α
1i
elec
t−i
+
q2
∑
i=0
α
2i
y
t−i
+
q3
∑
i=0
α
3i
y
2
t−i
+
q4
∑
i=0
α
4i
y
3
t−i
+
q5
∑
i=0
α
5i
p
t−i
+
q6
∑
i=0
α
6i
imp
t−i
+
∑ I
k
+
γ
t
+
ε
t
(3)
This equation is estimated by OLS, and the AIC and SIC information criteria is used to determine
the lags of the ARDL (q1, q2, q3, q4, q5, q6) model.
In addition, OLS is used to estimate the error correction model for the short-run, and the AIC
and SIC information criteria are used to determinate the order of the ARDL (p1, p2, p3, p4, p5, p6).
In addition, its stability is checked on the basis of the cumulative sum (CUSUM) test and cumulative
sum of squares (CUSUMSQ) test. According to Narayan and Smyth [
58
], and Belloumi [
59
], this model
may be written as:
Delec
t
=
c
+
p1
∑
i=1
β
1i
Delec
t−i
+
p2
∑
i=0
β
2i
Dy
t−i
+
p3
∑
i=0
β
3i
Dy
2
t−i
+
p4
∑
i=0
β
4i
Dy
3
t−i
+
p5
∑
i=0
β
5i
Dp
t−i
+
p6
∑
i=0
β
6i
Dimp
t−i
+
∑ I
k
+
γ
t
+
µ ECT
t−1
+
ε
t
(4)
Finally, the vector error-correction based Granger Causality analysis is used to study the
short-run and long-run Granger causality between variables. If evidence for cointegration is found,
the specification of the Granger causality test may be expressed, according to Engle and Granger [
63
],
as follows:
Delec
t
=
p−1
∑
i=1
β
1i
Delec
t−i
+
p−1
∑
i=0
β
2i
Dy
t−i
+
p−1
∑
i=0
β
3i
Dy
2
t−i
+
p−1
∑
i=0
β
4i
Dy
3
t−i
+
p−1
∑
i=0
β
5i
Dp
t−i
+
p−1
∑
i=0
β
6i
Dimp
t−i
+
∑ I
k
+
γ
t
+
τECT
t−1
+
ε
t
Dy
t
=
p−1
∑
i=0
β
1i
Delec
t−i
+
p−1
∑
i=1
β
2i
Dy
t−i
+
p−1
∑
i=0
β
3i
Dy
2
t−i
+
p−1
∑
i=0
β
4i
Dy
3
t−i
+
p−1
∑
i=0
β
5i
Dp
t−i
+
p−1
∑
i=0
β
6i
Dimp
t−i
+
∑ I
k
+
γ
t
+
τECT
t−1
+
ε
t
Dp
t
=
p−1
∑
i=0
β
1i
Delec
t−i
+
p−1
∑
i=0
β
2i
Dy
t−i
+
p−1
∑
i=0
β
3i
Dy
2
t−i
+
p−1
∑
i=0
β
4i
Dy
3
t−i
+
p−1
∑
i=1
β
5i
Dp
t−i
+
p−1
∑
i=0
β
6i
Dimp
t−i
+
∑ I
k
+
γ
t
+
τECT
t−1
+
ε
t
Dimp
t
=
p−1
∑
i=0
β
1i
Delec
t−i
+
p−1
∑
i=0
β
2i
Dy
t−i
+
p−1
∑
i=0
β
3i
Dy
2
t−i
+
p−1
∑
i=0
β
4i
Dy
3
t−i
+
p−1
∑
i=0
β
5i
Dp
t−i
+
p−1
∑
i=1
β
6i
Dimp
t−i
+
∑ I
k
+
γ
t
+
τECT
t−1
+
ε
t
(5)
where ECT
t−1
is one-period lagged error correction term and τ indicates the adjustment speed to reach
the equilibrium. The Wald statistics of the lagged explanatory variables coefficients inform about the
short-run causal effects, while the Wald statistic of τ informs about the long-run causal effect.
