Adaptive Polar Sampling is proposed as an algorithm where random drawings are directly generated from the target function (posterior) in all-but-one directions of the parameter space. The method is based on the mixed integration technique of Van Dijk, Kloek & Boender (1985) but extends this one...

This paper is concerned with the Bayesian estimation of non-linear stochastic differential equations when only discrete observations are available. The estimation is carried out using a tuned MCMC method, in particular a blocked Metropolis-Hastings algorithm, by introducing auxiliary points and...

This paper is concerned with the estimation of stochastic differential equations when only discrete observations are available. It primarily focuses on deriving a closed form solution for the one-step ahead conditional transition density using the Milstein scheme. This higher order Taylor...

Two-stage game models of information acquisition in stochastic oligopolies require the unrealistic assumption that firms observe the precision of information chosen by their competitors before determining quantities. This paper analyzes secret information acquisition as a one-stage game....

We consider a Bayesian analysis of the stochastic frontier model with composed error. Under a commonly used class of (partly) noninformative prior distributions, the existence of the posterior distribution and of posterior moments is examined. Viewing this model as a Normal linear regression...