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ENERGY SUPPLY, PUBLIC DEBT, AND ECONOMIC GROWTH
Author(s): Mohamed Awada, Moustapha Badran, Imtynan Khalifeh and Jules Sadefo
Kamdem
Source:
The Journal of Energy and Development
, Autumn 2022 and Spring 2023, Vol. 48,
No. 1/2 (Autumn 2022 and Spring 2023), pp. 233-258
Published by: International Research Center for Energy and Economic Development (ICEED)
Stable URL: https://www.jstor.org/stable/10.2307/27284861
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ENERGY SUPPLY, PUBLIC DEBT, AND ECONOMIC
GROWTH: CAUSALITY ANALYSIS FOR A PANEL
OF OECD EUROPEAN COUNTRIES
Mohamed Awada, Moustapha Badran, Imtynan Khalifeh, AND
Jules Sadefo Kamdem*
Introduction
Economists have focused on the importance of growth as it is considered a core
government objective and driver of living standards. Economic growth is
*Mohamed Awada earned his Doctorate in Economic Sciences from the University of Montpellier.
In his thesis, he examined the interrelationships between energy supply, public debt, and economic
growth as applied to a group of OECD European countries. His research interests include
macroeconomics, finance, and energy economics with a focus on European countries. His teaching
expertise covers several subjects including corporate finance, financial analysis, statistics,
microeconomics, macroeconomics, and financial mathematics.
Moustapha Badran earned his Doctorate in Economic Sciences from the University of Montpellier.
The author’s strong command and knowledge of the main financial and economic theoretical
frameworks have led to his earning multiple scholarships and awards. His research interests include
corporate finance, financial crises, and capital structure. He currently is at the University of Montpellier
as a temporary Teaching and Research Associate. His teaching expertise covers theoretical
econometrics, time series econometrics, macroeconomics, and microeconomics.
Imtynan Khalifeh is a Ph.D. candidate in Economics Sciences at the University of Montpellier,
specializing in Finance. She holds dual Master’s degrees in Banking and Financial Economics from the
Lebanese University and Banking and Finance from Limoges, establishing her strong academic
background. The author’s research centers around the impact of Basel III regulations on European
banks, showcasing her expertise in finance, banking, economics, and econometrics. Additionally, she
actively contributes to academia as a Lecturer of Statistics for Business at Montpellier Business School,
imparting her knowledge and fostering analytical skills among her students.
Jules Sadefo Kamdem is currently a Full Professor of Economics & Finance at the University
of Montpellier (UM). He previously was a Professor at the University de Guyane and Lecturer at UM.
(continued)
The Journal of Energy and Development, Vol. 48, Nos. 1-2
Copyright #2023 by the International Research Center for Energy and Economic Development
(ICEED). All rights reserved.
233
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strongly linked to production, energy, debt, the natural environment, and human
health. Therefore, countries must be aware of the essential role of economic growth
and its impact on economic development and global sustainability. The challenge
is how best to integrate these ideas into mainstream policies and consider how they
can be effectively implemented to support sustainability goals, which in our
research focus is within the context of Europe.
Today, the COVID-19 crisis and the Russian-Ukrainian conflict highlight the
importance of energy supply as an eco-political factor due to its role as a catalyst
for economic development and its implications on the worldwide economy via
public debt levels and inflation rates. The relationship between energy and eco-
nomic development has captured the attention of both researchers and academia
because of its crucial policy ramifications during the past decade. There have been
several studies undertaken to determine the causal linkages between energy and
economic growth applying various methods such as time-series analysis and panel
approaches especially after the seminal work of J. Kraft and A. Kraft in 1978,
which is considered as the starting point in this field. Energy plays a critical role in
an economy both on the demand and supply sides. On the demand side, energy is
one of the commodities that a consumer chooses to purchase to maximize his or
her utility. On the supply side, energy is an important input to production, capital,
human labor, and materials. In addition, energy supply is considered a vital factor
for the economic and social development of countries, where the countries that
produce the energy have a high probability of increasing both their economic
growth and living standards. Limiting energy supply can lead to negative effects
on a nation’s development and its economic growth.
1
An energy shortage and inad-
equate energy supply are essential factors that can adversely impact energy secu-
rity, economic and social welfare, and increase the costs of production and
transportation. The other topic that has been vigorously discussed in the literature
is the relationship between public debt expansion and economic growth, which has
grabbed the attention of many analysts during recent years stimulated by the sharp
increase in public debt after the 2008 financial crisis, especially in the Euro area.
Indeed, in response to the financial crisis, governments employed fiscal policies to
raise aggregate demand. The consensus among economists is that increases in pub-
lic debt in the short run, due to fiscal policies, will result in a boost to economic
growth. However, there are dissenting views about the long-term impact, some
After earning his Ph.D. in Mathematical Finance and the qualification to be MCF in Applied
Mathematics, he obtained a HDR in Economics and the qualifications to be Professor in Economics
and Management. He has published numerous economics, finance, and mathematics articles in
journals such as Insurance: Mathematics and Economics,Environmental Modeling and Assessment,
JORS,IJTAF,Economic Modeling,Journal of Multivariate Analysis,Quantitative Economics,ROIW,
Annals of Finance,CSDA,New Mathematics and Natural Computation,Annals of Operations
Research,andJQE, among others.
234 THE JOURNAL OF ENERGY AND DEVELOPMENT
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economists suggest that there is a negative relationship between public debt and
economic growth, while others deny the relationship between these variables in the
long term.
The explanation of economic growth—either by debt or by energy—appears to
be more complex than an intuitive interpretation of policy makers. Debt is a
double-edged sword. On the one hand, it promotes consumption and accelerates
capital accumulation, thus contributing to economic growth. On the other hand, by
increasing debt servicing costs, it exposes countries to financial risks. A strong
expansion of the debt can be associated with a significant economic contraction
that can last for years.
