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Another Look at Swedish Business Cycles, 1861-1988

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  • Skalin, Joakim

    () (Dept for Economic Affairs, Ministry of Finance)

  • Teräsvirta, Timo

    () (Department of Economic Statistics)

Abstract

This paper considers nine long Swedish macroeconomic time series whose business cycle properties were discussed by Englund, Persson, and Svensson (1992) using frequency domain techniques. It is found by testing that all but two of the logarithmed and difference series are non-linear. The observed nonlinearity is characterized by STAR models. The statistical and dynamic properties of the estimated STAR models are investigated using, among other things, parametrically estimated ‘local’ or ‘sliced’ spectra. Cyclical variation at business cycle frequencies does not seem to be constant over time for all series, and it is difficult to find a ‘Swedish business cycle’. Only two series may be regarded as having genuinely assymetric cyclical variation. Standard Granger non-causality tests are adapted to the nonlinear (STAR) case, and the null hypothesis of noncausality is tested for pairs of series. The results point at strong temporal interactions between series. They also indicate that the assumption of functional form (linear or STAR) strongly affects the outcome of these pairwise tests.

Suggested Citation

  • Skalin, Joakim & Teräsvirta, Timo, 1996. "Another Look at Swedish Business Cycles, 1861-1988," SSE/EFI Working Paper Series in Economics and Finance 130, Stockholm School of Economics.
  • Handle: RePEc:hhs:hastef:0130
    Note: This is the working paper version appearing in the References of the published version (Journal of Applied Econometrics 14, 359-378 (1999).
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    References listed on IDEAS

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    More about this item

    Keywords

    Granger causality; model spectrum; linearity test; time series model; nonlinearity; smooth transition autoregression;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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