Navigating economic growth challenges in developing countries: a case study of BIMSTEC

Abstract

Economic growth remains a central concern for policymakers and global scholars, especially in the context of pandemics like Covid-19. This study delves into the multifaceted growth issues in the BIMSTEC region. Drawing from empirical evidence, this study identifies significant factors influencing economic growth, including landlockedness, corruption and political crises. Landlockedness has a negative impact on economic growth. Corruption acts as grease in the wheel, while political crises hamper the economic growth rate in the pandemic era. These findings are robust under random effect models. The synthesis of this study focuses on accelerating good governance, providing coastal access to landlocked states and implementing free trade agreements to stimulate regional economic growth.

Full text

AREA STUDIES | RESEARCH ARTICLE
COGENT SOCIAL SCIENCES
2024, VOL. 10, NO. 1, 2431591
Navigating economic growth challenges in developing countries: a
case study of BIMSTEC
Arbind Chaudharya and Ramesh C. Paudelb
aPolicy Research Foundation, Kathmandu, Nepal; bNational Planning Commission, Government of Nepal, Kathmandu, Nepal
ABSTRACT
Economic growth remains a central concern for policymakers and global scholars,
especially in the context of pandemics like Covid-19. This study delves into the
multifaceted growth issues in the BIMSTEC region. Drawing from empirical evidence,
this study identifies significant factors influencing economic growth, including
landlockedness, corruption and political crises. Landlockedness has a negative impact
on economic growth. Corruption acts as grease in the wheel, while political crises
hamper the economic growth rate in the pandemic era. These findings are robust
under random effect models. The synthesis of this study focuses on accelerating good
governance, providing coastal access to landlocked states and implementing free trade
agreements to stimulate regional economic growth.
1. Introduction
Economic issues present significant challenges for the Bay of Bengal Initiative for MultiSectoral Technical
and Economic Cooperation (BIMSTEC), which includes Bangladesh, Bhutan, India, Myanmar, Nepal, Sri
Lanka, and Thailand. Notably, Bangladesh, Bhutan and Nepal are set to graduate from least developed
country (LDC) status in 2026, while the remaining nations are listed as developing countries (UNCTAD,
2021). Additionally, Bhutan and Nepal’s landlocked status adds complexity to their economic conditions.
Developing countries globally face numerous obstacles to sustainable economic growth, including infra-
structure deficiencies and various institutional, political, economic, geographical and cultural barriers
(World Bank, 2014; Moore, 2018; George et al., 2022; Kronick & Rodríguez, 2023). These challenges neces-
sitate innovative solutions and strong partnerships. BIMSTEC serves as a vital link between the Southeast
Asian (ASEAN) and South Asian (SAARC) regions, embodying a convergence of economic complexities
and developmental aspirations that profoundly impact the futures of billions.
A compelling narrative of economic diversification, regional integration, sustainable development, sec-
toral cooperation, security and stability, trade promotion and inclusive growth lies at the core objectives
of the BIMSTEC initiative. As member states navigate geopolitical shifts, technological advances and envi-
ronmental imperatives, coordinated action becomes more apparent to achieve measurable economic
outcomes (Ganeshan, 2021). BIMSTEC has abundant resources for sustainable growth and development
(Rasul et al., 2018). It shares 4.5% of global GDP and 22% of population (United Nations, 2023b), variety
of flora, fauna, minerals, climates and the world’s richest untapped natural resources, including gas, oil
and other seabed minerals (Brewster, 2015; Banerjee & Dey, 2016; Powell, 2017), fish stocks (Kumar etal.,
2016; Cmfri, 2018) and tourism (Banerjee, 2023).
In most of the developing economies, several prevalent factors challenge economic growth prospects.
From a governance perspective, corruption remains a challenging issue, undermining institutional
© 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group
CONTACT Ramesh C. Paudel ramesh.paudel@alumni.anu.edu.au  Central Department of Economics, Tribhuvan University, Former
Member, National Planning Commission, Government of Nepal, Kathmandu, Nepal
This article has been corrected with minor changes. These changes do not impact the academic content of the article.
https://doi.org/10.1080/23311886.2024.2431591
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which
permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been
published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.
ARTICLE HISTORY
Received 24 April 2024
Revised 8 August 2024
Accepted 11 November 2024
KEYWORDS
Economic growth;
landlockedness;
corruption; BIMSTEC;
pandemic; political crisis
JEL CODES
C23; D73; F43; H12; O11
SUBJECTS
Economics; Political
Economy; Cities & the
Developing World;
Development Policy;
Economics and
Development

