Exploring the Impact of Multivariate GARCH Innovations on Hypothesis Testing for Cointegrating Vectors |
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Authors: | Takamitsu Kurita |
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Institution: | Faculty of Economics , Fukuoka University , Nanakuma, Jonan Ward , Fukuoka , Japan |
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Abstract: | This article investigates the impact of multivariate generalized autoregressive conditional heteroskedastic (GARCH) errors on hypothesis testing for cointegrating vectors. The study reviews a cointegrated vector autoregressive model incorporating multivariate GARCH innovations and a regularity condition required for valid asymptotic inferences. Monte Carlo experiments are then conducted on a test statistic for a hypothesis on the cointegrating vectors. The experiments demonstrate that the regularity condition plays a critical role in rendering the hypothesis testing operational. It is also shown that Bartlett-type correction and wild bootstrap are useful in improving the small-sample size and power performance of the test statistic of interest. |
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Keywords: | Bartlett-type correction Cointegrating vector Monte Carlo experiment Multivariate GARCH Wild bootstrapping |
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