The impact of COVID‐19 pandemic on the Thai economy and the effectiveness of monetary policy: A Bayesian DSGE model approach

• Published date: 01 March 2024
• Author: Samuel Kwesi Dunyo,Saran Sarntisart
• Date: 01 March 2024
• DOI: http://doi.org/10.1111/asej.12316

ORIGINAL ARTICLE

The impact of COVID-19 pandemic on the Thai economy

and the effectiveness of monetary policy: A Bayesian

DSGE model approach

Samuel Kwesi Dunyo | Saran Sarntisart

Graduate School of Development Economics, National Institute of Development Administration—NIDA,

Bangkok, Thailand

Correspondence

Samuel Kwesi Dunyo, Graduate School of Development Economics, National Institute of Development

Administration—NIDA, 118 Seri Thai Road, Bangkok, Thailand.

Email: samdunyo@yahoo.com

Abstract

This study estimates a medium-scale dynamic stochastic general equilibrium model for

the Thai economy to evaluate the impact of the COVID-19 pandemic containment policy

on key macroeconomic aggregates. The shock to labor supply is considered as the main

transmission channel. The paper discussed the role of monetary policy in regard to eco-

nomic recovery and also identified the dominant shocks driving the business cycle. Thai

quarterly series from 2011Q1 to 2021Q2 is used for the Bayesian estimation of the model.

Though the pandemic shock caused a sharp decline in output, consumption and invest-

ment, the results suggest a fast recovery in the growth rates of the variables in about

2.5 years. At the same time, the dominant shocks that account for output variation in the

medium to long term are investment, labor supply and productivity shocks. Monetary

policy is effective in shortening the recovery due to its impact on private investment. The

key drivers of Thai household consumption in the long run are investment, labor supply

and productivity shocks. On average, the investment shock appears to be the key driver

of the business cycle at all horizons.

KEYWORDS

Bayesian estimation, COVID-19 pandemic, DSGE model, monetary policy, Thai economy

JEL CLASSIFICATION

C63, D58, E24, E27, E32, E37

DOI: 10.1111/asej.12316

© 2024 East Asian Economic Association and John Wiley & Sons Australia, Ltd.

Received: 9 December 2021; Accepted: 5 February 2024

Asian Econ. J. 2024;38:3–34. wileyonlinelibrary.com/journal/asej 3

1|INTRODUCTION

Thailand was the first country to record a COVID-19 pandemic case outside of

Wuhan, China where the pandemic was first documented in the last quarter of

2019.

1

The pandemic has since spread to nearly all corners of the globe cur-

tailing lives and slowing down economic activity. The focus of the paper is not

to examine the dynamics of the spread of the pandemic in Thailand, but rather

to assess how government policies aimed at controlling the spread and saving

lives have impacted economic activity.

Three months after recording the first case of COVID-19 pandemic,

Thailand imposed strict nationwide lockdown and a border closure.

2

While

these measures proved successful in controlling the outbreak, they came at a

huge cost to the economy. In spite of the initial success in curbing the spread of

the pandemic, the virus re-emerged in the last quarter of 2020. As at the time of

writing this paper (October 2021), the daily case load hovered at around 10 000.

At the same time, lockdown measures were being eased.

The negative effect of the COVID-19 pandemic on the economy encom-

passes both the supply and demand side. Containment policy forced workers to

stay at home without adding labor to the temporary labor supply shock, which

in turn triggered a downturn in aggregate private consumption and investment.

The COVID-19 pandemic shock can also be regarded as a permanent labor sup-

ply shock due to the death of a fraction of the workforce.

According to the International Monetary Fund, the spread of the COVID-19

pandemic could lead to severe contraction of the global output including

Thailand. The Bank of Thailand (BOT) revised its growth forecast from 1.8% to

0.7% in 2021 due to expansion of lockdown measures.

Past pandemics such as 1968 Hong Kong influenza and 2002 SARS nega-

tively affected economic activity, but output quickly returned to its pre-

pandemic level, often referred to as a V-shape recovery (Carlsson-Szlezak et al.,

2020). However, the COVID-19 pandemic is unlikely to follow a similar pattern

due to significant supply disruptions. Gourinchas (2020) estimated that about

50% of the workforce was unable to find work in the short term.

Stringent confinement measures such as lockdown, business shutdowns and

national border closures caused significant job losses, especially in the tourism

sector and related service providers. Figure 1shows the trend of unemployment

rate up to December 2020, 9 months after the first lockdown policy was

1

Thailand reported the first case of COVID-19 pandemic on January 13, 2020 (Ministry of Public Health,

Thailand).

2

Thailand population of about 66.65 million was on lockdown with only essential workers allowed to go to work.

National border closures and flight bans were also enforced. The pre-Covid economy was stable with

unemployment relatively low with a recorded gross domestic product (GDP) growth at 1.6% as at the fourth

quarter of 2019. By the third quarter of 2020, gross domestic product declined by 6.4%, unemployment increased

by 1.9%, and debt accumulated by households to GDP ballooned to 86.6%.

4DUNYO and SARNTISART

implemented. This shows the sudden increase in unemployment from the end of

the first quarter of 2020, when the lockdown policy was implemented, to the

beginning of the third quarter, when restrictions were being eased. Not only job

losses, but also bankruptcies among firms rose forcing some firms to perma-

nently close down operations. In addition, government revenue also dwindled.

The Thai financial sector is under considerable stress and becoming increasingly

vulnerable because of the weak balance sheet of firms and their inability to ser-

vice debt (BOT Monetary Policy Report June 2021).

3

Studies have used macro models to examine how the COVID-19 pandemic

has affected the economy as the pandemic spreads and more data becomes

available. One strand of literature looked into the dynamics of the disease as

well as the effectiveness of control measures and the behavior of economic

agents (Eichenbaum et al., 2020; Toda, 2020).

Another strand of literature has investigated how the actual policies put in

place to control the pandemic have impacted aggregate economic activity

(Guerrieri et al., 2022; Mihailov, 2020). The macroeconomic and distributional

effect of the COVID-19 pandemic was evaluated in Kaplan et al. (2020) using a

theoretical model with a pandemic possibility frontier. Evaluating the impact of

the government response to the COVID-19 pandemic is very important as it

would enable policymakers to see how the varying severity of control measures

affect the aggregate economy in the short and long term. It would also help in

the trade-off between saving lives and saving livelihoods.

The objective of this paper is to investigate the impact of COVID-19

pandemic lockdown policies implemented by the Thai government on the main

macroeconomic aggregates. In this light, our study intends to provide answers to

0.000

0.500

1.000

1.500

2.000

2.500

01-2013

05-2013

09-2013

01-2014

05-2014

09-2014

01-2015

05-2015

09-2015

01-2016

05-2016

09-2016

01-2017

05-2017

09-2017

01-2018

05-2018

09-2018

01-2019

05-2019

09-2019

01-2020

05-2020

09-2020

Unemployment rate in Thailand

FIGURE 1 Unemployment rate in Thailand from 2013 to 2020. Source: National Statistic

Office. [Color figure can be viewed at wileyonlinelibrary.com]

3

The BOT current framework is called flexible inflation targeting (FIT). FIT means that the central bank

maintains the price level within a certain range. In addition, it gives central banks the freedom to consider the

changes in inflation and other objectives such as output and financial stability.

ASIAN ECONOMIC JOURNAL 5