The article distinguishes the scientist of the opinable thing, because the epistemology must explain: the nature and the path to obtain the concepts and scientific theories; the methodology with which one threads the laws and theories that give sustenance to sciences. This is the importance of...

Recent mortality trends lead to the use of projected mortality tables when pricing and reserving for life annuities (as well as for other living benefits, such as Long Term Care benefits, whole life sickness benefits, etc.). However mortality patterns continuously evolve along time, so that any...

This paper analyzes the forecasting performance of an open economy dynamic stochastic general equilibrium (DSGE) model, estimated with Bayesian methods, for the Euro area during 1994Q1-2002Q4. We compare the DSGE model and a few variants of this model to various reduced-form forecasting models...

We propose a Bayesian approach for inference in a dynamic disequilibrium model. To circumvent the difficulties raised by the Maddala and Nelson (1974) specification in the dynamic case, we analyze a dynamic extended version of the disequilibrium model of Ginsburgh et al. (1980). We develop a...

GARCH models are commonly used as latent processes in econometrics, financial economics and macroeconomics. Yet no exact likelihood analysis of these models has been provided so far. In this paper we outline the issues and suggest a Markov chain Monte Carlo algorithm which allows the calculation...

Current techniques of DNA analysis enable the scoring of hundreds of electrophoretic bands using a small amount of DNA from an individual. The sample size in pilot experiments is typically orders of magnitude smaller then the number of bands contained in a molecular profile. Nevertheless, it is...

This paper describes a GAUSS program of a Markov-chain sampling algorithm for GARCH models proposed by Nakatsuma (1998). This algorithm allows us to generate Monte Carlo samples of parameters in a GARCH model from their joint posterior distribution. The samples obtained by this algorithm are...