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Bayesian SAR model with stochastic volatility and multiple time-varying weights

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  • Michele Costola
  • Matteo Iacopini
  • Casper Wichers

Abstract

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.

Suggested Citation

  • Michele Costola & Matteo Iacopini & Casper Wichers, 2023. "Bayesian SAR model with stochastic volatility and multiple time-varying weights," Papers 2310.17473, arXiv.org.
    • Handle: RePEc:arx:papers:2310.17473
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    1. Billio, Monica & Caporin, Massimiliano & Panzica, Roberto & Pelizzon, Loriana, 2023. "The impact of network connectivity on factor exposures, asset pricing, and portfolio diversification," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 196-223.
    2. Nicolas Debarsy & James P. LeSage, 2022. "Bayesian Model Averaging for Spatial Autoregressive Models Based on Convex Combinations of Different Types of Connectivity Matrices," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(2), pages 547-558, April.
    3. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    4. Grassi, Stefano & Santucci de Magistris, Paolo, 2015. "It's all about volatility of volatility: Evidence from a two-factor stochastic volatility model," Journal of Empirical Finance, Elsevier, vol. 30(C), pages 62-78.
    5. Guido M. Kuersteiner & Ingmar R. Prucha, 2020. "Dynamic Spatial Panel Models: Networks, Common Shocks, and Sequential Exogeneity," Econometrica, Econometric Society, vol. 88(5), pages 2109-2146, September.
    6. Carlos M. Carvalho & Nicholas G. Polson & James G. Scott, 2010. "The horseshoe estimator for sparse signals," Biometrika, Biometrika Trust, vol. 97(2), pages 465-480.
    7. Luisa Corrado & Bernard Fingleton, 2012. "Where Is The Economics In Spatial Econometrics?," Journal of Regional Science, Wiley Blackwell, vol. 52(2), pages 210-239, May.
    8. Black, Lamont & Correa, Ricardo & Huang, Xin & Zhou, Hao, 2016. "The systemic risk of European banks during the financial and sovereign debt crises," Journal of Banking & Finance, Elsevier, vol. 63(C), pages 107-125.
    9. Dario Caldara & Matteo Iacoviello, 2022. "Measuring Geopolitical Risk," American Economic Review, American Economic Association, vol. 112(4), pages 1194-1225, April.
    10. Matthew O. Jackson & Agathe Pernoud, 2021. "Systemic Risk in Financial Networks: A Survey," Annual Review of Economics, Annual Reviews, vol. 13(1), pages 171-202, August.
    11. Olivier Parent & James Lesage, 2005. "Bayesian Model Averaging for Spatial Econometric Models," Post-Print hal-00375489, HAL.
    12. Robert F Engle & Stefano Giglio & Bryan Kelly & Heebum Lee & Johannes Stroebel, 2020. "Hedging Climate Change News," The Review of Financial Studies, Society for Financial Studies, vol. 33(3), pages 1184-1216.
    13. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1593-1636.
    14. Stephen J. Taylor, 1994. "Modeling Stochastic Volatility: A Review And Comparative Study," Mathematical Finance, Wiley Blackwell, vol. 4(2), pages 183-204, April.
    15. Eun, Cheol S. & Shim, Sangdal, 1989. "International Transmission of Stock Market Movements," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 24(2), pages 241-256, June.
    16. Bonaccolto, Giovanni & Caporin, Massimiliano & Panzica, Roberto, 2019. "Estimation and model-based combination of causality networks among large US banks and insurance companies," Journal of Empirical Finance, Elsevier, vol. 54(C), pages 1-21.
    17. Lung-fei Lee & Jihai Yu, 2012. "QML Estimation of Spatial Dynamic Panel Data Models with Time Varying Spatial Weights Matrices," Spatial Economic Analysis, Taylor & Francis Journals, vol. 7(1), pages 31-74, March.
    18. Reboredo, Juan Carlos & Ugolini, Andrea & Hernandez, Jose Arreola, 2021. "Dynamic spillovers and network structure among commodity, currency, and stock markets," Resources Policy, Elsevier, vol. 74(C).
    19. Debarsy, Nicolas & LeSage, James, 2018. "Flexible dependence modeling using convex combinations of different types of connectivity structures," Regional Science and Urban Economics, Elsevier, vol. 69(C), pages 48-68.
    20. Kastner, Gregor & Frühwirth-Schnatter, Sylvia, 2014. "Ancillarity-sufficiency interweaving strategy (ASIS) for boosting MCMC estimation of stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 408-423.
    21. Zhang, Xinyu & Yu, Jihai, 2018. "Spatial weights matrix selection and model averaging for spatial autoregressive models," Journal of Econometrics, Elsevier, vol. 203(1), pages 1-18.
    22. Anindya Bhadra & Jyotishka Datta & Nicholas G. Polson & Brandon Willard, 2016. "Default Bayesian analysis with global-local shrinkage priors," Biometrika, Biometrika Trust, vol. 103(4), pages 955-969.
    23. Niklas Ahlgren & Jan Antell, 2017. "Tests for Abnormal Returns in the Presence of Event-Induced Cross-Sectional Correlation," Journal of Financial Econometrics, Oxford University Press, vol. 15(2), pages 286-301.
    24. Yang, Kai & Lee, Lung-fei, 2021. "Estimation of dynamic panel spatial vector autoregression: Stability and spatial multivariate cointegration," Journal of Econometrics, Elsevier, vol. 221(2), pages 337-367.
    25. Hudson, Robert & Urquhart, Andrew & Zhang, Hanxiong, 2020. "Political uncertainty and sentiment: Evidence from the impact of Brexit on financial markets," European Economic Review, Elsevier, vol. 129(C).
    26. Anirban Bhattacharya & Debdeep Pati & Natesh S. Pillai & David B. Dunson, 2015. "Dirichlet--Laplace Priors for Optimal Shrinkage," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(512), pages 1479-1490, December.
    27. Abiad, Abdul & Qureshi, Irfan A., 2023. "The macroeconomic effects of oil price uncertainty," Energy Economics, Elsevier, vol. 125(C).
    28. J. Paul Elhorst, 2003. "Specification and Estimation of Spatial Panel Data Models," International Regional Science Review, , vol. 26(3), pages 244-268, July.
    29. Harry H. Kelejian & Gianfranco Piras, 2016. "An Extension of the J‐Test to a Spatial Panel Data Framework," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(2), pages 387-402, March.
    30. Lee, Lung-fei & Liu, Xiaodong, 2010. "Efficient Gmm Estimation Of High Order Spatial Autoregressive Models With Autoregressive Disturbances," Econometric Theory, Cambridge University Press, vol. 26(1), pages 187-230, February.
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