The Texaco racial discrimination case and shareholder wealth

We analyze the wealth ejfects of the Texaco racial discrimination lawsuit both on the shareholders of Texaco and its major U.S. competitors. Employing a comprehensive data set which included every case docket entry and every Wall Street Journal article on the case as an experimental stimulus, our findings suggest that the overall cost of the case to Texaco shareholders exceeded $500 million, that Texaco's tribulations had little, if any, impact on the share prices of its major competitors, and that Wall Street Journal coverage of the case was highly correlated with significant changes in Texaco stock prices. This last finding provides significant support for Hite 's suppostion that newspaper editors “key ” on ex post stock price changes in selecting the events to be covered in the next day's edition. The authors are grateful to Kee Chung for helpful comments on earlier drafts and also acknowlege the help-ful assistance of the staff of the law library at the Cecil C. Humphreys School of Law at The University of Memphis.     

Implementation in generic environments

In this paper, we study implementation in “economic environments”. It is shown that there is a dense subset of the set of preference profiles such that given an arbitrary social choice function, f, and ε>0, there exists another social choice function, f _ε, within ε of f uniformly and implementable in Nash equilibrium on the dense subset.     

A Comparison of Partially Adaptive and Reweighted Least Squares Estimation

The small sample performance of least median of squares, reweighted least squares, least squares, least absolute deviations, and three partially adaptive estimators are compared using Monte Carlo simulations. Two data problems are addressed in the paper: (1) data generated from non-normal error distributions and (2) contaminated data. Breakdown plots are used to investigate the sensitivity of partially adaptive estimators to data contamination relative to RLS. One partially adaptive estimator performs especially well when the errors are skewed, while another partially adaptive estimator and RLS perform particularly well when the errors are extremely leptokur-totic. In comparison with RLS, partially adaptive estimators are only moderately effective in resisting data contamination; however, they outperform least squares and least absolute deviation estimators.     

Membranes, mitochondria and amoebae: shape models

Most real-world shapes and images are characterized by high variability- they are not rigid, like crystals, for example—but they are strongly structured. Therefore, a fundamental task in the understanding and analysis of such image ensembles is the construction of models that incorporate both variability and structure in a mathematically precise way. The global shape models introduced in Grenander's general pattern theory are intended to do this. In this paper, we describe the representation of two-dimensional mitochondria and membranes in electron microscope photographs, and three-dimensional amoebae in optical sectioning microscopy. There are three kinds of variability to all of these patterns, which these representations accommodate. The first is the variability in shape and viewing orientation. For this, the typical structure is represented via linear, circular and spherical templates, with the variability accomodated via the application of transformations applied to the templates. The transformations form groups: scale, rotation and translation. They are locally applied throughout the continuum and of high dimension. The second is the textural variability; the inside and outside of these basic shapes are subject to random variation, as well as sensor noise. For this, statistical sensor models and Markov random field texture models are used to connect the constituent structures of the shapes to the measured data. The third variability type is associated with the fact that each scene is made up of a variable number of shapes; this number is not assumed to be known a priori. Each scene has a variable number of parameters encoding the transformations of the templates appropriate for that scene. For this, a single posterior distribution is defined over the countable union of spaces representing models of varying numbers of shapes. Bayesian inference is performed via computation of the conditional expectation of the parametrically defined shapes under the posterior. These conditional mean estimates are generated using jump-diffusion processes. Results for membranes, mitochondria and amoebae are shown.     

INTERGENERATIONAL MOBILITY IN THE REPUBLIC OF IRELAND: Does Gender Make a Difference?

This article compares in regression models the effects of occupational status of both fathers and mothers simultaneously upon the attainment of men and women in the Irish Republic. The sample matches male respondents from the 1973/1974 Irish Mobility Study with the labour active female sibling next closest in age. Since the analysis compares working siblings and each 'matched pair' shares the same family origin characteristics, the problems attendant upon using a sample originally of men only are partially avoided. The results advance beyond previous research since, rather than separate models by gender, models include parents and children of both genders, allowing direct rather than indirect evaluation of gender-based determinants of occupational attainment. Both fathers and mothers significantly affect children's attainment, in ways that vary by the child's gender. The results highlight the salience of mothers' attainment for their children and question the 'mainstream' model of equivalent mechanisms of occupational attainment for both genders. Models of social mobility that consider men and women as special instances of a general perspective provide the most fruitful approach for further development.     

ON THE INDEPENDENCE OF THE SAMPLE MEAN AND TRANSLATION-INVARIANT STATISTICS FOR MATRIX NORMAL DISTRIBUTIONS

We present an explicit characterization of the joint dependency structure of an n×p matrix normal random matrix such that the p-dimensional sample mean vector is independent of all translation invariant statistics.     

UNDERSTANDING MAIL SURVEY RESPONSE BEHAVIOR A META-ANALYSIS

A meta-analysis of prior studies of techniques designed to inducemail survey response rates was conducted. Research encompassing184 effects (study outcomes) in 115 studies (articles) for 17predictors of response rate was examined. The average effectsize across all manipulations was r=.065, indicating an averageincrease of about 6.5 percent in response rates for manipulations.Effect sizes for specific predictors and two potential moderatorsof effects were examined. Results indicated that repeated contactsin the form of preliminary notification and follow-ups, appeals,inclusion of a return envelope, postage, and monetary incentives,were effective in increasing survey response rates. Significanteffect sizes for the predictors ranged from an increase in responseof 2 percent to 31 percent. Implications of the results forthe conduct of mail surveys and future research on mail surveyresponse behavior are discussed.