2 A. CHAUDHARY AND R. C. PAUDEL
integrity and economic efficiency (World Bank, 2014; Fraj & Lachhab, 2015). This situation discourages
both local and foreign investors (Alesina etal., 1996), which means less investment and, in general, less
employment and output (Uslaner, 2004; Ahmad et al., 2012). But in some cases, corruption helps the
economy, especially in lower-income countries where bureaucratic rules are very rigid. It is called grease
in the wheel (lubricant), the opposite of sand in the wheel (Méon & Sekkat, 2005).
In terms of trade facilitation, landlockedness presents major challenges, as it hinders direct access to
global markets and often necessitates costly alternatives for trade (Raballand, 2003; MacKellar etal., 2011;
Paudel, 2014; Simpson & Zazai, 2020). The world has 44 landlocked countries, including 32 landlocked
developing countries Least Developed Countries (LDCs) and 17 landlocked developed countries (LLDCs)
(United Nations, 2023a). World Bank (2014) estimates that the average level of development in LDCs is
about 20% points lower than that of non-LDCs. LLDCs are among the world’s most vulnerable countries,
with weak supply chains, only accounting for about 1% of global trade, and the lowest human develop-
ment index (Dumitrescu et al., 2018).
Politically, civil unrest, refugee crises, constitutional crises, genocides, coups and other instabilities are
key factors that adversely affect economic progress in the country (Kronick & Rodríguez, 2023; Giugni &
Grasso, 2016). Political trust links common people to institutions or governments and ultimately aug-
ments economic and political confidence. However, the political crisis breaks all these relationships and
hampers economic growth (Alesina et al., 1996; Ndulu, 2008; Muñoz, 2009; Dalyop, 2019; Kronick &
Rodríguez, 2023).
In the case of BIMSTEC, these are the primary attributes (Table A.1, Figure 3 Appendix A.1). The
Covid-19 pandemic emerged as a dominant global growth factor between 2019 and 2021, significantly
affecting all economies and populations worldwide. Since its onset in 2019, the pandemic’s prolonged
impact throughout 2020 and 2021 has posed a major challenge. In BIMSTEC, India suffered significant
casualties (Figure 1 in Appendix A.1) and economic losses during this pandemic (Goswami etal., 2021).
Bhutan and Myanmar are recorded as more pandemic-vulnerable regarding economic growth.
Bangladesh has had a remarkable growth history in recent decades, being the only nation to experi-
ence positive economic growth during the pandemic (Figure 2 in Appendix A.2). This is the result of
the Bangladesh government’s successful stimulus packages for the agriculture and garment industry
and migrants, money transfers, health regulations, smart lockdowns, food availability and international
travel bans to control the spread of Covid-19 and boost recovery rates (Kumar & Pinky, 2021).
Upon consideration of these arguments, it becomes evident that landlockedness, corruption and polit-
ical crises pose significant challenges in shaping national income. The primary goal of this paper is to
investigate the impact of these challenging factors on the BIMSTEC economic region’s economy. By
doing this, we will not only understand the key economic challenges of the region but also help to
generalize the context to other developing economies and regions. To achieve this paper’s objective, we
used a panel dataset for 11 years, from 2012 to 2022. The geopolitical location of BIMSTEC, spanning
from mountains to sea, justifies our choice of this region as the focus of our research. This region boasts
a plethora of natural resources, population, minerals, energy resources and other economic opportunities
(Brewster, 2015; Banerjee & Dey, 2016; Kumar et al., 2016; Powell, 2017; Cmfri, 2018; Banerjee, 2023).
Given these circumstances, examining BIMSTEC’s growth trajectory can provide valuable insights for pol-
icymakers and summit members, enabling them to fully leverage its provisions and enhance the eco-
nomic progress of all member countries.
This article has four major contributions in this context. First, it documents the economic dynamics and
developmental challenges within the BIMSTEC region, which comprises a diverse set of nations with vary-
ing levels of economic development. Second, it demonstrates how regional cooperation frameworks can
effectively address shared challenges such as trade facilitation, infrastructure development and disaster
management. These insights are crucial for policy decisions and strategies for regional integration and
cooperation. Third, the study contributes to the broader literature on economic development, governance
and resilience, offering valuable lessons for other regions facing similar challenges. Ultimately, this research
aids policymakers, researchers and stakeholders in crafting targeted interventions and initiatives that pro-
mote sustainable development, inclusive economic growth and stability across BIMSTEC member states.
The subsequent sections of this paper are organized as follows. Section 2 presents the major brief
issues in the BIMSTEC economy concerning this article. Section 3 offers a brief literature review providing

COGENT SOCIAL SCIENCES 3
insight into existing research and a keen gap. In Section 4, the methodology is outlined, encompassing
the research design, model specification, estimation strategy and specifics regarding data generation.
Building upon this foundation, Section 5 presents the empirical results and discusses their findings. The
final section concludes the key findings and discusses the policy implications.
2. Major issues in the BIMSTEC economy
BIMSTEC confronts a series of critical challenges – economic, geographical, institutional and political –
that significantly hinder regional integration and growth. The stark disparity in economic development
among member states, which poses challenges similar to those faced by other developing economies, is
a major concern. While nations like India and Thailand boast relatively robust economies, others, such as
Nepal, Bangladesh and Myanmar, continue to struggle with high levels of poverty and underdevelop-
ment. This uneven economic landscape complicates collaborative efforts and resource allocation, ulti-
mately impeding the region’s collective economic advancement BIMSTEC (2023a).
Another pressing issue in BIMSTEC nations is the infrastructure deficit, which severely restricts trade
and investment opportunities. Inadequate transportation networks hinder intra-regional commerce and
limit economic partnerships with other regions (Institute of South Asian Studies, 2019; Gupta & Dutta,
2022). Consequently, the lack of infrastructure leads to limited employment opportunities, prompting
millions of youths to migrate abroad for income generation (World Bank, 2021). This migration results in
significant remittance inflows, highlighting another economic reality. Although initiatives like the BIMSTEC
Master Plan for Connectivity aim to address these challenges (BIMSTEC, 2023b), progress remains slow
due to funding constraints and political instability in several member states (Observer Research
Foundation, 2021). Landlocked economies, such as Bhutan and Nepal, face compounded issues regarding
road connectivity and supply chain access to overseas markets.
The BIMSTEC region faces significant ecological and political challenges that hinder governance, sus-
tainable development and regional cooperation. Ecologically, the area is susceptible to climate change
impacts, such as extreme weather events, and biodiversity loss, which threaten livelihoods and food
security (Godbole, 2024). Politically, member states often grapple with governance and corruption issues
(Figure 3 in Appendix A.3), territorial disputes, refugee crises, riots, coups, terrorism and varying national
interests (Table A.1) that complicate collaborative efforts to address these environmental concerns. These
intertwined challenges necessitate a unified and coordinated approach to foster resilience and promote
sustainable practices across the region.
The global pandemic, particularly Covid-19, has posed significant challenges for BIMSTEC economies.
Its impact has exacerbated existing issues, resulting in widespread economic losses, increased mortality
rates and governance failures. Overwhelmed health systems exposed deep vulnerabilities and inadequate
preparedness, leading to high death tolls (Figure 1) and strained resources. Economically, lockdowns dis-
rupted trade and investment, causing significant GDP downturns (Figure 2) and pushing many into pov-
erty. Additionally, the pandemic highlighted and intensified governance breaches and policy
implementation failures, further complicating the region’s economic landscape.
3. Literature review
3.1. Theoretical foundation
3.1.1. Landlockedness and economic growth
Landlockedness, where countries lack direct access to maritime trade routes, significantly impacts eco-
nomic growth. Geographical economics reveals that the absence of coastlines in landlocked countries
increases transportation costs and trade barriers, restricting market access and economic integration
(Nuno & Venables, 1999). These higher trade costs diminish trade volumes and overall competitiveness,
posing challenges to sustaining robust economic growth. The new economic geography framework
expands the analysis to examine spatial factors influencing economic development, emphasizing the
importance of reducing distance-related trade costs through strategic investments in infrastructure and
regional integration initiatives (Snow et al., 2003). Enhancing transportation networks and logistics

