Working Papers

Flight to Safety in the Regional Bank Crisis of 2023 (with C. Caglio and M. Rezende) 

Who Pays the Price? Overdraft Fee Ceilings and the Unbanked (with B. Melzer and D. Morgan) 

Public Service or Private Benefits? Bankers in the Governance of the Federal Reserve System (with L. Black)  

Work in Progress

Diffusions of Innovations in Contract Language: The Case of Syndicated Loans (with S. Das, S. Li)

Uniform Pricing of Bank Deposits (with Edwin Song)

Publications

Decision-making Delegation in Banks (with Y. Gam, R. Gopalan, J. Skrastins)   Accepted, Management Science

Using natural disasters as shocks to local economies, we document that a bank branch’s ability to set deposit rates locally has real effects. Following disasters, branches with rates set locally increase deposit rates more and experience higher deposit volumes in affected counties. Consistent with imperfect insurance from internal capital markets, banks with more branches setting rates locally relatively expand mortgage lending in affected counties. House prices recover faster in local areas where more branches’ rates are set locally.

Bank Loan Supply Responses to Federal Reserve Emergency Liquidity Facilities (with A. Berger, L. Black, and C. Bouwman)   

Journal of Financial Intermediation, 2017, 12: 1-15.  (Winner of the JFI's Best Paper 2017 Award)

The Federal Reserve injected unprecedented liquidity into banks during the recent crisis through the discount window and Term Auction Facility. We examine the use and effectiveness of these facilities. We find that recipient banks increased their lending overall, both short- and long-term, and in most loan categories. The facilities resulted in enhanced lending at expanding banks and reduced declines at contracting banks. Small banks increased small business lending and large banks increased large business lending. There were no significant changes in loan quality or loan contract terms by either large or small banks. 

Securitization Without Adverse Selection: The Case of CLOs  (with E. Benmelech and V. Ivashina)   

Journal of Financial Economics, 2012, 1:91-113. 

In this paper, we investigate whether securitization was associated with risky lending in the corporate loan market by examining the performance of individual loans held by collateralized loan obligations. We employ two different data sets that identify loan holdings for a large set of CLOs and find that adverse selection problems in corporate loan securitizations are less severe than commonly believed. Using a battery of performance tests, we find that loans securitized before 2005 performed no worse than comparable unsecuritized loans originated by the same bank. Even loans originated by the bank that acts as the CLO underwriter do not show under-performance relative to the rest of the CLO portfolio. While some evidence exists of under-performance for securitized loans originated between 2005 and 2007, it is not consistent across samples, performance measures, and horizons. Overall, we argue that the securitization of corporate loans is fundamentally different from securitization of other assets classes because securitized loans are fractions of syndicated loans. Therefore, mechanisms used to align incentives in a lending syndicate are likely to reduce adverse selection in the choice of CLO collateral.

The Alchemy of CDO Credit Ratings (with E. Benmelech)

Journal of Monetary Economics, 2009, 5:617-634 

Collateralized loan obligations (CLOs) were one of the largest and fastest growing segments of the structured finance market, fueling the 2003–2007 boom in syndicated loans and leveraged buyouts. The credit crisis brought CLO issuance to a halt, and as a result the leveraged loan market dried up. Similar to other structured finance products, investors in CLOs rely heavily on credit rating provided by the rating agencies, yet little is known about CLO rating practices. This paper attempts to fill the gap. Using novel hand-collected data on 3912 tranches of collateralized loan obligations we document the rating practices of CLOs and analyze their structures.

The Credit Rating Crisis (with E. Benmelech) 

NBER Macroeconomics Annual, 2009, 161-207 

Since June 2007, the creditworthiness of structured finance products has deteriorated rapidly. The number of downgrades in November 2007 alone exceeded 2,000 and many downgrades were severe, with 500 tranches downgraded more than 10 notches. Massive downgrades continued in 2008. More than 11,000 of the downgrades affected securities that were rated AAA. This paper studies the credit rating crisis of 2007-2008 and in particular describes the collapse of the credit ratings of ABS CDOs. Using data on ABS CDOs we provide suggestive evidence that ratings shopping may have played a role in the current crisis. We find that tranches rated solely by one agency, and by S&P in particular, were more likely to be downgraded by January 2008. Further, tranches rated solely by one agency are more likely to suffer more severe downgrades.

Large Blocks of Stock: Prevalence, size, and measurement (with R. Fahlenbrach, P. Gompers, and A. Metrick)

Journal of Corporate Finance, 2006, 3:594-618  

Large blocks of stock play an important role in many studies of corporate governance and finance. Despite this important role, there is no standardized data set for these blocks, and the best available data source, Compact Disclosure, has many mistakes and biases. In this paper, we document these mistakes and show how to fix them. The mistakes and biases tend to increase with the level of reported blockholdings: in firms where Compact Disclosure reports that aggregate blockholdings are greater than 50%, these aggregate holdings are incorrect more than half the time and average holdings for these incorrect firms are overstated by almost 30 percentage points. For researchers using uncorrected blockholder data as a dependent variable, these errors will increase the standard error of coefficient estimates but do not appear to cause bias. However, we find that if blockholders are used as an independent variable, economically significant errors-in-variables biases can occur. We demonstrate these biases using a representative analysis of the relationship between firm value and outside blockholders. An online appendix to our paper provides a “clean” data set for our sample firms and time period. For researchers who need to work outside of this sample, we also test the efficacy of alternative (cheaper) fixes to this data problem, and find that truncating or winsorizing the sample can reduce about half of the bias in our representative application.