Influence diagnostics in a vector autoregressive model

Yonghui Liu, Guocheng Ji, Shuangzhe LIU

    Research output: Contribution to journalArticlepeer-review

    13 Citations (Scopus)
    6 Downloads (Pure)


    In this paper, we use a likelihood approach and the local influence method introduced by Cook [Assessment of local influence (with discussion). J Roy Statist Soc Ser B. 1986;48:133–149] to study a vector autoregressive (VAR) model. We present the maximum likelihood estimators and the information matrix. We establish the normal curvature and slope diagnostics for the VAR model under several perturbation schemes and use the Monte Carlo method to obtain benchmark values for determining the influence of directional diagnostics and possible influential observations. An empirical study using the VAR model to fit real data of monthly returns of IBM and SP500 index illustrates the effectiveness of our proposed diagnostics.
    Original languageEnglish
    Pages (from-to)2632-2655
    Number of pages24
    JournalJournal of Statistical Computation and Simulation
    Issue number13
    Publication statusPublished - 2015


    Dive into the research topics of 'Influence diagnostics in a vector autoregressive model'. Together they form a unique fingerprint.

    Cite this