Marvin Karson

Personal values and business decisions: An exploratory investigation

Interest in subjective values and decision responses are investigated empirically, including statistically testing the predictive relationships between subjective values, other independent variables such as level and area of executive responsibility, and decision responses.

Managers, values, and executive decisions: An exploration of the role of gender, career stage, organizational level, function, and the importance of ethics, relationships and results in managerial decision-making

A study of 513 executives researched decisions involving ethics, relationships and results. Analyzing personal values, organization role and level, career stage, gender and sex role with decisions in ten scenarios produced conclusions about both the role of gender, subjective values, and the other study variables and about situational relativity, gender stereotypes, career stages, and future research opportunities.

Estimation of p(y<x) in the gamma case

We consider estimation of P(Y<X) when X˜Γr(M,λ) and Y˜Γ(N,μ) are independent with M and N known. A concise representation of the UMVUE and several representations for the MLE are derived. Closed-form exact expressions of both MSEs and the bias of the MLE are obtained. Large-sample results are given and numerical comparison of the two point estimators is made. Confidence intervals are given.

Bayesian spatial prediction

This paper presents a complete Bayesian methodology for analyzing spatial data, one which employs proper priors and features diagnostic methods in the Bayesian spatial setting. The spatial covariance structure is modeled using a rich class of covariance functions for Gaussian random fields. A general class of priors for trend, scale, and structural covariance parameters is considered. In particular, we obtain analytic results that allow easy computation of the predictive distribution for an arbitrary prior on the parameters of the covariance function using importance sampling. The computations, as well as model diagnostics and sensitivity analysis, are illustrated with a set of precipitation data.

Managers Vs. Owners the Struggle for Corporate Control in American Democracy

This book deals with a subject of profound importance to understanding the place of the modern corporation in a democratic society. This is the inherent conflicts between the interest of corporate owners (the shareholders), the interest of the larger society, and the interest of the managers who run the corporations. Managers have created a shared professional ideology that is designed to preserve their autonomy. To protect itself from unbridled corporate power, government has enacted a myriad regulations to check this power. The book describes how, in different eras the balance between corporate power and government regulation has changed with the interests of society as a whole. The authors conclude by looking at the impact of collective investor action--especially institutional investors--on the efforts by managers to preserve their autonomy.

The effect of unequal priors and unequal misclassification costs on MDA

Multiple discriminant analysis (MDA) is a frequently used statistical technique. Although the dependence of this technique on the underlying assumptions concerning population priors and misclassification costs is well known, the assumption most often made by researchers is that both population priors and misclassification costs are equal. The purpose of this paper is to demonstrate the magnitude of the effect of these assumptions on statistical results. In the savings and loan case used here, the population priors are known:however, the relative misclassification costs are not. To test the sensitivity of the results to the unknown misclassification costs several different misclassification cost assumptions are used.

Confidence interval estimation of P(Y<X) in the gamma case

This paper is concerned with the problem of interval estimation of R = P(Y<X) when X and Y are independent gamma random variables. We compare ten different confidence interval estimators. An important thrust of this paper is to employ bootstrapping methodology to address the problem of robustness with respect to the shape parameters of the gamma distributions. We believe that bootstrapping provides a powerful methodology for studying these problems. Seven of the ten confidence interval estimators considered are based on bootstrapping. Simulation results are presented and discussed, with robustness recommendations.

On estimating the box-cox transformation to normality

This paper studies four methods for estimating the Box-Cox parameter used to transform data to normality. Three of these are based on optimizing test statistics for standard normality tests (the Shapiro-Wilk. skewness, and kurtosis tests); the fourth uses the maximum likelihood estimator of the Box-Cox parameter. The four methods are compared and evaluated with a simulation study, where their performances under different skewness and kurtosis conditions are analyzed. The estimator based on optimizing the Shapiro-Wilk statistic generally gives rise to the best transformations, while the maximum likelihood estimator performs almost as well. Estimators based on optimizing skewness and kurtosis do not perform well in general.

Corporate political action committees' strategies in the 1980 congressional elections

Abstract Corporate political action committees donate millions of dollars to political candidates. They outnumber and outspend labor unions. Begun as a reform in the 1971 Campaign Finance Act, PACs now appear to many as a threat to free elections. Using an original survey of 224 corporations whose PACs donated to 591 candidates, this article applies principal component analysis to evaluate them in terms of their strategy. Is it monolithic? Is it ideologically conservative? Is it anti-labor? Is it merely a pragmatic desire to ingratiate themselves with winners? The analysis finds that the pattern differs for winners and losers. While corporate PACs are not monolithic, they do tend to be either conservative ideologically or anti-labor.

Reliability estimation for the exponential distribution

This paper is concerned with classical statistical estimation of the reliability function for the exponential density with unknown mean failure time θ, and with a known and fixed mission time τ. The minimum variance unbiased (MVU) estimator and the maximum likelihood (ML) estimator are reviewed and their mean square errors compared for different sample sizes. These comparisons serve also to extend previous work, and reinforce further the nonexistence of a uniformly best estimator. A class of shrunken estimators is then defined, and it produces a shrunken quasi-estimator and a shrunken estimator. The mean square errors for both these estimators are compared to the mean square errors of the MVU and ML estimators, and the new estimators are found to perform very well. Unfortunately, these estimators are difficult to compute for practical applications. A second class of estimators, which is easy to compute is also developed. Its mean square error properties are compared to the other estimators, and it outperf...