Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/299032 
Year of Publication: 
2022
Citation: 
[Journal:] Journal of Central Banking Theory and Practice [ISSN:] 2336-9205 [Volume:] 11 [Issue:] 1 [Year:] 2022 [Pages:] 87-104
Publisher: 
Sciendo, Warsaw
Abstract: 
We conduct a Monte Carlo experiment using an ad-hoc New Keynesian model and a tractable agent-based model to generate artificial credit cycle episodes. We show that fluctuations in the implicit measures of the natural rate of interest obtained using a conventional trivariate Kalman filter on these artificial datasets occur in the vicinity of credit cycle peaks without any underlying changes in fundamentals (that is the agents' type or their behaviour). The empirical analysis confirms that the measures of the natural interest rate tend to increase prior to a credit cycle peak and decrease afterwards. We conclude that a decline in the estimated natural rates of interest does not necessarily indicate changes in macroeconomic fundamentals. Instead, it may simply reflect the innate properties of the measurement technique in the vicinity of credit cycle peaks.
Subjects: 
natural rate of interest
credit cycle
Kalman filter
agent-based models
JEL: 
C32
C63
E43
E44
E51
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc-nd Logo
Document Type: 
Article

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