This article is an attempt to shed light on the specification and identification of inefficiency in stochastic frontiers. We consider the case of a regulated firm or industry. Applying a simple principal-agent framework that accounts for informational asymmetries to this context, we derive the...

Cet article analyse la renégociation des contrats de gestion déléguée dans le secteur du transport en France. Nous décrivons tout d'abord brièvement le secteur, puis nous présentons dans ses grandes lignes un modèle théorique de renégociation des contrats expliquant les évolutions...

Les économètres ont estimé des frontières de coût et de production afin d'évaluer l'inefficacité des entreprises. En parallèle, les économistes ont considéré des problèmes d'information asymétrique dans les relations contractuelles entre des principaux et des agents. Cet article...

This paper is aimed at assessing the empirical relevance of the new theory of regulation. It relies on a principal-agent framework for studying the regulatory schemes used in the French urban transport industry. Taking the current regulatory schemes as given, the model of supply and demand...

The opportunity to watch TV on a mobile phone is taking more and more importance as mobile operators are investing in new technologies allowing a better quality of the broadcasting. According to US consultants of Visiongain, 270 Millions of new subscribers, which represents 10% of the mobile...

This article is aimed at deepening our understanding of the functioning of competition in the local bus transportation industry and to evaluate its effectiveness. It provides an overview of the competitive constraints that are at work in the industry as discussed in the economic literature, and...

Economic theory claims that contracts renegotiation prevents from reaching the informationally constrained efficient solution that could have been obtained under full commitment. Assessing the cost of renegotiation compared to the full commitment scenario still remains an open issue from an...