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The Impact of Political Risk and Institutions on Food Security
ABDULLAH*1, WANG QINGSHI1
MUHAMMAD AKBAR AWAN2 and JUNAID ASHRAF3
1School of Statistics, Dongbei University of Finance and
Economics, Dalian, Liaoning 116025, China.
2International Islamic University, Islamabad Pakistan.
3School of Statistics, Jiangxi University of Finance and Economics,
Nanchang, Jiangxi Province, R.P. China.
Abstract
The most challenging problem in today’s world is food insecurity, an
estimated approximately 832 million people around the world suffer
from a lack of adequate and healthy food on a regular basis for their life.
This problem is likely to intensify around the world due to high political
risk and weak institutions. Hence, this study utilizes the country-level
data, covering 124 countries in Asia, Africa, Europe, Latin America, and
the Caribbean between 1984-2018 to examine the impact of political
risk and institutions on food security, proxied by Dietary energy supply
(DES). We have finalized the System-GMM from Pooled-OLS, Fixed-
effect, Difference-GMM, and System-GMM, to recover the potential
endogeneity and unobserved heterogeneity of the independent variables.
Our outcomes provide supportive evidence that internal and external
conflicts, socioeconomic conditions, corruption, military in politics,
religious tensions, ethnicity tensions, and poor quality of bureaucracy
worsen food security in developed and developing countries. While
government stability, the role of law and order, democratic accountability,
and investment profile affect the food supply positively and significantly.
Current Research in Nutrition and Food Science
www.foodandnutritionjournal.org
ISSN: 2347-467X, Vol. 08, No. (3) 2020, Pg.
CONTACT Abdullah abdullahtanawli@gmail.com school of Statistics, Dongbei University of Finance and Economics, Dalian,
Liaoning 116025, China.
© 2020 The Author(s). Published by Enviro Research Publishers.
This is an Open Access article licensed under a Creative Commons license: Attribution 4.0 International (CC-BY).
Doi:
Article History
Received: 22 August
2020
Accepted: 12 November
2020
Keywords
Dynamic Panel Data;
Food Security;
Institutions;
Political Risk.
Introduction
Reducing the number of people suffering from
severe food insecurity has improved significantly
over the past decades. Many countries still have
severe food insecurity, whether they are developing
or developed countries.1–4 As the Food and
Agriculture Organization (FAO) found, 800 million
people are hungry and an extra population burden;
globally, it is challenging to eradicate hunger.5 Food
insecurity has an extreme effect on health, individual
2
productivity, overall economic growth of the region,
social peace, and general for learning.6–8 A current
study drafted by Food and Agriculture Organization
(FAO), the World Health Organization (WHO),
the United Nations Children Fund (UNICEF), the
World Food Program (WFP) and International Fund
for Agricultural Development (IFAD), more than
820 million people suffer from chronic malnutrition
in the world, which was 804 million malnourished
people in 2016.9,10 Political instability, sectarian
violence, and conflicts exacerbated the problem
of hunger and eventually brought food security
to a critical juncture.9 Therefore, the FAO every
year on 16 October, celebrates World Food Day
to raise global awareness about food security and
hunger and that emphasizes the need to keep food
security problems at the top of the international
research agenda and political plan, and to generate
a conducive environment for increasing food security
through proper investing and well policies.11
Food security term originates from the 1970s global
food crisis.12 It is a flexible conception that has
been changed from time to time, representing the
reconstructions of official thought on food security.12
Based on the Committee on World Food Security
(CFS) and Food Agricultural Organizations' (FAO)
existing food security definition is. "Food security
happens when all people have physical, social, and
economic access to adequate, secure and nutritious
food at all the times that satisfy their nutritional
needs and food preferences for an active and
healthy life." According to this definition, four pillars
of food security are adapted: food availability, food
accessibility, food utilization, and food stability.13,14
In this study, food security is evaluated in terms of
food availability. One of several factors suggested
by FAO is utilized.14 The dietary energy supply
kilocalories per day per capita is used to measure
food availability. Therefore, in this study, food security
is measured by dietary energy supply (DES) (kcal/
day/capita). The DES is an essential pillar of food
security.14
Previous studies have identified many significant
reasons for food insecurity, such as rapid population
growth,15–18 loss of arable land,19–22 and income
(GDP).17,23 With the level of food production not
being able to sustain the growing number of people,
which is reducing the arable land due to industry, and
because of low incomes, it has caused persisting
food insecurity in meeting human and nutritional
requirements.a,18,24
Despite numerous studies highlighting the
commitment to food security, one factor remains
to be given more attention, Mainly due to the high
quality of political risk data. This study focuses
on several aspects of political risk and seeks to
identify the factors of the political risks that are most
important to food security.b Logically, it should be
noted that political risk has a significant negative
effect on food security in countries; uncertainty in
food security comes due to several factors of high
political risks and worsening political institutions,c
such as incompetence in government bureaucracy
and corruption, unemployment and poverty (high-
socioeconomic conditions), religious and ethnicity
tension, internal and external conflicts, and when
military involves in politics. It is clear that these factors
also lead to political instability, which plays a dirty role
in increasing the country's food insecurity level and
poverty.25,26 In addition, other factors of political risk
and institutions play a vital role in increasing the level
of Dietary Energy Supply (DES), such as democratic
accountability and the rule of (law and order), to
enhance both measures of nutrition security and
food. Good governance is strengthened by strong
democratic institutions that elevate transparency
and accountability, and that's why food security
levels and economic growth increase. For instance,
the prohibition of corruption, strong democratic
accountability, law, and order, government stability,
play an important role in facilitating child malnutrition
and reducing their stunting.27
a Apart from population growth, arable land, and income, recently, Trade openness.67,84,85 Its importance has also been
confirmed. Details are available in the Literature Review section
b The political risk is defined as the possibility that political events in a country will affect the business environment and that
investors will not make as much money as expected,86 which does not help raise the level of food security.
c In our analysis, food insecurity is a problem in most of the countries where there is high political risk and political institutions
do not do their job properly, and where there are better institutions and less political risk, Dietary energy supply and food
security are more stable. Details are available in “Appendix C”.
