This paper extends the notions of common cycles and common seasonal features to time series having deterministic and stochastic seasonality at different frequencies. The conditions under which quarterly time series with these characteristics have common features are investigated, various representations are presented and statistical inference is discussed. Finally, the analysis is applied to study comovements between different components of consumption and income using UK data.
In this note we analyze via Monte Carlo simulations how serial correlation common features test statistics behave when X-11 seasonal adjusted data are encountered. We emphasize both size and power distortions. We illustrate the analysis on Japanese consumption/income relationship.
Berzelius failed to make use of Faraday's electrochemical laws in his laborious determination of equivalent weights.