Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/259459 
Year of Publication: 
2021
Citation: 
[Journal:] Latin American Economic Review [ISSN:] 2196-436X [Volume:] 30 [Issue:] 1 [Article No.:] 5 [Publisher:] Centro de Investigación y Docencia Económica (CIDE) [Place:] Ciudad de México [Year:] 2021 [Pages:] 1-24
Publisher: 
Centro de Investigación y Docencia Económica (CIDE), Ciudad de México
Abstract: 
This paper quantifies and assesses the impact of an adverse loan supply (LS) shock on Peru's main macroeconomic aggregates using a Bayesian vector autoregressive (BVAR) model in combination with an identification scheme with sign restrictions. The main results indicate that an adverse LS shock: (i) reduces credit and real GDP growth by 372 and 75 basis points in the impact period, respectively; (ii) explains 11.2% of real GDP growth variability on average over the following 20 quarters; and (iii) explained a 180-basis point fall in real GDP growth on average during 2009Q1-2010Q1 in the wake of the Global Financial Crisis (GFC). Additionally,the sensitivity analysis shows that the results are robust to alternative identification schemes with sign restrictions; and that an adverse LS shock has a greater impact on non-primary real GDP growth.
Subjects: 
Banking System
Loan Supply Shock
Bayes-ian Autoregressive Vector Model
Sign Restrictions
Peruvian Economy
JEL: 
C11
E32
E51
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc-nd Logo
Document Type: 
Article

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