Knowledge that Transforms

Pension plan termination, Financial slack, Overfunded pension funds

Decision making, Centralized decision making, Delegated decision making, Value of communication

Voluntary Disclosure, Management forecasts, Intraindustry effect, Information dissemination

Cost allocation, Noncontrollable cost allocation, Collusion, Performance evaluation

Auditing, Sampling, Qualified opinion

Stock market Disciplining, Rational expectations model, Managerial decision making

This paper provides a framework and some empirical evidence to evaluate the seriousness of problems in inference that arise in stockreturn-based studies when the data are cross-sectionally dependent. The study is motivated on the grounds that statistical procedures designed to address such problems are often infeasible, and even when they can be implemented they sometimes introduce other more serious difficulties. Thus, researchers have frequently adopted an approach that ignores the cross-sectional dependence (e.g., ordinary least squares [OLS]). The objective of this paper is to help identify the contexts in which ignoring the dependence would lead to serious misstatement of significance levels. Cross-sectional dependence in stock returns data is likely to exist when at least some of the returns are sampled from common time periods. This would be the case in all studies of the reaction of stock prices to a

Robert Jennings, Unsystematic Security Price Movements, Management Earnings Forecasts, and Revisions in Consensus Analyst Earnings Forecasts, Journal of Accounting Research, Vol. 25, No. 1 (Spring, 1987), pp. 90-110

Auditing, Auditor size, Audit fees, Audit partnerships

The model presented here extends previous corporate failure prediction models (e.g., Beaver [1966], Altman [1968], Altman, Haldeman, and Narayanan [1977], Ohlson [1980], Zavgren [1985], etc.) in two ways: (1) instead of the conventional failing/nonfailing dichotomy, five financial states are used to approximate the continuum of corporate financial health; and (2) instead of classifying a firm into a certain financial state, the new model will estimate the probabilities that a firm will enter each of the five financial states. The ranked probability scoring rule is then used to evaluate the quality of such probabilistic predictions. The first extension enables the prediction of prefailure distress in addition to ultimate failure. The second extension conforms with more recent advances in prediction methodologies (see, e.g., Epstein [1969] and Murphy and Winkler [1970]). Together, the two extensions provide a better approximation to the continuum of alternative financial judgment and actions in reality. Sections 2 and 3 explain the structure of the model and the data; section 4 explains the statistical methodology (multivariate logit analysis) and presents the constructed models. These models are evaluated in section 5.