Estimation and inference of the vector autoregressive process under heteroscedasticity. (English. Russian original) Zbl 1327.62337

Bodnar, T.; Zabolotskyy, T.

Theory Probab. Math. Stat. 83, 27-45 (2011); translation from Teor. Jmovirn. Mat. Stat. 83, 22-38 (2010).

Summary: In this paper we derive the asymptotic distribution of the estimator for the parameters of the vector autoregressive process of order \( p\) with an unconditionally heteroscedastic error process. The covariance matrix of the error process is modeled as a deterministic matrix function and it is estimated nonparametrically at each time point. This estimator is used for deriving inference procedures for the parameters of the vector autoregressive process.

MSC:

62H12	Estimation in multivariate analysis
62M15	Inference from stochastic processes and spectral analysis
62H10	Multivariate distribution of statistics

Keywords:

heteroscedasticity; inference procedure; parameter estimation; vector autoregressive process

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