Local strong D-Monotonicity of the Kalai-Smorodinsky and Nash bargaining solution

bargaining

On the Sensitivity Matrix of the Nash Bargaining Solution

In this note we derive the sensitivity matrix of the Nash bargaining solution w.r.t. the disagreement point d.This first order derivative is completely specified in terms of the Pareto frontier function.We show that whenever one player increases his threatpoint always at least one player will loose utility: i.e. the dual result of Pareto optimality.Furthermore,the dmonotonicity property is easily re-established from this matrix.This matrix also enables us to consider the concept of local strong d-monotonicity.That is,under which conditions on the Pareto frontier function . an infinitesimal increase of di,while for each j = i, dj remains constant,it happens that agent i is the only one who s payoff increases.We show that for the Nash bargaining solution this question is closely related to non-negativity of the Hamiltonian matrix of . at the solution.Nash bargaining solution;d-monotonicity;diagonally dominant Stieltjes matrix

Convergence and international policy coordination in the EU: A dynamic games approach

Maastricht Treaty;Dynamic Games;EU;Game Theory;International Policy

Is there room for convergence in the E.C.?

EEC

S.L.I.M., a small linear interdependent model of eight EU-member states, the USA and Japan

International Economics;EU

Provider Competition and Over-Utilization in Health Care

This paper compares the welfare effects of three ways in which health care can be organized: no competition (NC), competition for the market (CfM) and competition on the market (CoM) where the payer offers the optimal contract to providers in each case. We argue that each of these can be optimal depending on the contracting environment of a speciality. In particular, CfM is optimal in a clinical situation where the payer either has contractible information on provider quality or can enforce cost efficient protocols. If such contractible information is not available NC or CoM can be optimal depending on whether patients react to decentralized information on quality differences between providers and whether payer’s and patients’ preferences are aligned