We first analyse the general problem of admissible conditioning and next consider the evaluation of the loss of information when a non-admissible conditioning is used as an approximation of the exact posterior distribution. Considering the case of Fisher test, we evaluate from a Bayesian point...

In this paper, we develop a Bayesian analysis of semi-parametric binary choice model. The prior specification of the functional parameter, namely the distribution function of a latent variable, is of the Dirichlet process type and the prior specification of the Euclidean parameter, namely the...

The economic literature proposes several nonparametric frontier estimators based on the idea of enveloping the data (FDH and DEA-type estimators). Many have claimed that FDH and DEA techniques are non-statistical, as opposed to econometric approaches where particular parametric expressions are...

This paper proposes a general methodology for bootstrapping in frontier models, extending the more restrictive method proposed in Simar and Wilson (1998a) by allowing for heterogeneity in the structure of efficiency. A numerical illustration with real data is provided to illstrate the methodology.

This paper further examines the bootstrap method proposed by Simar and Wilson (1998) for DEA efficiency estimators. Some simplifications are provided, and we provide Monte Carlo evidence on the coverage probabilities of confidence intervals estimated by the method.

This paper further examines the bootstrap method proposed by Simar and Wilson (1998) for DEA efficiency estimators. Some simplifications are provided, and we provide Monte Carlo evidence on the coverage probabilities of confidence intervals estimated by the method.