4 A. CHAUDHARY AND R. C. PAUDEL
infrastructure can help landlocked countries mitigate geographic isolation, capitalize on economies of
scale and enhance market competitiveness.
Institutional economics emphasizes the role of governance structures and institutional quality in shaping
economic outcomes for landlocked countries. Weak institutions, corruption and bureaucratic inefficiencies
exacerbate trade costs and hinder economic growth prospects (World Bank, 2014). Investments in educa-
tion, skills training and technological infrastructure are essential for overcoming these challenges and bol-
stering economic resilience. Comparative regional analysis offers insights into successful economic strategies
for landlocked countries, examining cases where regional cooperation, targeted infrastructure investments
and policy reforms have effectively mitigated the adverse effects of geographic isolation and promoted
economic growth (United Nations, 2023a). Development economists emphasize the significance of human
capital development, technological advancement and structural transformation in driving long-term eco-
nomic growth. Landlocked countries often grapple with lower levels of human capital and technological
adoption, limiting productivity and diversification efforts (Hafkin & Taggart, 2001; Adams, 2009).
3.1.2. Corruption and economic growth
In the theoretical discourse, corruption underscores the detrimental effects on the economic growth rate,
often described as ‘sand in the wheels’ of economic progress (Mondiale, 2006). However, in certain
instances, particularly in developing economies, corruption can paradoxically facilitate economic activity,
a phenomenon known as ‘grease in the wheels’. In institutional economics institutional economics, weak
governance structures and widespread corruption are identified as factors that erode institutional quality,
distort market mechanisms and diminish overall efficiency (Mauro, 1995). Nations plagued by high levels
of corruption typically experience reduced levels of investment, increased transaction costs, and lower
productivity, all of which collectively hinder economic growth (Gupta etal., 2002).
Public choice theory and agency theory provide complementary perspectives on how corruption
undermines governmental decision-making and economic transactions. Public choice theory highlights
how rent-seeking behavior, where individuals or groups pursue economic gains through corrupt prac-
tices, results in the misallocation of resources and stifles entrepreneurial activity, thereby creating disin-
centives for investment and innovation (Krueger, 2008). This phenomenon directly dampens the prospects
for economic growth. Meanwhile, agency theory examines how corruption within the principal–agent
relationship, fueled by information asymmetries and moral hazard, can divert resources away from public
interests toward personal gain among public officials (Shleifer & Vishny, 1993). Such practices not only
lead to inefficiencies in resource allocation but also erode trust in public institutions, thereby adversely
impacting investor confidence and further impeding economic growth.
The political economy perspective emphasizes the role of political institutions and electoral processes
in shaping corruption levels. Countries with weak checks and balances, inadequate regulatory frame-
works and limited accountability mechanisms are prone to higher levels of corruption (Aidt, 2003).
Political corruption not only diverts resources away from productive investments but also erodes public
trust and social cohesion, which are essential for sustained economic growth.
3.1.3. Political crisis and economic growth
In institutional economics, political crises often lead to weak governance, policy uncertainty and institu-
tional instability (Acemoglu & Robinson, 2006). These conditions can deter investment, hinder policy
implementation and disrupt economic activities, thereby exerting a negative impact on economic growth
rates. From a political economy perspective, it undermines investor confidence, leads to capital flight and
increases risk premiums (Alesina et al., 1996). Moreover, prolonged political crises may result in policy
paralysis, delayed reforms and reduced public spending on critical infrastructure and development proj-
ects, further impeding economic growth.
Conflict theory posits that political crises, including civil conflicts and social unrest, can devastate
economies by destroying physical infrastructure, displacing populations and disrupting supply chains
(Collier & Hoeffler, 2004). These disruptions not only cause immediate economic losses but also create
long-term barriers to economic recovery and development. It often generates uncertainty about future
policies and regulatory environments, deterring both domestic and foreign investments (Baker et al.,

COGENT SOCIAL SCIENCES 5
2016). High levels of uncertainty can lead to reduced business confidence, reluctance to undertake
long-term investments, and capital flight, all of which undermine economic growth prospects. Political
crises can erode social capital and trust in institutions, essential elements for economic development
(Putnam, 1994). Reduced trust limits cooperation among economic actors, increases transaction costs
and impedes the implementation of economic policies and reforms that are necessary for growth.
3.2. Empirical analysis
3.2.1. Landlockedness and economic growth
Empirical evidence suggests that landlockedness poses significant challenges to economic growth by
increasing transportation costs, limiting trade opportunities and hindering market access (Arvis et al.,
2011; Huelin, 2013; World Bank, 2014; Moore, 2018). Studies indicate that landlocked countries generally
exhibit lower levels of trade openness and market access compared to coastal economies (Mellinger
et al., 2000; Bhattarai, 2019). These nations face greater logistical challenges and dependency on neigh-
boring countries for trade access, which increases transaction costs and limits market integration (Hafkin
& Taggart, 2001; Snow et al., 2003; Faye et al., 2004; Huelin, 2013).
Several studies emphasize the pivotal role of infrastructure development and connectivity in alleviating
the challenges posed by landlockedness. By investing in transport networks, border facilities, and regional
integration initiatives, landlocked countries can enhance trade efficiency and foster economic growth
(Arvis et al., 2011; Paudel, 2013; Moore, 2018). Comparative analyses also reveal disparities in economic
performance among landlocked nations, influenced by their integration into regional economies and
infrastructure capabilities (Huelin, 2013; United Nations, 2023a). Successful examples from certain European
landlocked countries underscore the potential for economic advancement through effective regional col-
laboration and strategic infrastructure investments (United Nations Development Programme, 2023).
The impact of landlockedness varies significantly across sectors, with agricultural and resource-based
industries in landlocked countries facing notable challenges stemming from high transportation costs
and constrained access to international markets (Ojha, 2022). During the Covid-19 pandemic, landlocked
states experienced compounded difficulties in international trade and supply chains (Rivera, 2020; Mold
& Mveyange, 2020). For instance, Nepal’s exports were particularly affected, whereas India’s exports
showed greater resilience in South Asia (Kumari & Bharti, 2021).
3.2.2. Corruption and economic growth
Empirical studies consistently demonstrate a mix of affairs between corruption and economic growth.
Countries with higher levels of corruption tend to experience slower economic growth due to various
mechanisms. Corruption distorts resource allocation, reduces investment levels, increases transaction
costs and undermines institutional quality (Uslaner, 2004). These types of cases are rife, such as in devel-
oping economies (Ahmad et al., 2012), African countries (Ade et al., 2011) and Latin America (Fraj &
Lachhab, 2015). However, it can be perceived as a cost-effective method to bypass pervasive and inef-
fective government regulations, potentially enhancing system efficiency and fostering economic growth.
This phenomenon often thrives in environments characterized by weak governance and rigid bureau-
cracy, akin to lubrication for a squeaky wheel (Mondiale, 2006).
The research underscores the sector-specific impacts of corruption on economic growth, particularly
in industries reliant on government contracts or approvals like construction and natural resources, which
are vulnerable to corruption’s adverse effects (Iossa & Martimort, 2014; Urbina & Rodríguez, 2022).
Corruption in these sectors often results in inflated costs, project delays and decreased efficiency, thus
impeding overall economic performance. Moreover, Mauro (2004) argues that the impact of corruption
depends on a rent-seeking equilibrium, where its effects can be positive under conditions of robust
governance and high economic growth, but detrimental when corruption is pervasive and growth is
stagnant. This relationship is further explored as quadratic by Méndez and Sepúlveda (2006), Ahmad
et al. (2012), Thach etal. (2017), while Sindzingre and Milelli (2010) and Mallik and Saha (2016) empha-
size that corruption yields benefits when rare but poses risks when prevalent.
Corruption has become a double threat during the Covid-19 pandemic. In reaction to Covid-19,
several countries have violated anti-corruption rules, such as by cutting corners in procurement

