Beyond Transparency: Information Overload and a Model for Intelligibility

The role and evaluation of the modern corporation is being challenged by multiple stakeholders, changing markets and public expectations. Unfortunately, corporate governance, regulation and accounting have played a prominent role in business failure for the past decade resulting in a growing lack of public confidence in our markets. We present a new model that contributes to improving the quality of corporate information by providing not more, but better information through increased intelligibility of overall information, benefiting both the firm and its broad array of stakeholders. It has become apparent that boards, management and regulators have been unable to cope with the rise of business failures by adding increasing layers of regulation that have often served only to exacerbate the complexity and further cloud the transparency of needed information. We have identified a growing number of forward‐thinking firms that have found alternative means to provide betterinformation and strengthen their companies. We offer a stakeholder‐centric model for improving information intelligibility based upon the extensive scope and variety of external input derived from the growing social movement organizations. With the added focus on intelligibility, these groups can help foster greater corporate responsibility, meaningful transparency, increased stakeholder benefits, and improved overall performance of the firm.     

On the Social Dimensions of Moral Psychology

Contemporary moral psychology has been enormously enriched by recent theoretical developments and empirical findings in evolutionary biology, cognitive psychology and neuroscience, and social psychology and psychopathology. Yet despite the fact that some theorists have developed specifically “social heuristic” (Gigerenzer, 2008) and “social intuitionist” (Haidt, 2007) theories of moral judgment and behavior, and despite regular appeals to the findings of experimental social psychology, contemporary moral psychology has largely neglected the social dimensions of moral judgment and behavior. I provide a brief sketch of these dimensions, and consider the implications for contemporary theory and research in moral psychology.     

Orthogonalized Residuals for Estimation of Marginally Specified Association Parameters in Multivariate Binary Data

Abstract. This paper focuses on marginal regression models for correlated binary responses when estimation of the association structure is of primary interest. A new estimating function approach based on orthogonalized residuals is proposed. A special case of the proposed procedure allows a new representation of the alternating logistic regressions method through marginal residuals. The connections between second‐order generalized estimating equations, alternating logistic regressions, pseudo‐likelihood and other methods are explored. Efficiency comparisons are presented, with emphasis on variable cluster size and on the role of higher‐order assumptions. The new method is illustrated with an analysis of data on impaired pulmonary function.     

DETECTION OF TURNING POINTS IN A TIME SERIES

Consider a time series for which, over a finite interval, there is a model that provides an adequate forecast of the series. Without loss of genality one can take the series over this period of time to have mean O and variance s̀². At some time the underlying process changes to some other model. The previous model no longer produces errors with mean zero. It is assumed, however, that the variance remains s̀². The problem considered here is to detect the change in the process as quickly as possible after it happens. The technique is a computationally feasible extension of Wald's [14] sequential analysis, to develop a parabolic mask centered over the most recent cumulative sum (“cusum”) of the forecast errors. Detection occurs when any previous point in the series of cusums lies outside the parabola. The technique is illustrated by an APL program applied to the logarithms of weekly changes in closing prices for IBM common stock on the New York Stock Exchange over the period 1968–1970.     

A STUDY OF TIMING AND WITHDRAWALS OF STUDENT ADMISSIONS APPLICATIONS*

This study explores two important characteristics of admissions applications to an M.B.A. and M.P.A. program: the timing of applications throughout the year preceding entrance, and the withdrawal rate by students whose applications have been accepted. Specifically, for the years 1961 through 1967, the aggregate patterns of timing and withdrawals (across all applications) are compared to the corresponding data for four groups of applications, ranging from low quality to high quality. (Quality is measured in terms of a first-year predicted grade point average, and is estimated by a linear regression equation using the applicant's total ATGSB score and his undergraduate grade point average.) The results are in the expected directions: “better” students tend to apply earlier, and also have a higher tendency to withdraw after their applications have been accepted. Potential usefulness of the results in forecasting total applications and estimating withdrawal rates is explored.