Why Renewable Energy Use Is worth for East African Community

(EAC) Countries’ Economies

Byiringiro Enock

1,2,*

and Yu Qian

School of Economics Wuhan University of Technology, Wuhan, Hubei, China

Kigali Independent University, Kigali, Rwanda

Keywords

: Renewable Energy, Economic Growth, Dumitrescu-Hurlin (2012) Panel Causality Test, EAC.

Abstract: The positive impact of renewable energy use to spur the economic growth is being scrutinized to assess its

economic impacts apart from its convenience to health conditions. This article investigates the direction of

causation between renewable energy consumption and economic growth in 5 countries of East African

Community (EAC) for the period of 1990Q1 to 2014Q4 due to the data availability. The analysis uses the

panel ARDL approach and Pairwise Dumitrescu- Hurlin(2012) Panel Causality to study the interdependence

between the use of renewable energy and economic growth in a bid to adequately inform related policies and

initiatives in EAC. The findings strongly support the feedback hypothesis as well as the nexus between

renewable energy use and economic growth in EAC for sampled period. Thus, policies that cheer joint projects

to increase the renewable energy in the region, should be encouraged to harmlessly secure sustainable

economic growth and environment protection as well as health.

1 INTRODUCTION

It is about three decades that the environment

deterioration due greenhouse gas emissions from

fossil fuels that leads even to the global warming and

climate change issues became a substantial concern

for international community, some countries ‘leaders,

different global institutions, researchers whose

interests are in the line with environment protection

and sustainable socio-economic development. The

international community through Kyoto Protocol in

1997 advocated the use of renewable energy to

mitigating the global warming and climate change

mitigation and adaptation as well. Despite its slow

implementation, this treaty marked an important

global voice of environment protection and proposed

to reduce the carbon dioxide emission with global

warming mitigation through adopting the clean

energy economy use where hydroelectric; wind and

solar are the most sustainable clean energy

recommended sources. It is important to study the

causal relationship between renewable energy use

and economic growth. The knowledge of interaction

ways between the two variables supports the national

and regional socio-economic development process as

energy is recognized as the conditional factor to

capital and labor in the production process(Stern and

Cleveland 2004).

The renewable energy sector provides new

investments opportunities worldwide. Individuals

and institutions that make innovative renewable

energy investment enjoy sustainable paybacks. The

investment in renewable energy sector, makes

affordable energy cost for investment in

manufacturing and infrastructure projects. More

renewable energy encourages investments that result

into harmless economic growth. Thus, this

hypothesized model can be more helpful in less

developed economies where EAC member states are

classified.

The core intention of this study is to determine the

direction of causality between renewable energy

consumption and economic growth for 5 East Africa

Community (EAC) countries.

This paper is structured such that the section 2

deals with theoretical debate on the nexus between

renewable energy use and economic growth, part 3

explains the methodology used, part4 presents and

discusses findings while section5 is for conclusion

and recommendations.

Enock, B. and Qian, Y.

Why Renewable Energy Use Is worth for East African Community (EAC) Countries’ Economies.

DOI: 10.5220/0011357800003355

In Proceedings of the 1st International Joint Conference on Energy and Environmental Engineering (CoEEE 2021), pages 51-56

ISBN: 978-989-758-599-9

2 THE THEORETICAL DEBATE

ON NEXUS OF RENEWABLE

ENERGY USE AND

ECONOMIC GROWTH

A significant number of studies have propped up the

renewable energy consumption and economic growth

nexus based on four hypothesized energy

consumption- growth models(Lee & Chang,

2007;Apergis & Payne, 2009, 2010; Ozturk, & Aslan,

2012; Nayan, & Abdullah, 2013): (i) growth

hypothesis which states that energy consumption

directly or indirectly causes economic growth; (ii)

The conservation hypothesis is based on the

evidences where economic growth induces energy

consumption, (iii) the feedback hypothesis relies on

the mutual interaction between energy and growth

while (iv) the neutrality hypothesis means the

nonexistence of energy-growth causation.

