Structural time series models are formulated in terms of components, such as trends,
seasonals and cycles, that have a direct interpretation. As well as providing a framework for …

Eric Ghysels and Denise R. Osborn provide a thorough and timely review of the recent
developments in the econometric analysis of seasonal economic time series, summarizing a …

Monthly data on road casualties in Great Britain are analysed in order to assess the effects
on casualty rates of the seat belt law introduced on January 31st, 1983. Such analysis is …

Seasonal adjustment has a long and well-documented tradition; see, for example, Nerlove,
Grether and Carvalho (1979), Zellner (1978), Moore et al (1981), Den Butter and Fase …

The paper considers stochastic linear trends in series with a higher than annual frequency of
observation. Using an approach based on ARIMA models, some of the trend models (or the …

I consider estimation and seasonal adjustment of population means based on rotating panel
surveys carried out at regular time intervals. The analysis uses a dynamic structural model …

We examine the implications of treating seasonality as an unobserved component which
changes slowly over time. This approach simplifies the specification of dynamic …

Several important economic time series are recorded on a particular day every week.
Seasonal adjustment of such series is difficult because the number of weeks varies between …

Many series are subject to data irregularities such as missing values, outliers, structural
breaks, and irregular spacing. Data can also be messy, and hence difficult to handle by …

This article describes a simple method of estimating the autocorrelations of survey errors for
the case of rotating-panel sampling designs. Such designs are in routine use, for example …