Proceedings of 5th Annual American Business Research Conference
6 - 7 June, 2013, Sheraton LaGuardia East Hotel, NY, USA, ISBN: 978-1-922069-24-5
The Causation between Energy Consumption and Gross
Domestic Product (GDP): A Multi-Sectoral and Comparative
Investigation from Five Continents (1980-2009)
Yasir Hassan, Kashif-ud-Din and Farzan Yahya
Consumption is generally the major GDP. Many persons review the economic
performance of their state primarily in terms of ingesting level and dynamics.
The focal point of this study is to determine effect between energy consumption
and GDP. Previous studies show no conformity or no relationship of gross
domestic product with personal consumption expenditure though this study
shows strong relation of GDP with energy consumption. SPSS and Microsoft
Excel, both have utilized to accomplish this research and generate results as
per objectives. Furthermore, many tests and statistical techniques have applied
to validate the results. Coefficient of variance has applied to corroborate most
consistent consumption years. ANOVA has tested to compare the regions and
identify the mean differences and to further authenticate the results LSD has
concerned. Finally, regression model has instigated to verify positive or
negative relation between GDP and energy consumption.
Keywords: GDP, ANOVA, LSD, OLS, Regions, Consumption
Introduction
First, ingesting might have estranged with respect to the permanence of bought objects.
This component, a wide cataloging splits durable merchandise (as carriages and T.V.
sets) from non-durable commodities and from amenities. These classes frequently
illustrate dissimilar tracks of expansion.
Secondly, consumption has separated giving to requirements it gratifies. A frequently
used cataloging recognizes 10 sections of expenditure:
i.
Nourishment
ii.
Heating & energy
iii.
Health
iv.
Housing
v.
Clothing and foot wear
vi.
Communication
vii.
Home fixtures and appliances
viii.
Culture and schooling
ix.
Transport
x.
EntertainingThe rich have equally advanced stages of ingesting & investments.
In distinguished markets, wealthy people can typically purchase healthier goods than
deprived ones. In supplementary terms, ingesting is contingent on societal clusters and
their behaviors.
Proceedings of 5th Annual American Business Research Conference
6 - 7 June, 2013, Sheraton LaGuardia East Hotel, NY, USA, ISBN: 978-1-922069-24-5
Third, one should distinguish "consumption" as utilization of belongings & facilities from
"ingesting spending" as trade operations. For sturdy commodities, this change might be
applicable, meanwhile they have used for extensive eras.
In this lode, the rich have a much wider growing package of durable goods bought over
time, so they take pleasure in a very extensively higher degree of need contentment,
whereas the poor can experience deficiencies even in the most indispensable goods.
Fourth, only recently produced merchandise enter into the meaning of consumption,
whereas the purchase of, say, an old home is not measured consumption in
macroeconomics, given that it was already calculated in the GDP of the time in which it
was assembled. For the user, both old and new goods offer some need fulfillment.
Energy consumption is apparently elevated in countries where below 5 percent of the
population lives lower than the poverty line than it is in states where the majority of
people live in scarcity four times greater. For instance, Americans make up below 5% of
the world’s population yet use 26% of the world’s energy.
Simultaneously, the United States and Canada account for 50 percent of power
consumed by the world’s wealthiest mechanized countries; Europe, 33 percent. When
there is a talk about energy consumption, then it is about the supply of energy that
produces our power: coal, oil, natural gas and alternatives like wind, solar, hydropower
and bio-fuels. (Brazil, for example, produces electricity by flaming sugarcane waste.)
Presently, the world’s population devours 15 terawatts of power from a blend of these
energy sources.
Communally, developing countries utilize 30 percent of the earth’s energy, but with
anticipated population and fiscal growth in those marketplaces, energy demands have
expected to climb 95 percent. In general, global consumption has expected to increase
50 percent from 2005 to 2030, mainly in the fossil-fuel zone.
At-least share of the increase in worldwide feasting is the consequence of populace
enlargement. The U.N. missions that world population will boost 41% in 2050 to
8.9(Billion) persons, by almost all of this expansion in developing countries.
This flow in human figures intimidates to offset any savings in resource use from
improved competence, over and above any gains in falling per-capita consumption.
Even though the standard American eats 20 percent fewer meat in 2050 than in 2000,
entire U.S. meat captivating will be 5 million tons larger in 2050 due to population
growth.
A rising share of the worldwide consumer group now subsists in developing countries.
China and India unaided claim above 20 percent of the global sum—with a shared
consumer group of 362 million, surplus in all of Western Europe. (Nevertheless, the
average Chinese or Indian member consumes significantly below the standard
European.)
Proceedings of 5th Annual American Business Research Conference
6 - 7 June, 2013, Sheraton LaGuardia East Hotel, NY, USA, ISBN: 978-1-922069-24-5
Developing countries also have the maximum potential to enlarge the lines of
consumers. China and India’s large consumer class comprises only 16 percent of the
region’s inhabitants, while in Europe the number is 89 percent. Certainly, in most
developing countries the consumer set accounts for below half of the population—
signifying substantial room to grow.
While the consumer class flourishes, great disparities linger. The 12 percent of the
world’s population that survives in North America and Western Europe reports for 60
percent of classified consumption expenses, whilst the one-third existing in South Asia
and sub-Saharan Africa reports for merely 3.2 percent.
