- Wong B, October 2017, Historical decompositions for nonlinear vector autoregression models paper no. 62/2017.
- Chan JCC, Song Y, October 2017, Measuring inflation expectations uncertainty using high-frequency data paper no. 61/2017.
- Mertens E, Nason JM, September 2017, Inflation and professional forecast dynamics: An evaluation of stickiness, persistence, and volatility paper no. 60/2017.
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.