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.     

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.      

Job Insecurity and the Timing of Parenthood: A Comparison between Eastern and Western Germany

This article contributes to the ongoing debate on the economic determinants of fertility behavior by addressing the role of job insecurity in couples’ intentions concerning parenthood and its timing. It starts from the hypothesis that cultural values moderate individuals’ reactions to job insecurity and the way it is related to family formation. With a systematic thematic content analysis of a set of semi-structured interviews with childless men and women around the age of 30 in eastern and western Germany, we are able to show that there are substantial differences in the consequences of job insecurity on intentions to have a first child. In western Germany, a relatively secure job career is expected to precede family formation, and this sequence of transitions is rather rigid, whereas in eastern Germany job security and family formation are thought of and practiced as parallel investments. We suggest that the lack of convergence in family formation patterns between eastern and western Germany after the unification of the country in 1990 is partially related to different attitudes toward job insecurity in the two contexts.     

A regression-based smoothing spline Monte Carlo algorithm for pricing American options in discrete time

American options in discrete time can be priced by solving optimal stopping problems. This can be done by computing so-called continuation values, which we represent as regression functions defined recursively by using the continuation values of the next time step. We use Monte Carlo to generate data, and then we apply smoothing spline regression estimates to estimate the continuation values from these data. All parameters of the estimate are chosen data dependent. We present results concerning consistency and the estimates’ rate of convergence.