Christa H. S. Bouwman

How Does Capital Affect Bank Performance During Financial Crises

This paper empirically examines how capital affects a bank’s performance (survival and market share) and how this effect varies across banking crises, market crises, and normal times that occurred in the US over the past quarter century. We have two main results. First, capital helps small banks to increase their probability of survival and market share at all times (during banking crises, market crises, and normal times). Second, capital enhances the performance of medium and large banks primarily during banking crises. Additional tests explore channels through which capital generates these effects. Numerous robustness checks and additional tests are performed.

Bank Liquidity Creation, Monetary Policy, and Financial Crises

This paper examines the interplay among bank liquidity creation (which incorporates all bank on- and off-balance sheet activities), monetary policy, and financial crises. We find that: (1) high liquidity creation (relative to trend) – particularly off-balance sheet liquidity creation – helps predict crises, controlling for other factors; (2) monetary policy has statistically significant, but economically minor effects on liquidity creation by small banks during normal times, and these effects are even weaker during financial crises; (3) monetary policy has very little effects on medium and large bank liquidity creation during both normal times and crises. These findings suggest that authorities may wish to monitor bank liquidity creation closely in order to predict and perhaps lessen the likelihood of financial crises. They might also consider other tools to control bank liquidity creation, such as capital and liquidity requirements.

Bank Loan Supply Responses to Federal Reserve Emergency Liquidity Facilities

The Federal Reserve injected unprecedented liquidity into banks during the recent financial crisis using the discount window and Term Auction Facility. We examine these facilities’ use and effectiveness and have three main findings. First, small bank users were generally weak, large bank users were not. Second, the funds were weak substitutes to other funding sources. Third, these facilities increased aggregate lending, enhancing lending at expanding banks and reducing decline at contracting banks. Small banks increased small business lending, while large banks enhanced large business lending. Loan quality only improved at small banks, while both left loan contract terms unchanged.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.

How the Dodd-Frank Act Affected Bank Acquisition Behavior

Size threshold-based regulatory requirements are pervasive, but little is known about how they affect the merger and acquisition (M&A) behavior of firms around the thresholds. M&As cause discrete increases in size, so we hypothesize changes in firms’ M&A behavior near regulatory size thresholds. Our identification strategy relies on size thresholds imposed by the Dodd-Frank Act. We develop a novel research design that estimates indirect treatment effects for banks just below the thresholds. We find strong evidence of indirect treatment effects on M&A behavior. Our results also illustrate the limitations of a standard difference-in-differences approach to studying events that involve size thresholds.

Understanding Financial Statements

To understand how bank liquidity creation is measured, it is important to comprehend bank financial statements. Since these are very different from financial statements of nonfinancial firms, this chapter briefly examines the differences among the financial statements of a large nonfinancial firm, a large commercial bank, and a small commercial bank. The key takeaway is a deeper understanding of how financial statements differ across types of firms, so that the liquidity creation measures, which use data from these statements, become intuitive and easier to comprehend.

How Can Bank Executives, Financial Analysts, Researchers (including Academics and Students), and Policy Makers (including Legislators, Regulators, and Central Bankers) Use Bank Liquidity Creation Data to Their Advantages?

This chapter shows how various parties can use the bank liquidity creation data on the book’s website ( http://booksite.elsevier.com/9780128002339 ) to their advantages. Liquidity creation may be used by bank executives and financial analysts to assess a bank against its peers and against its own past behavior to pick an appropriate scale of liquidity creation (in dollar terms and/or relative to assets). Policy makers can use the data in designing legislation, prudential regulation, and supervision. Researchers and policy makers can use the data when investigating the effects of prudential regulation and supervision, as well as monetary policy. Researchers and policy makers can also use the data to investigate many existing and future issues in banking. The key takeaway is that the bank liquidity creation data are useful to a broad audience interested in benchmarking, research, and policy work.

Measurement of Bank Liquidity Creation

This chapter introduces the “cat fat” measure of bank liquidity creation that is used in the empirical analyses in this book. This measure classifies virtually all bank activities as liquid, semiliquid, or illiquid using information on product category and maturity combined, but classifies loans purely by category (“cat”) due to data limitations, and includes off-balance sheet activities (“fat”). It also compares this measure to several alternative measures of liquidity creation that classify loans purely by maturity (“mat”), exclude off-balance sheet activities (“nonfat”), take into account takedown probabilities of off-balance sheet guarantees, and take into account securitization frequencies. It discusses why the “cat fat” measure is preferred to these alternative measures. The key takeaways are the method for calculating “cat fat” liquidity creation and the understanding that the “cat fat” measure is preferred because it is most consistent with the liquidity creation theories.

Where We Stand Now and the Open Research and Policy Questions

This chapter identifies open research and policy questions. Existing research centers on the United States and a few other nations, but should be expanded to nations around the world. Unanswered questions include: how liquidity creation is affected by bank mergers and acquisitions, competition or market power, deregulation, deposit insurance, and corporate governance; the relation between liquidity creation and risk; the effects of bank liquidity creation on real economic activity; the existence of an optimal scale of liquidity creation for the banking sector and individual banks; liquidity creation dynamics; the effects of liquidity creation in different financial and legal systems; liquidity created by financial institutions other than commercial banks, markets, and their interactions. In all cases, it is helpful to examine whether the results hold during normal times and financial crises. The key takeaway is that there are many important questions left to address using the liquidity creation data and methodology.

How Much Liquidity Do Banks Create During Normal Times and Financial Crises

This chapter gives summary statistics and shows graphically how liquidity creation by US commercial banks changed from 1984:Q1 to 2014:Q4, and how it behaved during normal times and financial crises. It first examines “cat fat” liquidity creation and its on- and off-balance sheet components, both in levels and normalized by assets. It does this for the entire commercial banking sector and also separately by bank size class. Two alternative liquidity creation measures – takedown probability-adjusted and securitization-adjusted “cat fat” liquidity creation – and three other measures of bank output are also shown. The key takeaways are that US bank liquidity creation has grown tremendously over time, that about half is created off the balance sheet, that large banks create the vast majority of it while constituting only a small percentage of the banking sector in numbers, and that liquidity creation tends to be high before financial crises and then falls during the crises.

Defining and Dating Financial Crises

This chapter first outlines a number of existing approaches used to define and date financial crises: some rely on the use of policy interventions and some focus on liquidity shocks. It then picks one approach that best suits the empirical analyses shown in this book, which focus on the United States over the period 1984:Q1–2014:Q4. The chosen approach allows for the examination of crises that do not have significant policy interventions, and are generated by banking and market shocks that do not necessarily involve liquidity problems. The key takeaway is that there is no single formula or set of rules for defining and dating financial crises that is best for every situation – some judgment is needed.