2
Whatever the economic situation (expansion or recession),
we have noted that for some European OECD countries, the pace of growth is not
the same as for others due to their high indebtedness ratios and lack of energy
resources,
3
where the pace of GDP growth is affected by energy supply for some
countries or by their debt policies for others. Given the financial and economic
downturn, the group of European OECD members, especially the ones with weak
economies—the so-called GIIPS countries (Greece, Ireland, Italy, Portugal, and
Spain)—represent a valuable case for testing the dynamics and relationships of per-
sistently high levels of public deficits and external imbalances. It is, therefore,
important to understand the link not only between debt and economic growth but
also between energy and economic growth to derive useful policy indications,
which are necessary to understand whether a reduction in debt or an increase in
energy supply is sufficient to resolve the imbalances.
4
Therefore, the added value
of our study lies in taking into account the energy supply for a better three-
dimensional explanation between energy, debt, and economic growth, on the one
hand, and by splitting the OECD European countries into two sub-samples, GIIPS
and Non-GIIPS counties, on the other hand. It would be appropriate to highlight
our variables of interest, which are energy supply, public debt, and economic
growth, and will be addressed further in the subsequent parts of our article.
First of all, priority must be given to an efficient and sustainable energy supply.
Sustainability is no longer limited to the preservation of the environment. Accord-
ing to the OECD, primary energy supply is defined as energy production plus
energy imports, minus energy exports, minus international bunkers, then plus or
minus stock changes. The International Energy Agency (IEA) energy balance
methodology is based on the calorific content of the energy commodities and a
common unit of account: tone of oil equivalent (toe). Toe is defined as 107 kilocal-
ories (41.868 gigajoules). This quantity of energy is, within a few percent, equal to
the net heat content of one tone of crude oil. The difference between the “net”and
the “gross”calorific value for each fuel is the latent heat of vaporization of the
water produced during the combustion of the fuel. For coal and oil, the net calorific
value is about 5% less than the gross, but for most forms of natural and manufac-
tured gas the difference is 9% to 10%, while for electricity the concept of calorific
has no meaning. The IEA calculates balances using the physical energy content
235ENERGY SUPPLY, PUBLIC DEBT, & ECONOMIC GROWTH
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method to find the primary energy equivalent. This indicator is measured in million
tons of oil equivalent (toe) and toe per $1.000 USD. Secondly, public debt refers
to the total financial commitments made in the form of loans by the State, public
authorities, and the organizations that depend directly on them. It is constantly
changing as a function of the rate of repayment of loans by the State and public
administrations and the new loans they take out to finance their deficits, which
occur when expenditures, made possible by borrowing, exceed revenues, leading
to an increase in the debt. Finally, a country’s growth is measured by the increase
in its gross domestic product (GDP) over a given period: month, quarter, half-year,
or year. It is calculated in “constant euros,”i.e., excluding price increases. It is
manifested by a significant and lasting increase in the supply of goods and services.
This positive fluctuation is evaluated by the annual variation of the GDP indicator,
evaluated in constant currency to take into account inflation. This is an indispens-
able, but not always sufficient, proxy for development. Therefore, gaining a greater
understanding of the interactions between these variables is immensely useful for
policy formulation.
This paper proceeds as follows. The next section reviews the literature to estab-
lish the existing knowledge of the relationships between energy, debt, and eco-
nomic growth. The methodology section includes details of the model and
hypotheses, then the results are analyzed and discussed. Finally, future research
directions are suggested.
Brief Literature Review
Energy –Economic Growth: In considering the relationship between energy
consumption and economic growth, two opposing views have emerged. One view
is that energy consumption limits growth. It also is argued that the potential impact
of energy consumption on growth varies with the structure of the economy and the
economic growth cycle of the country. Through the development of the economy,
its production structure should move toward services, which are not energy-
intensive activities, as argued by a group of authors such as E. Denison, B. Cheng,
J. Asafu-Adjaye, and R. Solow.
5
The other view implies that energy can be the
source and driver of economic growth. The increase of energy consumption is one
of the effects of economic growth. Moreover, energy is a key source of economic
growth because it multiplies consumption and production activities that involve
energy as a basic production factor.
6
From a physical perspective, energy con-
sumption drives economic productivity and industrial growth and is essential to the
development of any modern economy.
7
Broadly speaking, the connections between energy and growth, developed by
C. Jumbe, A. Shiu and P.-L. Lam, G. Altinay and K. Erdal, S.-T. Chen et al., P.
Mozumder and A. Marathe, J. Squalli, N. Apergis and J. E. Payne, and I. Ozturk
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and A. Acaravci, have been grouped into four categories, each of which has impor-
tant implications for energy policy:
8
(i) The growth hypothesis asserts that there is a unidirectional relationship
between energy consumption and economic growth. It argues that energy
consumption plays a dominant role in economic growth both as a direct
factor in the production process and indirectly as a complement to labor
and capital. Energy is considered here as a complementary factor of
production to the usual factors such as capital and labor. Under these con-
ditions, the implementation of energy policy influences the level of produc-
tion, according to E. Yu and J.-Y. Choi, S. Tsani, A. Belke et al., and
M. Destek.
9
(ii) The conservation hypothesis suggests that growth generates an increase in
energy consumption. This assumes that a restrictive energy policy can be
implemented in an economy without negative effects on growth. If there is
a unidirectional Granger causality from growth to energy consumption,
this hypothesis is confirmed. Indeed, S. Paul and R. Bhattacharya, A.
Hatemi et al., and T. Gelo assert that energy conservation policies can be
implemented with little or no negative effects on economic growth.
10
(iii) The neutrality hypothesis implies that there is no causal relationship
between energy consumption and economic growth. These two variables
are not correlated. In other words, any increase or decrease in energy con-
sumption does not affect economic growth. This means that neither an
energy-saving policy nor an energy-intensive policy influences the level of
wealth creation in an economy, as explained by T. Jobert and F. Karanfil.
