Regression analyses of cross-country economic growth data are complicated by two main forms of model uncertainty: the uncertainty in selecting explanatory variables and the uncertainty in specifying the functional form of the regression function. Most discussions in the literature address these...

This paper presents the R package MitISEM, which provides an automatic and flexible method to approximate a non-elliptical target density using adaptive mixtures of Student-t densities, where only a kernel of the target density is required. The approximation can be used as a candidate density in...

In this paper we test for mean reversion in the Nordic stock markets using monthly nominal data 1947-1998. By simply account for the heteroscedasticity of the data with a regime-switching model of normal distributions and taking estimation bias into account via a Bayesian approach we can find no...

This paper introduces a new non-parametric approach to integrate empirical probability functions of the real return for different investment horizons for five portfolios of Swedish stocks and bonds. In our setting the problem reduces to generating new generalizations from an empirical Markov...

Growth rate data that are collected incompletely in cross-sections is a quite frequent problem. Chow and Lin (1971) have developed a method for predicting unobserved disaggregated time series and we propose an extension of the procedure for completing cross-sectional growth rates similar to the...

This paper presents the R package MitISEM, which provides an automatic and flexible method to approximate a non-elliptical target density using adaptive mixtures of Student-t densities, where only a kernel of the target density is required. The approximation can be used as a candidate density in...

This paper presents the R package bayesGARCH which provides functions for the Bayesian estimation of the parsimonious but effective GARCH(1,1) model with Student-t innovations. The estimation procedure is fully automatic and thus avoids the time-consuming and difficult task of tuning a sampling...