Using different techniques, studies at country and

cross-country level in developed and less developed

economies; findings have provided evidence that

renewable energy consumption and economic growth

have relationship. But the direction of causation

continued to be contrasted from different contexts. At

the cross section level in developed countries,

Ozturk, & Aslan, (2012) studied the causal

relationship between renewable energy consumption,

non-renewable energy sources and economic growth

for the G-7 using ARDL technique and causality test

for the period of 1980–2009 and results evidenced

that renewable and non-renewable energy

consumption spur the production, Apergis & Payne,

(2010) employed panel cointegration and error

correction model for a panel of 20 OECD countries

over the period 1985–2005, findings discovered a

validation of feedback hypothesis in both short and

long run between renewable energy consumption and

economic growth; employing asymmetric causality

test approach and autoregressive distributed lag

(ARDL) techniques, Alper & Oguz, (2016) for the

period of 1990–2009, investigated the renewable

energy consumption and economic growth nexus for

new EU members and results confirmed that

renewable energy consumption is pro economic

growth. For 80 mixed countries, Apergis & Dan,

2014), using Canning and Pedroni (2008) to test the

long run causality for the sample period of 1990 -

2012 and findings supported the two ways

relationship between renewable energy consumption

and economic growth; (Cho & Kim, 2015) have done

a comparative study of causal relationship between

energy consumption and economic growth for 31

OECD countries developed countries and 49 non-

OECD less developed countries for 1990–2010 under

multivariate panel vector error correction technique

and findings supported the conservative hypothesis

in OECD countries and feedback hypothesis in non –

OECD countries; (Al-Mulali.et al., 2013)

investigated the renewable energy consumption-

growth hypothesis for high income, upper middle

income and lower middle income under fully

modified OLS technique and findings testified that

the feedback hypothesis is supported in 79% of total

countries under the study, 2% with one way causality

running from GDP to renewable energy use and 19%

were found with neutrality hypothesis.

For less developed countries, (Hamit-

haggar,2016) investigated clean energy consumption

and economic growth for 11 sub-Saharan African

countries for 1971–2007 with the use of bootstrap-

corrected Granger causality test and results confirmed

that clean energy consumption granger causes

economic growth.

At the country revel also the renewable energy

consumption and economic growth nexus got has

been studied. For the German (Rafindadi & Ozturk,

2017) using combined cointegration test for the

period of 1971Q1 to 2013QIV results validated that

renewable energy consumption drives economic

growth; for Turkey (Dogan, 2016) under the use of

estimation techniques with structural break,

renewable energy consumption was found

insignificant while non-renewable energy

consumption was found relevant to economic growth;

in Lithuania (Bobinaite& Konstantinaviciute, 2011)

studied the causal link between renewable energy and

GDP for the time of 1990-2009 and have found one

way causality running from renewable energy

consumption granger to GDP.

This article seeks in the light of reviewed literature

to scrutinize the route of Dumitrescu-Hurlin (2012)

Panel Causality test between renewable energy use

and economic growth in selected EAC countries.

3 DATA AND METHODOLOGY

3.1 Data

All used annual data that have been transformed into

quarterly data arrayed from 1990Q1-2014Q4 for

selected five East Africa Community (EAC) member

countries (Burundi, Kenya, Rwanda, Tanzania and

Uganda) were obtained from World Bank

Development Indicators database 2019. This study

considered this sample period because data for

CoEEE 2021 - International Joint Conference on Energy and Environmental Engineering

renewable energy consumption were available till

2014.

3.2 Methodology

As the main purpose of this work is to investigate if

there is cointegration and to determine the direction

of causality between renewable energy consumption

and economic growth in EAC. This study employs the

Panel ARDL method to investigate the long run and

short run dynamics between renewable energy

consumption and economic growth as well as uses

Dumitrescu-Hurlin (2012) Panel Causality test to

assess the direction of causality among variables.

3.2.1 The Ardl Panel Method

The capability of panel Auto Regressive Distributed

Lag (ARDL) test to test the existence of cointegration

among variables for dynamic models has been

recognized numerous researchers such as Simplice

A.et al, 2015 and Offermanns, 2007 among others.

The ARDL is advantageous in studies of dynamic

models as it provides unbiased long run estimates.

Following the Pesaran et al., (1999) tactic, the panel

ARDL model with long run dynamics is structured as

below.

∆𝐿𝑌𝑖, 𝑡 = 𝛼𝑖 +

∑

β𝑖j∆𝐿𝑌𝑖, 𝑡 − 𝑗 +





∑

ϒik∆LEi, t − k +





∑

Ψip∆𝐿𝐼𝑖, 𝑡 − 𝑝 +





ɤ1LYi, t − 1 +ɸ1𝐿𝐸𝑖, 𝑡 − 1 + ƴ1𝐿𝐼𝑖, 𝑡 − 1 +

ε1i, t

(

)

Yi, t: Represents real gross domestic product in

US dollars based on the 2000 constant price, for i that

represents the cross-section dimension and at the time

t. Ei, t: Stands for renewable energy consumption for

individual i and at the period t. The E is the main

independent variable in this work.

