A new model for time-varying spatial dependencies is introduced. It forms an extension to the popular spatial lag model and can be estimated conveniently by maximum likelihood. The spatial dependence parameter is assumed to follow a generalized autoregressive score (GAS) process. The theoretical...

This paper proposes a latent dynamic factor model for low- as well as high-dimensional realized covariance matrices of stock returns. The approach is based on the matrix logarithm and allows for flexible dynamic dependence patterns by combining common latent factors driven by HAR dynamics and...

This paper investigates whether information complementarities can explain the strong patterns of sectoral comovement observed empirically. It tests the theoretical model by Veldkamp and Wolfers (2007), which suggests that firms' output decisions are based on aggregate information rather than...