Do Small Banks have an Advantage in Lending? An Examination of Risk-Adjusted Yields on Business Loans at Large and Small Banks

Consolidation in the banking industry has sparked concern about the survival of small banks, particularly as it relates to the availability of credit to small businesses. However, if small banks have an advantage in processing credit information, compared to large banks, they should continue to survive in a competitive environment. We evaluate risk-adjusted commercial loan yields (gross yields less net charge-offs and the risk-free rate of return) at small and large banks for the period of 1996 through 2001. Our primary finding is that, after controlling for market concentration, cost of funds, and a variety of other factors that might influence yields, smaller banks earn greater risk-adjusted yields than larger banks. This result suggests that small banks make better choices from the available small business loans and is consistent with the notion that these banks have an information advantage in evaluating credit.     

Risk taking and failure in de novo savings and loans in the 1980s

This article examines failure rates in de novo S&Ls that initiated operations during the 1980–1986 period. Overall failure rates are similar to those for existing institutions but are found to vary significantly by location, time of charter, and organizational form. Both univariate tests and results from a probability-of-failure model indicate that inadequate capital, economic stress, poor management of higher risk lending allowed by broader powers, and operating inefficiencies contributed significantly to the likelihood of failure. Use of brokered funds and rapid asset growth are also significantly related to failure likelihood. Interestingly, for those S&Ls which eventually failed, rapid asset growth and high proportions of nonperforming assets actually delayed the timing of their failure. We interpret this to be the result of regulatory forbearance. We also find significant differences between the financial characteristics of de novo and non-de novo S&Ls.     

Reserves and cash flows under stochastic retirement

Uncertain time of retirement and uncertain structure of retirement benefits are risk factors for life insurance companies. Nevertheless, classical life insurance models assume these are deterministic. In this paper, we include the risk from stochastic time of retirement and stochastic benefit structure in a classical finite-state Markov model for a life insurance contract. We include discontinuities in the distribution of the retirement time. First, we derive formulas for appropriate scaling of the benefits according to the time of retirement and discuss the link between the scaling and the guarantees provided. Stochastic retirement creates a need to rethink the construction of disability products for high ages and ways to handle this are discussed. We show how to calculate market reserves and how to use modified transition probabilities to calculate expected cash flows without significantly more complexity than in the traditional model. At last, we demonstrate the impact of stochastic retirement on market reserves and expected cash flow in numerical examples.     

Attribute differences between U.S. GAAP and IFRS earnings: An exploratory study

In this study we explore attribute differences between U.S. GAAP and IFRS earnings. Our study is motivated by the ongoing harmonization process in accounting standard setting as well as by recent convergence projects by the FASB and the IASB. We test two market-based earnings attributes, i.e., value relevance and timeliness, as well as two accounting-based earnings attributes, i.e., predictability and accrual quality. These attributes are tested for German New Market firms as they are allowed to choose between IFRS and U.S. GAAP for financial reporting purposes. Overall, we find that U.S. GAAP and IFRS only differ with regard to predictive ability. The fact that U.S. GAAP accounting information outperforms IFRS also holds after controlling for differences in firm characteristics, such as size, leverage and the audit firm. However, our results also seem to suggest that these differences are not fully valued by investors, as we do not observe significant and consistent differences for the value-relevance attribute.     

Firm exit after distress: differentiating between bankruptcy, voluntary liquidation and M&A

