Search

This paper examines the determinants of the choice of the college major when the length of studies and future earnings are uncertain. We estimate a three-stage schooling decision model, focusing on the effect of expected earnings on major choice. We control for dynamic selection through the use of mixture distributions. Exploiting variations across the French business cycle in the relative returns to the majors, our results yield a very low, though significant, elasticity of major choice to expected earnings. This suggests that, at least for the French university context, non-pecuniary factors are a key determinant of schooling choices. [ABSTRACT FROM AUTHOR]

Unit-dose drug distribution systems provide optimal choices in terms of medication security and efficiency for organizing the drug-use process in large hospitals. As small hospitals have to share such automatic systems for economic reasons, the structure of their logistic organization becomes a very sensitive issue. In the research reported here, we develop a generalized multi-level optimization method - multi-level particle swarm optimization (MLPSO) - to design a shared unit-dose drug distribution network. Structurally, the problem studied can be considered as a type of capacitated location-routing problem (CLRP) with new constraints related to specific production planning. This kind of problem implies that a multi-level optimization should be performed in order to minimize logistic operating costs. Our results show that with the proposed algorithm, a more suitable modeling framework, as well as computational time savings and better optimization performance are obtained than that reported in the literature on this subject. [ABSTRACT FROM AUTHOR]

Although numerous mathematical models focusing on measles dynamics have been proposed in the literature, efforts in this area have concentrated essentially on the mechanisms of measles propagation. If present, vaccination diffusion is treated as an exogenous factor. Here we propose a model focused on the course of measles in France in which the mechanisms of vaccination diffusion are explicitly modeled. The parameters in this model are estimated by an original method based on an expectation-maximization algorithm. This model gives indications of the way in which measles propagation and vaccination diffusion interact. It also allows discussion of the possibility of eliminating this disease in France in the near future. [ABSTRACT FROM AUTHOR]