Global and local components of output gaps - Florian Eckert; Nina Mühlebach (ETH Zurich, KOF Swiss Economic Institute, 2021)
This paper proposes a multi-level dynamic factor model to identify common components in output gap estimates. We pool multiple output gap estimates for 157 countries and decompose them into one global, eight regional, and 157 country-specific cycles. Our approach easily deals with mixed frequencies, ragged edges, and discontinuities in the underlying output gap estimates. To restrict the parameter space in the Bayesian state space model, we apply a stochastic search variable selection approach and base the prior inclusion probabilities on spatial information. Our results suggest that the global and the regional cycles explain a substantial proportion of the output gaps. On average, 18% of a country's output gap is attributable to the global cycle, 24% to the regional cycle, and 58% to the local cycle.
hdl:20.500.11850/514977
Keywords: C11; C32; C52; F44; R11; 330; Multi-Level DFM; Bayesian State Space Model; Output Gap Decomposition; Model Combination; Business Cycles; Variable Selection; Spatial Prior