Nearly unstable autoregressive models with coefficient matrices in Jordan normal form

Nearly unstable multidimensional autoregressive models are studied where the coefficient matrices are given in Jordan normal form. Weak convergence of the sequence of the appropriately normalized least squares estimates of the eigenvalues is proved. The limit distribution is compared with the maximum likelihood estimate of the eigenvalue of the coefficient matrix of the corresponding continuous time model.