The evolution of cost-productivity and efficiency among US credit unions

Advances in information-processing technology have eroded the advantages of small scale and proximity to customers that traditionally enabled small lenders to thrive. Nonetheless, the membership and market share of US credit unions have increased, though their average size has also risen. We investigate changes in the efficiency and productivity of US credit unions during 1989–2006 by benchmarking the performance of individual firms against an estimated order-α quantile lying “near” the efficient frontier. We construct a cost analog of the Malmquist productivity index, which we decompose to estimate changes in cost and scale efficiency, and changes in technology. We find that cost-productivity fell on average across all credit unions but especially among smaller credit unions. Smaller credit unions confronted a shift in technology that increased the minimum cost required to produce given amounts of output. All but the largest credit unions also became less scale efficient over time.     

Nonparametric efficiency estimation in stochastic environments: Noise-to-signal estimation,finite sample performance and hypothesis testing

This study considers the issues of noise-to-signal estimation, finite sample performance and hypothesis testing for a new nonparametric and stochastic efficiency estimation technique. We apply the technique for analyzing the efficiency of European banks from various regions and with various specializations. The technique seems well suited for this application area because banking inputs and outputs generally are measured with error, the banking production technology is not well-defined and large banking data sets such as BankScope allow for a nonparametric approach.     

The diversification and financial performance of US credit unions

For US credit unions, revenue from non-interest sources has increased significantly in recent years. We investigate the impact of revenue diversification on financial performance for the period 1993–2004. The impact of a change in strategy that alters the share of non-interest income is decomposed into a direct exposure effect, reflecting the difference between interest and non-interest bearing activities, and an indirect exposure effect which reflects the effect of the institution’s own degree of diversification. On both risk-adjusted and unadjusted returns measures, a positive direct exposure effect is outweighed by a negative indirect exposure effect for all but the largest credit unions. This may imply that similar diversification strategies are not appropriate for large and small credit unions. Small credit unions should eschew diversification and continue to operate as simple savings and loan institutions, while large credit unions should be encouraged to exploit new product opportunities around their core expertise.     

Renegotiation of financial contracts: Evidence from private credit agreements

Using a large sample of private credit agreements between U.S. publicly traded firms and financial institutions, we show that over 90% of long-term debt contracts are renegotiated prior to their stated maturity. Renegotiations result in large changes to the amount, maturity, and pricing of the contract, occur relatively early in the life of the contract, and are rarely a consequence of distress or default. The accrual of new information concerning the credit quality, investment opportunities, and collateral of the borrower, as well as macroeconomic fluctuations in credit and equity market conditions, are the primary determinants of renegotiation and its outcomes. The terms of the initial contract (e.g., contingencies) also play an important role in renegotiations; by altering the structure of the contract in a state contingent manner, renegotiation is partially controlled by the contractual assignment of bargaining power.     

Financial and economic performance of major Brazilian credit cooperatives

The credit union's main functions are the provision of individual financial loans based on collective savings, reaching up to provide full banking services, with expansion of its social function. Cooperatives are an alternative to supply a credit demand in the market, because a third of the municipalities have no bank branches. Although the participation of cooperatives in credit operations is still small compared to the Brazilian national banking system, its continued growth demonstrates the importance of this sector. In this sense, the analysis of the performance of these cooperatives becomes relevant to the extent that incentives to industry expansion differ from other financial institutions. In this context, this study aimed to analyze which the financial and economic performance of Brazil's largest credit unions. This performance analysis was performed using the indicators proposed by the CAMEL model, then the data envelopment analysis (DEA). It can be seen that there is a positive relationship between the use of variables in the model and the measurement of financial performance of credit unions. Moreover, according to the results, it can be observed that Uniprime Northern Paraná, Sicoob Cocred and Sicredi North RS/SC were cooperatives that stood out as efficient.     

A simple model of credit contagion

We propose a simple model of credit contagion in which we include macro- and microstructural interdependencies among the debtors within a credit portfolio. The microstructure captures interdependencies between debtors that go beyond their exposure to common factors, e.g., business or legal interdependencies. We show that even for diversified portfolios, moderate microstructural interdependencies have a significant impact on the tails of the loss distribution. This impact increases dramatically for less diversified microstructures.     

Corporate social responsibility in the banking industry: Motives and financial performance

The current study investigates the association between corporate social responsibility (CSR) and financial performance (FP), and discusses the driving motives of banks to engage in CSR. Three motives, namely, strategic choices, altruism, and greenwashing, suggest that the relationship between CSR and FP is positive, non-negative, and non-existent, respectively. We obtained our sample, which covered 2003–2009, from the Ethical Investment Research Service (EIRIS) databank and Bankscope database. The data consists of 162 banks in 22 countries. We then classified the banks into four types based on their degree of engagement in CSR. This study proposes the use of an extended version of the Heckman two-step regression, in which the first step adopts a multinomial logit model, and the second step estimates the performance equation with the inverse Mills ratio generated by the first step. The empirical results show that CSR positively associates with FP in terms of return on assets, return on equity, net interest income, and non-interest income. In contrast, CSR negatively associates with non-performing loans. Hence, strategic choice is the primary motive of banks to engage in CSR.     