Energies 2018, 11, 1656
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3. Data and Descriptive Analysis
Table
1
summarizes the main statistics of the variables. All variables refer to the period from 1970
to 2013. Data on residential electricity consumption, GDP, imports of goods and services and total
population come from the World Development Indicators database [
64
]. Electricity price data come
from the information provided by the Official Journals of the Algerian Government [
65
]. Real electricity
price have been considered in this study. Nevertheless, the nominal price is also shown in Table
1
and
Figure
1
to explain the real price trend.
Table 1.
Descriptive statistics.
Variable
Mean
Max.
Min.
Std. Dev.
Obs.
Residential electricity consumption (kWh per capita)
563.22
1277.37
133.08
296.02
44
GDP per capita (at constant 2010 US$)
3646.85
4617.51
2322.06
528.09
44
Imports of goods and services (% of GDP)
27.78
42.96
18.41
5.58
44
Real Electricity price (at constant 2010 DZD * per kWh)
0.48
7.03
0.016
1.11
44
Price of electricity (DZD * per kWh)
1.32
2.97
0.37
1.11
44
DZD *: The Algerian Dinar (national currency of Algeria).
The top left graph in Figure
1
shows the residential electricity consumption per capita trend.
A continuously positive growth is observed through the period. This growth is in line with the growing
trend in Algerian electricity consumption observed over the last forty years. According to Bélaïd and
Abderrahmani [
15
], this strong demand for electricity can be explained by two factors: the expansion
of economic activities and the population growth. Although the Algerian Government had been
establishing several development plans to boost economic growth by developing and modernizing
the industry sector, which had led to increasing electricity consumption, the growth of Algerian
residential electricity consumption has been higher than that of industry, especially over recent years.
While, in 1990, electricity use by the industry sector was 48.5% of total electricity consumption and the
electricity use by the residential sector was 49.15%; in 2014, the industry sector electricity consumption
was only 35% and the residential consumption was more than 63%. This greater residential electricity
consumption may be explained by several factors, such as changes in lifestyles [
15
].
The top right graph in Figure
1
shows the Algerian GDP per capita trend. Over these forty four
years, Algeria has not experienced a significant global growth, the average annual growth rate being
equal to 1.25%. Three main periods are observed in its evolution. In the first period, from 1970 to
1979, the GDP per capita experienced a strong positive trend. From 1970, Algeria adopted a centrally
planned command economy, formulating two four-year plans: from 1970 to 1973 and from 1974 to
1977. This organization led to enormous physical capital investments which, according to Zouache [
66
],
could explain the notable growth of the Algerian economy. The average investment rate was 28.3%
from 1970 to 1973 and 40.4% from 1973 to 1978 [
67
]. Over the second period, from 1980 to 1994,
the GDP per capita decreased to $3165.90 in 1994. This situation was the consequence of several
factors, especially the oil price crashes in 1979 and 1986 and the political instability in the early 1990s.
Finally, from 1994, the GDP per capita again started to increase significantly. In 1994, Algeria suffered
from the first IMF stabilization program, and one year later from the second. In general, the aims
of these stabilization programs were to liberalize the economy, from socialism to a market-oriented
economy [
66
]. In particular, these programs had two main objectives: to strongly increase investment
in public infrastructures and to decrease the unemployment rate by stimulating domestic demand [
68
].
Finally, at the end of the nineties, this strategy benefited from a favorable context, due to a better
political climate and rising oil prices.
The graph at the bottom left of Figure
1
shows the evolution of imports with respect to GDP.
Four main stages can be observed. From 1970 to 1975, a notable growth of imports is shown, which
may be related to the development system implemented in Algeria, based on strong industrialization.
