Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/195276
Authors: 
Cuerpo, Carlos
Cuevas, Ángel
Quilis, Enrique M.
Year of Publication: 
2018
Citation: 
[Journal:] SERIEs - Journal of the Spanish Economic Association [ISSN:] 1869-4195 [Volume:] 9 [Year:] 2018 [Issue:] 3 [Pages:] 275-304
Abstract: 
Over the last decades, the estimation of the slack in the economy has become an essential piece of analysis for policymakers, both on the monetary policy and the fiscal policy front. Output gap estimation techniques have flourished accordingly, although there is no consensus on a best-performing methodology, as the selection criteria often imply important trade-offs. This paper presents a novel approach putting the focus on the specification of the model rather than on a prior selection of the methodology itself. Ideally, an agreeable method should achieve three necessary conditions: economic soundness, statistical goodness and transparency. On top of this, consistency with the business cycle narrative, as often implemented by policymakers, is also a critical condition. In practice, fulfilling these conditions can prove to be challenging. The main issues in practice are related to the specification of the model, the selection of the relevant variables, the stability and uncertainty of the estimates and its use on a real-time basis. This paper presents a methodological approach based on a structural multivariate time series model and Kalman filtering. The method fulfils the necessary criteria and allows for enough flexibility in order to get a country-specific approximation to the sufficient criterion as it could accommodate specific cycles (financial, external, investment, fiscal, etc.). The method is put to the test with an illustration for the Spanish economy, assessing its merits as well as its limitations.
Subjects: 
Spanish economy
Output gap
Kalman filter
Business cycle
JEL: 
C11
C32
C51
C53
C61
Persistent Identifier of the first edition: 
Creative Commons License: 
https://creativecommons.org/licenses/by/4.0/
Document Type: 
Article

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