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.     

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.     

Exploring multivariate data graphically:a brief review with examples

Many methods for obtaining graphical representations of multivariate data have been suggested over the last decade, but it is only relatively recently that software has become available which makes use of these procedures routine. In this paper, a number of examples are used to illustrate the application of graphical methods for the exploration of multivariate data. The diagrams produced may prove useful in consultations with clients and in examining the results from more formal methods.     

Sources of drug information among adolescent students

A sample of 1023 eighth and tenth grade students in small to medium-sized central Texas school districts was assessed to determine the amount of information they receive from ten sources about six categories of drugs. The amount of information males reported receiving about each drug category was significantly greater than what females reported, and the amount of information that eighth graders reported receiving about each drug category was significantly greater than what tenth graders reported. Television was the primary source of drug information for all categories of drugs except inhalants, for which friends and television were equally important sources. Parents and printed media (magazines or newspapers) were of secondary importance, followed by friends and teachers. Adolescents were less likely to receive drug-related information from experience, siblings, church, doctors, and police. The reliance on the mass media for drug information in smaller school districts is a pattern which has been previously observed in larger urban districts. This consistency suggests that mass media approaches to drug education are likely to be as effective in rural areas and smaller towns as they are among urban adolescents. Implications for television programming are discussed.     

Book Review: Beyond Earth Day: Fulfilling the Promise. Gaylord Nelson with Susan Campbell and Paul Wozniak. Madison,WI: The University of Wisconsin Press, 2002: 160 pp.

Population and Environment -     

Bayesian analysis of directed graphs data with applications to social networks

Summary.  A fully Bayesian analysis of directed graphs, with particular emphasis on applica- tions in social networks, is explored. The model is capable of incorporating the effects of covariates, within and between block ties and multiple responses. Inference is straightforward by using software that is based on Markov chain Monte Carlo methods. Examples are provided which highlight the variety of data sets that can be entertained and the ease with which they can be analysed.     

A Review of Kyoto Protocol Adoption in Russia: Joint Implementation in Focus

Russia’s role in ‘animation’ of the Kyoto Protocol was crucial. Its initial vacillation on ratification was predominantly due to political bargaining with the EU. Domestic economic rationales [i.e. impacts of emission trading and Joint Implementation (JI) projects] were important to a much lesser extent and environmental motives did not seem to play any role in the decision. Since the Protocol entered into force, there have been significant delays in complete establishment of policy implementation frameworks, which are necessary for Russia to start benefiting from JI and emission trading. Only recently, in 2007, have GHG inventories and a national registry been established and the responsibilities for implementation of the Protocol and JI among the government departments have been distributed only to a certain extent. Some constraints hindering JI projects, such as vague legislation, an unfavourable economic climate, lack of commitment to JI projects, corruption, xenophobia, state and agency ‘capture’ still remain.