Adaptive Polar Sampling (APS) is proposed as a Markov chain Monte Carlo method for Bayesian analysis of models with ill-behaved posterior distributions. In order to sample efficiency from such a distribution, location-scale transformation and a transformation to polar coordinates are used.

Recent developments in the econometric estimation of multi-output, multi-inp ut distance functions have provided a promising new solution to the single-output restriction implicit in the standard production function. However, a suspicion that regressor endogeneity may introduce possible sim...

This paper develops a posterior simulation method for a dynamic tobit model. The major obstacle rooted in such a problem lies in high dimensional integrals, induced by dependance among censored observations, in the likelihood function.