Research Grant
[Cite as https://purl.org/au-research/grants/arc/DP140103220]Researchers: A/Prof George Athanasopoulos (Chief Investigator) , Anastasios Panagiotelis (Chief Investigator) , Prof Farshid Vahid (Chief Investigator) , Prof Robin Hyndman (Chief Investigator)
Brief description Macroeconomic forecasting in a 'Big Data' world. This project will develop methods for forecasting important macroeconomic variables where a large set of predictors is available. As well as raw variables and composite indices such as principal components. This project will also include various lags and nonlinear functions of potential predictors. The project will adapt Bayesian statistical methods for selecting these predictors so that they can be applied to time series data, thus developing innovative forecasting methods that can be used on a range of important problems involving 'Big Data'. The project will compare forecasts from different methods using simulated and empirical data from the US and Australia. For the latter an outcome will be an online handbook of available Australian economic data for public use.
Funding Amount $335,000
Funding Scheme Discovery Projects
- PURL : https://purl.org/au-research/grants/arc/DP140103220
- ARC : DP140103220