3
The level of food security may decrease due to high
political risk and weak institutions. As can be seen in
the historical trend of political risk and Dietary energy
supply, it is presented in Figure 1. d That high political
risk and weak institutions could threaten countries'
food security levels and eventually increase food
insecurity levels, and the level of hunger can become
more worsening. However, a limited study is formally
available to address this issue, and this study may
be among the first to measure the effect of political
risk and institutions on food security.
The purpose of this article is to inspect an extensive
range of political risk components and to point out
the significance of these political risk components for
food security. We explore the effects of government
stability, conditions of the socioeconomic, investment
profile, the military in politics, religious tension,
ethnic tensions, external conflicts and internal
conflicts, corruption, law and order, the Quality of
Bureaucracy, and democratic accountability; On
the level of food security in 124 developed and
less developed countries (Appendix A). Some
components of these political risks have also been
related to political institutions quality. Above all,
the quality of bureaucracy is closely related to
the strength of institutional of a particular country.
Similarly, ensuring law and order and reducing
the level of corruption are important determinants
(and implications) of better institutions. These
effects comprise the related sub-components of
"Good Governance" overall assessment.30 In a
similar context, Greif and Kingston argued that an
institution's quality is often described as formal sets
(For example, rules, laws, order, and constitutions),
and informal constraints (For example, norms of
behaviours, conventions, and self-imposed codes),
that jointly motivating regularity in person and social
behavior.31,4 In this study, we utilize the dietary energy
supply indicator of food security, a dynamic panel
regression model was adopted, which is conducive
to assessing the impact of long-term policy reforms
for food security.4,32,33 A dynamic panel data model
with the generalized method of moments (GMM),
the approach was employed to account for potential
endogeneity, autocorrelation, omitted variable bias
and unobserved heterogeneity of the independent
variables.34–36
The rest of the paper is organized as follows:
review past studies is in the next section, the
variables and data set used in the regression model
are presented in section 3, section 4 provides
Methodology, including estimation strategies and
model specification, the empirical results and its
explanation stated in section 5, and finally, section
6 conclude the article.
Fig.1: Political risk and dietary energy supply of 124 developed and
developing countries between 1984 and 2018. The data source of DES and political
risks are the Food and Agriculture Organization Corporate Statistical Database
(FAOSTAT) and the Political Risk Service (PRS) group.28,29
d In Figure.1, the political risk index is measured by the average, first, we indexed all the 12 political risk indicators,68,87–89
then we measured it by the average (and then finally, assessed on a scale from 1 to 5, with higher values indicating less
political risk and better institutions.68 while the Dietary Energy Supply (DES) in terms of kilocalories per capita per day, is
also measured by average, which is used as a proxy for food security.43,63,65–67
4
Literature Review
There are several factors that have been found as
critical to food security based on given theories.
According to Malthusian theory, food shortages
are caused by overpopulation.37 that is why food
insecurity occurs for a long period of time. In simple
terms, the population grows faster than humanoid
substances, such as food and agriculture products.
By empirical analysis of Brown, Master, and Tian,
more food demand increases after an increasing
abundance of people and contributes to inadequate
food to feed the whole population.15,38,39 For example,
water and land use rise significantly in many
Populations; as a result, the capacity of farming
production is affected.38 Likewise, Tian claimed that
rapid population growth has significantly affected
food availability and has lead to food insecurity,
mostly in central South and northern America,
Southeast Asia, and sub-Saharan Africa.39 As time
went on, the Malthusian theory began a revitalization
in the form of Neo Malthusian. Considering the
original Malthus, the Neo Malthusian only adds
to the classic Malthus theory that in addition to
population size, the arable land is too considered
a vital source of food security. Liu and Schneider
have been identified that the arable land is more
important for food security and food production.21,40
A real examplar of this would be the industrialization
in China, which has occupied a large amount of land
to the detriment of agricultural activities.40 Therefore
the arable land is the most important of farming
activities; without the arable land, it is impossible to
secure food production.21 In short, Malthus classical
theories and Neo Malthusian show that population
growth and arable land play a key role in meeting
the requirement for food.
The Food Entitlement Declaration (FED) theory
suggests that food shortages are caused by a lack
of privileges, indicating that certain groups of people
do not have access to adequate food.41 FED's theory
raises concerns about food access, or it can be
called a demanding aspect of food security. In these
aspects, the third indicator that needs to be verified
for food security is income. Pingali, in this aspect,
emphasizes that economic access to food has been
proven by growing their ability to buy home-made
protein and nutritious food from income.42 There
will be more food in the house when the house
has more income, and vice versa. Therefore, under
the strategy to reduce appetite and malnutrition by
meeting dietary requirements and food preferences
for an active and healthy life, higher income levels
(i.e., provide more jobs or a better political system)
is compulsory.
The fourth factor that needs to be verified for food
security is trade openness. Hanie and Pangaribowo
in this context argued, that increasing trade openness
in a country could result in a rise in the total amount
of food available to the national population and
a variety of foods available to help increase food
security.43,44 Globally, international trade can link food
production and consumption and thus play a key role
in enhancing food security; because it allows global
production to take place in regions that are suitable
for it and is able to supply food from countries that
have abundant food supplies.45 Dithmer empirically
examined that the trade openness influence on food
security is positive and statistically significant, and
calorie consumption trade openness also increases
food quality and food diversity-related aspects of food
security.32 Biniaz also empirically measured the effect
of trade openness on agriculture has food security
levels increasing positively and significantly.46
Consequently, for a 1 percent increment in the
degree of agricultural trade openness, the long-term
growth in the food security index would increase by
0.21 percent.46
It should be noted, so far, no research has examined
the combined effect of all 12 indications of political
risk (and institutions) on food security.e However,
some studies have checked the relationship
of some of these indicators with food security.