11
(iv) The feedback hypothesis states that there is a two-way causality between
energy consumption and economic growth. This means that energy and
economic policies will be implemented jointly. In this case, the energy
consumption policy should be developed to avoid a negative impact of
energy consumption on economic growth (studies applied to one or groups
of countries: Greece, G7, OECD countries), according to G. Hondroyian-
nis, C.-C. Lee et al., M. Mutascu, and J. Dos et al.
12
Thus, empirical studies related to the above-mentioned hypotheses show a uni-
directional causality that exists from total energy consumption to economic growth
(applied to a group of African countries) concluded by A. Akinlo and S. Solarin.
13
A unidirectional causality in the other direction was concluded by J. Kraft and A.
Kraft
14
applied to the United States for a period from 1947 to 1974 and by R.
Abaidoo
15
using quarterly data over 39 years. The study by M. Behname found a
bidirectional relationship between the two variables.
16
No relationship between
energy and growth was concluded by T. Carminel, explaining that the decoupling
between energy and growth is limited by concerns about the supply of raw materi-
als.
17
As an example, energy-related technologies needed to extract certain
237ENERGY SUPPLY, PUBLIC DEBT, & ECONOMIC GROWTH
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materials are subject to geopolitical constraints. The raw material supply problem,
in turn, limits the deployment of the equipment needed to improve energy inten-
sity. U. Erol and E. Yu researched a group of countries to find the causal link
between energy consumption and GDP using the Granger and Sims causality
tests.
18
They concluded that there was one-way causality between energy con-
sumption and GDP for West Germany, two-way causality in Italy, and a lack of
causality between the two variables for France, the United Kingdom, and Canada.
A. Masih and R. Masih applied their work to six Asian countries (India, Indonesia,
Malaysia, Pakistan, the Philippines, and Singapore) using Johansen’s methodology,
vector error-correction model, and variance decomposition.
19
The discrepancies in
the results are summarized as cointegration between energy consumption and GDP
in India, Indonesia, and Pakistan, and non-cointegration between the two variables
in Malaysia, Singapore, Pakistan, and the Philippines; energy consumption causing
GDP (more energy consumption, more growth) in India; GDP causing energy con-
sumption in Indonesia; and two-way causality in Pakistan. J. Chontanawat et al.
assessed the relationship between the two variables on a panel of over 100 coun-
tries, including 30 OECD and 78 non-OECD countries, to detect the relationship
between energy and growth.
20
Their findings reveal that energy consumption
drives GDP (more energy consumption, more growth) in 21 OECD countries. For
non-OECD countries, this relationship is found in 36 of the 78 countries or 46%.
In summary, a more common causality between energy consumption and GDP is
noted for advanced OECD countries. From this point of view, a measure focused
on limiting energy consumption would have a greater negative impact on GDP in
OECD countries than in non-OECD countries.
I. Ozturk and A. Acaravci sought to test the relationship between energy and
growth in four Eastern European countries (Albania, Bulgaria, Hungary, and
Romania) over the period 1980-2006 using the Engle and Granger model.
21
They
found a lack of causality for Albania, Bulgaria, and Romania; however, a presence
of bidirectional causality was observed in Hungary.
Public Debt –Economic Growth: The second strand of literature is related to
the relationship between public debt and economic growth. The empirical literature
on this topic not only presents ambiguous results but focuses mainly on the possi-
ble impact of high debt levels on economic growth, ignoring the possibility of
reverse causality from growth to debt, with rare exceptions such as the works of
M. Ferreira and M. Puente.
22
However, A. Bell et al. find that there is some theo-
retical evidence that public debt is likely to accumulate when growth is low.
23
In
this regard, since low growth means more limited government revenues, govern-
ments may be forced to increase their debt levels to maintain the welfare state,
stimulate demand in the short run, and increase growth in the long run, according
to M. Feldstein.
24
Theoretically, neoclassical and endogenous growth models, such
as those of F. Modigliani, P. Diamond, G. Saint-Paul, and J. Aizenman et al., sug-
gest that high levels of public debt would undeniably reduce the rate of economic
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growth.
25
Other channels to support the negative effect of public debt on long-run
growth include the debt overhang hypothesis (P. Krugman and N. Roubini et al.),
26
the liquidity constraint hypothesis (T. Moss and H. Chiang),
27
the crowding-out
hypothesis (H. Hansen),
28
and the uncertainty hypothesis (L. Codogno et al. and J.
Cochrane).
29
Another channel through which high debt can negatively impact
growth is through long-term interest rates (D. Elmendorf and G. Mankiw, V. Tanzi
and N. Chalk).
30
Finally, some of the effects associated with financial liberaliza-
tion, ranging from increased risk-taking by banks to the accumulation of large
external debt, can make a country vulnerable to economic shocks that often can
have severe recessionary consequences (B. Eichengreen and D. Leblang, U. Nyam-
buu and L. Bernard).
31
Given the theoretical predictions highlighted above, it is
somewhat surprising that C. Reinhart and K. Rogoff concluded that a country’s
debt must reach a threshold of 90% of GDP, beyond which the rate of GDP growth
declines significantly, has generated such controversy.
32
Other researchers have
strongly criticized this by noting that over the period 1946-2009, countries with
a debt-to-GDP ratio above 90% had an average annual real GDP growth of 2.2%
not -0.1%.
Additional empirical studies have shown the relationship between debt and
growth. C. Checherita-Westphal and P. Rother analyzed the average impact of pub-
lic debt on GDP per capita growth in 12 euro area countries over about 40 years,
starting in 1970.
33
They conclude that there is a non-linear effect of debt on growth
with a turning point beyond which the ratio of public debt to GDP harms growth
in the long run at around 90/100% of GDP. U. Panizza and A. Presbitero studied
the causal effect of government debt on economic growth in a sample of OECD
countries.
