We examine the effects of structural change in the U.S. banking industry, as well as key regulatory changes, including recently enacted deposit insurance reform legislation, on the resiliency of the FDIC-administered bank insurance fund (BIF) by estimating and comparing the probability of BIF insolvency over time. We do this using a Markov-switching model that relies on historical patterns of BIF disbursements to define the probability of switching among three “states” of the banking industry's financial health. Monte Carlo simulations are then performed to project the financial condition of the BIF over a 50-year period. Our results indicate that the insolvency risk to the bank insurance fund has increased significantly due to industry consolidation, and is mainly due to the concentration of deposits in the 10 largest U.S. banking companies. We also find that recent deposit insurance reforms will cause only a marginal reduction in the risk of BIF insolvency. The increased risk associated with a more concentrated industry structure simply dominates the reform effect.

Abstract We examine the role private equity (PE) sponsors play in the resolution of financial distress of portfolio companies. PE-backed firms have higher leverage and default at higher rates than other companies borrowing in leveraged loan markets. But, PE-backed firms restructure more quickly, avoid bankruptcy court more often, and liquidate less often compared to other highly leveraged firms experiencing financial distress. PE owners are also more likely to retain control post-restructuring, often by infusing capital as firms approach distress. While default frequencies are higher among PE-backed firms, PE investors appear to manage financial distress at lower cost compared to other owners. (JEL G23, G32, G33)

upon establishing a means of distinguishing which of two alternative disclosure treatments is the more -useful. The traditional means of attempting to make such distinction is through rational argumentation. Rational argumentation is very useful in exploring and drawing out the logical implications of alternative treatments, but may not be sufficient to enable selection of the better treatment. Recently attempts have been made to employ the Predictive as the means of distinguishing the better of two alternative accounting measurements. This criterion selects as the better of two alternative accounting measurements the one which has the greater to predict a given event considered to be of particular importance.' Surely the application of the predictive ability criterion in accounting research can accomplish much, but continual effort should be made to bring other research methods to bear on the problem of improving accounting disclosure. This paper presents an effort to develop a criterion

Neil C. Churchill, Audit Recommendations and Management Auditing: A Case Study and Some Remarks, Journal of Accounting Research, Vol. 4, Empirical Research in Accounting: Selected Studies 1966 (1966), pp. 128-151

Research Methodology, Security market model, Prediction errors, Daily returns data

Research Methodology, Market model prediction errors, Omitted variables

Complexity has been linked to the quality of an income tax system (Dean, Keenan, and Kenney [1980]), including its possible influence on the system's ability to generate revenues (New York State Bar Association [1972]). Given the IRS' recent estimate that $81 billion in annual revenue is lost through noncompliance (IRS [1983, p. 21]), the question of whether tax complexity has a significant effect on taxpayers' reporting positions is a potentially important issue. Complexity represents but one strand in a web of interrelated factors and propositions influencing compliant tax reporting in a democratic society. Nevertheless, it has been singled out as a factor affecting compliance and a study of its effect thereon can be viewed as one step in an ongoing program of study of noncompliance. This study involved two distinct phases. The first phase was devoted to obtaining operational definitions of tax complexity, using multidimensional scaling. These definitions of tax complexity were then used in the second phase of the study to test for potential effects of complexity on reporting position selections in four different tax situations. While phase 1 is critical to phase 2 of my study, this paper highlights the results of the latter. Details of phase 1 can be obtained in Milliron [1984]. In section 2 I discuss previous literature involving tax complexity. Section 3 provides an overview of the methodology and the research issues studied. Sections 4 and 5 describe the data collection procedures

Corporate failure, Reporting delays, Information dissemination, Annual reports

Asset valuation, Replacement costs, Fixed asset lives, Depreciation

Information evaluation, Information systems, Group decision making, Group performance