Helal globally checked that food insecurity
had increased significantly in countries facing
corruption.47 Corruption hinders social and economic
development, negatively affects international and
regional development agencies' efforts to combat
hunger and famine in a systematic way, and disrupts
market operations.48 Helal and Uchendu clearly
stated that corruption thrives in societies when there
are failures in governance or weak government
e These are all political indicators (government stability, democratic accountability, religious and ethnic tension, socioe-
conomic condition, external and internal conflict, investment profile, corruption, law and order, military in politics, and
the quality of bureaucracy), a complete description of each political indicator is available in “Appendix B” and Table 1.
5
institutions.47,48 Due to weak political institutions and
bad governance, it leads to high-level corruption
and rapidly decreases food security. In this regard,
Zhou argued that the political institution's quality is
considered an essential component in promoting
a conducive environment that plays a crucial role
in food security.49 He further claims that apart from
Political institutions, any country's food security
could not be better and argued that food security
is a high level in a country where these institutions
work correctly. And where the food insecurity is
high level, these institutions don't work correctly.
In this context, Smith claims that the government's
four aspects, the prohibition of corruption, strong
democratic accountability, political stability, law, and
order, play a vital role in facilitating child malnutrition
and reducing their stunting.27 Government efficiency,
political stability, democratic accountability, and the
rule of law and order enhance both measures of
nutrition security and food.4,50
Good governance is strengthened by strong
democratic institutions that elevate transparency and
accountability, and that's why food security levels and
economic growth increase.50 In the same way, due
to bad governance and rampant corruption, conflicts
are arises within the country or between countries,
which is the biggest threat to food safety.51–53
For instance, more than 60 percent of the world’s
hungry and 75 percent of the stunted children under
age five live in conflict-affected countries, while these
alarming statistics indicate the adverse effects of
conflict on food security.54,55 Conflicts are caused not
only by poor governance and widespread corruption
but also by religious and ethnic tensions.56 Fox said
that religion and ethnicity tension had been a major
cause of internal conflicts (for example, civil disorder
or political violence, civil war, terrorism), which play
a significant role in destroying a country's food
security.56,57 In this context, Brinkman argued that
food insecurity arises, especially when food prices
rise, and this increase is due to the increased risk
of democratic breakdown, protests, civil war, and
sectarian strife.58 Further, Mauro and Montalvo
claim that religious polarization does not directly
affect economic development but is important in
explaining investment rates, government spending,
and the potential for civil war.59,60 However, ethnicity
tension directly affects economic growth and is also
important in explaining the potential for civil war.60
So, the concluding remarks from the above past
studies, that political stability and institutional reforms
are essential for the country to attain a stable food
supply and thus enhanced long-term food security,
while the political conditions and general social and
economic affect undernutrition (the fundamental
causes in Figure 2).43,49,61
Variables and Data
We used a panel sample of 124 countries (developed
and developing) throughout 1984-2018.f Our main
goal is to examine the political risk and institution's
influence on food security. We have taken data
of all the variables from three main sources,
the dependent variable taken from Agriculture
Organization Corporate Statistical Database
(FAOSTAT).29 Information on political risk and
institutions have taken from the International Country
Risk Guide (ICRG) provided by the Political Risk
Services (PRS) Group,28 and the World Bank (WB)
provides the information about control variables.62
We have measured the level of food security
through the Dietary Energy Supply (DES) in terms
of kilocalories per capita per day (kcal/capita/day).
Information on the dietary energy supply, provided
by (FAOSTAT),29 which is the largest global dataset
available for this kind of data.
Measuring food security can be difficult, given
the many components that affect food supply and
demand, and which ultimately helps determine if an
individual has adequate access to food that will meet
their nutritional needs. It’s complicated to estimate
the quantity of food an individual or each household
consumes at the macro level almost impossible.
It is necessary that appropriate alternative action
or proxy is mandatory. Therefore, this research
work will depend on an aggregate measure that
captures the available Dietary Energy Supply
(DES) in terms of (kcal/capita/day). The (DES) is
an important component of food security in the
literature used.43,63–67 This measure is calculated by
the country’s total food supply, which is available for
domestic consumption and is distributed by the size
of the population to reach per capita.
f Countries not included in this study due to lack of data, the countries covered in this article are in the ‘'Appendix A.
6
g The detailed descriptions of political risk components are available in Appendix B, also available in in the international
country risk guide methodology.68
h In the ICRG methodology, the first 5 components of political risk are scale from 0-12 and the first 6 of the last 7
components are scale from 0-6. The last one bureaucracy quality is a scale from 0-4.
i Some scholars as Harms, Rodrik, Busse, and Hayakawa have used these components (political risk and institutions)
in their study.90–93
Source: Maternal and child undernutrition: global and regional exposures and health consequences.61
Fig.2: A Conceptual Undernutrition Framework
The data used for political risk and institutions in this
study are taken from the International Country Risk
Guide (ICRG) provided by the Political Risk Services
(PRS) group.28 The ICRG delivers information
regarding the political institution and political risk.
The political risk and institutions indicator comprises
a total of 12 subcomponents. The detail information
is available in Appendix B.g Each component is
allotted a numerical value within a specified range
from 0 to 100, is then divided into categories,h,.68
with low values representing the weak political
institutions and high political risk country while high
value representing the better political institution and
less political risk country. In general, these indicators
of political risk and institutions are extensively
recognized and used as political risk and high-quality
institutional measures.i
7
Table 1. Source of the Data and explanations of variables
Symbols Variables Explanations Source
Dependent variable
FS Food security the food security level assessed through the Dietary FAOSTAT
energy supply (DES) in terms of (kcal/capita/day).
