likelihood. It considers specifically the estimation of stochastic frontier models but the same issue arises in many other models …. The model can be estimated for any single value of the time-index t by maximizing a likelihood that depends on the …, and except in the normal case none is "obviously" correct. The paper observes the well-known fact that maximizing a quasi-likelihood …

we use the Bayesian penalized approach to stochastic frontiers developed in Hajargasht et al. (2003). Finally we …

A general Bayesian Markov Chain Monte Carlo methodology is utilized for conducting an analysis of the intensity process … of stock market data. The sampling scheme employed is a hybrid of the Gibbs and Metropolis Hastings algorithms. Both …

Under a Bayesian framework of model uncertainty, closed economy models of monetary policy typically suggest that policy …, qualitatively the models recommend standard results: policy attenuation if the policymaker maintains a Bayesian view of uncertainty …