The assumption that equity returns follow the normal distribution, most commonly made in financial economics theory and applications, is strongly rejected by empirical evidence presented in this paper. As it was found in many other studies, we confirm that stock returns follow a leptokurtic...

In this paper we have demonstrated the implications of incorrectly normalising the parameters of a reduced rank regression model to achieve global identification, and presented a method for estimating this model without using the ordering restrictions imposed in previous Bayesian and frequentist...

The standard introductory texts to mathematical statistics leave the Bayesian approach to be taught later in advanced topics courses -- giving students the impression that Bayesian statistics provide but a few techniques appropriate in only special circumstances. Nothing could be further from...

What assumptions and methods allow us to turn observations into causal knowledge, and how can even incomplete causal knowledge be used in planning and prediction to influence and control our environment? In this book Peter Spirtes, Clark Glymour, and Richard Scheines address these questions...

Several central banks have adopted inflation targets. The implementation of these targets is flexible; the central banks aim to meet the target over the long term but allow inflation to deviate from the target in the short-term in order to avoid unnecessary volatility in the real economy. In this...

This book presents the theory of probability and mathematical statistics at a level suitable for researchers at the frontiers of applied disciplines. Examples and exercises make essential concepts in measure theory and analysis accessible to those with preparation limited to vector calculus....

This is a theoretic and econometric assessment of Peter Ferderer’s seminal paper published in the Journal of Post Keynesian Economics with the same title in 1993. New data shows that high forecaster discords coincide with a decrease in Investment expenditure. Specifically, the forecaster...

I describe algorithms for drawing from distributions using adaptive Markov chain Monte Carlo (MCMC) methods, introduce a Mata function for performing adaptive MCMC, amcmc(), and a suite of functions amcmc *() allowing an alternative implementation of adaptive MCMC. amcmc() and amcmc *() may be...

We propose the unified approach to construct the non–informative prior for time–series econometric models that are invariant under some group of transformations. We show that this invariance property characterizes some of the most popular models hence the applicability of the proposed...