VAR Cointegration in VARMA Models

The method for estimation and testing for cointegration put forward by Johansen assumes that the data are described by a vector autoregressive process. In this article we extend the data generating process to autoregressive moving average models without unit roots in the MA polynomial. We first extend some matrix algebraic relationships for I(1) processes and derive their implications for the structure theory of cointegration. Specifically we show that the cointegrating space is invariant to MA errors which have no unit roots in the MA polynomial. The above results permit to prove the robustness of the Johansen estimates of the cointegrating space in a Gaussian vector autoregressive framework when the true model is vector autoregressive moving average, without unit roots in the MA polynomial. The small sample properties of the theoretical results are examined through a small simulation study.Cointegration, Johansen procedure, Misspecification, Robustness, Simulation, Hausdorff distance

Irreducibility criteria for pairs of polynomials whose resultant is a prime number

We use some classical estimates for polynomial roots to provide several irreducibility criteria for pairs of polynomials with integer coefficients whose resultant is a prime number, and for some of their linear combinations. Similar results are then obtained for multivariate polynomials over an arbitrary field, in a non-Archimedean setting.Comment: 20 page