Recent work suggests VAR models of output, inflation, and interest rates may be prone to instabilities. In the face of such instabilities, a variety of estimation or forecasting methods might be used to improve the accuracy of forecasts from a VAR. The uncertainty inherent in any single representation of instability could mean that combining forecasts from a range of approaches will improve for...

We explore two popular approaches to empirical analysis of monetary policy: the New Keynesian and the identified vector autoregression approaches. Stylized models of private behavior coupled with simple rules describing policy behavior characterize New Keynesian work. Vector autoregressions consist of minimally identified dynamic descriptions of private behavior coupled with a detailed rule for...

In this paper we provide analytical, simulation, and empirical evidence on a test of equal economic value from competing predictive models of asset returns. We define economic value using the concept of a performance fee — the amount an investor would be willing to pay to have access to an alternative predictive model that is used to make investment decisions. We establish that this fee can be ...

Modeling financial volatility is an important part of empirical finance. This paper provides a literature review of the most relevant volatility models, with a particular focus on forecasting models. We firstly discuss the empirical foundations of different kinds of volatility. The paper, then, analyses the non-parametric measure of volatility, named realized variance, and its empirical applica...

Four model selection methods are applied to the problem of predicting business cycle turning points: equally-weighted forecasts, Bayesian model averaged forecasts, and two models produced by the machine learning algorithm boosting. The model selection algorithms condition on different economic indicators at different forecast horizons. Models produced by BMA and boosting outperform equally-weig...

Economic value calculations are increasingly used to compare the predictive performance of competing models of asset returns. However, they lack a rigorous way to validate their evidence. This paper proposes a new methodology to test whether utility gains accruing to investors using competing predictive models are equal to zero. Monte Carlo evidence indicates that our testing procedure, that ca...

Technical traders base their analysis on the premise that the patterns in market prices are assumed to recur in the future, and thus, these patterns can be used for predictive purposes. This paper uses the daily Dow Jones Industrial Average Index from 1897 to 1988 to examine the linear and nonlinear predictability of stock market returns with simple technical trading rules. The nonlinear specif...

Integrated assessment models of climate change typically analyze the case of a doubling of atmospheric CO2.over the pre-industrial concentration of about 270 ppm. This is a serious shortcoming since under a scenario in which all accessible fossil fuels are burned, atmospheric CO2 concentrations will more than quadruple. We introduce an analytical framework that endogenously accounts for potenti...

The general-to-specific (GETS) approach to modelling is widely employed in the modelling of economic series, but less so in financial volatility modelling due to computational complexity when many explanatory variables are involved. This study proposes a simple way of avoiding this problem and undertakes an out-of-sample forecast evaluation of the methodology applied to the modelling of weekly ...