We introduce a new model for time-varying spatial dependence. The model extends the well-known static spatial lag model. All parameters can be estimated conveniently by maximum likelihood. We establish the theoretical properties of the model and show that the maximum likelihood estimator for the...

We introduce a new and general methodology for analyzing vector autoregressive models with time-varying coefficient matrices and conditionally heteroskedastic disturbances. Our proposed method is able to jointly treat a dynamic latent factor model for the autoregressive coefficient matrices and...

We propose a new unified approach to identifying and estimating spatio-temporal dependence structures in large panels. The model accommodates global crosssectional dependence due to global dynamic factors as well as local cross-sectional dependence, which may arise from local network structures....

This paper revisits the credit spread puzzle in bank CDS spreads from the perspective of information contagion. The puzzle, first detected in corporate bonds, consists of two stylized facts: Structural determinants of credit risk not only have low explanatory power but also fail to capture...