6 A. CHAUDHARY AND R. C. PAUDEL
processes or by utilizing the crisis to maximize their private benefits. It was more robust in low-income
countries (Steingrüber et al., 2020). In South Africa, Covid-19 uplifts the corruption and foreign debt
liabilities (Mlambo & Masuku, 2020). In India, Usman et al. (2022) explain that during the pandemic,
emergency supplies and corruption go hand in hand. In Sri Lanka, it remains a significant barrier to
sustainable income, political stability, investment, resource allocation and social equity (World
Bank, 2020).
3.2.3. Political crisis and economic growth
Economists point out that a political crisis or instability is a serious malaise harmful to economic perfor-
mance. Africa, the world’s largest political unrest, has decreased the economic growth rate since the era
(Alesina et al., 1996; Ndulu, 2008; Dalyop, 2019). Since its independence, Venezuela has suffered three
economic catastrophes: one in each of the nineteenth, twentieth and twenty-first centuries. The political
system was entirely elite-centric and inadequately inclusive. This leads to political instability and consis-
tent economic losses (Muñoz, 2009; Kronick & Rodríguez, 2023).
In lower-income countries, political and economic instability become common characteristics (Saeed,
1986; Pindyck & Solimano, 1993; Azeng & Yogo, 2013; Saggu & Anukoonwattaka, 2015). Political unrest
sometimes has a two-way causality with economic crises. But it hurts economic growth and develop-
ment ultimately Alesina etal. (1996); Giugni and Grasso (2016). Recently in Sri Lanka, a root cause of the
political crisis eruption was the balance of payment crisis (Sebastian, 2022), and the balance of payment
crisis was strongly originated by Covid-19 pandemic and the Ukraine–Russia war in the background of
the massive Sri Lankan infrastructure investment (Bhowmick, 2022). Since history, Sri Lanka has been
financially less liberal (Paudel & Jayanthakumaran, 2009). The Sri Lankan political crisis led to the worst
economic and humanitarian crisis (George etal., 2022). In Nepal, the Maoist insurgency (1996–2006) cost
3 percent of GDP per year (Pradhan, 2009) and also declined the tourism industry (Bhattarai etal., 2005;
Pokharel et al., 2018).
Overall, the existing research has primarily examined factors such as landlockedness, corruption and
political crises in isolation or localized contexts, ignoring the nuanced dynamics shaped by BIMSTEC’s
regional integration and diverse socioeconomic landscape, particularly during a pandemic. As a result,
there is a significant gap in understanding how these interconnected elements interact within the
BIMSTEC framework, particularly during the pandemic, and their cumulative impact on economic growth.
4. Research methodology
4.1. Research design
This article addresses the research question using a longitudinal framework, analyzing a macro panel
database covering BIMSTEC member states (Bangladesh, Bhutan, India, Myanmar, Nepal, Sri Lanka and
Thailand) over 11 years from 2012 to 2022. Nepal and Bhutan, both landlocked mountain economies,
joined BIMSTEC in 2004. BIMSTEC, founded in 1997, initially focused on six areas of cooperation: trade,
technology, energy, transportation, tourism and fisheries. By 2008, it had expanded to include nine new
sectors: agriculture, public health, poverty alleviation, cultural cooperation, counter-terrorism, environ-
mental and disaster management, people-to-people contact, connectivity and climate change (BIMSTEC,
2023a). The first decade marked the expansion of its structure, while the last decade saw its operational
phase, making it a suitable sample for the analysis.
The variables under consideration exhibit a heterogeneous nature, encompassing both quantitative
and qualitative dimensions. Notably, the global Covid-19 pandemic has exerted profound influence over
the most recent triennium, spanning from 2019 to 2021. Political crises have sporadically occurred within
the BIMSTEC region. Additionally, the representation of landlockedness pertains specifically to Nepal and
Bhutan, denoting a qualitative attribute. Thus, these three variables are categorical. In mathematical
terms, these are formally expressed as:
Dmmy
i=−1 19if "landlockedness", "Covid or political crisis pr
", " " eesence
otherwise0




