Density forecast combinations are becoming increasingly popular as a means of improving forecast `accuracy’, as measured by a scoring rule. In this paper we generalise this literature by letting the combination weights follow more general schemes. Sieve estimation is used to optimise the score...

Recent literature has focuses on realized volatility models to predict financial risk. This paper studies the benefit of explicitly modeling jumps in this class of models for value at risk (VaR) prediction. Several popular realized volatility models are compared in terms of their VaR forecasting...

We propose a methodology for producing forecast densities for economic aggregates based on disaggregate evidence. Our ensemble predictive methodology utilizes a linear mixture of experts framework to combine the forecast densities from potentially many component models. Each component represents...

The deviance information criterion (DIC) has been widely used for Bayesian model comparison. However, recent studies have cautioned against the use of the DIC for comparing latent variable models. In particular, the DIC calculated using the conditional likelihood (obtained by conditioning on the...

Cointegration ideas as introduced by Granger (1981) are commonly embodied in empirical macroeconomic modelling through the vector error correction model (VECM). It has also become common practice in these models to treat some variables as weakly exogenous, resulting in conditional VECMs. This...

Cointegration ideas as introduced by Granger in 1981 are commonly embodied in empirical macroeco- nomic modelling through the vector error correction model (VECM). It has become common practice in these models to treat some variables as weakly exogenous, resulting in conditional VECMs. This...

We carry out a meta-analysis of the very large literature on Granger causality tests between energy use and economic output to determine if there is a genuine effect in this literature or whether the large number of apparently significant results is due to publication and misspecification bias....

This paper employs concepts from information theory to choosing the dimension of a data set. We propose a relative information measure connected to Kullback-Leibler numbers. By ordering the series of the data set according to the measure, we are able to obtain a subset of a data set that is most...

Though there is a very large literature examining whether energy use Granger causes economic output or vice versa this literature is fairly inconclusive. Almost all existing studies use relatively short time series or panels with a relatively small time dimension. Additionally, many recent...

We consider an adaptive importance sampling approach to estimating the marginal likelihood, a quantity that is fundamental in Bayesian model comparison and Bayesian model averaging. This approach is motivated by the difficulty of obtaining an accurate estimate through existing algorithms that...