Systemic risk contributions: A credit portfolio approach

We put forward a framework for measuring systemic risk and attributing it to individual banks. Systemic risk is coherently measured as the expected loss to depositors and investors when a systemic event occurs. The risk contributions are calculated so as to ensure a full risk allocation among institutions. Applying our methodology to a panel of 54–86 of the world’s major commercial banks for a 13-year time span with monthly frequency not only allows us to closely match the list of G-SIBs; we can also use individual risk contributions to compute bank-specific surcharges: systemic capital charges as well as countercyclical buffers. We therefore address both dimensions of systemic risk – cross-sectional and time-series – in a single integrated approach. As the analysis of risk drivers confirms, the main focus of macroprudential supervision should be on a solid capital base throughout the financial cycle and de-correlation of banks’ asset values.     

Irish credit unions: Investigating performance determinants and the opportunity cost of regulatory compliance

The study investigates how producer-specific environmental factors influence the performance of Irish credit unions. The empirical analysis uses a two-stage approach. The first stage measures efficiency by a data envelopment analysis (DEA) estimator, which explicitly incorporates the production of undesirable outputs such as bad loans in the modelling, and the second stage uses truncated regression to infer how various factors influence the (bias-corrected) estimated efficiency. A key finding of the analysis is that 68% of Irish credit unions do not incur an extra opportunity cost in meeting regulatory guidance on bad debt.     

Variations in sovereign credit quality assessments across rating agencies

We investigate agency variation in credit quality assessment (Standard and Poor’s vs. Moody’s vs. Fitch) employing sovereign ratings data for 129 countries, spanning the period 1990–2006. While we find that the credit rating agencies often disagree about credit quality, it is usually confined to one or two notches on the finer scale. We find that several variables have varying importance in explaining ratings across agencies which leads us to conclude that material heterogeneity exists between them. Also, while watch and outlook procedures are generally strong predictors of rating changes relative to other public data, additional significant variables suggest that it might be possible to augment these agency data to provide better forecasts of future rating changes.     

Counter-cyclical substitution between trade credit and bank credit

This paper explores the substitution relationship between trade credit and bank credit, and its counter-cyclic dynamic pattern through economic cycles. We propose a new theoretical model, using a mechanism design method, which predicts the substitution between the two credits and its counter-cyclic behavior, subject to the condition of technological efficiency not less than one. This model also helps explain the somewhat contradictory evidence in the literature, on the relationship between the two credits. We present empirical evidence on the substitution effect and its counter-cyclic behavior, by using a balanced panel data set of 284 listed Chinese companies for the period 1998-2006. We further find that the substitution behaves counter-cyclically with respect to the coincident macroeconomic indicator, namely, GDP. Our empirical analysis also has some new features such as treating endogeneity carefully and incorporating the lag-effect of trade credit coherently.     

Asymmetric effects of the business cycle on bank credit risk

Prior empirical research on the relation between credit risk and the business cycle has failed to properly investigate the presence of asymmetric effects. To fill this gap, we examine this relation both at the aggregate and the bank level exploiting a unique dataset on Italian banks’ borrowers’ default rates. We employ threshold regression models that allow to endogenously establish different regimes identified by the thresholds over/below which credit risk is more/less cyclical. We find that not only are the effects of the business cycle on credit risk more pronounced during downturns but cyclicality is also higher for those banks with riskier portfolios.     

Reject inference in consumer credit scoring with nonignorable missing data

We generalize an empirical likelihood approach to deal with missing data to a model of consumer credit scoring. An application to recent consumer credit data shows that our procedure yields parameter estimates which are significantly different (both statistically and economically) from the case where customers who were refused credit are ignored. This has obvious implications for commercial banks as it shows that refused customers should not be ignored when developing scorecards for the retail business. We also show that forecasts of defaults derived from the method proposed in this paper improve upon the standard ones when refused customers do not enter the estimation data set.     

Checking for asymmetric default dependence in a credit card portfolio: A copula approach

Traditional credit risk models adopt the linear correlation as a measure of dependence and assume that credit losses are normally-distributed. However some studies have shown that credit losses are seldom normal and the linear correlation does not give accurate assessment for asymmetric data. Therefore it is possible that many credit models tend to misestimate the probability of joint extreme defaults.This paper employs Copula Theory to model the dependence across default rates in a credit card portfolio of a large UK bank and to estimate the likelihood of joint high default rates. Ten copula families are used as candidates to represent the dependence structure. The empirical analysis shows that, when compared to traditional models, estimations based on asymmetric copulas usually yield results closer to the ratio of simultaneous extreme losses observed in the credit card portfolio.Copulas have been applied to evaluate the dependence among corporate debts but this research is the first paper to give evidence of the outperformance of copula estimations in portfolios of consumer loans. Moreover we test some families of copulas that are not typically considered in credit risk studies and find out that three of them are suitable for representing dependence across credit card defaults.     

