The purpose of this paper is to define the concept of expected minimum cost function and to present the methodology for a non parametric estimation of it. Generally, in cost enonometric analysis, inference is made on the cost function, namely the conditional expectation of cost given some level...

The focus of the paper is the nonparametric estimation of an instrumental regression function * defined by conditional moment restrictions stemming from a structural econometric model: E[Y- *(Z) | W]=0, and involving endogeneous variables Y and Z and instruments W.

We propose an operational concept of Constrained Strategic Equilibrium (CSE) applicable to a broad class of empirical game theoreticmodels with incomplete information. By restricting the players' strategic sets, we can compute solutions from a strategic form of analyis based upon auxiliary Monte...

This paper synthesize different econometric models of the postal delivery, estimated using a french data set. These models explain the demand of labor (representing the essential part of the cost) by a vector of outputs (different types of delivered objects) and by geographical characteristics...

We consider a kernel based approach to nonlinear canonical correlation analysis and its implementation for time series. We deduce various diagnostics for reversible processes and gaussian processes. The method is first applied to a stimulated series satisfying a diffusion equation allowing us to...

We consider a kernel based approach to nonlinear canonical correlation analysis and its implementation for time series. We deduce a test procedure of the reversibility hypothesis. The method is applied to the analysis of stochastic differential equation from high frequency data on stock returns.

We decompose a stationary Markov process (X^t) as: X^t = a^o + [Sommation from j=1 to infinity) a^j Z^(j,t), where the Z^j 's processes admit ARMA specifications. These decompositions are deduced from a nonlinear canonical decomposition of the joint distribution of (X^t, X^(t-1)).