Global and local components of output gaps

Area of Science:

• Economics
• Econometrics
• International Finance

Background:

• Output gap estimates are crucial for macroeconomic analysis but often exhibit inconsistencies.
• Existing models struggle with mixed frequencies, discontinuities, and missing data in output gap series.

Purpose of the Study:

• To develop a robust multi-level dynamic factor model for identifying commonalities in international output gap estimates.
• To decompose output gaps into global, regional, and country-specific components.

Main Methods:

• A multi-level dynamic factor model was applied to pooled output gap estimates from 157 countries.
• Bayesian state space models with stochastic search variable selection were used to manage parameter space.
• Spatial information informed prior inclusion probabilities for model parsimony.

Main Results:

• The model successfully handles mixed frequencies, ragged edges, and discontinuities in data.
• Global cycles account for 18% of a country's output gap on average.
• Regional cycles contribute 24%, and country-specific cycles explain the remaining 58%.

Conclusions:

• A significant portion of national output gaps can be explained by global and regional economic cycles.
• The proposed model offers a flexible framework for analyzing international business cycle synchronization.
• Understanding these multi-level cycles is vital for effective monetary and fiscal policy coordination.