COGENT SOCIAL SCIENCES 7
In certain instances concerning Covid-19, we additionally incorporate several interaction variables
associated with corruption, landlockedness and political crises. Initially, we organized the panel data set
utilizing the stacked cross-sectional technique. Subsequently, we conduct panel regression analyses,
employing the Hausman test statistic to ascertain the most suitable (fixed or random effect) model. In
the context of the random effect model, we give preference to the utilization of the Swamy and Arora
random effects methodologies.
4.2. Model and variables
Our next step involves developing a model to achieve the research objective of this article. For this
purpose, we have developed the preliminary equations for the base model specification based on the
earlier sections.
Y Landlockedness Covid Landlockedness
it iii
Z= + + −×
()
+
ββ β β
01 2 3
19
iit it
u+ (1)
where Yit (the dependent variable) is the economic growth rate of ith BIMSTEC members – Bangladesh,
Bhutan, India, Myanmar, Nepal, Sri Lanka and Thailand – over 11 years (t= 2012,…,2022). We selected this
sample period based on data availability to cover Covid-19 and its left-over effects on the economies of
the region. We include a number of independent variables to support our research objectives based on
the literature. Landlockedness is a dummy variable to represent landlocked countries in our selected
sample, which includes Nepal and Bhutan. Therefore, landlockedness is time-invariant. Similarly, Covid-19
is another dummy variable that represents the Covid-19 years, such as after 2020 onwards. The interac-
tion term of landlockedness and Covid-19, such as Covid-19 ×Landlockednessirepresents the dummies
(=1 for the presence, 0 otherwise), which helps us to find the impact of Covid-19 in the landlocked
countries in the region.
Similarly, Zit is our set of control variables: Infrastructureit, Inflation rateit, Remittancesit and Labor
forceit. Among these variables, infrastructure is measured as the share of GDP in percentage, inflation is
as a traditional fashion, remittances as a share of GDP in percentage, and labor force is growth rate in
percentage Infrastructureit is the investment in the infrastructure of ithcountries over the time t, β0 and
uit denote intercept and error term, respectively. The expected sign of β1 and β2 are supposed to be
negative. The rationale for including investment in the model is due to its significant positive impact on
determining the growth rate; higher investment levels generally lead to accelerated economic growth.
Inflation, as another variable, signifies the price levels of goods and services and directly influences
household and government savings and expenditures, thereby impacting the economic growth rate.
Remittance inflows function as an endowment that can foster economic growth when effectively utilized
within the economy. Additionally, the labor force, as discussed in the literature, is pivotal to economic
growth, and its positive impact depends on the quality of human resources.
Similarly, Equation (2) is estimated to examine the impact of corruption on the economic growth of
the BIMSTEC region. The interactory term, such as Covid-19 × Corruptionit shows the combined effect of
corruption and Covid-19 on the dependent variable. The expected sign of the coefficients θ1 and θ2 can
be positive or negative. In most developing economies, it is negative (Fraj & Lachhab, 2015). We remove
the variable infrastructure from this model due to collinearity concerns (Table A.3 in Appendix A.6).
Y Corruption Covid Corruption
it it
it i it it
Zu
= + + −×
()
++
βθ θ β
01 2 3
19 (2)
We now want to know how political crises affect the region’s economic growth. For this purpose, we
estimate Equation (3) by substituting the corruption variables with those related to political crises, along
with relevant interaction terms, to illustrate the impact of both variables. Political crises hurt the current
economic growth rate. This type of crisis erupts more powerfully in pandemic situations around the
globe. Therefore, both coefficients γ1 and γ2 are expected to be negative.
Y Politicalcrisis Covid Politicalcrisis
it i i
= + + −×
()
+
βγ γ β
01 2 3
19
ii it it
Zu
+ (3)

8 A. CHAUDHARY AND R. C. PAUDEL
4.3. Estimation strategy
Our next step involves formulating an estimation strategy based on existing literature, tailored to the con-
text and informed by two distinct scenarios found in our database. First, as we have different countries in
the sample, there are unobserved heterogeneity issues among the countries. Second, we have time-invariant
data, like landlockedness, that remain constant over the sample period for the specific country.
Therefore, we employ a one-way error component modeling approach as discussed in Baltagi (2008)
and Wooldridge (2015). This model allows us to examine the relationship between interest variables and
economic growth in BISMTEC.
YX
it it
c
=++
′
0
β
ε (1.1)
where Yit= economic growth rate (dependent variable) observed for the ithcountries and at time t, X′is
the time-variant 1 × k regressor vector, β is the k × 1 matrix of parameters/coefficients, c0 is constant,
and ϵit is the error term. In a panel data regression, if the model, for instance, Equation (1.1) is affected
by the fixed effects or an unobserved effect that varies from one cross-section to another but does not
change over time (t), it is called the fixed effect model (Wooldridge, 2015). Hence, under this approach,
Equation (1.1) can be converted like this:
YX
it i it
= +′ +Γ
1
β
ε
(1.2)
i = 1,2,….7. and t = 2012,….2021.
where Γ1i is the different individual’s intercepts, and it depends upon c0 and an unobserved (dummy)
variable Di. Hence, Γ1i = c0 + Diψ, where ψ is the vector of ith coefficients of the dummy variables.
Another way, instead of treating Γ1i as fixed, we assume that it is a random variable with a mean value
of Γ1 (not subscript i here). The intercept value for an individual country can be expressed as follows:
ΓΓ
11ii
= +
 (1.3)
where ϱi is a random error term with the mean value of zero and a variance of σϱ2. It is also known as
an unobservable or latent variable. Putting the value of Equation (1.3) into Equation (1.2) yields:
Yit it i it it it
XX=+ ++ =+ +
′′
ΓΓ
11
β βω
ε (1.4)
where ωit= ϱi+ ϵit.
The composite error term, ωit, consists of two components: ϱi, which is the cross-section or individual
specific error component, and ϵit, which is the combined time series and cross-section error component
and is sometimes referred to as the idiosyncratic term because it varies over both cross-section and time.
Hence, it is named the error component model (ECM) (Gujarati, 2009). This ECM implies that each error compo-
nent is uncorrelated with the others and that there is no autocorrelation across both cross-section and
time series units.
4.4. Data and sources
In our dataset, the variables exhibit a combination of quantitative and categorical attributes. While the
Corruption Perception Index (CPI) represents a quantitative measure, the remaining outcome variables–
political crisis, Covid-19 and landlockedness – possess qualitative characteristics. We have provided com-
prehensive details regarding these variables, along with their associated data and valid sources, in Table
A.2, Appendix A.5. This table serves as a reference point, ensuring transparency and reliability in our
data analysis process.
In this study, the annual GDP growth rate serves as a proxy for measuring economic growth.
Specifically, we define the occurrence of a political crisis as taking the value of 1 for a particular year of
the ith country, and 0 otherwise (Table A.1). Similarly, there are three indices to demonstrate the size of
corruption: the International Country Risk Guide (ICRG), the CPI by Transparency International, and the

