Decision Maps for Bivariate Time Series with Potential Thrshold Cointegration
AbstractBivariate 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.
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Bibliographic InfoPaper provided by Institute for Advanced Studies in its series Economics Series with number 121.
Length: 28 pages
Date of creation: Sep 2002
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Find related papers by 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
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