Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/301977 
Authors: 
Year of Publication: 
2024
Series/Report no.: 
CBM Working Papers No. WP/04/2024
Publisher: 
Central Bank of Malta, Valletta
Abstract: 
This paper presents a credit gap for Malta derived from a semi-structural multivariate filter. This modelling approach has several advantages over univariate approaches typically used, for example to construct the Basel gap. The multivariate filtering of observed data into trends and cycles is informed by economic relationships, making estimates of gaps more sensible and robust, and the framework is flexible, allowing for further model development with relative ease. The estimated credit gap is cyclical with an average duration of 13 years, it was positive between the years 2006-2013, and has turned positive again since 2019. The model also provides estimates of other economic concepts like potential output, trend inflation and the house price gap. The semi-structural credit gap estimated in this paper correlates with other existing measures of cyclical risks and is shown to have early warning properties. Moreover, the gap can be decomposed into contributions from the household and firm sectors, yielding a better picture of the drivers of the financial cycle, thereby guiding policy on the appropriate macroprudential policy tool to deploy.
Subjects: 
Credit gap
semi-structural model
multivariate filter
Bayesian estimation
Basel gap
house prices
JEL: 
C11
C32
C51
E32
E44
E58
G51
Document Type: 
Working Paper

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.