The situation of electronic, information and communications technologies in France : current trends and future prospec

13 p.There is a widespread consensus among experts as to the crucial importance of what are known as the “new information and communications technologies” (NICTs) for economic growth and employment in a new millennium characterised by the onward march of economic globalisation. Undoubtedly, the areas of activity subsumed under the general NICT heading seem much broader than the definitions adopted for the international surveys associated with the Denki Rengo. However, there is enough overlap between the various areas for them to serve as a backdrop to this report on the French situation in these sectors. The report will deal in succession with the following points : 1. some observations on the definition of the technologies as a whole and their “comparability” across countries ; 2. the French situation in the electronics, computer and telecommunications sectors, together with future trends ; 3. the evolution of employment in the various sectors ; 4. the industrial relations situation in these sectors : recent developments and new issues ; 5. some findings from the Audit of french firms

Income Redistribution and Public Good Provision: an Experiment

We provide a new experimental investigation of the neutrality theorem of Warr (1983), who states ”when a single public good is provided at positive levels by private individuals, its provision is unaffected by a redistribution of income”. Instead of comparing different income distributions across groups as Chan et al. (1996), in our experiment the total group endowment is redistributed after a 10 rounds sequence. We compare an unequalizing redistribution (EI) and an equalizing redistribution (IE), to two benchmark treatments for which the 10 rounds sequence is repeated, either with an equal distribution (EE) or an unequal distribution (II). The constituent game has a unique interior dominant strategy equilibrium. Our data support the neutrality theorem (after controlling for the restart effect): redistribution has no effect on the total amount of public good in none of the tested treatments. However, the analysis of individual behavior shows that ”poor” subjects over-contribute with respect to their Nash-contribution, while ”rich” subjects tend to play their Nash-contribution or under-contribute slightly. Furthermore, after a redistribution, subjects react asymetrically: subjects who get poorer reduce their contribution of a larger amount than the amount of contribution added by subjects who become richer. And it is shown that the latter do not react enough to the redistribution.

"Combinatorial Bootstrap Inference IN in Prtially Identified Incomplete Structural Models"

We propose a computationally feasible inference method infinite games of complete information. Galichon and Henry (2011) and Beresteanu, Molchanov, and Molinari (2011) show that such models are equivalent to a collection of moment inequalities that increases exponentially with the number of discrete outcomes. We propose an equivalent characterization based on classical combinatorial optimization methods that alleviates this computational burden and allows the construction of confidence regions with an effcient combinatorial bootstrap procedure that runs in linear computing time. The method can also be applied to the empirical analysis of cooperative and noncooperative games, instrumental variable models of discrete choice and revealed preference analysis. We propose an application to the determinants of long term elderly care choices.

Lazy Model Expansion: Interleaving Grounding with Search

Finding satisfying assignments for the variables involved in a set of constraints can be cast as a (bounded) model generation problem: search for (bounded) models of a theory in some logic. The state-of-the-art approach for bounded model generation for rich knowledge representation languages, like ASP, FO(.) and Zinc, is ground-and-solve: reduce the theory to a ground or propositional one and apply a search algorithm to the resulting theory. An important bottleneck is the blowup of the size of the theory caused by the reduction phase. Lazily grounding the theory during search is a way to overcome this bottleneck. We present a theoretical framework and an implementation in the context of the FO(.) knowledge representation language. Instead of grounding all parts of a theory, justifications are derived for some parts of it. Given a partial assignment for the grounded part of the theory and valid justifications for the formulas of the non-grounded part, the justifications provide a recipe to construct a complete assignment that satisfies the non-grounded part. When a justification for a particular formula becomes invalid during search, a new one is derived; if that fails, the formula is split in a part to be grounded and a part that can be justified. The theoretical framework captures existing approaches for tackling the grounding bottleneck such as lazy clause generation and grounding-on-the-fly, and presents a generalization of the 2-watched literal scheme. We present an algorithm for lazy model expansion and integrate it in a model generator for FO(ID), a language extending first-order logic with inductive definitions. The algorithm is implemented as part of the state-of-the-art FO(ID) Knowledge-Base System IDP. Experimental results illustrate the power and generality of the approach