34
Their results are consistent with the existing literature, showing a nega-
tive correlation between the two variables. J. Mencinger et al. empirically analyzed
the relationship between the ratio of government debt to GDP and GDP growth on
a panel dataset of 25 European Union (EU) countries.
35
To take into account the
impact of the level of the debt-to-GDP ratio on the real GDP growth rate, they
used panel estimation on a generalized economic growth model augmented with a
debt variable, while also considering some methodological issues such as heteroge-
neity and endogeneity problems. The results of all models indicate a statistically
significant non-linear impact of government debt ratios on annual growth rates of
GDP per capita. Their research has contributed to a better understanding of the
problem of high public debt and its effect on economic activity in the EU.
The debt-growth and energy-growth relationships have been discussed in the lit-
erature, which leads us to look at the decoupling of growth and energy, on the one
hand, and the problem of public debt in OECD European countries, on the other.
These two facts raise a fundamental question: What can be said about the links
between energy, debt, and GDP? The question is crucial today because we are
exposed to many challenges. The current fall in the global growth rate and its con-
sequences are the subjects of much debate. Is it due to pressure on energy
239ENERGY SUPPLY, PUBLIC DEBT, & ECONOMIC GROWTH
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resources? Is the high level of public debt related to the link between energy and
economic growth? All of these issues spur greater interest in determining the
potential econometric short- and long-term relationships between energy, debt, and
growth.
Model and Methodology
Model: Based on our brief literature review, and to achieve the study’sobjec-
tive, we form a long-run relationship between economic growth, energy supply,
and public debt in a linear logarithmic form as follows in equation (1):
EGRit 5
a
01
b
1ESUit 1
b
2PDEit 1uit (1)
Where i51, …, N (number of the chosen countries) denotes the country; t5
1, …,T denotes the time period from 1970 to 2021; u
it
is assumed to be a serially
uncorrelated error term;
a
0
represents the constant in our model; EGR represents
the economic growth, which is our dependent variable; and ESU and PDE repre-
sent the energy supply and the public debt, respectively, which are our independent
variables. The expected signs of energy supply and public debt are positive and
negative, respectively, meaning that energy supply and public debt have, respec-
tively, a positive and negative impact on economic growth in the long term.
Cointegration Methodology: To test the existence of a long-run relationship
among the variables and to capture the short-run dynamics of the variables using
the vector error-correction model (VECM), our methodological strategy is com-
posed of two essential steps.
The first step is to verify the order of integration for all variables because the
several cointegration tests are valid only if all the study’s variables are integrated
in the same order, meaning that they have the same order of integration. We test
the stationarity using four different types of unit root tests divided into common
and individual unit root: Levin, Lin, and Chu (LLC); Im, Pesaran, and Shin (IPS);
a Fisher-type test using Augmented Dickey-Fuller (ADF); and Phillips-Perron
(PP). In 1997, H. Zapata and A. Rambaldi
36
reported that if the variables are not
integrated in the same order (meaning that some variables are I(0) and the others
are integrated of order one I(1)), the application of Toda and Yamamoto (TY) is
required to be on the safe side and to overcome this problem, whereas the TY pro-
cedure does not impose any prerequisites and knowledge on cointegration.
The second step requires testing the panel cointegration relationship. When all
series and variables are integrated into the same, we can move on to test the panel
cointegration between the variables based on the three fundamental tests: Pedroni;
Kao; and Johansen Fisher. The Pedroni and Kao tests are based on the Engle-
Granger two-step (residual-based) cointegration test. Overall, Pedroni provides
240 THE JOURNAL OF ENERGY AND DEVELOPMENT
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seven statistics to test the null hypothesis of no cointegration in the heterogeneous
panels. These seven tests can be categorized as either within-dimension (panel tests)
or between-dimension (group tests). These tests are all based on the residuals from
equation (1) and are variants of the ADF and PP tests. The within-dimension tests
pool the autoregressive coefficients across different members of the panel. On the
other hand, the between-dimension tests are less restrictive than the within-dimension
tests in the sense that they allow for the heterogeneity of the parameters across coun-
tries. Kao’s test follows the same basic approach as Pedroni’s tests but specifies
cross-section-specific intercepts and homogeneous coefficients in the first step. In
addition, the Fisher test is a combined Johansen and Juselius test. If cointegration
exists between the variables, the ordinary least squares (OLS) method is applied to
ensure that the estimation of equation (1) does not lead to a spurious regression result.
In addition, the parameters estimated by the OLS method are super consistent.
Granger Causality: Then, we look forward to examining the existence and the
direction of the causality between the variables in a panel context. The existence of
cointegration implies that there are long-run equilibrium relationships between the
variables and, thus, Granger causality between them in at least one direction. The
vector error-correction model (VECM) is used to correct the disequilibrium in the
cointegrating relationship, captured by “ECT,”as well as to test for long- and
short-run causality between the cointegrated variables. The VEC model by defini-
tion is a restricted VAR that has cointegration restrictions built into the specifica-
tion so it is designed for use with nonstationary series that are known to be
cointegrated. The VEC specification restricts the long-run behavior of the endoge-
nous variables to converge to their cointegrating relationships while allowing a
wide range of short-run dynamics. The cointegration term is known as the error-
correction term since the deviation from long-run equilibrium is corrected gradu-
ally through a series of partial short-run adjustments. The panel-based VECM is
defined as follows in equation (2):
DEGRit
DESUit
DPDEit
2
6
43
7
51
a
1
a
2
a
3
2
6
43
7
51Pr
p51
b
11p
b
21p
b
31p
b
12p
b
22p
b
32p
b
13p
b
23p
b
33p
2
6
6
43
7
7
5
DEGRit2p
DESUit2p
DPDEit2p
2
6
43
7
5
1
u
1
u
2
u
3
2
6
43
7
5ECTit211
«
1it
«
2it
«
3it
2
6
43
7
5
(2)
Where i51, …, N (number of the chosen countries) denotes the country; t5
1, …,T denotes the time period from 1970 to 2021;
«
it
is assumed to be a serially
uncorrelated error term; and ECT is the lagged error-correction term derived from
the long-run cointegration relationship. We follow Abdalla and Murinde’s process
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to determine the optimal lag length in each equation for a linear system which is
selected by maximizing the value of the R-squared (R
2
) and minimizing the AIC
criteria. In terms of causality, we test four main hypotheses that sum up all the
cases between the three chosen variables as follows:
H
1
: Unidirectional causality relation from variable 1 to variable 2 (Meaning
that the first variable does Granger causes the second one).
