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**Testing for cointegration using principal components methods.**
*(English)*
Zbl 0647.62103

Summary: This paper studies cointegrated systems of multiple time series which are individually well described as integrated processes (with or without a drift). Necessary and sufficient conditions for cointegration are given. These conditions form the basis for a class of diagnostic statistical procedures designed to test for cointegration. The procedures rely on principal components methods. They are simple to employ and they involve only the standard normal distribution. Monte Carlo simulations reported in the paper indicate that the new procedures provide simple and useful diagnostics for the detection of cointegration. Some empirical applications to macroeconomic data are conducted and discussed.

### MSC:

62P20 | Applications of statistics to economics |

91B84 | Economic time series analysis |

62M10 | Time series, auto-correlation, regression, etc. in statistics (GARCH) |

62H25 | Factor analysis and principal components; correspondence analysis |

### Keywords:

cointegrated systems of multiple time series; Necessary and sufficient conditions for cointegration; principal components; normal distribution; diagnostics for the detection of cointegration### References:

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