Control variables
POP Population growth The annual population growth rate in percentage World Bank
AL Arable land agricultural land as a percentage of the total land World Bank
GDP Gross domestic GDP per capita in constant 2010 US dollar World Bank
product
TO Trade openness Trade as a percentage of gross domestic product (GDP) World Bank
Political variables
GST Government stability Sum of government unity, legislative strength, PRS Group
popular support, (scale 0 to 12)
SEC Socioeconomic Sum of unemployment, consumer confidence, poverty, PRS Group
condition (scale 0 to 12)
INVP Investment Profile Sum of contract viability/expropriation, profit repatriation, PRS Group
payment delay, (scale 0 to12)
INTC Internal conflict Sum of coup threat /civil war, political violence/terrorism, PRS Group
civil disorder, (scale 0 to 12)
EXTC External conflict Sum of war, foreign pressures, cross border conflict PRS Group
(scale 0 to 12)
CORR Corruption Corruption level, (0 to 6 scale) PRS Group
MINP Military in politics The influence of the military in politics, (0 to 6 scale) PRS Group
RELT Religious tensions Tension in religious groups, (0 to 6scale) PRS Group
LAO Law and order Sum of law and order, (0 to 6 scale) PRS Group
ETNT Ethnic tensions Tension in ethnic groups, (0 to 6 scale) PRS Group
DEMA Democratic the government Democratic accountability (0 to 6 scale) PRS Group
accountability
BURQ Bureaucracy Quality of the Bureaucracy and institutional PRS Group
quality strength, (0 to 4 scale)
Source: FAOSTAT stands for food and agricultural organization corporate statistical database, PRS Group
stands for the political risk service group and World Bank.28,29,62
The first one in all the control variables data that
world bank provided is the Population (POP) which
measured in terms of annual population growth
rate.62 The second one is Arable Land (AL) as a
percentage of total land size (the size of the land
is a proxy that can be plowed and used to grow
crops). The third one is income denoted by the
Gross Domestic Product (GDP). And the last one is
Trade Openness (TO) an overall country's exports
and imports are measured as a percentage of the
country's GDP.
The explanation and source of all variables are
available in Table 1 and the symbols used for the
empirical purpose.
8
Table.2: Descriptive Statistics, 1984-2018
Variables Obs Mean S.Dev Min Max
FS 4340 2747.489 505.619 1241 3828
POP 4340 1.512 1.407 -7.09 15.18
AL 4340 16.198 14.541 -0.42 73.39
GDP 4340 12076.47 16356.39 164.192 92119.52
TO 4340 75.804 44.07 0.02 442.62
GST 4340 7.114 2.553 0.00 12.00
SEC 4340 5.332 2.477 0.00 11.00
INVP 4340 7.054 2.872 0.00 12.00
INTC 4340 8.356 2.991 0.00 12.00
EXTC 4340 9.208 2.898 0.00 12.00
CORR 4340 2.779 1.427 0.00 6.00
MINP 4340 3.566 1.914 0.00 6.00
RELT 4340 4.340 1.651 0.00 6.00
LAO 4340 3.423 1.595 0.00 6.00
ETNT 4340 3.765 1.584 0.00 6.00
DEMA 4340 3.703 1.776 0.00 6.00
BURQ 4340 2.032 1.204 0.00 4.00
Table 2 provides information about the summary of
statistics which include total observations, mean,
minimum, maximum, and standard deviation values
of each series earlier transformation into logarithm
form.
We have already stated that our purpose was to
inspect the effect of political risk, institutions on food
security, assessed by dietary energy supply (DES),
in terms of (kcal/day/capita) through a dynamic panel
(GMM) generalized method of moment approach.
According to the prior studies of Subramaniam
and Masron, we used the following econometric
structure.4,69
Methodology
Malthusian and Neo-Malthusian, emphasize in their
theory that the main reason for food insecurity in the
presence of more people than the quantity of food
supply.37 Malthus claims in its theory that the leading
cause of food insecurity is the rapid population
growth.37 Everything in the world progresses over
time. Similarly, progress has been made in the
classical Malthusian theory, which is called by the
name of Neo-Malthusian theory. The Neo-Malthusian
approach is that food insecurity occurs due to limited
and finite land.70 It is a common argument that as
the population grows, the demand for food increases
and the use of arable land also increases. Hence the
basic food security equation can be written as follow.
FSit = α0 + β1 POPit + β2ALit + εit ...(1)
Where FS denotes the food security assessment by
dietary energy supply, POP stands for population
growth, and AL represents the Arable land. The
food consumption or demand determined by many
variables such as trade openness (TO), and income
(GDP).32,39,42,67 Hence the food security function can
be rewritten as follow.
FSit = α0 + β1 POPit + β2ALit + β3 TOit + β4GDPit + εit
...(2)
A country’s food insecurity cannot be eradicated
unless its better institution quality and less political
risk. The political risk and institution are the most
important in affecting countries' food security.4,43,49
Zhou and Pangaribowo in this regard claim that apart
from better institutions and less political risk, the
9
j The null hypothesis (H0) of [AR (1)] is equal to no 1st order serial correlation, while the null hypothesis of the [AR(2)] is
equal to no 2nd order serial correlation.
food security of any country could not be better.43,49
So, to finalize the econometrics model by incorporating
the political risk and institutions variable.
FSit = α0 + β1 POPit + β2ALit + β3 TOit + β4GDPit +
β3POLITICALit + εit ...(3)
where i=1……124,t=1……35, ε ~N(0,σ2)
Where POLITICALit is indicating political risk and
institution of the 12 indicators. In the final model,
the estimated parameter is α and β while the error
term is ε. The subscript i indicates the countries and
t denotes time-period for each country. Further, to
transform all the variables into a logarithm. Then
Equation (3) can be written as follows.
lnFSit
=α+βlnXit+εit
...(4)
Where lnFS is the log form of food security, the set of
the explanatory variables is X, including population
growth, arable land, income, trade openness, and
political risk and institution. The nature of our data is
a panel. So, according to Arellano and Blundell, we
adopt a dynamic panel (GMM) generalized method
of the moment.34,35 To inspect the effect of political
risk and institutions on food security for the cross-
section of countries. For the potential endogeneity
of explanatory variables, the GMM plays a vital role.
Hence, Equation (4) can be seen in the form of a
dynamic panel regression model.
lnFSit = δlnFSit,t-1 + βlnXit + μi + εit ...(5)
Where εit is the disturbance or error term,while μi
denotes the country-specific effect unobservable.