H
2
: Unidirectional causality relation from variable 2 to variable 1 (Meaning
that the second variable does Granger causes the first one).
H
3
: Bidirectional causality relation between variable 1 and variable 2 (Mean-
ing that both variables do Granger cause each other).
H
4
: No causality relation between both variable 1 and variable 2 (Meaning
that the first variable does not Granger causes the second variable).
Empirical Results
Data Analysis: In this paper, we have conducted a statistical and econometrical
analysis of 21 OECD European countries for which the most energy-related and
macroeconomic annual data are available from 1970 to 2021. The 21 countries
include the 5 GIIPS (Greece, Ireland, Italy, Portugal, Spain) and the 16 Non-GIIPS
(Germany, Belgium, Finland, France, Netherlands, Luxembourg, Austria,
Denmark, Poland, Hungary, Sweden, Switzerland, Norway, England, Iceland, and
Turkey). The objective was to select the largest and the longest balanced panel.
The full sample is divided into two sub- samples: GIIPS and the Non-GIIPS. Thus,
we construct three different models (balance panel) for the analysis. The data
come from OECD’sEconomic Outlook No 110-December 2021 (primary energy
supply, general government gross financial liabilities, and gross domestic product
volume market prices). To complete the series, we have also used the OECD’s
Economic Outlook No 73-June 2003 for all the countries selected to have the
largest observations possible (data calibration between two data sources).
Figures 1-3 show the changing trends for each series of the OECD European
countries (Full sample, GIIPS, and Non-GIIPS countries). Figure 1 shows that the
full sample and Non-GIIPS countries have shown the same significant increase in
economic growth all over the period (1970-2021). Whereas the series for the other
sample (GIIPS countries) show an almost monotonic increase over the entire time
span. In term of economic growth, we can notice that the full sample is well pre-
sented by the Non-GIIPS countries.
Figure 2 represents the evolution of energy supply from 1970 to 2021 for the
three samples. Overall, we observe that the series have almost the same trend;
however, there were two impactful events. The first was marked by the response of
energy supply following the financial crisis of 2008, where we find the effect to be
242 THE JOURNAL OF ENERGY AND DEVELOPMENT
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more pronounced for the GIIPS (countries with low growth and high debt as already
discussed in the literature). The second event was in regard to the COVID-19 crisis,
which favored the GIIPS countries as their energy supply was improved in compari-
son to the other two samples (full sample and non-GIIPS countries).
Figure 1
ECONOMIC GROWTH: AVERAGE FOR GDP PER YEAR, 1970–2021
4,5E+12
4E+12
3,5E+12
3E+12
2,5E+12
2E+12
1,5E+12
1E+12
5E+11
0
Full sample GIIPS countries Non-GIIPS countries
1970
1972
1974
1976
1978
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
2010
2012
2014
2016
2018
2020
Source: Authors.
Figure 2
ENERGY SUPPLY: AVERAGE PER YEAR, 1970–2021
100000000
90000000
80000000
70000000
60000000
50000000
40000000
30000000
20000000
10000000
Full sample GIIPS Non-GIIPS
1970
1972
1974
1976
1978
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
2010
2012
2014
2016
2018
2020
Source: Authors.
243ENERGY SUPPLY, PUBLIC DEBT, & ECONOMIC GROWTH
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The trend for public debt is presented in Figure 3. The graph shows that all
three series have the same upward trend reflected in an excessive increase in debt
levels, mainly in response to three important events: the 2008 financial crisis; the
sovereign debt crisis (2011); and the COVID-19 crisis (2019).
Descriptive Statistics and Correlation Matrix: We present the summary of
descriptive statistics of the study’s variables as shown in table 1. The mean of eco-
nomic growth in the full sample is equal to 27.16 and ranges from 23.10 to 31.36,
which are the same minimum and maximum values for the Non-GIIPS countries.
We have recognized that the energy supply and public debt have a difference in
the mean between the GIIPS countries and the Non-GIIPS countries. The results
ensure the energy supply and public debt vary between the GIIPS countries and
the Non-GIIPS countries, indicating the need to split the full sample into two sub-
samples to capture the difference.
We present the Pearson correlation coefficients among the study’s variables in
Table 2. The correlation between economic growth and energy supply is negative
and significant at 1% while there is a positive and significant correlation between
economic growth and public debt. The result supports the hypothesis according to
which there is a positive relationship between economic growth and public debt
and a negative relationship between economic growth and energy supply. Regard-
ing the correlation between the energy supply and public debt, the results indicate
a strong positive relationship between these two variables.
Figure 3
ENERGY SUPPLY: AVERAGE PER YEAR, 1970–2021
1,6E+12
1,4E+12
1,2E+12
1E+12
8E+11
6E+11
4E+11
2E+11
0
Full GIIPS Non-GIIPS countries
1970
1972
1974
1976
1978
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
2010
2012
2014
2016
2018
2020
Source: Authors.
