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Modelling Business Cycle Features Using Switching Regime Models

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  • Hans-Martin Krolzig
  • Michael P. Clements

Abstract

The ability of Markov-switching (MS) autoregressive models to replicate selected classical business-cycle features found in US post-war consumption, investment and output is compared to that of linear models. Univariate MS models appear to offer more dynamically parsimonious representations, but generally are unable to reproduce features missed by linear models. In the multivariate models, some cointegration restrictions were found to have a crucial impact, and the ability of models that imposed cointegration to reproduce business cycle features was enhanced by Markov-switching

Suggested Citation

  • Hans-Martin Krolzig & Michael P. Clements, 2001. "Modelling Business Cycle Features Using Switching Regime Models," Economics Series Working Papers 58, University of Oxford, Department of Economics.
  • Handle: RePEc:oxf:wpaper:58
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    References listed on IDEAS

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    Cited by:

    1. Melike Bildirici & Özgür Ömer Ersin, 2014. "Nonlinearity, Volatility and Fractional Integration in Daily Oil Prices: Smooth Transition Autoregressive ST-FI(AP)GARCH Models," Journal for Economic Forecasting, Institute for Economic Forecasting, pages 108-135.
    2. Matteo Manera & Alessandro Cologni, 2006. "The Asymmetric Effects of Oil Shocks on Output Growth: A Markov-Switching Analysis for the G-7 Countries," Working Papers 2006.29, Fondazione Eni Enrico Mattei.

    More about this item

    Keywords

    business cycle asymmetries; Markov-switching models; cointegration;

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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