To avoid unobservable μi we followed the role of
Arellano the role is to take the first difference-GMM
of Equation (5).34 Then we have a new equation
becomes.
lnFSit - lnFSit ,t-1 = δlnFSit ,t-1 - δlnFSit ,t-2 + βlnXit - βlnXit ,t-1
(lnFSit - lnFSit ,t-1) = δ(lnFSit ,t-1 - δlnFSit ,t-2) + β(lnXit -
βlnXit ,t-1) + (εit-εit-1) ...(6)
According to Arellano, the lag explanatory variables
use in level as the instrument.34 Because the above
Equation (6) produces a correlation among the
lagged explained variable and the new error term.
And because of this correlation (lnFSit,t-1 - lnFSit,t-2
and εit - εit - 1) we have the problem of endogeneity.4,69
To solve this problem, we should need to follow
another estimator called System-Generalized
Method of Moments (GMM).35 The System-GMM
constructed from the estimation of a structure of two
simultaneous Equations, one in first difference (with
lagged level as an instrument), and the other in level
(with a lagged first difference as an instrument). This
two-moment condition as follows:
E[Xi t-s (εit - εit - 1)] = for s≥2; t=3……T and
E[FXi t-s (εit - εit - 1)] =for s≥2; t=3……T
The System-GMM is a more accurate estimator in
a dynamic panel data model than estimator first
difference-GMM.35 Additionally, in the generalized
method of moment approach, the scaler p-value
is utilized to comparison high-quality (superiority)
among the System-GMM and the first difference
GMM.35 Furthermore, we consider two kinds of test
statistics to justify the validity of the GMM estimator.
Hansen and the serial correlation test. The first one
Hansen test is utilized to inspect the validity of the
generalized method of moment estimator.71
The second for the serial correlation properties test
is [AR(1)] and [AR(2)].j,34 For further specification,
Arellano and Blundell have told that a good estimate
of the lag-dependent regressor should fall in the
range of its fixed effect and pooled OLS.34,35 Thus
these estimates test a useful solidity on the results.
Empirical Results
The level of the food security, measured through
dietary energy supply (DES), in the 124 countries of
the world, were lower in Yemen, Ethiopia, Uganda,
Guinea-Bissau, Bangladesh, Niger, Pakistan,
Armenia, Azerbaijan, Guinea, Nigeria, Moldova, Iraq,
Croatia, Kenya, Tanzania, Malawi, Mozambique,
Zambia, Zimbabwe, Congo, Angola, Namibia,
Botswana, Madagascar, Togo, Liberia, Sierra Leone,
Bolivia, Nicaragua, Haiti, Mongolia, Burma, and
higher in Japan, Australia, New Zealand, Finland,
Sweden, Netherlands, Iceland, united states,
Canada, Ireland, Portugal, France, Italy, Switzerland,
10
Fig.3: the food security level in 124 countries has a geographical distribution
k We have mapped it after extracting the average of the Dietary energy supply from 1984 to 2018.
l those 20 countries whose food security level have decreased by high political risk and weak institutions, are in the
“Appendix C”.
Austria, Germany, Poland, Denmark, Norway,
Greece, Turkey, Israel, and Egypt (see Figure.3)k.
Countries with low food security levels among them
are 20 countries whose low food security level is
due to high political risk and weak institutions are
three from eastern
Africa, seven from western Africa, one from south-
eastern Asia, two from southern Asia, four from
western Asia, one from the Caribbean, one from
eastern Europe,l and one from southern Europe .
Before the average dietary energy supply (DES),
The lowest level of DES (1241(kcal/capita/day) in
1984) was in Ethiopia. At the same time, the highest
level of dietary energy supply (3539 (kcal/capita/day)
in 1984) was in Ireland. Regarding the political risk
rating, Yemen had the lowest level with 2129 DES
(kcal/day/capita) in 2018, In contrast, the United
states of America had the highest level with 3828
DES (kcal/day/capita) in 2018.
In Table 3. We summarized a correlation matrix
results of the key variables.72 All the 12 components
of the political risk and institutions have a positive
and strongly significant correlation with food security.
Besides that, (GDP, TO, AL) is also significantly
and positively correlated with food security, except
populace growth (POP) has a negative and highly
significant relations with food security (FS), which
confirms the current literature that determines food
security.
In general, we guess all 12 components of the political
risk and institutions to be positively connected to the
food security since better political institutions, and
less political risk may be expected to rise the food
security level. Nevertheless, we do not know the
exact result of these factors on the food security level.
It can also happen as have said that Falk and Miller,
that the path coefficient (regression coefficient) and
the correlation among latent constructs do not have
the same sing, the original relations among the two
has been suppressed.73
So, we utilize the estimation of a System-GMM
method to estimate Equation (5) for the 124 countries
using panel balanced data from 1984-2018. In our
study, four different estimation methods used to
compare the results, such as Pooled-OLS, Fixed-
effect, Difference-GMM, and System-GMM. The
estimated results of all these regression models are
presented in Table 4.
For the robustness and validity of the result of the
System-GMM, we followed the roles of Arellano
and Blundell, and Bolarinwa has used this role in
his study, that the coefficient of the natural log of
lagged dependent variable (lnFSt-1) of the System-
GMM falls in the range of coefficient of (lnFSt-1)
of the Pooled-OLS and the coefficient of (lnFSt-1)
of the Fixed-effect model.34,35,74 In our study, in
Table 4, the lagged food security of the System-GMM
has occurred between the coefficient of the lagged
food security of Pooled-OLS and the Fixed-effect
model. That is, 0.65<0.80<0.88. therefore, the validity
of the System-GMM model is confirmed.
