On fair compensation

This paper analyses the problems arising in the pure exchange fair division model, when some dimensions of the resources are personal, fixed, and cannot be redistributed. The remaining resources must then be allocated in a compensatory way. A set of desirable normative properties is defined. No-envy satisfies these properties, but is not generally non-empty in this setting and other criteria are examined, for which existence results are given. General impossibility results obtain. In particular, it is generally impossible to compensate fully and only for differential personal resources, when preferences differ.     

Metropolitanizing Nonmetro Space: Population Redistribution and Emergent Metropolitan Areas, 1965–901

Abstract The recent volatility of population redistribution trends in the U.S. continues to stimulate the demographic imagination. This research sheds new light on this subject through an examination of newly designated metro areas, which collectively constitute the largest source of national metropolitan growth in two of the past three decades. The results show that, over this period, new metro areas have consistently drawn the majority of migrants from inter-state exchanges with existing metro territory and that these exchanges are greatest from census divisions that achieved metropolitan dominance prior to 1920. Employment data also reveal a strong positive association between FIRE activities and net in-migration. Together, these findings suggest that traditional processes of urban concentration, while present, now play a secondary role in the development of new metro centers, thus challenging conventional theories of metropolitanization where we might most expect them to apply.     

Decentralizing Risk Analysis in Large Engineered Systems: An Approach to Articulating Technical and Socioorganizational Dimensions of System Performance1

Nuclear power production in France, as the domain of one national utility and one reactor builder, has a standardized profile of technical installations, safety procedures, and personnel qualifications. Despite this relative homogeneity, discrepancies are observed from one production unit to another, notably in the area of worker-safety performance. There is a strong implication for risk analysis: varying performance cannot be attributed solely to the technical dimensions of equipment, procedures, and human skills. The authors retain as a working hypothesis that safety performance is an outcome of interactions between technical and organizational factors. Traditional risk analysis appears to be underequipped to represent such interactions. The notion of decentralized risk analysis (DRA) is introduced as a means of achieving this goal. A program of applied research carried out in a NPP facility is presented. It aims at increasing, across plant work structure, knowledge and control of these interactions specific to the given context. Systematic measurements and feedback of social representations are performed, using a three-dimensional factor space of individual and organizational values. Direct involvement of the total plant population, transfer of analytic tools, methodological continuity, interactive elaboration of data, coordination of different levels of findings with operations, follow-up and feedback of measured change, are the main features of this DRA process. In the case cited, improvement observed in safety performance parallels changes in measured social representations. The value of DRA for articulating technical and organizational dimensions of risk, and for integrating information into decision-making, is argued.     

Sur l'estimation du risque encouru en reconstruisant une forme aléatoire

The problem of estimating the risk corresponding to the reconstruction of a random pattern is reviewed. It is shown that for a particular but important model, the problem is reduced to the estimation of two parameters closely related to those appearing in a two-state Markov chain, which is of independent interest. The estimation of the Markov chain's parameters is studied from the decision-theoretic point of view. Estimators which are better than others previously considered are obtained and adapted to the estimation of the corresponding risk. Examples are are analyzed; even if a very empirical method is used to give values to the parameters of an a priorilaw, some good estimators of the risk are obtained.     

Comparison of open versus closed group interventions for sexually abused adolescent girls

A first aim of this study is to evaluate the efficacy of an open group therapy for sexually abused teenagers using a quasi-experimental pretest/posttest treatment design. A second aim was to explore whether differential gains were linked to an open versus a closed group format. Results indicate that sexually abused girls involved in an open group therapy showed significant gains relative to teenagers of the control group girls for the majority of the variables considered. Analyses contrasting the two formats of group therapy fail to identify statistical differences suggesting that both open and closed group formats are likely to be associated with the same significant gains for sexually abused teenagers.     

Profit implications of estimation methods for the allocation of marketing resources

We deal with the question whether estimating heterogeneous multiplicative sales response models without carry over effects by either ordinary least squares or Gibbs sampling makes a difference if resources (like advertising budgets, sales budgets, sales force sizes, sales calls) have to be allocated to sales units (like sales districts, customer groups, individual costumers or prospects) in a profit maximizing way and only short time series are available. To this end we generate artificial series on sales and allocations by stochastic simulation. These series are used to estimate multiplicative models whose coefficients are either specific to individual sales units or follow a hierarchical Bayesian framework. Ordinary least squares and Gibbs sampling serve as appropriate estimation methods. Performance of the two estimation methods is measured by recovery of optimal profits which are computed on the basis of the known true parameter values. We start to determine optimal allocations based on the plug-in method which uses average coefficients to determine expected profits. Gibbs sampling always leads to profits nearer to the true optima. This advantage of Gibbs sampling is especially pronounced for combinations with high average elasticity, high variation of elasticity and high number of sales units. On the other hand, differences between Gibbs sampling and OLS become smaller the more observations are available. Optimization with expected profits taking parameter uncertainty (i.e., the distribution of parameters) into account leads to higher profits than the plug-in method, but relative increases turn out to be rather small.