- Chan JCC, February 2019, Large Bayesian vector autoregressions paper no. 19/2019.
- Karagedikli O, Vahey SP, Wakerly EC, February 2019, Improved methods for combining point forecasts for an asymmetrically distributed variable paper no. 15/2019.
- Lee K, Morley J, Shields K, Tan MSL, February 2019, The Australian real-time fiscal database: A overview and an illustration of its use in analysing planned and realised fiscal policies paper no. 14/2019.
This program focuses on the role of model uncertainty in empirical macroeconomics. This literature treats the ‘true’ model as an unobservable - an admission that has implications for many areas of macroeconomic analysis and has generated two distinct research sub-programs. One represents a renewed interest in model evaluation, comparison, selection and combinations when model misspecification is explicitly recognized. A second sub-program is based on accounting for model uncertainty explicitly in constructing predictive densities for objects of economic interest, conducting statistical inference and evaluating policies.