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On Periodic Correlations between Estimated Seasonal and Nonseasonal Components in German and U.S. Unemployment

Marius Ooms () and Philip Hans Franses

Journal of Business & Economic Statistics, 1997, vol. 15, issue 4, 470-81

Abstract: The authors examine the orthogonality assumption of seasonal and nonseasonal components for official quarterly unemployment figures in Germany and the United States. Although nonperiodic correlations do not seem to reject the orthogonality assumption, a periodic analysis based on correlation functions that vary with the seasons indicates the violation of orthogonality. The authors find that the unadjusted data can be described by periodic autoregressive models with a unit root. In simulations, the authors replicate the empirical findings for the German data, where they use these simple models to generate artificial samples. Multiplicative seasonal adjustment leads to large periodic correlations. Additive adjustment leads to smaller ones.

Date: 1997
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