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Studies of Depression-era financial remediation have generally focused on federal deposit insurance and the provision of equity to banks by the Reconstruction Finance Corporation (RFC). This paper broadens the concept of financial remediation to include other programs – RFC lending, federal guarantees of farm and home mortgages, and the elimination of interest on demand deposits – and other intermediaries – savings and loans, mutual savings banks, and life insurance companies. The benefits of remediation or the amounts potentially at risk to the government in these programs are calculated annually and allocated to the various intermediaries. The slow remediation of real estate loans (two-thirds of these intermediaries' loans) needs further study with respect to the slow economic recovery. The paper compares Depression-era remediation with efforts during the 2008–2009 crisis. Today's remediation contrasts with the 1930s in its speed, magnitude relative to GDP or private sector nonfinancial debt, the share of remediation going to nonbanks, and emphasis on securities markets.

Purpose – This chapter investigates the influence of bank loan underwriting practices on loan losses and identifies potential determinants of lending practices for five categories of loans: business, consumer, commercial real estate, home equity, and construction and land development loans.

Methodology/approach – Using data on the riskiness of lending practices obtained from the U.S. Federal Deposit Insurance Corporation (FDIC) bank examiner surveys from January 1996 to March 2009, I fit a two-step treatment effects model to measure the effects of underwriting practices on loan losses, controlling for the potential endogeneity of lending practices.

Findings – In the selection step, I find that for business loans, the likelihood that bank management will adopt low-risk lending practices increases with bank financial performance and management quality hierarchical complexity and decreases with market competition. Results for the selection of lending practices for consumer loans and three categories of real estate loans are similar to those found for business loans but show weaker statistical relationships to all explanatory variables. In the loss determination step, I find that lower (higher) risk underwriting practices are generally associated with lower (higher) gross loan charge-offs (as percentage of gross loans and leases) for five categories of loans: business, consumer, commercial real estate, home equity, and construction and land development loans.

Originality/value of chapter – This is the first study to model the determinants of loan underwriting practices with the practices being characterized in terms of their risk to the bank. In addition, this is the first study to consider the effects of the riskiness of lending practices on loan losses, controlling for the endogeneity of practices.

This chapter reports on the “CEO’s-eye-view” of the 1990 financial crisis at Citibank using unique data from CEO John Reed’s private archives. This qualitative analysis sheds light on questions that have perennially plagued executives and intrigued scholars: How do organizations change routines in order to overcome inertia in the face of radical change in the environment? And, specifically, what is the role of the CEO in this process? Inertial behavior in such circumstances has been attributed to ingrained routines that are based on cognitive and motivational truces. Routines are performed because organizational participants find them to cohere to a particular cognitive frame about what should be done (the cognitive dimension) and to resolve conflicts about what gets rewarded or sanctioned (the motivational dimension). The notion of a “truce” explains how routines are “routinely” activated. Routines are inertial because the dissolution of the truce would be inconsistent with frames held by organizational participants and fraught with the risk of unleashing unmanageable conflict among interests in the organization. Thus, the challenge for the CEO in making intended change is both to break the existing truce and to remake a new one. In this study, I uncover how the existing organizational truce led to the crisis at Citibank, why Reed’s initial attempts to respond failed, and how he ultimately found ways to break out of the old truce and establish new routines that helped the bank survive. These findings offer insight into the cognitive and motivational microfoundations of macro theories about organizational response to radical change.

Both neoclassical and Keynesian economists have widely favored the use of equilibrium models to understand economic activity, but dramatic periods of change such as the current global economic downturn are poorly understood by assuming equilibrium. The economist Joseph Schumpeter tried to inject dynamism and disequilibrium into economic models by arguing for the role of entrepreneurs in creating microeconomic change, and for examining long-term macroeconomic change as represented in business cycles. No economist, including Schumpeter, has ever connected these two approaches to change and these approaches are not typically used as alternative and complementary ways of viewing transformation over time. We suggest that these theories can be connected in a “mesoeconomic” institutional analysis rooted in economic sociology; we demonstrate this connection by examining the US commercial building industry. This industry has changed in qualitatively distinct ways over the past two centuries in what we call market orders, economic orders sometimes lasting for decades or more. In each market order, entrepreneurs of different sorts are able to flourish and push forward institutional changes that result in long-term economic shifts. Credit and finance have been pivotal influences in each market order, a factor supporting Schumpeter's focus on entrepreneurial action and speculation and one not largely discussed today. We view the recent disruption of financial markets as a signal of the destruction of a reigning market order.

This chapter studies banks’ loan pricing behavior in mainland China during 2003–2013 by applying panel regressions to firm-level loan data and the estimated default likelihood for listed companies. The authors find that with the progress of market-oriented financial reforms, banks generally require compensation for their exposure to borrowers’ default risks. It is even more so if the borrower is a non-state-owned enterprise (non-SOE), mainly due to the pricing behavior of the Big Four banks. Bank lending rates are shown to be less sensitive to the default risks of state-owned enterprises (SOEs). Our results also reveal that banks priced in firm default risks before 2008 financial crisis, but not necessarily so after the crisis. As for industries, we find that after the 2008 Global Financial Crisis, the real estate sector and other government-supported industries tended to enjoy better terms on loan pricing in terms of default risks. We believe the main reason is that the government stimulus policies tilted toward those industries that have played crucial roles in China’s economic growth.

Portfolios of mortgage loans played an important role in the Great Recession and continue to compose a material part of bank assets. This chapter investigates how cross-sectional dependence in the underlying properties flows through to the loan returns, and thus, the risk of the portfolio. At one extreme, a portfolio of foreclosed mortgage loans becomes a portfolio of real estate whose returns exhibit substantial cross-sectional and spatial dependence. Near the other extreme, almost all loans perform and yield constant returns, which do not correlate with other performing loan returns. This suggests that loan performance effectively censors the random returns of the underlying properties. Following the statistical properties of the correlations among censored variables, the authors build off this foundation and show how the loan return correlations will rise as economic conditions deteriorate and the defaulting loans reveal the underlying housing correlations. In this chapter, the authors (1) adapt tools from spatial statistics to document substantial cross-sectional dependence across house price returns and examine the spatial structure of this dependence, (2) investigate the nonlinear nature of correlations among loan returns as a function of the default rate and the underlying house price correlations, and (3) conduct a simulation exercise using parameters from the empirical data to show the implications for holding a portfolio of mortgages.