糖心TV

Title: Traumatic Financial Experiences and Persistent Changes in Financial Behavior: Evidence from the Freedman's Savings Bank 

Abstract: The failure of the Freedman's Savings Bank (FSB), one of the only Black-serving banks in the early post-bellum South, was an economic catastrophe and one of the great episodes of racial exploitation in post-Emancipation history. It was also most Black Americans' first experience of banking. Can events like these permanently alter financial preferences and behavior? To test this, we examine the impact of FSB collapse on life insurance-holding, an accessible alternative savings vehicle over the late 19th and early 20th centuries. We document a sharp and persistent increase in insurance demand in affected counties following the shock, driven disproportionately by Black customers. We also use FSB migrant flows to disentangle place-based and cohort-based effects, thus identifying psychological and cultural scarring as a distinct mechanism underlying the shift in financial behavior induced by the bank's collapse. Horizontal and intergenerational transmission of preferences help explain the shock鈥檚 persistent effects on financial behavior.

Title: Identification of Informative Core Structures in Weighted Directed Networks with Uncertainty Quantification

Abstract: In network analysis, noises and biases, which are often introduced by peripheral or non-essential components, can mask pivotal structures and hinder the efficacy of many network modeling and inference procedures. Recognizing this, identification of the core--periphery (CP) structure has emerged as a crucial data pre-processing step. While the identification of the CP structure has been instrumental in pinpointing core structures within networks, its application to directed weighted networks has been underexplored. Many existing efforts either fail to account for the directionality or lack the theoretical justification of the identification procedure. In this work, we seek answers to three pressing questions: (i) How to distinguish the informative and noninformative structures in weighted directed networks? (ii) What approach offers computational efficiency in discerning these components? (iii) Upon the detection of CP structure, can uncertainty be quantified to evaluate the detection? We adopt the signal-plus-noise model, categorizing different types of noninformative relational patterns, by which we define the sender and receiver peripheries. Furthermore, instead of confining the core component to a specific structure, we consider it complementary to either the sender or receiver peripheries. Based on our definitions on the sender and receiver peripheries, we propose spectral algorithms to identify the CP structure in directed weighted networks. Our algorithm stands out with statistical guarantees, ensuring the identification of sender and receiver peripheries with overwhelming probability. Additionally, we propose a hypothesis testing framework to infer CP structure upon detection. Our methods scale effectively for expansive directed networks. Implementing our methodology on faculty hiring network data revealed captivating insights into the informative structures and distinctions between informative and noninformative sender/receiver nodes across various academic disciplines.

This is a joint work with Wenqin Du, Tianxi Li, and Lihua Lei.