This paper identifies how financial contagion spreads through physical and virtual spaces. Using an unbalanced panel of publicly traded U.S. bank holding companies from 2000 to 2023, we find that geographic proximity to failing institutions is positively associated with systemic risk across specifications. Social proximity exhibits no systematic association with systemic risk during normal times, as mixed signals wash out in aggregate. During acute stress episodes, however, social ties become a meaningful channel through which sentiment and panic propagate across the banking sector, consistent with Wake-up Call Theory and herding documented in the broader literature. These findings suggest that the channels through which systemic risk propagates extend beyond the balance sheet, and that monitoring the spatial and social architecture of banking networks may offer regulators early warning signals that traditional indicators miss.
This paper examines how bank branching decisions spill over across socially connected but geographically distant markets. Using county-level data, Facebook’s Social Connectedness Index, and a shift-share instrumental-variable design, I find that branch expansion in connected markets predicts local expansion in normal years but local contraction during COVID-19. These responses are strongest in urban and less concentrated markets. New branches also gather more deposits where the bank has a stronger presence in socially connected counties, consistent with reputation or information traveling through social ties. The findings suggest that social networks connect banking markets beyond conventional geographic boundaries.
My research agenda examines how economic shocks, information, and technological change affect firms and local markets, particularly when economic connections extend beyond geographic boundaries.
I plan to extend my research in three directions. First, I will examine how bank branch networks shape financial access, local competition, and credit allocation, including implications for housing markets and regional development. Second, I will investigate how localized shocks to consumer attention and demand propagate through social networks, influencing economic activity in geographically distant markets. Third, I am developing research on how access to high-skilled labor affects firms' adoption of artificial intelligence and its consequences for productivity, employment, and task allocation.
Across these projects, I aim to combine causal inference, large-scale administrative and spatial data, and modern econometric methods to understand how economic changes propagate across firms, industries, and regions.