Ii, t: Is the gross fixed capital that represents the

level of investments in US dollars, for individual

country i and at the period t. It is considered as

mediator factor between Y and E. Investing in

renewable energy sector can make possible other

investments that necessitate energy as input which

late stimulate economic growth. To another hand

investments in renewable energy due to the economic

growth, the payback will come again through

investments which need energy as a complement

factor to capital and labour and later this will increase

the economic growth. The Δ and L respectively

represent first differentiator and the logarithmic

expression, i: varies from 1to 5 stands for the cross

countries under the study, t is the period of time, M,

N, Q represent the lag order that must be identical for

all countries under the study while εi, t, is the error

term which must be normally distributed with mean

zero constant covariance and variance.

The equation (1) included the short and long run

equations. The part with first differentiator ∆ stands

for short run equation that includes lagged values of

variables involved in this study and the remaining one

in the right side represents the long run relationship

between renewable energy use and economic growth.

∆𝐿𝑌𝑖, 𝑡 = 𝛼2𝑖 +

∑

β2ij∆LYi, t − j +





∑

ϒ2ik∆Lei, t − k +

∑

Ψ2ip∆LIi, t −









p + ε2i,t (2)

LYi, t = α3i + ɤ2𝐿𝑌𝑖, 𝑡 − 1 + ɸ2𝐿𝐸𝑖, 𝑡 − 1 +

ƴ2𝐿𝐼𝑖, 𝑡 − 1 + ε3i, t (3)

3.2.2 The Pairwise Dumitrescu-Hurlin Panel

Causality Test

Following the model of [20], the renewable energy

consumption and economic growth panel granger

causality for EAC ‘s countries represented by k(1 to

5) is specified as follow:

LYi, t = α4i +

∑

Ω1𝑖k𝐿𝑌𝑖, 𝑡 − 𝑘 +

∑

ɣ1ikLEi, t − k +









∑

ρ1ik𝐿𝐼𝑖, 𝑡 − 𝑘





+u1i,t (4)

LEi, t = α5i +

∑

Ω2𝑖k𝐿𝑌𝑖, 𝑡 − 𝑘 +

∑

ɣ2ikLEi, t − k +









∑

ρ2ik𝐿𝐼𝑖, 𝑡 − 𝑘





+u2i,t (5)

LIi, t = α5i +

∑

Ω3𝑖k𝐿𝑌𝑖, 𝑡 − 𝑘 +

∑

ɣ3ikLEi, t − k +









∑

ρ3ik𝐿𝐼𝑖, 𝑡 − 𝑘





+u3i,t (6)

The dependent variable Yi, t-k, specifies the

dynamic nature of real economic growth and explains

the interdependence of economic growth. It means

that the current economic growth requires the

significance influence of previous growth as well as

the significant influence of the previous values of

renewable energy use and gross fixed capital

formation. Thus, the existence of panel Granger

causality between renewable energy and economic

growth in EAC is proved by the validity as such as

that:

Ω i1=…= Ω𝑖3≠ 0; ɣi1 =…...= ɣi3≠ 0; ρ i1=…...=

ρ i3≠0 (7)

Why Renewable Energy Use Is worth for East African Community (EAC) Countries’ Economies

4 RESULTS AND DISCUSSION

This section presents and discusses results for panel

unit root, panel, and individual country granger

causality among variables.

4.1 Results of the Unit Root Test

The panel unit root tests to check whether data series

is stationary on not is performed using the following

tests: (Levin, Lin & Chu2002; Im, Pesaran & Shin,

2003; Dickey & Fuller, 1979; and Phillips & Perron,

1988) .The outcomes of panel unit root tests at first

difference revealed that all variables are integrated of

order I(1). The results prove that the null hypothesis

of a panel unit root (non-stationarity) at the first

difference of the series is rejected as per majority of

unit root tests. The table 1below shows unit root test

results.

***, ** and * are levels of statistical significance

at 1%,5% and 10% respectively, ** Probabilities for

Fisher tests are computed using an asymptotic Chi-

square distribution. All other tests assume asymptotic

normality. The probability values for the tests are in

parentheses.