244 THE JOURNAL OF ENERGY AND DEVELOPMENT
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Panel Unit Root and Panel Cointegration Tests: The time-series properties
of the variables in Eq. (1) are checked through four types of panel unit root tests:
LLC, IPS, ADF, and PP tests. The panel unit root test is based on the null hypothe-
sis to prove the existence of the unit root, while the alternative hypothesis indicates
the absence of the unit root. (H
0
: Data are not stationary (Unit root exists) and H
1
:
Data are stationary (Unit root does not exist)). We apply the common unit root test
by using the LLC and the individual unit root by applying IPS, ADF, and PP. The
results as shown in table 3 indicate that all the series in Eq (1) appear to contain a
panel unit root in their level while stationary in their first difference, showing that
they are integrated at order one I (1).
Table 2
CORRELATION MATRIX
a
Economic Growth Energy Supply Public Debt
EGR 1.0000
ESU 20.0564* 1.0000
(0.0626)
PDE 0.5888*** 0.2355*** 1.0000
(0.0000) (0.0000) 1.0000
a
Numbers in parentheses 5p-values; * indicates significance at 10%; ** indicates significance at
5%; and *** indicates significance at 1%.
Table 1
DESCRIPTIVE STATISTICS
a
Variables Mean Median Min Max Std. Dev. No. of Obs.
Full Sample
EGR 27.16812 27.24722 23.10801 31.36414 1.491998 1,092
ESU 16.9409 17.30243 10.83985 19.71831 2.138101 1,092
PDE 25.91719 26.1166 19.08927 28.91897 1.647482 1,092
GIIPS Countries
EGR 26.40955 26.0062 24.1153 28.21585 1.114771 260
ESU 17.3481 17.01438 15.56645 19.08631 1.090601 260
PDE 25.44128 25.53252 19.08927 28.81175 1.938355 260
Non-GIIPS Countries
EGR 27.40517 27.52745 23.10801 31.36414 1.516219 832
ESU 16.81364 17.34393 10.83958 19.71831 2.358597 832
PDE 26.06592 26.24476 10.85372 28.91897 1.516368 832
a
Min5minimum; Max 5maximum; Std. Dev. 5standard deviation; No. of Obs. 5number of
observations.
245ENERGY SUPPLY, PUBLIC DEBT, & ECONOMIC GROWTH
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According to the findings from the panel unit root test, the cointegration
between economic growth, energy supply, and public debt can be investigated. For
that, we apply the panel cointegration test between economic growth and its deter-
minants by using the Pedroni test, Kao test, and Fisher test. (H
0
: there is no cointe-
gration and H
1
: there is cointegration). The results are provided in table 4.
Based on the Pedroni test results, we find that 9 out of 11 of the results are sig-
nificant at 1%, and this is an indicator of panel cointegration. After applying the
Kao test, the results indicate the existence of panel cointegration where it is signifi-
cant at 1%. Additionally, the Johansen Fisher test reveals the existence of two
cointegration vectors at 1%. We can summarize that there is strong statistical evi-
dence of panel cointegration among our variables: economic growth (EGR), energy
supply (ESU), and public debt (PDE). The existence of cointegration among the
variables attempts to exclude the possibility of having a bias in the equation.
VEC-Model and Panel Causality Tests: The time series of our model must be
stationary in a long-run analysis to avoid dummy results. For that, before examin-
ing the panel cointegration, all variables (economic growth, energy supply, and
Table 3
PANEL UNIT ROOT TESTS
a
Common Unit Root
LLC IPS
Variable Level 1
st
Diff. Level 1
st
Diff.
EGR 23.223 212.760*** 1.064 222.459***
(1.0000) (0.0000) (0.8564) (0.0000)
ESU 6.043 226.521*** 22.856*** 226.108***
(1.0000) (0.0000) (0.0021) (0.0000)
PDE 15.046 211.476*** 0.326 219.636***
(1.0000) (0.0000) (0.6278) (0.0000)
Individual Unit Root
ADF PP
Level 1
st
Diff. Level 1
st
Diff.
EGR 0.4149 212.449*** 0.0641 214.413***
(1.0000) (0.0000) (1.0000) (0.0000)
ESU 7.931 226.474*** 8.943 227.510***
(1.0000) (0.0000) (1.0000) (0.0000)
PDE 1.927 213.188*** 1.238 216.007***
(1.0000) (0.0000) (1.0000) (0.0000)
a
Numbers in parentheses 5p-values; * indicates significance at 10%; ** indicates significance at
5%; and *** indicates significance at 1%.
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public debt) must be integrated into order one. Table 5 provides the short- and
long-run equilibrium results for the full sample.
The VEC model for the dependent variable EGR is as follows:
D EGR
ðÞ
520:53208 20:13937EGR 21
ðÞ
20:00000283ESU 21
ðÞ
20:0000184ESU 22
ðÞ
20:00000591PDE 21
ðÞ
20:00000334PDEð22Þ
EGRð21Þ50:00000677ESU ð21Þ20:00000688PDEð21Þ
The result in the equation shows in the short run there is no impact of energy
supply and public debt on economic growth in the first equation. However, in the
third model where the public debt is the dependent variable, the coefficient of
adjustment is negative and significant at 1%. Contrarily, in the long run, both
energy supply and public debt are significant at 1%. The impact of energy
supply is positive and significant by 0.00000677 on economic growth while there
is a negative and significant impact of public debt on economic growth by
0.00000688.
Table 4
PANEL COINTEGRATION TESTS
a
Pedroni Test
Test statistics Statistics (p-value) Weighted statistic (p-value)
Alternative hypothesis: Common AR coefs. (within-dimension)
Panel v-stat 0.224690 (0.4111) 20.773904 (0.7805)
Panel rho-stat 26.756258*** (0.0000) 26.738820*** (0.0000)
Panel PP-stat 28.899870*** (0.0000) 29.365574*** (0.0000)
Panel ADF-stat 28.517234*** (0.0000) 29.151758*** (0.0000)
Alternative hypothesis: Individual AR coefs. (between dimension)
Group rho-stat 26.120249*** (0.0000)
Group PP-stat 212.62997*** (0.0000)
Group ADF-stat 211.65244*** (0.0000)
Kao Test t-Statistic
ADF 28.623625*** (0.0000)
Fisher Test Trace test Maximum Eigen Value
Null hypothesis
r50 301.8*** (0.0000) 215.8*** (0.0000)
r#1 161.0*** (0.0000) 138.0*** (0.0000)
r#2 77.83*** (0.0006) 77.83*** (0.0000)
a
*, **, and *** indicate the rejection of the null hypothesis at 10%, 5%, and 1% level of
significance, respectively. r denotes the number of cointegration equations.
