Center for Financial Research
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+Reducing Moral Hazard at the Expense of Market Discipline: The Effectiveness of Double Liability Before and During the Great Depression- PDF
FDIC Center for Financial Research Working Paper No. 2018-05
Haelim Anderson, Daniel Barth, and Dong Beom Choi
This Version: September 2018
Prior to the Great Depression, regulators imposed double liability on bank shareholders to ensure financial stability and protect depositors. Under double liability, shareholders of failing banks lost their initial investment and had to pay up to the par value of the stock in order to compensate depositors.We examine whether double liability was effective at mitigating bank risks and providing a safety net for depositors before and during the Great Depression. We first develop a model that demonstrates two competing effects of double liability: a direct effect that constrains bank risk-taking due to increased skin in the game, and an indirect effect that promotes risk-taking due to weaker monitoring by better-protected depositors. We then test the model’s predictions using a novel identification strategy that compares state Federal Reserve member banks and national banks in New York and New Jersey. We find no evidence that double liability reduced bank risk prior to the Great Depression, but do find evidence that deposits in double-liability banks were stickier and less susceptible to runs during the Great Depression. Our findings suggest that the banking system was inherently fragile under double liability because of the conflict between shareholder incentive alignment and depositor market discipline; the depositor protection feature of double liability reduced the threat of funding outflows but may have undermined its effectiveness as a regulatory tool for reducing bank risk.
JEL Codes: G21, G28, N22
Keywords: Double Liability, Moral Hazard, Market Discipline, Bank Runs, Great Depression.
+On the Rise of the FinTechs—Credit Scoring using Digital Footprints- PDF
FDIC Center for Financial Research Working Paper No. 2018-04
Tobias Berg, Valentin Burg, Ana Gombovic and Manju Puri
This Version: September 2018
We analyze the information content of the digital footprint – information that people leave online simply by accessing or registering on a website – for predicting consumer default. Using more than 250,000 observations, we show that even simple, easily accessible variables from the digital footprint equal or exceed the information content of credit bureau scores. Furthermore, the discriminatory power for unscorable customers is very similar to that of scorable customers. Our results have potentially wide implications for financial intermediaries’ business models, for access to credit for the unbanked, and for the behavior of consumers, firms, and regulators in the digital sphere.
+Modeling Loss Given Default- PDF
FDIC Center for Financial Research Working Paper No. 2018-03
Phillip Li, Xiaofei Zhang, and Xinlei Zhao
This Version: July 2018
We investigate the puzzle in the literature that various parametric loss given default (LGD) statistical models perform similarly by comparing their performance in a simulation framework. We find that, even using the full set of explanatory variables from the assumed data generating process, these models still show similar poor performance in terms of predictive accuracy and rank ordering when mean predictions and squared error loss functions are used. Therefore, the findings in the literature that predictive accuracy and rank ordering cluster in a very narrow range across different parametric models are robust. We argue, however, that predicted distributions as well as the models’ ability to accurately capture marginal effects are also important performance metrics for capital models and stress testing. We find that the sophisticated parametric models that are specifically designed to address the bi-modal distributions of LGD outperform the less sophisticated models by a large margin in terms of predicted distributions. Also, we find that stress testing poses a challenge to all LGD models because of limited data and relevant explanatory variable availability, and that model selection criteria based on goodness of fit may not serve the stress testing purpose well. Finally, the evidence here suggests that we do not need to use the most sophisticated parametric methods to model LGD.
JEL Codes: G21, G28
Keywords: loss given default, bi-modal distribution, simulation, predicted distribution, stress testing.
+Deposit Inflows and Outflows in Failing Banks: The Role of Deposit Insurance- PDF
FDIC Center for Financial Research Working Paper No. 2018-02
Christopher Martin, Manju Puri and Alexander Ufier
This Version: May 2018
Using unique, daily, account-level balances data we investigate deposit stability and the drivers of deposit outflows and inflows in a distressed bank. We observe an outflow (run-off) of uninsured depositors from the bank following bad regulatory news. We find that government deposit guarantees, both regular deposit insurance and temporary deposit insurance measures, reduce the outflow of deposits. We also characterize which accounts are more stable (e.g., checking accounts and older accounts). We further provide important new evidence that, simultaneous with the run-off, gross funding inflows (run-in) are large and of first-order impact - a result which is missed when looking at aggregated deposit data alone. Losses of uninsured deposits were largely offset with new insured deposits as the bank approached failure. We show our results hold more generally using a large sample of banks that faced regulatory action. Our results raise questions about depositor discipline, widely considered to be one of the key pillars of financial stability, raising the importance of other mechanisms of restricting bank risk taking, including prudent supervision.
JEL Codes: G21, G28, D12, G01
Keywords: deposit insurance, deposit inflows, funding stability, depositor discipline
+The Dark-Side of Banks’ Nonbank Business: Internal Dividends in Bank Holding Companies- PDF
FDIC Center for Financial Research Working Paper No. 2018-01
Jonathan Pogach and Haluk Unal
This Version: January 2018
Last Updated: February 2019
Our study highlights the liquidity and capital pressures created by non-banking activities on banks residing within the same bank holding company (BHC). We use a sample of BHCs with large non-bank subsidiaries between 2002 and 2007 to show that banks bear the pressures of dividend smoothing. Banks in BHCs increase internal dividends to parents regardless of their own income. In contrast, non-banks in BHCs appear to be shielded from the pressures of inflexible external dividend policies. We also show that when faced with declining incomes, the banks fund their internal dividends through increased borrowing. Using a differences-in-differences, we show that banks in BHCs increase their payout ratios by 7 percentage points following major non-bank acquisitions during an expanded sample period of 1993-2007. Our evidence on the extraction of cash from banks to fund non-bank activities and capital market pressures to smooth dividends sheds new light on the debate on the optimal scope of BHCs. These observations support the arguments of a dark-side to internal capital markets in which the federally insured banks become a source of strength to the BHC and its non-bank segment.
JEL Codes: D22, G21, G31, G35, G38, L25
Keywords: dividends, payout policy, internal capital markets, bank holding company, risk shifting, bank scope-economies