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

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  • Kurita, Takamitsu

Abstract

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.

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  • Kurita, Takamitsu, 2020. "Likelihood-based tests for parameter constancy in I(2) CVAR models with an application to fixed-term deposit data," Journal of Multivariate Analysis, Elsevier, vol. 178(C).
    • Handle: RePEc:eee:jmvana:v:178:y:2020:i:c:s0047259x19300910
    DOI: 10.1016/j.jmva.2020.104622
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