11
Table 3: Correlation Matrix
FS POP AL GDP TO GST SEC INVP INTC EXTC CORR MINP RELT LAO ETNT DEMA BURQ
FS 1
POP -0.404*** 1
AL 0.154*** -0.322*** 1
GDP 0.622*** -0.194*** -0.0727*** 1
TO 0.164*** -0.123*** -0.0616*** 0.146*** 1
GST 0.169*** 0.0748*** -0.133*** 0.168*** 0.0706*** 1
SEC 0.519*** -0.0967*** -0.114*** 0.639*** 0.157*** 0.443*** 1
INVP 0.404*** -0.0562*** -0.0984*** 0.462*** 0.194*** 0.681*** 0.701*** 1
INTC 0.354*** -0.118*** -0.0885*** 0.385*** 0.160*** 0.664*** 0.628*** 0.666*** 1
EXTC 0.195*** -0.0238 -0.104*** 0.243*** 0.0595*** 0.642*** 0.530*** 0.620*** 0.807*** 1
CORR 0.380*** -0.107*** -0.0884*** 0.583*** 0.0265 0.353*** 0.649*** 0.465*** 0.587*** 0.516*** 1
MINP 0.506*** -0.245*** -0.0664*** 0.553*** 0.220*** 0.420*** 0.671*** 0.632*** 0.712*** 0.591*** 0.646*** 1
RELT 0.127*** -0.154*** -0.157*** 0.258*** 0.0364* 0.463*** 0.474*** 0.484*** 0.674*** 0.657*** 0.505*** 0.552*** 1
LAO 0.494*** -0.165*** -0.00992 0.597*** 0.125*** 0.539*** 0.700*** 0.616*** 0.766*** 0.614*** 0.718*** 0.717*** 0.525*** 1
ETNT 0.315*** -0.105*** -0.119*** 0.298*** 0.0531*** 0.530*** 0.498*** 0.495*** 0.723*** 0.632*** 0.488*** 0.551*** 0.600*** 0.612*** 1
DEMA 0.409*** -0.218*** 0.0188 0.477*** 0.0601*** 0.401*** 0.549*** 0.635*** 0.626*** 0.593*** 0.624*** 0.680*** 0.504*** 0.613*** 0.458*** 1
BURQ 0.551*** -0.200*** -0.0449** 0.671*** 0.112*** 0.389*** 0.739*** 0.616*** 0.607*** 0.510*** 0.725*** 0.714*** 0.424*** 0.719*** 0.468*** 0.687*** 1
Note: if the value of (P<0.01) then ***, if the value of (P<0.05) then **, and if (P<0.1) then *. FS. Stands for food security; POP stands for the population growth; AL stands for arable land;
GDP indicates the gross domestic product; TO stands for trade openness; GST stands for government stability; SEC stand for socioeconomic; INVP stand for investment profile; INTC
stands for internal conflict; EXTC stand for external conflict; CORR stand for corruption; MIN stand for the military in politics; RELT stand for religious tension; LAO stand for law and order;
ETNT stands for ethnic tension; DEMA stand for democratic accountability, and BURQ stands for bureaucracy quality.
12
Table 4: Regression Models (Static and Dynamic Panel Model), 1984-2018
Variables Pooled OLS Fixed-Effect Difference-GMM System- GMM
Dependent Variable
LnFSt-1 0.879*** 0.652*** 0.461*** 0.797***
-139.12 -62.85 -35.33 -79.1
Control Variables
lnPOP -0.048*** -0.022*** -0.016*** -0.036***
(-8.26) (-3.02) (-9.49) (-10.53)
lnAL 0.007*** 0.075*** 0.044*** 0.014***
-4.76 -9.57 -7.63 -6.11
lnGDP 0.008*** 0.046*** 0.080*** 0.013***
-7.78 -14.89 -34.9 -8.81
lnTO -0.001 0.013*** 0.004** 0.012***
(-0.35) -4.51 -2.46 -7.2
Political Variables
lnGST 0.036*** 0.020*** 0.003 0.010**
-5.3 -2.96 -1.08 -2.52
lnSEC -0.021*** -0.009 -0.003 -0.022***
(-3.06) (-1.16) (-0.60) (-3.68)
lnINVP 0.012* 0.016** 0.008*** 0.095**
-1.74 -2.11 -3.06 -2.38
lnINTC -0.025*** -0.058*** -0.111*** -0.079***
(-2.95) (-6.72) (-10.97) (-9.66)
lnEXTC -0.027*** -0.035*** -0.098*** -0.100***
(-3.67) (-4.20) (-8.37) (-10.42)
lnCORR -0.031*** -0.032*** -0.052*** -0.052***
(-3.31) (-3.00) (-3.86) (-7.29)
lnMINP -0.014* -0.007 -0.023*** -0.049***
(-1.92) (-0.70) (-2.91) (-7.86)
lnRELT -0.057*** -0.047*** -0.111*** -0.054***
(-7.43) (-4.07) (-5.84) (-3.07)
lnLAO 0.011 -0.001 0.019 0.059***
-1.14 (-0.11) -1.12 -2.98
lnETNT -0.033*** -0.043*** 0.025 -0.113***
(-4.12) (-3.53) -1.5 (-7.19)
lnDEMA -0.01 -0.005 0.109*** 0.030***
(-1.37) (-0.55) -11.04 -3.13
lnBURQ -0.011 -0.043*** 0.007 -0.030**
(-0.96) (-3.07) -0.23 (-2.31)
Hansen Test 108 109
AR (1) -7.61*** -7.85***
AR (2) -0.4 -0.15
Note that: if the value of (P<0.01) then ***, if the value of (P<0.05) then **, and if ( P<0.1) then
*, The Value Of t-statistics In (), The AR And Hansen Test Value Is Stand for The P-Value. A
Two-Step Estimates the Models System-GMM and Difference-GMM Both.
13
Further, the coefficient of the (lnFSt-1) of the
Difference-GMM not good because the value of
(lnFSt-1) is out of the (0.65, 0.88). Arellano and
Blundell in this context stated that, if the coefficient
estimate of the (lnFSt-1) of the Difference-GMM lies
below or close to the Fixed-effect estimate, it biased
and downwards34,35. So, we, therefore, believe that
the System-GMM estimate of the dynamic panel
data is more appropriate than Difference-GMM
among food security. Besides that, all the variables
are mostly strongly significant in the System-GMM,
since it is neither in the Difference-GMM nor in the
rest of the other regression models.
