Model Uncertainty and Macro-Econometrics
- Kamber G, Morley J, Wong B, March 2024, Trend-Cycle Decomposition After COVID paper no. 24/2024.
- Di Guilmi C, Rylah GK, March 2024, Behind the Curve: Econometric Estimation and Sectoral Decomposition of the Japanese Beveridge Curve’s Evolution Around the COVID-19 Pandemic paper no. 20/2024.
- Chang Y, Durlauf SN, Hu B, Park JY, February 2024, Accounting for Individual-Specific Heterogeneity in Intergenerational Income Mobility paper no. 18/2024.
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.
Updated: 28 April 2024/Responsible Officer: Crawford Engagement/Page Contact: CAMA admin