This paper looks at combining expert forecasts for the US macro data from Bloomberg. Contrary to Genre et al. (2013) (who analyzed the European case), the finding is that we can improve upon the simple benchmarks such as mean or median. To achieve this improvement one needs to identify a small...

This paper proposes the use of forecast combination to improve predictive accuracy in forecasting the U.S. business cycle index as published by the Business Cycle Dating Committee of the NBER. It focuses on one-step ahead out-of-sample monthly forecast utilising the well-established coincident...

Expert forecast combination—the aggregation of individual forecasts from multiple subject-matter experts— is a proven approach to economic forecasting. To date, research in this area has exclusively concentrated on local combination methods, which handle separate but related forecasting...

Combinations of point forecasts from expert forecasters are known to frequently outperform individual forecasts. It is also well documented that combination by simple averaging very often has performance superior to that of more sophisticated combinations. This empirical fact is referred to as...

The problem of finding appropriate weights to combine several density forecasts is an important issue that is currently being debated in the forecast combination literature. A recent paper by Hall and Mitchell (IJF, 2007) proposes to combine density forecasts with the weights obtained from...

In applied forecasting, there is a trade-o between in-sample t and out-of-sample forecast accuracy. Parsimonious model specifi cations typically outperform richer model speci fications. Consequently, there is often predictable information in forecast errors that is di cult to exploit. However,...

The Heterogeneous Autoregressive (HAR) model of Corsi (2009) has become the benchmark model for predicting realized volatility given its simplicity and consistent empirical performance. Many modifications and extensions to the original model have been proposed that often only provide incremental...

This paper provides a methodology for combining forecasts based on several discrete choice models. This is achieved primarily by combining one-step-ahead probability forecast associated with each model. The paper applies well-established scoring rules for qualitative response models in the...