The descriptive tests of the System-GMM estimators
mentioned under Table.4 propose the eligibility of
System-GMM estimators. The criteria for serial
correlation [AR (1)], which accepted the alternative
hypothesis (H1) that is the first-order autocorrelation.
While [AR (2)] accepted the null hypothesis (H0)
that is the no second-order autocorrelation. About
instrument validity, Hansen test statistic presents
that the instruments used are valid.
The outcomes of the estimated model, as shown in
Table 4, are in line with our expectations that the level
of food supply declined with the growing populace.
The statistically significant and negative value of
population growth (POP), the level of food security
has been shown to decrease by 3.6%, with a 1%
increase in population. From the consequences,
we can confirm according to prior studies, that
inadequate food supply is a major factor in population
growth, leading to hunger.4,18,32,38,69
As expected, also, the statistically significant and
positive value of trade openness (TO) showed a
positive influence on food security. As trade grows,
so improves a country's food security level. Thomas,
Dither, and Fusco have argued with reference to
this result that increasing food supplies can reduce
consumer prices, especially for developed countries,
making it easier to buy food products.32,67,75
Regarding agricultural land, we find that the arable
land (AL) variable has a statistically significant and
positive impact on food security. Negash, Swinnen,
Subramaniam, and Masron have stated with
reference to this outcome that the incrementation
in the food supply is due to the incrementation in
agricultural land.4,69,76 An interesting fact about the
enlargement of agricultural land is that as a means of
production, this land can provide maximum income
to the poor agricultural landowners whether the
government will help or not. So, in food production,
the arable land is the major factor in providing more
food resources. Our experimental results highlight
the status of the economic feature at the level
of food security. The coefficient among our food
security (proxied by Dietary Energy Supply) and the
explanatory variable (GDP) statistically significant
and positive. Therefore, the citizen of a country with
a high income have good access to quality food.67,69,77
Hence, having adequate income levels can help
individuals achieve adequate nutrition and energy
intake levels.
Moving to discuss our main points, as corruption
(CORR) indicate that increasing the level of
corruption strongly negatively affects the food
security level. This result is in line with the results
reported by food and agricultural organization in
2018, who argue that the main reason for corruption
is that 196 million people in India suffer from chronic
Malnutrition.9 However, we are able to verify food
and agricultural organization results in dynamic
regression analysis. The coefficient between
our independent variable (Bureaucracy) and the
dependent variable (Dietary energy supply) was
negative and significant. Therefore, Malnutrition
and food insecurity in India due to widespread
instability in government bureaucracy and due to
weak political institutions.9,49,78 9,78 Weak institutions
would increase food insecurity in the country, so the
food security level is greatly affected by the level of
Bureaucracy.49,79
Our results further confirmed that the statistically
significant and negative value of the external-conflict
(EXTC) Indicates that food and nutrition insecurity
is becoming increasingly concentrated in external
conflict-affected countries. As a result, between
2015 and 2018, the figure of malnourished people
improved by 23.4 million - a significant increase
compared to non-conflict countries.10 Our results
further indicate that the internal conflict (INTC)
is the leading cause of food insecurity. Hendrix
and FAO in this aspect, clearly stated that civil
disorder or political violence, civil war, terrorism
is a vital factor behind severe food insecurity and
14
high food prices.9,53 One hundred and twenty-four
countries sample are included in our study, most
of which are developing countries. The majority
of malnourished people due to race, nationality,
or language division (ethnic tension) are found in
developing countries.10 Similarly, Religious stresses
can lead to the dominance of society and/or rule by
a one religious group seeking to change the civil
law to religious law and exclude all other religions
from the social and/or political process, and such a
religious group wants to supremacy (governance);
as well as pressure on religious freedom. And such
a religious group that also wants to implement its
identification apart from the whole country. Under
these circumstances, inexperienced people run the
government, which makes wrong policies that lead
to internal and external conflicts, which plays a vital
role in ruining food security.9,80
The negative sign and strongly significant coefficient
of the military in politics (MINP), showing that due
to the military in politics, the economic growth going
on to decreases.81 while economic growth plays a
vital role in enhancing the food security level and
reducing the food shortage especially of a developing
country.66,82 Further, a relevant and more beautiful
argument is given by David G. Acker, who has said
that in a democratic country there has never been a
famine in any era, Acker said that in countries with
multiple elections and dynamic, free media, there are
strong political incentives for famine prevention and
economic security freedom and the freedom to live.83
The contrary part of the above eight negative
and significant political indicators, in the two-step
System-GMM results, the sign of government
stability (GST), and law and order (LAO) positively
and significantly affect the food supply. It shows
that Good governance and better institutions are
considered an essential element in promoting a
conducive environment that plays a vital role to
national nutrition, food security, and economic
growth. The result of GST and LAO is in line with the
results reported by Ogunniyi, has argued that due to
political stability, government effectiveness, and the
rule of law had enhanced the level of food security
and decreased hunger.50 The significance level of
the GST and LAO estimated coefficient is at 5%
and a one % level. Next, the positive and significant
coefficient for democratic accountability (DEMA),
show that the level of democratic accountability
of the government is important over time for food
security. For instance, Smith argued that the role
of democratic accountability in facilitating child
malnutrition and national food availability is highly
positive.27 He also claims that the government
democratic accountability and four other components
of governance such as government stability,
bureaucracy quality, restraint of corruption, law and
order played essential facilitating roles in, safe water
access, child stunting, and food supply.
Conclusion
This study empirically examined the association
among food security and political risk and institution's
variables using dynamic panel data for 124 countries
from 1984 to 2018 in the global (Asia, Europe,
Africa, Latin America, and the Caribbean), based
on System- GMM, Difference-GMM, Fixed-Effect,
and Pooled-OLS models. According to the outcomes
of the System-GMM, we concluded that all factors
of political risk and institutions significantly affect
food supply, four of them (i.e., government stability,
the rule of law and order, investment profile,
and democratic accountability) affect the food
supply positively and significantly. Besides that,
socioeconomic condition, internal conflicts, external
conflicts, corruption, military in politics, and ethnicity
tensions, religious tensions, and bureaucracy quality
negatively and significantly affect food supply. Food
insecurity occurs when there are high-level political
risk and weak institutions. So, the conclusions of
this article that high-level political risk and weak
institutions are perilous for food security, which
ensures an unstable food supply.
