Characteristics of good and competitive equilibrium

We analyse the consequences of a change of the characteristics of goods due to new information on the equilibrium of a pure exchange economy with n goods and m agents. Some changes of the characteristics of goods à la Lancaster have a positive effect on utility. In the general competitive equilibrium, some agents gain but others may lose. Nevertheless there is an increase of a linear combination of the utilities of the agents. The different possibilities of gains and losses are explicitly analysed in an example with two goods and two agents.Pure exchange economy, Characteristic of goods, Price determination, Pareto efficiency

Hochschild cohomology and Atiyah classes

In this paper we prove that on a smooth algebraic variety the HKR-morphism twisted by the square root of the Todd genus gives an isomorphism between the sheaf of poly-vector fields and the sheaf of poly-differential operators, both considered as derived Gerstenhaber algebras. In particular we obtain an isomorphism between Hochschild cohomology and the cohomology of poly-vector fields which is compatible with the Lie bracket and the cupproduct. The latter compatibility is an unpublished result by Kontsevich. Our proof is set in the framework of Lie algebroids and so applies without modification in much more general settings as well.Comment: Reference to work of Cattaneo, Felder and Willwacher adde

Hochschild cohomology for Lie algebroids

We define the Hochschild (co)homology of a ringed space relative to a locally free Lie algebroid. Our definitions mimic those of Swan and Caldararu for an algebraic variety. We show that our (co)homology groups can be computed using suitable standard complexes. Our formulae depend on certain natural structures on jetbundles over Lie algebroids. In an appendix we explain this by showing that such jetbundles are formal groupoids which serve as the formal exponentiation of the Lie algebroid.Comment: The authors were informed that the fact that jetbundles are formal groupoids is already contained in arXiv:0904.4736 (with a somewhat different proof

Piecework versus merit pay: a Mean Fi eld Game approach to academic behavior

This paper applies the Mean Fi eld Game approach pioneered by Lasry and Lions (2007) to the analysis of the researchers' academic productivity. It provides a theoretical motivation for the stability of the universaly observed Lotka's law. It shows that a remuneration scheme taking into account the researchers rank with respect to the academic resume can induce a larger number of researchers to overtake a minimal production standard. It thus appears as superior to piecework remuneration.Mean Field Game, Academic production, incentives, Lotka's law.

Fast Selection of Spectral Variables with B-Spline Compression

The large number of spectral variables in most data sets encountered in spectral chemometrics often renders the prediction of a dependent variable uneasy. The number of variables hopefully can be reduced, by using either projection techniques or selection methods; the latter allow for the interpretation of the selected variables. Since the optimal approach of testing all possible subsets of variables with the prediction model is intractable, an incremental selection approach using a nonparametric statistics is a good option, as it avoids the computationally intensive use of the model itself. It has two drawbacks however: the number of groups of variables to test is still huge, and colinearities can make the results unstable. To overcome these limitations, this paper presents a method to select groups of spectral variables. It consists in a forward-backward procedure applied to the coefficients of a B-Spline representation of the spectra. The criterion used in the forward-backward procedure is the mutual information, allowing to find nonlinear dependencies between variables, on the contrary of the generally used correlation. The spline representation is used to get interpretability of the results, as groups of consecutive spectral variables will be selected. The experiments conducted on NIR spectra from fescue grass and diesel fuels show that the method provides clearly identified groups of selected variables, making interpretation easy, while keeping a low computational load. The prediction performances obtained using the selected coefficients are higher than those obtained by the same method applied directly to the original variables and similar to those obtained using traditional models, although using significantly less spectral variables