Dynamic connectedness across U.S. state-level regional equity markets: The role of time-varying common and idiosyncratic factors

We investigate the dynamic connectedness of equity returns and volatilities across the fifty U.S. state-level stock markets, with particular emphasis on disentangling time-varying common and idiosyncratic components. Employing a Least Absolute Shrinkage and Selection Operator regularization framework, we filter latent national factors and eliminate statistically negligible linkages to isolate economically meaningful spillovers. Using monthly data spanning February 1994 to November 2024, our results show that disregarding common drivers systematically inflates spillover estimates, thereby distorting inference on financial interconnectedness. Compared to the unfiltered ones, filtered spillover indices are up to 50% lower for returns and up to 30% lower for variances. The proposed methodology refines empirical measurement and carries substantive implications for risk management, portfolio diversification, and macroprudential oversight, underscoring the critical importance of methodological precision in regional asset market analysis. • Analyze connectedness of equity returns and volatilities for 50 fifty U.S. states • Emphasis on disentangling time-varying common and idiosyncratic components • Employing LASSO regularization framework, we filter latent national factors • Eliminate statistically negligible linkages to isolate meaningful spillovers • Disregarding common drivers systematically inflates spillover estimates