modified in a short period of time. Therefore, it is of interest for policy making and decision taking to have the seasonal variations removed from the original series. The main reason for seasonal adjustment is the need of standardizing socioeconomic series because seasonality affects them with different timing and intensity.

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Authors and Affiliations

  1. Department of Statistical Sciences, University of Bologna, Bologna, Italy

    Estela Bee Dagum & Silvia Bianconcini

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  1. Estela Bee Dagum
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  2. Silvia Bianconcini
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Bee Dagum, E., Bianconcini, S. (2016). Seasonal Adjustment: Meaning, Purpose, and Methods. In: Seasonal Adjustment Methods and Real Time Trend-Cycle Estimation. Statistics for Social and Behavioral Sciences. Springer, Cham. https://doi.org/10.1007/978-3-319-31822-6_3

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