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Table 5
VEC MODEL: SHORT- AND LONG-RUN EQUILIBRIUM FOR THE FULL SAMPLE
a
Dep. Var. Source of causation (independent variables)
Short-run equation R
2
F-statistics
ECT DEGR
(21)
DEGR
(22)
DESU
(21)
DESU
(22)
DPDE
(21)
DPDE
(22)
DEGR 20.53208*** 20.13937*** 20.13352*** 22.83E-06 21.84E-05 25.91E-06 23.34E-06 0.3522
DESU 129.9695 29.9088 210.8347 20.3188*** 20.0117 0.0572** 20.0015 0.1048
DPDE 2288.7375*** 129.1592 168.0498 20.0280 20.0230 20.1463*** 20.1714*** 0.0471
Long-run equation
t-statistics
DEGR
(21)
DESU
(21)
DPDE
(21)
ECT 1.0000 6.77E-06*** 26.88E-06***
a
Dep. Var. 5dependent variable; *, ** and *** indicate the level of significance at 10%, 5% and 1%, respectively.
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In the long run, the results indicate for every 1% increase in the energy supply,
there will be an increase in the economic growth by 0.000677%. The results also
indicate that for every 1% increase in the public debt there will be a decrease in
the economic growth by 0.000688%.
The existence of a panel long-run cointegration relationship among economic
growth, energy supply, and public debt suggests that there is Granger causality in
at least one direction. The balanced panel Granger causality results are presented
in table 6. We have divided our work into three samples to provide a more
in-depth analysis between the GIIPS and Non-GIIPS countries. After applying the
panel Granger causality test for the full sample, the results show unidirectional cau-
sality from public debt to economic growth, while there is bidirectional causality
from energy supply to economic growth, economic growth to energy supply, eco-
nomic growth to public debt, public debt to energy supply, and energy supply to
public debt.
To permit the use of the Granger causality test for the GIIPS countries, we have
applied the VEC model. The results, shown in table 7, indicate there is a negative
and significant impact of 1% of energy supply on economic growth, where every
1% increase in energy supply will decrease the economic growth in the long
run by 38.63%. For the public debt, the results demonstrate there is a negative
and significant impact of 1% of public debt on economic growth in the long run,
where every 1% increase in public debt will decrease the economic growth
by 70.70%.
As can be seen in table 8, the panel Granger causality test for the GIIPS coun-
tries demonstrates there is unidirectional causality from energy supply to economic
growth, from economic growth to energy supply, from public debt to economic
growth, and from public debt to energy supply, while there is bidirectional causal-
ity from economic growth to public debt, and energy supply to public debt.
Table 6
PANEL GRANGER CAUSALITY TEST FOR THE FULL SAMPLE
a
Null hypothesis No. of Obs. F-Statistic P-value
ESU does not Granger cause EGR 1050 9.99874*** 5.E-05
EGR does not Granger cause ESU 11.4395*** 1.E-05
PDE does not Granger cause EGR 1050 1.79728 0.1663
EGR does not Granger cause PDE 13.9026*** 1.E-06
PDE does not Granger cause ESU 1050 10.1356*** 4.E-05
ESU does not Granger cause PDE 5.68112*** 0.0035
a
No. of Obs. 5number of observations; *, ** and *** indicate the level of significance at 10%, 5%
and 1%, respectively.
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Table 7
VEC MODEL: SHORT- AND LONG-RUN EQUILIBRIUM FOR THE GIIPS COUNTRIES
a
Dep. Var. Source of causation (independent variables)
Short-run equation R
2
F-statistics
ECT DEGR
(21)
DEGR
(22)
DESU
(21)
DESU
(22)
DPDE
(21)
DPDE
(22)
DEGR 0.005409*** 0.365950*** 0.156006* 20.066823 0.003312 20.007864 0.020506 0.1614
DESU 0.012910** 20.358241** 0.610836*** 20.394976* 20.026784 20.007611 0.009621 0.0816
DPDE 0.053573*** 20.333889 20.186522 20.105665 20.186808 0.139021** 0.081984 0.0819
Long-run equation
t-statistics
DEGR
(21)
DESU
(21)
DPDE
(21)
ECT 1.0000 20.386387*** 20.707003***
a
Dep. Var. 5dependent variable; *, ** and *** indicate the level of significance at 10%, 5% and 1%, respectively.
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The same procedure follows to test the Granger causality test for the Non-
GIIPS countries. Table 9 provides the VEC model short- and long-run equations
for the Non-GIIPS, and the results indicate a long-run relationship. The impact of
energy supply has a positive and significant impact of 1% on the economic growth,
where the increase of 1% of energy supply will increase the economic growth by
64.04%; while the impact of public debt on economic growth is negative and sig-
nificant at 1%, where any increase of 1% of public debt will decrease the economic
growth by 11.005%.
The panel Granger causality test for Non-GIIPS countries, as can be seen in
table 10, demonstrates there is just unidirectional causality from public debt to eco-
nomic growth, while there is bidirectional causality from energy supply to eco-
nomic growth, from economic growth to energy supply, from economic growth to
public debt, from public debt to energy supply, and energy supply to public debt.
