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Decision Maps for Bivariate Time Series with Potential Thrshold Cointegration

Author

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  • Kunst, Robert M.

    (University of Vienna and Department of Economics, Institute for Advanced Studies, Vienna)

Abstract

Bivariate time series data often show strong relationships between the two components, while both individual variables can be approximated by random walks in the short run andare obviously bounded in the long run. Three model classes are considered for a time-series model selection problem: stable vector autoregressions, cointegrated models, and globally stable threshold models. It is demonstrated how simulated decision maps help in classifying observed time series. The maps process the joint evidence of two test statistics: a canonical root and an LR--type specification statistic for threshold effects.

Suggested Citation

  • Kunst, Robert M., 2002. "Decision Maps for Bivariate Time Series with Potential Thrshold Cointegration," Economics Series 121, Institute for Advanced Studies.
    • Handle: RePEc:ihs:ihsesp:121
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    File URL: https://irihs.ihs.ac.at/id/eprint/1453
    File Function: First version, 2002
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    References listed on IDEAS

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    Cited by:

    1. Kunst, Robert M., 2005. "Approaches for the Joint Evaluation of Hypothesis Tests: Classical Testing, Bayes Testing, and Joint Confirmation," Economics Series 177, Institute for Advanced Studies.
    2. Mendonca, Gui Pedro, 2008. "Structural Breaks, Regime Change and Asymmetric Adjustment: A Short and Long Run Global Approach to the Output/Unemployment Dynamics," MPRA Paper 14648, University Library of Munich, Germany.

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    More about this item

    Keywords

    Model selection; Bayes testing; Nonlinear time series models;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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