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Likelihood-based tests for parameter constancy in \(I(2)\) CVAR models with an application to fixed-term deposit data. (English) Zbl 1440.62217

Summary: This paper explores likelihood-based tests for parameter constancy in \(I(2)\) cointegrated vector autoregressive (CVAR) models. A new class of test statistics for parameter stability is introduced in the \(I(2)\) CVAR framework. This study proves that their asymptotic distributions take non-standard forms involving the integrals of Brownian motions, but they are free of any nuisance parameters. It is thus feasible to approximate the non-standard distributions by simulation. Selected quantiles of the approximate distributions are presented as statistical tables for applied use. Monte Carlo experiments are also conducted to investigate finite-sample properties of the test statistics. Finally, an empirical study of Japan’s fixed-term deposit data is performed to demonstrate the practicality of the proposed tests in applied research.

MSC:

62H15 Hypothesis testing in multivariate analysis
62M10 Time series, auto-correlation, regression, etc. in statistics (GARCH)
60J65 Brownian motion
62P05 Applications of statistics to actuarial sciences and financial mathematics
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