Bayes estimates are derived in multivariate linear models with unknown distribution. The prior distribution is defined using a Dirichlet prior for the unknown error distribution and a ormal-Wishart distribution for the parameters. The posterior distribution for the parameters is determined and...

The Normal Inverse Gaussian (NIG) distribution recently introduced by Barndorff-Nielsen (1997) is a promising alternative for modelling financial data exhibiting skewness and fat tails. In this paper we explore the Bayesian estimation of NIG-parameters by Markov Chain Monte Carlo Methods. --...

We investigate the small sample properties of two types of weak exogeneity tests in cointegrated VAR models that are frequently used in applied work. The first one is the standard Likelihood Ratio (LR) test in the Johansen framework. The second test is based on mapping the cointegrated VAR model...

In empirical applications of structural equation modeling researchers often assume that the sample under investigation is homogenous unless observed characteristics allow for a division of the sample into mutual exclusive homogenous subgroups. If such information is not available, unobserved...

Healthcare expenditure has increased substantially in all western industrialized countries in the last decades. The necessity to contain the increase in health care expenditure has motivated the Analysis of its determinants to explain differences across countries and health systems. However,...

We consider the partially linear model relating a response Y to predictors (X,T) with mean function XT ß + g (T) when the X's are measured with additive error. The semiparametric likelihood estimate of Severini and Staniswalis (1994) leads to biased estimates of both the parameter ß and the...

Likelihood ratio (LR) tests for the cointegrating rank of a vector autoregressive (VAR) process have been developed under different assumptions regarding deterministic terms. For instance, nonzero mean terms and linear trends have been accounted for in some of the tests. In this paper we provide...

Bootstrap confidence intervals for impulse responses computed from autoregressive processes are considered. A detailed analysis of the methods in current use shows that they are not very reliable in some cases. In particular, there are theoretical reasons for them to have actual coverage...