Bank credit risk and structural credit models: Agency and information asymmetry perspectives

This work investigates the effects of agency and information asymmetry issues embedded in structural form credit models on bank credit risk evaluation, using American bank data from 2001 to 2005. Findings show that both the agency problem and information asymmetry significantly cause deviations in the credit risk evaluation of structural form models from agency ratings. Five independent factors explain a deviation of 42.6–78.3% and should be incorporated into future credit risk modeling. Additionally, both the effects of information asymmetry and debt-equity agency positively relate to the deviation while that of management-equity agency relates to it negatively.     

Estimating the degree of operating efficiency gains from a potential bank merger and acquisition: A DEA bootstrapped approach

We propose a bootstrapped Data Envelopment Analysis (DEA)-based procedure to pre-calculate and pre-evaluate the short-run operating efficiency gains of a potential bank merger or acquisition (M&A). As an illustrative example, we apply our proposed procedure to investigate the degree of operating efficiency gains of 45 possible bank M&As in the Greek banking industry over the period from 2007 to 2011. The results reveal that a year before and a year after the initiation of the Greek fiscal crisis, the majority of the potential bank M&As under examination were unable to generate short-run operating efficiency gains. In addition, our results for 2011 indicate that the majority of bank M&As can lead to short-run operating efficiency gains. Finally, the empirical findings support the view that a merger or acquisition between efficient banks does not ensure an efficient bank M&A.     

Good and bad credit contagion: Evidence from credit default swaps

This study examines the intra-industry information transfer effect of credit events, as captured in the credit default swaps (CDS) and stock markets. Positive correlations across CDS spreads imply that contagion effects dominate, whereas negative correlations indicate competition effects. We find strong evidence of contagion effects for Chapter 11 bankruptcies and competition effects for Chapter 7 bankruptcies. We also introduce a purely unanticipated event, in the form of a large jump in a company's CDS spread, and find that this leads to the strongest evidence of credit contagion across the industry. These results have important implications for the construction of portfolios with credit-sensitive instruments.     

Lending competition and credit availability for new firms: Empirical study with the price cost margin in regional loan markets

In this paper, I present statistical evidence of the impact of lending competition on credit availability for new firms. A discrete-time duration analysis with respect to the years from the start-up to the first loan approval by a commercial bank or a cooperative bank, which is collected from survey data in Japan, shows that the higher price cost margin (PCM) of banks, which reflects the existence of a quasi-rent for a bank, improves the credit availability for younger firms. Additional analysis to detect the regional determinants of the PCM of banks shows that the share of larger banks in each local credit market has a negative and significant impact on the PCM. In light of the existing empirical finding that smaller banks are more likely to provide relationship banking, these findings provide indirect evidence for the hypothesis that the intensity of relationship banking in each local credit market increases the PCM and this encourages banks to extend a loan to new firms so that they can pre-empt the opportunity to establish lending relationships that are expected to yield such quasi-rents.     

Corporate credit risk modeling and the macroeconomy

Despite a surge in the research efforts put into modeling credit and default risk during the past decade, few studies have incorporated the impact that macroeconomic conditions have on business defaults. In this paper, we estimate a duration model to explain the survival time to default for borrowers in the business loan portfolio of a major Swedish bank over the period 1994–2000. The model takes both firm-specific characteristics, such as accounting ratios and payment behaviour, loan-related information, and the prevailing macroeconomic conditions into account. The output gap, the yield curve and consumers’ expectations of future economic development have significant explanatory power for the default risk of firms. We also compare our model with a frequently used model of firm default risk that conditions only on firm-specific information. The comparison shows that while the latter model can make a reasonably accurate ranking of firms’ according to default risk, our model, by taking macro conditions into account, is also able to account for the absolute level of risk.     

A framework for assessing the systemic risk of major financial institutions

In this paper we propose a framework for measuring and stress testing the systemic risk of a group of major financial institutions. The systemic risk is measured by the price of insurance against financial distress, which is based on ex ante measures of default probabilities of individual banks and forecasted asset return correlations. Importantly, using realized correlations estimated from high-frequency equity return data can significantly improve the accuracy of forecasted correlations. Our stress testing methodology, using an integrated micro–macro model, takes into account dynamic linkages between the health of major US banks and macro-financial conditions. Our results suggest that the theoretical insurance premium that would be charged to protect against losses that equal or exceed 15% of total liabilities of 12 major US financial firms stood at $110 billion in March 2008 and had a projected upper bound of $250 billion in July 2008.