This system generated notable semi-finished products and industrial equipment imports. From 1975
Energies 2018, 11, 1656
7 of 18
to 1987, a prominent decreased is observed. This decline was mostly caused by the fall in the value of
oil exports, and over these years, export revenues paid for nearly 80% of imports. From 1987 to 2006,
an evolution with peaks and troughs is observed around a percentage value equal to 22%. Finally,
from 2006, the imports percentage starts growing again, except for 2009–2010. This rise was due to the
increase in imported goods to cover the needs of the economic recovery program and to satisfy the
increasing demands of the population [
69
].
Energies 2018, 11, x FOR PEER REVIEW
7 of 18
the fall in the value of oil exports, and over these years, export revenues paid for nearly 80% of
imports. From 1987 to 2006, an evolution with peaks and troughs is observed around a percentage
value equal to 22%. Finally, from 2006, the imports percentage starts growing again, except for
2009–2010. This rise was due to the increase in imported goods to cover the needs of the economic
recovery program and to satisfy the increasing demands of the population [69].
Figure 1. Graphs of studied variables. DZD *: The Algerian Dinar (national currency of Algeria).
Finally, the graph at the bottom left of Figure 1 shows the evolution of the annual average
household real electricity price. Over the whole period, the Algerian Government fixed and
subsidized the electricity prices. It is worth noting that the production and the distribution of
electricity are completely in the hands of the government company, namely SONELGAZ. From 1970
to 1994, the prices remain quite constant around constant 2010 DZD 0.05 per kWh. Since then, the
Algerian Government proceeded to increase the household electricity price. As from June 1994, the
household electricity prices became different for those consuming less or more than 500 kWh per
year. In addition, gas and electricity quarterly price revision systems were implemented and most
controls were eliminated, raising electricity prices toward their opportunity cost. Therefore, the
Figure 1.
Graphs of studied variables. DZD *: The Algerian Dinar (national currency of Algeria).
Finally, the graph at the bottom left of Figure
1
shows the evolution of the annual average
household real electricity price. Over the whole period, the Algerian Government fixed and subsidized
the electricity prices. It is worth noting that the production and the distribution of electricity are
completely in the hands of the government company, namely SONELGAZ. From 1970 to 1994,
the prices remain quite constant around constant 2010 DZD 0.05 per kWh. Since then, the Algerian
Government proceeded to increase the household electricity price. As from June 1994, the household
electricity prices became different for those consuming less or more than 500 kWh per year. In addition,
gas and electricity quarterly price revision systems were implemented and most controls were
Energies 2018, 11, 1656
8 of 18
eliminated, raising electricity prices toward their opportunity cost. Therefore, the electricity price grew
with the greater liberalization [
70
]. Nevertheless, after few years, the electricity prices only adjusted
partially to the increasing cost of living, becoming much lower again. Additionally, the real electricity
prices growth between 1995 and 2000 may be also explained by the Algerian currency devaluation on
April 1994 (40.17%). This devaluation had remarkable negative effect on the purchasing power [
70
].
4. Results
4.1. Break Point Unit Root Test (Selection of Structural Break Point)
Table
2
shows the results of the Lee-Strazicich two breaks unit root test. The LM unit root test
rejects the unit root null for y and imp, while do not reject the unit root null for the others. In addition,
the results also show that there are six structural break points from 1987 to 2002 (1987, 1994, 1995,
2000, 2001 and 2002). Indeed, since the end of the 1980s, the Algerian economy has experienced real
mutations. After the oil crisis of 1986, the Algerian Government started to initiate economic reforms
aimed at transforming from a socialist to a liberal economy [
66
]. Later on, the Algerian Government
adopted a structural adjustment plan in 1994. In order to capture these economic changes, the dummy
variable of the year 1987 and that related to the structural adjustment plan period (1994–2002) have
been introduced into the econometric analysis. The first variable takes the value one for the year
1987 and zero otherwise. The second variable takes the value one for the years 1994 to 2002 and
zero otherwise.
Table 2.
LM two breaks unit root test (Lee-Strazicich test [
53
]).
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