Singular vector autoregressions with deterministic terms: Strong consistency and lag order determination
نویسنده
چکیده
A vector autoregression is singular when explosive characteristic roots have geometric multiplicity larger than one. The singular component is a mixingale. Martingale decompositions are constructed for sample moments involving the singular component. This permits weak and strong analysis in the case of martingale difference innovations. While least squares estimators are shown to be inconsistent in the singular case, procedures for lag length determination are shown to have the same asymptotic properties in regular and singular cases.
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