This paper contributes to the productivity literature by using results from firm-level productivity studies to improve forecasts of macro-level productivity growth. The paper employs current research methods on estimating firm-level productivity to build times-series components that capture the...

This paper contributes to the productivity literature by using results from firm-level productivity studies to improve forecasts of macro-level productivity growth. The paper employs current research methods on estimating firm-level productivity to build times-series components that capture the...

Several lessons learned from a Bayesian analysis of basic economic time series models by means of the Gibbs sampling algorithm are presented. Models include the Cochrane-Orcutt model for serial correlation, the Koyck distributed lag model, the Unit Root model, the Instrumental Variables model...

Several lessons learned from a Bayesian analysis of basic economic time series models by means of the Gibbs sampling algorithm are presented. Models include the Cochrane-Orcutt model for serial correlation, the Koyck distributed lag model, the Unit Root model, the Instrumental Variables model...

A foundation is provided for a correct and accurate analysis of the relationship between monetary values and physical dimensions in economic production. A distinction is proposed between direct and indirect substitution. Linked to this, a classification is offered of various types of...

A foundation is provided for a correct and accurate analysis of the relationship between monetary values and physical dimensions in economic production. A distinction is proposed between direct and indirect substitution. Linked to this, a classification is offered of various types of...

Nancy Cartwright views models as blueprints for nomological machines - machines which, if properly shielded, generate lawlike behaviour or regularities. Marcel Boumans has argued that we can look for devices inside models which enable us to measure aspects of these regularities. So, if models do...

Nancy Cartwright views models as blueprints for nomological machines - machines which, if properly shielded, generate lawlike behaviour or regularities. Marcel Boumans has argued that we can look for devices inside models which enable us to measure aspects of these regularities. So, if models do...

We forecast the term structure of U.S. Treasury zero-coupon bond yields by analyzing a range of models that have been used in the literature. We assess the relevance of parameter uncertainty by examining the added value of using Bayesian inference compared to frequentist estimation techniques,...

Highly non-elliptical posterior distributions may occur in several econometric models, in particular, when the likelihood information is allowed to dominate and data information is weak. We explain the issue of highly non-elliptical posteriors in a model for the effect of education on income...