Robust Estimation of Credit Shocks in Peru during the COVID-19 Crisis

Abstract The Covid-19 pandemic introduced an unprecedented disruption in macroeconomic activity while credit continued to expand in several economies due to large policy interventions aimed at preserving financial intermediation. In Peru, this episode represented a clear deviation from the historical relationship between credit growth and economic activity. This paper studies the transmission of credit supply and credit demand shocks using a Bayesian structural VAR estimated with monthly macro-financial data from 2010 to 2024. To account for the extreme volatility observed during the pandemic, the identification combines sign and zero restrictions with information from higher-order moments and heteroskedasticity. The results indicate that, conditional on the maintained identifying assumptions, credit supply shocks are associated with stronger responses of economic activity during and after the pandemic than in the pre-pandemic period, while credit demand shocks display weaker and less persistent responses. These findings suggest that credit conditions became a more important driver of macroeconomic fluctuations during episodes of heightened uncertainty, although the framework does not separately identify policy-induced credit shocks.

Authors

Institutions

Publication Details

Journal
Journal of Central Banking Theory and Practice
Published
2026-08-27
DOI
https://doi.org/10.2478/jcbtp-2026-0022
Primary Topic
COVID-19 Pandemic Impacts
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Robust Estimation of Credit Shocks in Peru during the COVID-19 Crisis

Renzo Pardo, Pilar Soriano, David Cortés
Journal of Central Banking Theory and Practice
COVID-19 Pandemic Impacts
article

Robust Estimation of Credit Shocks in Peru during the COVID-19 Crisis

Renzo Pardo, Pilar Soriano, David Cortés
article en

Abstract

Abstract The Covid-19 pandemic introduced an unprecedented disruption in macroeconomic activity while credit continued to expand in several economies due to large policy interventions aimed at preserving financial intermediation. In Peru, this episode represented a clear deviation from the historical relationship between credit growth and economic activity. This paper studies the transmission of credit supply and credit demand shocks using a Bayesian structural VAR estimated with monthly macro-financial data from 2010 to 2024. To account for the extreme volatility observed during the pandemic, the identification combines sign and zero restrictions with information from higher-order moments and heteroskedasticity. The results indicate that, conditional on the maintained identifying assumptions, credit supply shocks are associated with stronger responses of economic activity during and after the pandemic than in the pre-pandemic period, while credit demand shocks display weaker and less persistent responses. These findings suggest that credit conditions became a more important driver of macroeconomic fluctuations during episodes of heightened uncertainty, although the framework does not separately identify policy-induced credit shocks.

Journal of Central Banking Theory and PracticeVol. 15(3)
Universitat de València (ES), Instituto Geofísico del Perú (PE), Universidad Carlos III de Madrid (ES)
Openalex Percentile: Top 5%
COVID-19 Pandemic Impacts
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Robust Estimation of Credit Shocks in Peru during the COVID-19 Crisis — Renzo Pardo, Pilar Soriano, et al. · Journal of Central Banking Theory and Practice (2026) | TGRS Research Map | TGRS