Asymmetric Time Series and Temporal Aggregation
Kurt Brännäs () and
The Review of Economics and Statistics, 1999, vol. 81, issue 2, 341-344
The detection of nonlinearities could depend on the sampling frequency. Asymmetric monthly series may become symmetric when aggregated to quarterly or annual frequencies. We test against nonlinearity using the nonlinear autoregressive asymmetric moving average (ARasMA) model, which nests the linear ARMA model as a special case. Using monthly, quarterly, and annual Swedish unemployment series, we find support for symmetry/linearity in the annual series but not in the monthly and quarterly series. © 1999 by the President and Fellows of Harvard College and the Massachusetts Institute of Technology
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Working Paper: Asymmetric Cycles and Temporal Aggregation (1995)
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