The Credit Cycle and Measurement of the Natural Rate of Interest

Elena Deryugina, Maria Guseva () and Alexey Ponomarenko
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Maria Guseva: Bank of Russia, Moscow, Russian Federation

Journal of Central Banking Theory and Practice, 2022, vol. 11, issue 1, 87-104

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.

Keywords: natural rate of interest; credit cycle; Kalman filter; agent-based models. (search for similar items in EconPapers)
JEL-codes: C32 C63 E43 E44 E51 (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:cbk:journl:v:11:y:2022:i:1:p:87-104

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