Acknowledgements
We thank our respected reviewers and especially
to Wang Qingshi for their valuable comments and
suggestions that really helped us to improve this
paper.
Funding
We have not received any funding from any
organization.
Conflict of interest
The authors declare that there is no conflict of
interests regarding the publication of this paper.
15
Appendix A.
Developed and Developing Countries Sample
Albania Viet Nam Ukraine Turkey Armenia Hong Kong
Azerbaijan Austria Zimbabwe Panama Gabon United Arab Emirates
Israel Malaysia Bulgaria Burkina Faso Burma Colombia
Ecuador Cote d'Ivoire Bolivia Cameroon Guinea Suriname
Chile Croatia Russia Cyprus Czech Republic Denmark
Dominican Canada Hungary Nicaragua Malta Iceland
Republic
France Finland Belarus South Africa Germany Ghana
Peru Guatemala Congo Guinea-Bissau Netherlands Norway
Saudi Arabia Australia Egypt Ethiopia Poland Indonesia
Iran Tunisia Ireland Botswana Italy Jamaica
Sri Lanka Venezuela Kazakhstan Kenya Korea, Republic of Trinidad and Tobago
Honduras Nigeria Liberia Sierra Leone Madagascar New Zealand
Brazil Mali Estonia Angola Mongolia Morocco
Mozambique Namibia Guyana Malawi El Salvador Togo
Lebanon Haiti Uganda Pakistan Bangladesh Senegal
Greece Philippines India Portugal Republic of Moldova Romania
Cuba Latvia Paraguay Lithuania Slovakia Slovenia
Gambia Spain Japan Costa Rica Sweden Tanzania
Yemen Niger Kuwait Iraq Argentina Oman
Mexico China Switzerland United States Uruguay Jordan
Algeria Thailand Zambia Bahamas
16
Appendix B.
The detail explanation of political risk components
Political risk components Description
Government stability Measures the ability of government to put its policies into practice and
stay in government
Socioeconomic condition It affirms the social and economic pressures of those working in a society
that can hinder the functioning of the government or promote social
dissatisfaction and thus destabilize the political system. (poverty, unemployment)
Investment profile It is an estimate of components that affect investment risk that is not
included in other financial, economic, and political risk components.
Internal conflict It is an estimate of the real or potential effects of political violence on
governance in the country.
External conflict The external conflict measure is an assessment both of the risk to the
incumbent government from foreign action, ranging from non-violent external
pressure (diplomatic pressures, withholding of aid, trade restrictions,
territorial disputes, sanctions, etc) to violent external pressure (cross-border
conflicts to all-out war)
Corruption This is a measure of the level of corruption
Military in politics this is an estimate of the involvement of the army in politics. The army
joins the government when there are internal or external threats to the
country. But I don't think it's an excellent solution to such problems; it hurts
the country's economy
Religious tensions Religious tensions may stem from the domination of society and/or
governance by a single religious group that seeks to replace civil law by
religious law and to exclude other religions from the political and/or
social process; the desire of a single religious group to dominate
governance; the suppression of religious freedom; the desire of a
religious group to express its own identity, separate from the country as a
whole. The risk involved in these situations range from inexperienced
people imposing inappropriate policies through civil dissent to civil war
and external conflicts.
Law and order Gives legitimacy to law and order, i.e., the power and impartiality of the rule
of law.
Ethnicity tensions It is an estimate of the level of stress attributed to race, language division,
or nationality.
Democratic accountability It is related to the government's democratic accountability, that is,
the government's response to its peoples, but also about fundamental
civil freedoms and political rights.
Bureaucracy Quality The institutional strength and quality of the bureaucracy is another
shock absorber that tends to minimize revisions of the policy when
governments change.
Source: International Country Risk Guide (ICRG).68
17
Appendix C:
The Changes in Political Risk Rating and Food Security
Very High-level Political Risk countries Very low-level Political Risk countries
Changes 1984-2018 Changes 1984-2018 Changes 1984-2018
Countries PRIAVG FSAVG Countries PRIAVG FSAVG Countries PRIAVG FSAVG
Ethiopia 45.88 1795 Azerbaijan 34.80 2231 Japan 83.06 3285
Haiti 40.87 1925 Guinea 47.91 2185 Sweden 86.87 3291
Zimbabwe 49.43 2065 Nigeria 45.83 2088 Australia 83.84 3345
Burma 45.62 2067 Republic of 35.31 2223 New Zealand 86.62 3358
Moldova
Yemen 46.47 2110 Iraq 35.24 2038 Finland 89.58 3376
Sierra Leone 47.58 2151 Croatia 41.29 2243 Netherlands 87.01 3302
Togo 49.61 2176 Iceland 86.19 3279
Liberia 40.12 2204 Denmark 85.15 3316
Uganda 49.45 2222 Canada 85.10 3339
Guinea-Bissau 46.44 2157 Norway 87.24 3363
Bangladesh 48.00 2176 Switzerland 89.25 3406
Niger 49.89 2197 Ireland 83.83 3611
Pakistan 46.19 2200 Austria 85.93 3613
Armenia 33.55 2220 United States 82.46 3638
NOTE: PRIAVG, the political risk index is measured by the averagem, While FSAVG , food security is also
measured by the average of dietary energy supply. The higher value of PRIAVG indicating better institutions
and less political risk countries, while the higher value of FSAVG indicating high food secure country.
Source: Food and Agriculture Organization Corporate Statistical Database and the Political Risk Service
Group.28,29,68
m We first indexed all the 12 political risk indicators, according to international country risk guide methodology68, then we
measured it by the average.
18
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