COGENT SOCIAL SCIENCES 9
World Bank’s Corruption Control Index (Baliamoune-Lutz & Ndikumana, 2010). For our analysis, we opt to
employ Transparency International’s CPI as an indicator of corruption levels.
Moreover, we incorporate fixed control variables common to many growth models. Specifically, we
utilize gross fixed capital formation (% of GDP) as a proxy variable for measuring infrastructure develop-
ment within a country. Additionally, we consider the active labor force participation rate for individuals
aged 15–24 as an indicator of the available active labor force within the region. An increased labor
supply not only reduces production costs but also stimulates investment, thus fostering economic
growth. Personal remittances received (% of GDP) reveal the role of migrant workers in the economy,
household resilience to external shocks, and the potential to use remittances for economic development.
These control variables are fundamental in capturing the broader economic context and ensuring com-
prehensive analysis within our study framework.
5. Results and discussions
The estimated outcomes provide a notable adverse impact of landlockedness, corruption and political
crises on the economic growth trajectory of BIMSTEC. Moreover, these effects appear to have been exac-
erbated during the Covid-19 crisis, indicating heightened vulnerability in the face of external shocks. The
detailed results of our models are presented in Table 1, providing comprehensive insights into the mag-
nitude and significance of each variable.
The economic growth trajectory of BIMSTEC from 2012 to 2022 is profoundly impacted by the
Covid-19 pandemic, which serves as a significant barrier. The pandemic has led to a marked decline in
the economic growth rate, aligning with global trends. Statistical analysis reveals a highly significant
coefficient of −4.75 (p= 0.00) associated with Covid-19, emphasizing its detrimental effect on economic
growth within the BIMSTEC region. This adverse impact is clearly illustrated in Figure 2, where all mem-
ber nations, except Bangladesh, experienced a negative growth rate. Moreover, the repercussions of the
Covid-19 outbreak extend beyond economic realms, encompassing governance structures, service deliv-
ery integrity, political stability, transportation efficiency, production and value chain systems. Particularly
in developing economies, these effects are more pronounced compared to developed groups (Kim, 2020).
Column 3 of Table 1 illustrates the adverse impact of landlockedness on the economic growth rate,
as evidenced by its coefficient of −4.89 (p = 0.0497), which is statistically significant. Furthermore, its
interaction variable with Covid-19, although negative, is deemed insignificant. This underscores the seri-
ous trading costs associated with landlocked status within the BIMSTEC region, particularly affecting
Nepal and Bhutan due to their lack of access to seacoasts.
The average annual growth rate is estimated to be approximately 5% points lower due to landlock-
edness, highlighting its significant implications for international trade. Landlocked countries face trade
restrictions at borders and incur additional costs during transportation, loading, unloading and other
logistical expenses. The World Trade Organization (2021) has acknowledged the challenges faced by
LLDCs when integrating into global supply chains, resulting in increased trading costs. This premise is
bolstered by Paudel and Cooray (2018), World Bank (2014), Bhattarai (2019) and Moore (2018).
During its 1997 inaugural summit, BIMSTEC discussed a ‘free trade area (FTA)’, committing to regional
economic integration. Currently, a trade negotiating committee (TNC) oversees seven working groups on
trade and economic cooperation, including goods, rules of origin, services, investment, legal matters,
customs cooperation and trade facilitation (BIMSTEC, 2023c). Despite these institutional efforts, the land-
lockedness cost in BIMSTEC persists. For over 15 years, landlocked states have had no effective trade
facilitation measures, causing trade flows and economic growth uncertainty.
The result from column 4 of Table 1 highlights the significant impact of corruption on the economic
growth rate. The corruption coefficient is negative. A negative sign indicates a positive association
between corruption and economic growth. This phenomenon is common in most low-income countries,
where bribes or similar activities lubricate economic activity (Mallik & Saha, 2016). BIMSTEC economies
are seen as deeply rooted in corruption (Figure 3). However, the interaction variable of corruption with
Covid-19 is statistically significant, with a coefficient of −0.114 (p= 0.00). This negative coefficient explains
that there is a positive relationship between corruption and economic growth rate, a phenomenon often
referred to as ‘grease in the wheel’ in economic literature (Mondiale, 2006).

10 A. CHAUDHARY AND R. C. PAUDEL
The concept of ‘grease in the wheel’ implies that corruption can facilitate economic activity and stim-
ulate growth, particularly during times of crisis such as the Covid-19 pandemic (Terziev et al., 2020;
Rose-Ackerman, 2021). In this context, corruption may act as a lubricant that helps smooth the function-
ing of institutions and facilitates transactions, thereby mitigating the adverse effects of the pandemic on
economic activities. It might involve offering bribes to expedite permit approvals, bypass regulatory hur-
dles, or secure favorable treatment, ultimately undermining the integrity of the investment environment
and perpetuating a culture of corruption, which is not visioned by Transparency International (2019).
The impact of political crises on economic growth rates within the region is a topic of significant
concern and study. In BIMSTEC, the major forms of crises are military coups, refugees, constitutional and
electoral violence, rioting, election result disputes and communal violence (Table A.1 in Appendix A.4).
The findings from column 5 in Table 1 shed light on this relationship, indicating that the political crisis
indeed has a negative impact on economic growth rates in the BIMSTEC region. However, it is notewor-
thy that the interaction variable of political crises with Covid-19 is the only statistically significant factor.
A political crisis can disrupt governance structures, create uncertainty and undermine investor confi-
dence, all of which can have adverse effects on economic growth. This discusses that while political
crises generally exert a detrimental influence on economic growth rates, their impact is significantly
exacerbated by the presence of the Covid-19 pandemic. The statistical significance of the interaction
variable underscores the heightened economic challenges faced by countries grappling with both polit-
ical instability and the Covid-19 crisis simultaneously.
The control variables have a consistent impact on all estimated models. The inflation rate is negative
and statistically significant. Higher inflation rates reduce economic growth by decreasing consumer pur-
chasing power, increasing uncertainty in investment decisions and potentially distorting resource alloca-
tion. Infrastructure development and personal remittances received contribute positively to BIMSTEC’s
economic growth. All of the findings in this study are robust under the random effect model.
6. Conclusion and policy implications
This study documents the major economic attributes of the BIMSTEC region, discussing the major issues
at this time. In doing so, it aims to provide insights into the region’s economic growth challenges and
opportunities, with important implications for policymakers and other stakeholders. Then, those issues
are reviewed in the border prospectives of global literature before moving to investigate the effects of
landlockedness, corruption and political crises on economic growth in the BIMSTEC region employing a
formed econometric method. In this process, we conducted rigorous panel regression analysis using the
data for 11 years, from 2012 to 2022, to analyze the multifaceted dynamics shaping the economic tra-
jectories of the BIMSTEC region.
The findings of this paper are threefold. First, our research confirms the adverse impact of landlock-
edness on economic growth within the BIMSTEC region. The constraints imposed by geographical factors
underscore the urgent need for strategic interventions to alleviate the economic vulnerabilities faced by
landlocked member states, as discussed in Paudel (2014).
Second, corruption may act as a lubricant, smoothing institutional functioning and facilitating trans-
actions, thereby mitigating the pandemic’s negative effects on economic activity. However, this practice
undermines the integrity of the investment environment and fosters a culture of corruption. The findings
highlight the complex interplay between corruption, economic growth and crisis management, empha-
sizing the importance of effective governance mechanisms and anti-corruption measures in promoting
sustainable and equitable development in the BIMSTEC region.
Third, the analysis underscores the detrimental impact of political crises on economic growth, partic-
ularly during pandemics. The destabilizing effects of political instability exacerbate economic uncertain-
ties, dampen investor confidence and hinder growth prospects. Strengthening democratic institutions,
promoting political stability and fostering inclusive governance structures are essential prerequisites for
ensuring sustained economic growth and resilience in the face of crises.
This article’s major policy implication and recommendation is that policymakers in this region should
focus on improving the quality of governance, regional connectivity and economic resilience in the
region. In addition, addressing infrastructural deficits, enhancing connectivity and fostering regional
cooperation are imperative steps towards unlocking the economic potential of these regions, which may

