Suchergebnisse

We model the choice of transportation mode in a simplified Hotelling-like city, with a fixed number of total travellers, fixed road capacity and with no trade-off between when to travel and the time spent in a queue. A person that chooses to take her own car will inflict a congestion cost on all travellers. To get the travellers to internalise these external costs, a congestion charge has to be imposed. We derive an optimal congestion charge within in a discrete-choice framework, with a benevolent government maximising expected tax-adjusted social surplus. The congestion charge to be imposed on private driving, beyond the opportunity cost - equal to the fare on public transportation - is shown to be a weighted average of a Ramsey-like term (capturing the goal to raise public revenue) and a Pigou-term capturing the environmental cost of a person's private driving. This property is similar to the optimal environmental tax derived by Sandmo (1975). However, the behavioural assumption underlying the present framework is quite different from the standard theory of consumer choice adopted by Sandmo.

We compare two options of integrating discrete working time choice of heterogenous households into a general equilibrium model. The first, known from the literature, produces household heterogeneity through a working time preference parameter. We contrast this with a model that directly incorporates a logit discrete-choice approach into a AGE framework. On the grounds of both calibration consistency and adequate accomodation of within-household interaction, we argue that the logit approach is preferable.

Nonlogit maximum‐likelihood estimators are inconsistent when using data on a subset of the choices available to agents. I show that the semiparametric, multinomial maximum‐score estimator is consistent when using data on a subset of choices. No information is required for choices outside of the subset. The required conditions about the error terms are the same conditions as for using all the choices. Estimation can proceed under additional restrictions if agents have unobserved, random consideration sets. A solution exists for instrumenting endogenous continuous variables. Monte Carlo experiments show the estimator performs well using small subsets of choices.

Combinatorial Materials Science describes new developments and research results in catalysts, biomaterials, and nanomaterials, together with informatics approaches to the analysis of Combinatorial Science (CombiSci) data. CombiSci has been used extensively in the pharmaceutical industry, but there is enormous potential in its application to materials design and characterization. Addressing advances and applications in both fields, Combinatorial Materials Science :.:.; Integrates the scientific fundamentals and interdisciplinary underpinnings required to develop and apply CombiSci concepts.; Di.