4.2 The Panel ARD Results

Based on the results of specified panel ARDL model,

estimates show that the renewable energy use is

dynamically cointegrated with economic growth in

selected EAC countries. As it is revealed by this

investigation, if renewable energy use increases by

1% percent, the economic growth will increase by

0.99%. The adjustment coefficient sign also proves

that the disequilibrium can be at quarterly adjusted on

the rate of 7% to achieve the equilibrium. The

summary of results for dynamic relationship is

presented in table 2.

Table1: Panel unit root test results.

Variable LLI IPS ADF PP

LY -0.153(0.44) -4.81*** 45.47*** 69.12***

LE -0.76 0(0.22) -5.83*** 56.50 *** 80.38***

LI -0.290 (0.38) -6.35*** 62.14*** 91.01***

Table 2: Panel ARDL results for long run and short run.

Long run relationship among variables: LYi, t=-0.4181+ 0.987LEi, t + 0.42 LIi,t

Variable Coefficient Std. Error t-Statistic Prob.

LEi, t 0.987154 0.139678 7.067337 0.0000

LIi,t 0.427631 0.038735 11.03979 0.0000

C -0.418171 0.018260 -22.90113 0.0002

Short run relationship among variables

CointEq(-1) -0.070013 0.000617 -113.4361 0.0000

D (LEi, t) 0.309046 0.005349 57.77703 0.0000

D (LIi, t) 0.189139 0.000629 300.5361 0.0000

4.3 The Pairwise Dumitrescu- Hurlin

Panel Causality Estimates

Employing granger causality based on the causality

test proposed by Dumitrescu-Hurlin (2012) that even

under the presence of cross-sectional dependence is

believed to generate reliable results. The importance

of checking the causation among multiple variables is

intended to prove if previous values of K can be

predictors of Y. In this case the null hypothesis is set

as such K does not granger cause Y. The rejection of

the null hypothesis due to the tiny probability values

is the proof of the link between variables and it is said

that variable K can granger cause variable Y.

The outcomes reported in the table 2, signify that

there is a long rung and a bidirectional relationship

between renewable energy consumption and

economic growth in selected East African Countries

(EAC). These findings are in the line with results of

prior works such as the studies of (Nasreen & Anwar,

CoEEE 2021 - International Joint Conference on Energy and Environmental Engineering

2014;Shakouri & Khoshnevis Yazdi, 2017). Findings

supported that renewable energy use can cause

international trade. This finding relates to one of

Brini, Amara & Jemmali (2017).

The highest level of

significance of probability values validate the idea

that the renewable energy use incites the economic

growth in EA. The causation that runs from

renewable energy use to investments and trade

openness makes sense as the late two variables

witnessed to be best predictors of economic growth.

Furthermore, the two ways causality exists between

investments and trade openness as it is presented in

table3 below.

Table 3. Results of Dumitrescu- Hurlin panel causality tests.

Null h

othesis No of la

AIC criteria W stati Z stat. Prob.value

LE does not cause LY 3 8.37 3.23 0.0013

LY does not cause LE 3 6.09 1.73 0.0844

LI does not cause LY 3 8.052 2.67 0.0076

LY does not cause LI 3 10.41 4.08 0.00005

LI does not cause LE 3 6.33 1.65 0.0997

LE does not cause LI 3 9.96 3.81 0.0001

***, ** and * are levels of statistical significance

at 1%,5% and 10% respectively. The probability

values for the tests are in parentheses.

5 CONCLUSIONS

The contribution of renewable energy use to the

economic growth cannot be neglected among the

factors of pro economic growth in EAC. To find the

dynamic nexus and the route of causation between

main variables of the hypothesized study, the panel

ARDL approach and Pairwise Dumitrescu- Hurlin

Panel Causality techniques have been used. The fact

of long run and two ways causal relationship between

renewable energy and economic growth revealed that

this study qualifies for feedback hypothesis. The

results indicated that the renewable energy use is a

best predictor of economic growth in all selected

EAC countries and vice versa. The outcomes of this

work advocate that using renewable energy is not

useful for environmental purposes, but it at same time

promotes the economic growth especially in

developing countries such as EAC’s countries that

need to promote the manufacturing sector which

necessitates a huge amount of energy for its

operations. The EAC member states should take this

opportunity of membership to bring big profitable

renewable energy projects that can create a regional

competitive advantage. Upcoming investigations

with updated data sets for this critical research point

are valuable as the renewable energy use produces

more economic and environmental advantages that

are harmless to the ecosystem.

ACKNOWLEDGMENTS

The authors are thankful for provided support for this

research. We would also like to thank our anonymous

reviewers for the precious observations for the

completion of this paper.

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