COGENT SOCIAL SCIENCES 11
be the focus for the overall development of the region. Regional cooperation, bolstered by free trade
agreements and infrastructure development projects, unlocks the full potential of BIMSTEC economies
and promotes prosperity for all member states. In the case of landlocked countries, policymakers can
promote inclusive and sustainable economic growth by prioritizing reforms that address corruption and
political instability to mitigate the negative impact of landlocked constraints.
This article leaves scope for further research in this region. Different studies at the disaggregated and
country levels can be performed similarly. Even at the aggregate level, the database covering a longer
period and the variation in methodology would make the literature robust.
Author Contributions
All authors have read and approved the nal manuscript.
Arbind Chaudhary: Conceptualization, Methodology, Data management, Formal analysis, Initial manuscript drafting,
Addressing reviewers’ comments.
Ramesh C. Paudel: Research design, Methodology, Manuscript editing, Final manuscript drafting, Addressing review-
ers’ comments.
Disclosure statement
We declare that we do not have any competing interests.
Funding
We do not have any research funds for this study.
About the authors
Mr. Arbind Chaudhary is a freelancer. He is a former researcher at the National Planning Commission, Government
of Nepal and the Chair of the Policy Research Foundation, Kathmandu, Nepal. Mr. Chaudhary remains committed to
advancing evidence-based policymaking and academic excellence in the eld of Development Economics.
Dr Ramesh Chandra Paudel is an Associate Professor of Economics and has extensive experience in the academia,
research and public policy arena. Ramesh has authored/cothoured about ve dozen of research articles published in
journals, book chapters and books.
Table 1. Elements of economic growth in BIMSTEC, 2012–2022.
Regressors (1) (2) (3) (4) (5)
Ination rate −0.807
(0.78)
−0.24***
(0.00)
−0.204***
(0.00)
−3.453***
(0.00)
−0.172**
(0.031)
Infrastructure 0.129*
(0.09)
0.092
(0.21)
0.261***
(0.00)
0.099
(0.177)
Remittances 0.054
(0.61)
0.014
(0.89)
0.284**
(0.014)
−0.036
(0.77)
Covid-19 −4.75***
(0.00)
Landlockedness −4.89**
(0.049)
Covid-19 × Landlockedness −2.56
(0.20)
Corruption −0.012
(0.86)
Covid-19 × Corruption −0.114***
(0.00)
Political crisis −0.34
(0.82)
Covid-19 × Political crisis −4.14* (0.076)
Constant 0.807 3.78 03.389 7.47** 2.28
(0.78) (0.18) (0.29) (0.02) (0.36)
R¯2 0.077 0.321 0.129 0.288 0.122
N 77 77 77 77 77
∗∗∗, ∗∗ and ∗ denote signicance levels at 1%, 5% and 10%, respectively.

12 A. CHAUDHARY AND R. C. PAUDEL
ORCID
Arbind Chaudhary http://orcid.org/0000-0003-0036-232X
Ramesh C. Paudel http://orcid.org/0000-0001-7721-3205
Data availability statement
The data that underpin the ndings of this study are available upon request from the corresponding author (Ramesh
C. Paudel). Access will be granted subject to reasonable requests and following applicable data-sharing policies.
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Appendices
A. Additional information
A.1. Human casualties due to Covid-19 in BIMSTEC
Coronavirus has wreaked havoc on the economies and public health of nations bordering the Bay of Bengal.
Myanmar, Sri Lanka and Thailand are the subsequent most impacted nations in terms of Covid-19 fatalities, after
India, Bangladesh, and Nepal. Bhutan and Thailand, which were the least impacted nations in the region, appear to
have avoided the worst of the pandemic. The majority of countries in the Bay of Bengal are combating a second or
third wave of Covid-19 infections.
A.2. Economic growth performances
The average income of BIMSTEC is 2,960 USD per capita with an average economic growth rate of about 4.3%
(World Bank, 2023). Nepal and Bhutan, two landlocked mountain economies, exhibit strikingly similar trends of
growth. At all times, India and Bangladesh have the highest growth rates among all members. The economic growth
rates of Myanmar and Sri Lanka are severely hindered. The economic growth outlook for Thailand is the lowest in
BIMSTEC.
A.3. Corruption in BIMSTEC
The overall corruption perception index (CPI) of BIMSTEC is not overwhelming. Except for Bhutan, other members
are comparatively more corrupt. Bhutan has made noteworthy strides in reducing the pressure of corruption. CPI
trends have improved and reached up to 68, whereas other members remain below 40. Myanmar achieved the
lowest CPI. Sri Lanka, Thailand, and Bangladesh have a decreasing CPI trend. After Bhutan, India has performed
relatively well.

16 A. CHAUDHARY AND R. C. PAUDEL
Figure 2. PartLabel-upper GDP growth rate of BIMSTEC members, 2012–2022.
Source: The World Bank.
Figure 1. PartLabel-upper per-day death numbers.
Source: World Health Organization.

COGENT SOCIAL SCIENCES 17
Figure 3. PartLabel-upper trend of corruption perception index (0–100) in BIMSTEC, 2012–2022.
Source: Transparency International.

