  This paper investigates the structural changes in the parameters of
first-order autoregressive models by analyzing the edge eigenvalues of the
precision matrices. Specifically, edge eigenvalues in the precision matrix are
observed if and only if there is a structural change in the autoregressive
coefficients. We demonstrate that these edge eigenvalues correspond to the
zeros of some determinantal equation. Additionally, we propose a consistent
estimator for detecting outliers within the panel time series framework,
supported by numerical experiments.