This paper examines firm-level determinants of mature firm exits after economic distress. Using nested logit models and a sample of 6,118 distress-related exits in Belgium, we analyze the type of exit that distressed firms experience. We show that 41% of the firms in our sample exit through a court driven exit procedure (mainly bankruptcy), 44% are voluntarily liquidated and 14% are acquired, merged or split (hereafter M&A). Distressed firm exit follows two distinct stages. First, a firm either decides to exit voluntarily or is forced into bankruptcy, which is the least efficient exit strategy. Compared to bankruptcy, the probability of a voluntary exit increases with higher levels of cash, lower leverage, holding no secured debt and being embedded in a group. If a firm exits voluntarily, it enters a second stage and decides either to exit through voluntary liquidation or through a M&A. Conditional on not going bankrupt, the likelihood of voluntary liquidation compared to M&A increases with higher levels of cash or secured debt, with smaller size and with an absence of group relations. We contribute to the firm exit literature by jointly analyzing three exit types and showing that bankruptcy and voluntary liquidation are fundamentally different exit routes. While voluntary liquidation is an important exit route for distressed firms, most previous studies have failed to distinguish between bankruptcy and liquidation. We hence contribute to the exit literature by showing that bankruptcy, voluntary liquidation and M&A are fundamentally distinct exit routes for distressed firms, driven by different firm level characteristics and following a two-stage process.     

Matchmaking in organizational change: Does every employee value participatory leadership? An empirical study

Although leadership is generally considered an important lever to increase commitment during organizational change, empirical research has yet to unravel many of the underlying mechanisms. In this paper, we propose that the impact of participative leadership on affective commitment to change will be contingent on employees’ orientation toward leadership. In our empirical study in two police organizations, we find evidence that followers’ orientation toward leadership is a useful interacting variable. Participative leadership lowers affective commitment to change for individuals with high dominance orientation. In contrast, participative leadership increases affective commitment to change for employees with high development orientation toward leadership. Implications for theory and practice are discussed.     

Forecasting inflation with an uncertain output gap

The output gap is a crucial concept in the monetary policy framework, indicating demand pressure that generates inflation. However, its definition and estimation raise a number of theoretical and empirical questions. This paper evaluates a series of univariate and multivariate methods for extracting the output gap in Norway, and compares their value added in predicting inflation. We find that models including the output gap have better predictive power than models based on alternative indicators, and they forecast significantly better than simple benchmark models. Furthermore multivariate measures of the output gap perform better than the univariate gaps. Comments from two anonymous referees, Q. Farooq Akram, Tommy Sveen, Ken West, Fredrik Wulfsberg and seminar participants in Norges Bank are gratefully acknowledged. All mistakes remain our own. The views expressed are those of the authors and do not necessarily represent those of Norges Bank.     

HORIZONTAL MISMATCH BETWEEN EMPLOYMENT AND FIELD OF EDUCATION: EVIDENCE FROM A SYSTEMATIC LITERATURE REVIEW

This paper provides a systematic review of the growing literature on the poor match between employees’ field degree and the job requirements, also referred to as horizontal mismatch. We identify the different definitions used in the literature and find that each measure of horizontal mismatch yields substantially different incidence rates. We discuss the validity of the different measures and conclude that a more uniform definition of horizontal mismatch is needed. The likelihood of horizontal mismatch is among other things determined by the extent to which employees possess general skills as opposed to occupation‐specific skills, and, it appears to be more frequently present among older workers. Compared to well‐matched employees, horizontally mismatched workers generally incur a wage penalty, are less satisfied with their jobs, and are more likely to regret their study programme. The ensuing findings offer guidance to prevent horizontal mismatch as well as a roadmap for future research.     

Machine learning for quantitative finance: fast derivative pricing,hedging and fitting

In this paper, we show how we can deploy machine learning techniques in the context of traditional quant problems. We illustrate that for many classical problems, we can arrive at speed-ups of several orders of magnitude by deploying machine learning techniques based on Gaussian process regression. The price we have to pay for this extra speed is some loss of accuracy. However, we show that this reduced accuracy is often well within reasonable limits and hence very acceptable from a practical point of view. The concrete examples concern fitting and estimation. In the fitting context, we fit sophisticated Greek profiles and summarize implied volatility surfaces. In the estimation context, we reduce computation times for the calculation of vanilla option values under advanced models, the pricing of American options and the pricing of exotic options under models beyond the Black–Scholes setting.