18 A. CHAUDHARY AND R. C. PAUDEL
A.4. Political crisis
Table A.1 Political crisis in BIMSTEC, 2012–2022.
Country Year Brief description
Sri Lanka 2018 Sri Lanka has faced political instability, ethnic war, and communal violence. Conicts between diverse communities
and political instability threaten the nation’s democratic administration. President Maithripala Sirisena red and
replaced Prime Minister Ranil Wickramasinghe with former President Mahinda Rajapaksa, beginning the Sri
Lankan political crisis in 2018. Sirisena’s extreme actions paralyzed the political culture. The SLMC, the largest
Muslim party, supported Wickramasinghe. The SLMC worries that Rajapaksa will revive Sinhala nationalism in
politics. In the past decade, Muslim political elites have prioritized Islamic aliation. However, the new political
turmoil may revive an older denition of Sri Lankan Muslims based on Tamil, which they share with other
religious communities. After years of separating from Hindus and Christians, Muslim leaders may rekindle a
Tamil alliance to combat the growing Sinhalese nationalist trend (Johansson, 2018).
„ 2021 Sri Lanka was in economic and political turmoil, with protesters taking to the streets. This is the country’s rst
crisis since independence in 1948. The crisis has left the government’s coers empty and the people without
money to buy food and medicine. The pandemic, rising energy prices, and populist tax cuts have hurt Sri
Lanka’s economy. Medication, fuel, and other necessities are scarce due to a lack of foreign currency and rising
ination. Citizens wait hours in fuel station lines due to foreign reserve depletion. The country’s fuel, power, and
energy budgets are exhausted. With $51 billion in debt, the economy was stalled (Sharma, 2022).
Thailand 2014 A military coup in Thailand toppled the democratically elected government of Prime Minister Yingluck Shinawatra.
The military junta seized control of the country and imposed restrictions on freedom of expression and
assembly, prompting widespread condemnation from human rights organizations and the international
community. Since the coup, Thailand has been ruled by a military-backed government that has been confronted
with ongoing protests and political crises (Chachavalpongpun, 2014).
2019 Massive demonstrations broke out in Bangkok and other cities, demanding the dissolution of parliament and
democratic reforms. The government responded to the protests with repression, including arrests and
restrictions on free speech. Additionally, Thailand faces ongoing tensions between various political factions,
including the military and the pro-democracy movement, which has resulted in frequent government changes
and instability (Kongkirati, 2019).
India 2016 On November 8, 2016, the Government of India, led by Prime Minister Narendra Modi, announced the
demonetization ofď500 and ď1000 banknotes. This move aimed to curb black money, corruption, and
counterfeit currency (Shirley, 2017). Opposition parties organized protests and demonstrations across the
country against demonetization. These protests aimed to highlight the hardships faced by ordinary citizens,
especially those in rural areas and the informal sector, due to cash shortages and disruptions in economic
activities.
2019 In 2019, India faced a political crisis when Jammu and Kashmir lost its special status and came under the direct
administration of the central government. The move was widely denounced as unconstitutional, leading to
protests and disturbances in the region. The government’s treatment of opposition leaders and activists, which
included the arrest and detention of many leaders of Jammu and Kashmir, as well as most of the area of India,
were candled for this event.
2020 India faced a political crisis in 2020 when farmers launched enormous demonstrations against the government’s
new agricultural legislation. There were reports of violence and intimidation by the police against demonstrators
in response to the generally peaceful demonstrations in a few parts of Delhi (Rather, 2020).
Myanmar 2017 In Myanmar, the Rohingya ethnic minority, a predominantly Muslim group that has lived in Rakhine (formerly
Arakan) for millennia, has faced discrimination and persecution. Myanmar denies Rohingya citizenship,
education, health care, and employment. The government has conned many of them to overcrowded camps
with limited access to necessities and limited mobility. The Rohingya have also suered rape, torture, and
extrajudicial killings, forcing a mass exodus from Myanmar to neighboring countries. Military actions forced
many to ee, creating a refugee crisis (Prasse-Freeman, 2017).
2021 On February 1, 2021, Myanmar’s armed forces, the Tatmadaw, removed democratically elected members of the
ruling National League for Democracy (NLD) early in the morning, establishing a military junta. After arresting
de facto leader Aung San Suu Kyi, Myanmar’s military declared a state of emergency. The acting president,
Myint Swe, announced that the Commander-in-Chief of Defense Services Min Aung Hlaing has taken over
power and declared a year-long state of emergency. It nullied the November 2020 general election results and
promised a new election when the state of emergency ended (Chappell & Diaz, 2021).
2022 Myanmar continued to experience political turmoil and instability, following the military coup that took place in
February 2021. The political crisis in Myanmar in 2022 was characterized by ongoing protests, repression by the
military junta, humanitarian concerns, and diplomatic eorts to address the situation.

COGENT SOCIAL SCIENCES 19
A.5. Data and source
A.6. Correlation analysis
Table A.2. Overview of variables and data sources.
Variable Description Data source
Yit The annual GDP growth rate of ith countries over time t (2012,…, 2022) The World Bank
Landlockedness For Bhutan and Nepal = 1 over time t, 0 for others Dummy formation
Covid-19 For ith member for time (t = 2019,…, 2021) =1, 0 for others Dummy formation
Political crisis For the presence of political turmoils of ith cross-section =1 at time t, 0 for others Dummy formation
Corruptionit The index varies from 0–100. 0 means most corrupted and 100 score means fair for all ith
members over time t
Transparency International
Infrastructureit Gross xed capital formation (% of GDP) of ith member at t. The World Bank
Ination rateit GDP deator (annual %) The World Bank
Labor Forceit Labor force participation rate for ages 15-24, total (%) (modeled ILO estimate) of ith
members over time t.
The World Bank
Remittancesit Personal remittances received (% of GDP) by ith countries over time t. The World Bank
Table A.3. Correlation matrix.
1 2 3 4 5 6 7 8 9 10
1Ination rate 1
2 Infrastructure 0.007 1
3 Remittances 0.069 −0.228 1
4 Covid-19 −0.087 −0.084 −0.015 1
5 Landlockedness 0.008 0.57 0.52 −0.3E-34 1
6 Covid-19 ×
Landlockedness
−0.036 0.155 0.23 0.47 0.298 1
7 Corruption −0.044 0.73 −0.294 0.05 0.63 0.24 1
8 Covid-19 × Corruption −0.087 0.002 −0.005 0.93 0.114 0.63 0.24 1
9Political crisis 0.25 −0.2 −0.07 0.111 −0.23 −0.232 −0.119 0.08 1
10 Political crisis ×
Covid-19
0.107 −0.11 −0.12 0.43 −0.16 −0.07 −0.2 0.036 0.58 1