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Time series models of GDP: a reappraisal

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  • Marchese, Malvina

Abstract

We propose a model diagnostic device to compare different linear and non linear parametric time series models of real GDP business cycle.The comparison appears of remarkable economic importance since different models have very different implications in term of long run persistence of negative shocks on the level of aggregate output.On the basis of the proposed diagnostic six popular models of real GDP are compared in a Monte Carlo simulation.We find that SETAR models and three stages Markov-switching models significantlly overperform the other statistical representation of the series.Since the SETAR form of non linearity is far easier to handle for both estimation and testing we argue in their favour.

Suggested Citation

  • Marchese, Malvina, 2010. "Time series models of GDP: a reappraisal," MPRA Paper 36389, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:36389
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    References listed on IDEAS

    as
    1. Potter, Simon M, 1995. "A Nonlinear Approach to US GNP," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(2), pages 109-125, April-Jun.
    2. Chang‐Jin Kim & James Morley & Jeremy Piger, 2005. "Nonlinearity and the permanent effects of recessions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(2), pages 291-309.
    3. John Y. Campbell & N. Gregory Mankiw, 1987. "Are Output Fluctuations Transitory?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 102(4), pages 857-880.
    4. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
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    More about this item

    Keywords

    SETAR models; ARMA models; Markov-switching models; impulse response functions; residual based misspecification tests; busyness-cycle stylized facts;
    All these keywords.

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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