TY  - UNPD
A1  - Costola, Michele
A1  - Iacopini, Matteo
A1  - Wichers, Casper
T1  - Bayesian SAR model with stochastic volatility and multiple time-varying weights
N2  - A novel spatial autoregressive model for panel data is introduced, which incor-porates 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.
T3  - SAFE working paper - 407 
KW  - Bayesian inference
KW  - International relationships
KW  - Multilayer networks
KW  - Spatial autoregressive model
KW  - Time-varying networks
KW  - Stochastic volatility
Y1  - 2023
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/71536
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-715363
UR  - https://ssrn.com/abstract=4620913
N1  - JEL-Klassifikation:  	
C58 Financial Econometrics
PB  - SAFE
CY  - Frankfurt am Main
ER  -