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Forecasting European GDP Using Self-Exciting Threshold Autoregressive Models. A Warning

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  • Crespo-Cuaresma, Jesus

    (Institute for Advanced Studies, Vienna)

Abstract

A two-regime self-exciting threshold autoregressive process is estimated for quarterly aggregate GDP of the fifteen countries that compose the European Union, and the forecasts from this nonlinear model are compared, by means of a Monte Carlo simulation, with those from a simple autoregressive model, whose lag length is chosen to minimize Akaike's AIC criterion. The results are very negative for the SETAR model when the Monte Carlo procedure is used to generate multi-step forecasts. When the "naive" procedure of generating forecasts is used, the results are surprisingly better for the SETAR model in long-term predictions. Due to the characteristics of the residuals, a bootstrapping method of forecasting was also used, yielding even poorer results for the nonlinear model.

Suggested Citation

  • Crespo-Cuaresma, Jesus, 2000. "Forecasting European GDP Using Self-Exciting Threshold Autoregressive Models. A Warning," Economics Series 79, Institute for Advanced Studies.
    • Handle: RePEc:ihs:ihsesp:79
    as

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    File URL: https://irihs.ihs.ac.at/id/eprint/1254
    File Function: First version, 2000
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Nonlinear Time Series Models; SETAR Models; Forecasting;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • 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

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