Assistant Professor of Finance
Texas Christian University
v.traweek@tcu.edu
Interests: financial intermediation, household finance, corporate finance
Publications:
Traweek, Virginia, and Malcolm Wardlaw. “Freedman’s Savings and Trust Bank Passbook and Dividend Repayment Records.” Journal of Slavery and Data Preservation 3, no. 1 (2022). https://doi.org/10.25971/7jn5-5×58.
Working Papers:
“Societal Inequality and Financial Market Participation: Evidence from the Freedman’s Savings Bank“ (with Malcolm Wardlaw)
Revise and Resubmit, Review of Financial Studies
Using a unique set of linked records from the Freedman’s Savings Bank, we examine how depositors react to an evolving financial crisis, and how this behavior impacts policy makers’ goals of increased financial participation. We find that the target Black depositor responds similarly to White depositors in nationwide panics but more slowly in environments where bank-specific information is present, with White depositors twice as likely to close their accounts before the bank’s failure and disproportionate losses born by community organizations. Our results demonstrate how the structure of simple financial institutions can create systematic disadvantages for minority communities.
Media Coverage:
Michigan Ross Faculty News, November 2021
Conversations with Kenyatta, November 2021
“Violence, Positive Political Developments, and Financial Market Participation: Evidence from the Freedman’s Savings Bank“ (with Malcolm Wardlaw)
Revise and Resubmit, Journal of Banking & Finance
Using a detailed depositor arrival data from the Freedman’s Savings Bank, we examine how social unrest impacts policy makers’ goals of increased financial participation and economic integration for minorities. We find that events that imperil public safety also decrease participation in banks. Alternatively, events that increase social stability increase the arrival of new depositors at the bank. We show that these differences in participation occur along racial lines during violent events. Our results demonstrate how social conditions can alter participation in the banking system.
“A Tale of Two Cities: The Rural-Urban Divide in Banking”
Bank branches in counties with a high rural population offer certificate of deposit (CD) rates of up to 22% higher than banks in counties that are more urban. Although bank size does explain some of this result, controlling for large bank results in a 5.6% to 8% rural CD premium. I show that higher CD rates in rural counties are not a function of credit quality of rural borrowers and are not explained by rural CD depositor impatience or rural bank capital constraints. Overall, my findings highlight an important difference in the way rural and urban depositors interact with the financial system.
“Shadows on Main Street: Mapping America’s Financial Architecture from the Yellow Pages of the 20th Century” (coauthored with Amiyatosh Purnanandam and Taylor Begley)
We construct a novel and comprehensive database of the branches of all financial services providers, including banks and nonbank financial institutions, at the county level over 1920-2000 from Yellow Pages published in Indiana, Michigan, and Ohio. We find that about one-third of these branches are shadow banks, i.e., non-regulated entities, and that there is strong county-specific persistence in both the number of branches and the share of shadow banks over time. We examine the statistical and economic implications of these findings for extant empirical literature on the effect of finance on real outcomes, which mostly focuses on easily-measured regulated institutions. Ignoring shadow banks in these analyses creates a non-classical measurement error since shadow banks evolve as a complement to regulated institutions. Using banks alone as a proxy for financial development can understate the true effect by as much as 50% or overstate the true effect by as much as 80%, depending on the empirical application. Routine empirical choices such as whether to use the number of branches or their log-transformed values in the regression analysis create large differences in the direction and extent of bias. We provide suggestions for correcting for these biases in future empirical studies.