We recognize that the panel causality relations for the Non-GIIPS countries fol-
low the same path as the full sample, caused by the fact that the Non-GIIPS coun-
tries represent three-quarters of the full sample. Based on the strong causality
results, evidence shows that economic growth does Granger cause public debt,
while public debt does not Granger cause economic growth. We can conclude that
economic growth can attract the public debt in the full sample, GIIPS, and Non-
GIIPS countries. Moreover, the causality runs from energy supply to public debt
and public debt to energy supply in the full sample and the Non-GIIPS countries.
In the GIIPS countries, the direction is not reversed, where the causality is unidi-
rectional. Nevertheless, the results indicate that the development of energy is a key
factor for domestic economic growth, which is an essential factor for the energy
supply. Both economic growth and energy supply depend on each other due to a
bidirectional causality relationship. Figure 4 provides a visual overview of the
panel causality relationships in our study. Our results are in line with the findings
of C. Checherita-Westphal and P. Rother.
37
They find that public debt has a
Table 8
PANEL GRANGER CAUSALITY TEST FOR THE GIIPS COUNTRIES
a
Null hypothesis No. of Obs. F-Statistic P-value
ESU does not Granger cause EGR 250 2.23562 0.1091
EGR does not Granger cause ESU 1.30216 0.2738
PDE does not Granger cause EGR 250 0.23344 0.7920
EGR does not Granger cause PDE 12.5350*** 7.E-0.6
PDE does not Granger cause ESU 250 1.04650 0.3527
ESU does not Granger cause PDE 11.2017*** 2.E-05
a
No. of Obs. 5number of observations; *, ** and *** indicate the level of significance at 10%, 5%
and 1%, respectively.
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Table 9
VEC MODEL: SHORT- AND LONG-RUN EQUILIBRIUM FOR THE NON-GIIPS COUNTRIES
a
Dep. Var. Source of causation (independent variables)
Short-run equation R
2
F-statistics
ECT DEGR
(21)
DEGR
(22)
DESU
(21)
DESU
(22)
DPDE
(21)
DPDE
(22)
DEGR 20.001581*** 0.257541 0.144308 0.033658 20.064739** 20.005236 0.005667 0.1425
DESU 0.002676*** 20.316063** 0.251094*** 0.019722** 0.039701 0.003066 0.015695 0.0433
DPDE 0.017706 20.247384*** 0.159324*** 20.086160 0.059519 0.104183 0.031107 0.0565
Long-run equation
t-statistics
DEGR
(21)
DESU
(21)
DPDE
(21)
ECT 1.0000 0.640416*** 21.100575***
a
Dep. Var. 5dependent variable; *, ** and *** indicate the level of significance at 10%, 5% and 1%, respectively.
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negative effect on economic growth in the long term. The findings are also some-
what consistent with those of U. Panizza and A. Presbitero, who reported evidence
of a negative correlation between government debt and economic growth.
38
In con-
trast, in 2009, M. Ferreira, using OECD annual data for 20 countries from 1988 to
2001, finds evidence of a clear bidirectional Granger causality relationship between
economic growth and public debt.
39
Figure 4
PANEL CAUSALITY RELATIONS
EGR
ESU PDE
Full
Sample
GIIPS
countries
Non-GIIPS
countries
Table 10
PANEL GRANGER CAUSALITY TEST FOR THE NON-GIIPS COUNTRIES
a
Null hypothesis No. of Obs. F-Statistic P-value
ESU does not Granger cause EGR 800 9.09218*** 0.0001
EGR does not Granger cause ESU 5.91700*** 0.0028
PDE does not Granger cause EGR 800 0.81032 0.4451
EGR does not Granger cause PDE 8.48876*** 0.0002
PDE does not Granger cause ESU 800 5.45424*** 0.0044
ESU does not Granger cause PDE 2.96195* 0.0523
a
No. of Obs. 5number of observations; *, ** and *** indicate the level of significance at 10%, 5%
and 1%, respectively.
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Conclusions
In this article, we analyze the impact of energy supply and public debt on eco-
nomic growth taking the European countries as a case study during 1970-2021 by
applying a panel approach. To achieve added value in our research, we divided our
sample into GIIPS countries (which are the weaker economies of Greece, Ireland,
Italy, Portugal, and Spain) and Non-GIIPS countries. In addition, previous articles
focused on energy consumption and its impact on economic growth; however,
these researchers did not pay attention to energy supply, which elevates the value
of our study. The main findings for the GIIPS countries are the non-evidence of a
causal relationship between energy supply and economic growth. These two vari-
ables are not correlated. In other words, any increase or decrease in energy supply
does not affect economic growth. This means that neither an energy-savings policy
nor an energy-intensive policy influences the level of wealth creation in the econ-
omy. Regarding the two other samples (full and Non-GIIPS), we found a two-way
causality between energy supply and economic growth. This means that energy
and economic policies will be implemented jointly. In this case, the energy supply
policy should be developed as an essential factor to attain higher levels of eco-
nomic growth in the long term while avoiding its negative impact in the short
term. In addition, there is a negative relationship between public debt and eco-
nomic growth in full, GIIPS, and Non-GIIPS countries. In regard to causality, there
is unidirectional causality from economic growth to public debt. Thus, the Euro-
pean countries should consider the accumulation of government liabilities as a
main issue due to the fact that public debt, in the long term, will deactivate the
wheels of the economy and disrupt economic growth. Governments in European
countries have to perceive the importance of public debt and energy supply as part
of their public policy and they should be aware that the public debt is a double-
edged sword. The governments’strategic priorities should focus more on energy
supply, especially renewable energy sources, and other economic factors that can
stimulate economic growth as a way of combatting public debt in the long run.
Moreover, in terms of energy, it would be useful for future research papers to
include in their modeling the primary energy consumption that represents the
demand to know its effect on the causal relationships between the variables.
Acknowledgments
The authors would like to thank anonymous reviewers for their valuable sug-
gestions and helpful comments, which have greatly enhanced the quality of this
paper.
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