We study a model of a financial market in which two risky assets are paying dividends with rates changing their initial values to other constant ones when certain events occur. Such events are associated with the first times at which the value processes of issuing firms, modeled by geometric...

Bayesian model selection with posterior probabilities and no subjective prior information is generally not possible due to the Bayes factors being ill-defined. Using careful consideration of the parameter of interest in cointegration analysis and a respecifcation of the triangular model of...

Economic policy decisions are often informed by empirical analysis based on accurate econometric modeling. However, a decision-maker is usually only interested in good estimates of outcomes, while an analyst must also be interested in estimating the model. Accurate inference on structural...

Economic policy decisions are often informed by empirical economic analysis. While the decision-maker is usually only interested in good estimates of outcomes, the analyst is interested in estimating the model. Accurate inference on the structural features of a model, such as cointegration, can...

The empirical support for a real business cycle model with two technology shocks is evaluated using a Bayesian model averaging procedure. This procedure makes use of a finite mixture of many models within the class of

Capability indices that qualify process potential and process performance are practical tools for successful quality improvement activities and quality program implementation. Most existing methods to assess process capability were derived on the basis of the traditional frequentist point of...

Bayesian hierarchical models that characterize the distributions of (transformed) gene profiles have been proven very useful and flexible in selecting differentially expressed genes across different types of tissue samples (e.g. Lo and Gottardo, 2007). However, the marginal mean and variance of...