Global and local components of output gaps
Bibliographic Data
| ID | 21541872 |
|---|---|
| Authors | Florian Eckert (0000-0001-6191-0161, ETH Zurich), Nina Mühlebach (0000-0001-7995-8948, ETH Zurich, corresponding author) |
| Year | 2023 |
| Volume | 65 |
| Issue | 5 |
| Pages | 2301-2331 |
| Publication date | 2023-11-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Empirical Economics (JOURNAL) |
| Journal identifiers | ISSN: 0377-7332 • E-ISSN: 1435-8921 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1007/s00181-023-02419-5 |
| PMID | 37361951 |
| OpenAlex | W4365458590 |
| Language | EN |
| References cited | 45 |
This paper proposes a multi-level dynamic factor model to identify common components in output gap estimates. We pool multiple 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
Algorithm · Bayesian probability · Classification of discontinuities · Econometrics · Economics · Macroeconomics · Output gap · State space · State-space representation · Statistics · Computer Science · Economic Growth and Productivity · Economic Policies and Impacts · Mathematics · Monetary Policy and Economic Impact
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| Highly cited | No |
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