An additional explanation is provided for the decline in output variability that began in the mid-1980s. Using state, regional and aggregate data for the US, we examine the shifting influence from manufacturing to services on this variability. At all levels, we find support for this output...

Employing US state data, a positive correlation is found between inflation and growth during the 1980s, accompanied by a downward trend in inflation. During the 1960s and 1970s, a negative correlation was accompanied by an upward trend in inflation.

We incorporate risk aversion into the technology component of the production function. In a traditional theoretic framework, we show that an increase in risk aversion increases unemployment and reduces potential output. Our out-of-sample forecasting experiments suggest that while interest rates...

This paper proposes finite mixtures of different Archimedean copula families as a flexible tool for modelling the dependence structure in multivariate data. A novel approach to estimating the parameters in this mixture model is presented by maximizing the penalized marginal likelihood via...

In this paper we show that fully likelihood-based estimation and comparison of multivariate stochastic volatility (SV) models can be easily performed via a freely available Bayesian software called WinBUGS. Moreover, we introduce to the literature several new specifications which are natural...

This paper reviews the general Bayesian approach to parameter estimation in stochastic volatility models with posterior computations performed by Gibbs sampling. The main purpose is to illustrate the ease with which the Bayesian stochastic volatility model can now be studied routinely via BUGS...

Stochastic volatility (SV) models provide more realistic and flexible alternatives to ARCH-type models for describing time-varying volatility exhibited in many financial time series. They belong to the wide class of nonlinear state-space models. As classical parameter estimation for SV models is...

The paper presents a hierarchical discrete time survival model for the analysis of the 2000 Malawi Demographic and Health Survey data to assess the determinants of transition to marriage among women in Malawi. The model explicitly accounts for the unobserved heterogeneity by using family and...

A crucial problem in Bayesian posterior computation is efficient sampling from a univariate distribution, e.g. a full conditional distribution in applications of the Gibbs sampler. This full conditional distribution is usually non-conjugate, algebraically complex and computationally expensive...