A novel spatial autoregressive model for panel data is introduced, which incorporates
multilayer networks and accounts for time-varying relationships. Moreover,
the proposed approach allows the structural variance to evolve smoothly over time
and enables the analysis of shock propagation in terms of time-varying spillover
effects.
The framework is applied to analyse the dynamics of international relationships
among the G7 economies and their impact on stock market returns and volatilities.
The findings underscore the substantial impact of cooperative interactions and
highlight discernible disparities in network exposure across G7 nations, along with
nuanced patterns in direct and indirect spillover effects.
