Peter J. Nigro

Risk-based capital, portfolio risk, and bank capital: A simultaneous equations approach

This paper examines the impact the recently implemented risk-based standards have had on both bank capital and portfolio risk. To date, little if any attention has focused on how the risk-based capital standards have impacted bank risk and capital levels. Building on previous research, this paper uses a three-stage least squares (3SLS) model to analyze the relationship between bank capital, portfolio risk, and the risk-based capital standards. The results suggest that the risk-based capital standards had a significant impact on capital and risk levels in well-capitalized banks, but little impact on undercapitalized banks.

Mutual fund shareholders: characteristics, investor knowledge, and sources of information

Abstract This paper examines responses from a survey of 2,000 randomly selected mutual fund investors who purchased shares from six different distribution channels. The survey provides data on the demographic, financial, and fund ownership characteristics of mutual fund investors. It also provides data on investors’ knowledge of the costs and investment risks of mutual funds and the information sources these investors use to learn about these costs and risks. Our survey results strongly suggest there is room for improvement in the level of financial literacy of mutual fund investors.

Measuring the Default Risk of Small Business Loans: A Survival Analysis Approach

In this paper we report that, although medium-maturity loans originated under the SBA 7(a) loan guarantee program are targeted to small firms that fail to obtain credit through conventional channels, the default experience is comparable to that of a large percentage of loans held by larger commercial banks. We establish that the default behavior of these loans is time sensitive— as a loan seasons, the likelihood of default increases initially, peaks in the second year, and declines thereafter. Using a discrete-time hazard framework, we show that the likelihood of default is conditional on borrower, lender, and loan characteristics, and changes in economic conditions.

Do Predatory Lending Laws Influence Mortgage Lending? An Analysis of the North Carolina Predatory Lending Law

In this paper, we examine the effect of the 1999 North Carolina predatory lending law on mortgage activity in that state as compared to other states in the Southeastern United States. Using 1998–2000 Home Mortgage Disclosure Act (HMDA) data, we find that the North Carolina law reduced the overall level of subprime mortgage lending activity. Furthermore, we find that the North Carolina decline was caused by a decline in loan application volume and not by a change in loan denial rates, suggesting less aggressive marketing in that state after the imposition of the law. Finally, the impact of the legislation was different by both the type of financial service provider and borrower. Specifically, non-bank subprime lending contracted faster in North Carolina when compared to the control group, while both minority and low-income applicants were also less likely to get loans following the legislation. These results have wide ranging policy implications given that several predatory lending proposals are currently before Congress, as well as proposed in almost forty other states.

The Information Revolution and Small Business Lending: The Missing Evidence

This paper provides empirical confirmation for Petersen and Rajans (2002) widely accepted conjecture that information technology was the primary driver of the observed increase in small business borrower-lender distances in the United States in recent years. Using a different data source for small business loans, we show that annual increases in borrower-lender distances were slow and steady prior to 1993 (the end point in Petersen and Rajans data) but accelerated rapidly after that. Importantly, we are able to assign at least half of this acceleration to the adoption of credit scoring technologies by the lending banks. Our tests also reveal strong statistical associations between lending distances and borrower characteristics, lender characteristics, market conditions, regulatory constraints, moral hazard incentives, and principal-agent incentives.

Investor Self-Selection: Evidence from a Mutual Fund Survey

Using survey data on a random sample of 2000 mutual fund investors, we classify investors by their level of financial literacy and their place of mutual fund purchase. After using a probit model to separately estimate the determinants of an investors choice of distribution channel and level of financial literacy, a bivariate probit model that jointly endogenizes an investors level of financial literacy and choice of distribution channel is estimated. Strong evidence that an investors level of financial literacy and choice of distribution channel are jointly determined is found. Thus, the hypothesis put forth in this paper, that investors self-select into different distribution channels based on their overall level of financial literacy, is supported by the data.

Does mutual fund disclosure at banks matter? Evidence from a survey of investors.

Abstract This paper examines the responses from a survey of investors who purchased mutual funds from banks and elsewhere. We find that bank-channel investors are less financially literate than those investors purchasing funds through other distribution channels. Using a treatment-effects econometric model, however, we also find that purchasing only through banks actually raised the knowledge level of these investors. This result suggests that the increased focus on disclosure at banks has had a positive effect on investor financial literacy, and that disclosure requirements in the Gramm-Leach-Bliley Act of 1999 are likely to be beneficial. However, investor financial literacy still needs improvement.

Disparities in Mortgage Lending, Bank Performance, Economic Influence, and Regulatory Oversight

This study investigates factors affecting changes in the disparity of home mortgage denial rates between white and minority loan applicants in the U.S. during the period 1991–1997. We develop a two-stage least-squares regression model that incorporates applicant-level characteristics, neighborhood characteristics, regional economic data, and bank-specific data as explanatory variables. Some have argued that mortgage lenders were under increasing pressure from industry regulators to extend additional credit to minorities and low-income groups during the period under study. The model includes each institutions periodic CRA rating as a proxy for regulatory influence. An alternative explanation is that market forces, such as improvements in economic conditions and in bank financial condition and performance, affected default loss estimates and credit standards in a way that disproportionally benefited minority and low-income applicants. The empirical findings are consistent with the latter hypothesis. We conclude that policy makers should consider the impact of market factors when assessing the allocation of mortgage credit in a particular demographic market. The findings also underscore the importance of controlling for lender assessments of credit risk when evaluating compliance with CRA and fair lending statutes.

Evaluating the performance of static versus dynamic models of credit default: evidence from long-term Small Business Administration-guaranteed loans

The financial crisis exposed the limitations of credit risk models to risk managers, financial regulators, investors and rating agencies. We compare the performance of conventional static-scoring techniques employed in practice with dynamic survival-time models to predict dollar losses on a portfolio of smallbusiness loans.We find that the dynamic models consistently generate more accurate dollar-loss forecasts over multiple time periods and performance horizons. Ourresultssupportthehypothesisthatseasoningisakeyfactorinthedevelopment ofaccuratelossforecastsforlonger-termamortizingloans(eg,small-businessand mortgageloans).Furthermore,ourresultssuggestthatbanksconsiderdeveloping capital adequacy, loan-loss provisioning and securitized loan valuation models with a dynamic sample and model design.

Do Persistence and Passion Matter: Evidence from the Educational Testing Service Major Field Test in Business.

ABSTRACT The authors examined the determinants of success on the Educational Testing Service Major Field Test in Business. The authors find that gender, SAT performance, and concentration are significant predictors of performance. Additionally, they derive proxies for student passion and persistence, and find that the greater the students passion for business is, the higher the score is. The authors discover that students who demonstrate persistence, as measured by the extent to which they outperform their grade point average expectations, also score higher on the exam.