Economic policy responses to the COVID‐19 pandemic and growth of nonperforming loans

• Published date: 01 September 2022
• Author: Hassan F. Gholipour,Amir Arjomandi
• Date: 01 September 2022
• DOI: http://doi.org/10.1111/irfi.12362

SHORT REPORT

Economic policy responses to the COVID-19

pandemic and growth of nonperforming loans

Hassan F. Gholipour

1

| Amir Arjomandi

2

1

School of Business, Western Sydney

University, Sydney, Australia

2

School of Business, Faculty of Business and

Law, University of Wollongong, Wollongong,

New South Wales, Australia

Correspondence

Amir Arjomandi, School of Business, Faculty

of Business and Law, University of

Wollongong, Wollongong, NSW 2522,

Australia.

Email: amira@uow.edu.au

Abstract

In this paper, we investigate the relationship between vari-

ous economic policy responses to the COVID-19 pandemic

(liquidity support, prudential policies, borrower support,

asset purchase, and policy rate decisions) and the growth of

nonperforming loans (NPLs) in 2020 across 47 economies.

Controlling for other relevant determinants of NPLs,

our regression analyses show that economies in which

policymakers have used prudential and borrower support

measures reported significantly slower growth of aggregate

NPLs. The prudential measures also confirmed a more

robust relationship with NPL reductions compared with

borrower support measures. Added to this, non-mortgage

consumer loans are found to be more sensitive than

mortgage loans to economic policy responses.

KEYWORDS

COVID-19 pandemic, default, economic policy, nonperforming

loans

INTRODUCTION

The outbreak of the COVID-19 pandemic in late 2019 came as shock for most of the world's nations with unprece-

dented uncertainty about their economic growth and recovery. In response, governments and central banks through-

out the world have implemented several economic policies to limit the human and economic damage caused by the

COVID-19 pandemic (IMF, 2020). These policies range from economic support payments to millions of individuals to

new monetary policies such as interest rates cuts implemented by the US Federal Reserve and the Reserve Bank of

Australia, while quantitative easing was used by the European Central Bank to assist distressed sectors accessing

more bank loans. Demirgüç-Kunt et al. (2020) classify these economic responses to COVID-19 into four main

Received: 27 January 2021 Revised: 7 July 2021 Accepted: 24 July 2021

DOI: 10.1111/irfi.12362

© 2021 International Review of Finance Ltd.

International Review of Finance. 2022;22:551–566. wileyonlinelibrary.com/journal/irfi 551

categories: (1) liquidity support taking the form of measures employed by monetary authorities to expand banks'

short-term funding in domestic and foreign currency; (2) prudential measures which deal with the temporary easing

of regulatory and monitoring requirements, including capital buffers; (3) borrower assistance that comprises

government-sponsored credit lines to strategic sectors and government liability guarantees so that the flow of credit

to households and businesses is secured; and (4) monetary policies which include directives such as asset purchases

and policy rate decisions.

This study aimsto examine the relationship betweenthese economic policy responsesto the COVID-19 pandemic

and the growth of nonperforming loans (NPLs) in 2020 across 47 economies which have implemented some of these

measures. More specifically, we investigate if there is a significant relationship between various types of government

economic policy responses to COVID-19 in 2020 (liquidity, prudential, borrower support, asset purchases, and policy

rates measures) and defaults on aggregate NPLs. The impact of these policies on the two main components of con-

sumer loans,that is, consumer credit (or non-mortgage loans) andhousing mortgage are also evaluatedin this study.

Controlling for other important determinants of NPLs and applying multivariate regressions, our results show

that economies in which policymakers implemented prudential and/or borrower support measures have NPLs

experiencing slower growth. We also find that the growth of default on non-mortgage loans is more sensitive to

economic policies than the growth of default on mortgage loans.

The contribution of this paper is two-fold. First, although the literature on the effect of policy responses to the

COVID-19 pandemic on banking and financial variables is growing very rapidly (Demirgüç-Kunt et al., 2020;Narayan

et al., 2020; Phan & Narayan, 2020; Zaremba et al., 2020), no empirical research has been done on the relationship

between economic policy responses to COVID-19 pandemic and nonperforming loans across countries. This point is

critical as NPLs' growth reflects adversely on the stability of finance systems (Dimitrios et al., 2016;Tajaddini &

Gholipour, 2017) and consequently, may even lead to a solvency crisis in banking sectors and large declines in eco-

nomic activities (e.g., Barseghyan, 2010; Reinhart & Rogoff, 2011; Salas & Saurina, 2002). Second, while there have

been several studies on determinants of nonperforming or problem loans (e.g., Breuer, 2006;Dimitriosetal.,2016;

Ghosh, 2015; Tajaddini & Gholipour, 2017), no study has yet investigated the link between newlyemployed economic

policies relatedto the COVID-19 pandemic and differenttypes of default on loans. Our findings provide policymakers

with timely research-based information to make informeddecisions in the current butalso the post-pandemic period.

DATA AND METHODOLOGY

Sample

This study uses yearly data from 47 economies and they are as follows: Argentina, Australia, Austria, Brazil, Canada,

Chile, China, Columbia, Czech Republic, Denmark, Egypt, France, Germany, Greece, Hong Kong, Hungary, India,

Indonesia, Israel, Italy, Japan, Malaysia, Mexico, Morocco, The Netherlands, Nigeria, Norway, Peru, The Philippines,

Poland, Portugal, Romania, Russia, Saudi Arabia, Singapore, South Africa, South Korea, Spain, Sweden, Taiwan,

Thailand, Turkey, UAE, United Kingdom, Ukraine, United States, and Vietnam. The sample covers all the economies

for which data on various types of rates of nonperforming loans are obtainable.

Dependent variables

The three dependent variables employed in this study are: (1) 2019–2020 nonperforming consumer loan growth

rate; (2) 2019–2020 nonperforming consumer credit (or non-mortgage loans) growth rate; and (3) 2019–2020 non-

performing consumer housing mortgage growth rate. Data on nonperforming loans were obtained from Euromonitor

International (2021). Table 1provides a detailed description of the variables and data sources used in this study.

552 GHOLIPOUR AND ARJOMANDI