The consumer civilization has strong magnetism and carries with it many financial
benefits, and it would be unjust to argue that those who come later should not share the
advantages gained by an earlier cohort of consumers. Undeniably, lack of concentration
to the needs of the poorest can effect in greater uncertainty for the prosperous and in
augmented spending on self-protective measures. The necessity to spend billions of
dollars on wars, boundary security, and mediation debatably has linked to ignorance for
the world’s imperative social and environmental tribulations.
Regardless of increasing utilization in the developing world, manufacturing countries
remain in charge for the immensity of the world’s reserve consumption—over and above
the associated global environmental squalor. Yet there is little proof that the
consumption locomotive is braking, still in the United States, where the majority of
people are adequately supplied with the goods and services required to lead a decorous
life.
Individuals often face personal expenses related with serious altitudes of consumption:
the monetary debt; the time and strain related with working to shore up high
consumption; the time required to hygienic, advance, store, or otherwise keep
possessions; and the ways in which consumption restores time with family and friends.
Belligerent pursuit of a throng consumption society also associates with a decline in
health gauges in many countries, as corpulence, offense, and other social ills persist to
surge.
Consumer advocates, economists, policymakers, and ecologist have developed
inventive options for meeting people’s requirements while dampening the ecological and
social costs associated with bunch consumption. As well as serving individuals locate
the balance between surplus and insufficient consumption, they stress placing more
importance on publicly provided commodities and services, on services instead of
goods, on goods with elevated levels of recycled content, and on authentic option for
consumers.
Governments can redesign economic inducements and regulations to make sure that
businesses offer reasonable options that congregate consumers’ requirements. They
Proceedings of 5th Annual American Business Research Conference
6 - 7 June, 2013, Sheraton LaGuardia East Hotel, NY, USA, ISBN: 978-1-922069-24-5
also have a responsibility for limiting consumption glut, chiefly by eliminating incentives
to consume—from subsidized energy to endorsement of low-density expansion.
Objectives
The objectives of this research are as follows:
1. To identify most highest GDP and energy consumption regionally
2. To corroborate most consistent consumption years
3. To test out if there are any mean differences regionally by taking all variables
dependent one by one
4. To check positive or negative effect of consumption on GDP
Literature review
Chioma applied regression analysis to scrutinize the casual association between GDP
and individual consumption expenditure of Nigeria by facts and figures from 1994 2007. A non-insignificant value of 0.0514 was found as a slope coefficient
demonstrating that an increase in GDP has no significant result on the individual
ingesting spending of Nigeria.
Goudie and Ladd (1999) described there are indications that here is possibly an
adverse outcome in the opposite way, to inferior growth from high disparity. Countries
with extreme inequality of land and ingesting, may then be less effective at declining
poverty, because they change a given growth rate into leisurelier poverty reduction
Taylor and Weiserbs (1972) originate a positive collision of advertising on consumption.
Therefore, the informative function of advertising shows to be strong enough to motivate
potential consumer to boost their consumption expenditure.
Heckman (1974) shows that if consumption and leisure are substitutes for each other,
consumption also intensifies over the lifecycle. This explains a optimistic association
between consumption and existing income in a lifecycle model. Browning, Deaton and
Irish (1985) and Macurdy (1981, 1983, 1985) added comprehensive this theory and
practiced its experiential cogency.
Samuelson inspects a model of an evolutionary environment in which Nature optimally
builds comparative consumption effects into predilections in order to compensate for
imperfect ecological information. (Samuelson, 2004)
Per capita energy ingesting has been one of maximum frequently used metrics of
ingesting for a figure of motives. It is informal to amount (comparative to resources
usage), it has simply adaptable components (joule, calories, etc.), and every unit of
energy ingesting is environ mentally evocative (in terms of green-house gas releases).
Up till now understanding of national per/capita feasting of any reserve propose partial
Proceedings of 5th Annual American Business Research Conference
6 - 7 June, 2013, Sheraton LaGuardia East Hotel, NY, USA, ISBN: 978-1-922069-24-5
insight for strategy act, meanwhile differences within inhabitants can be countless, they
are meaningfully prejudiced by household features. (Currann and de Sherbinine, 2004)
Study in California originate that energy consumption for a single individual household
was only half that of four and five person households (Lutzenhiser, 1997).
Spangenberg and Lorek (2002) have recognized three household ingesting "bunches"
that collected account for closely (70%) of an economy's material abstraction and
energy consumption, and more than (90%) of land use.
A closer look at the dealt merchandises show that India’s export and import baskets are
extremely varied compared to other associates of the region. India’s sale of production
is sophisticated and it has better competences in the production of certain products than
other states of the region can offer. (Mohanty 2003)
Islam and Clarke (2002) integrate price advantage study of financial growth in an
embryonic economy in operating the attuned GDP, uttered as the cost benefit adjusted
GDP.
Hicks (1940) and Pigous (1962) started with actual GDP as an amount of societal
wellbeing. Whilst Pigous recognized that well-being was more than the amount of
financial actions that GDP measures and thus was not a indicator "or index of entire
welfare" (Pigou, 1962, p. 12)
The claim of welfare monetary tools to development economics safeguards that
"progress is not one of a matter of long run development" (Sen, 1999, p. 45).
Somewhat, it can be consider that chances and prerogatives of people to guarantee
that their humanoid progress can occur both in times of high and low economic growth
(Sen, 1984).
Methodology
This research has accomplished with analysis on secondary data. Data has been
collected from financial websites. Energy consumption and GDP of all countries has
brought together and then further accumulate them regionally. Two types of software
have utilized to make this research comprehensive, Statistical Software for Social
Sciences and Microsoft Excel. Furthermore, Graphical representation has prepared for
more concise review of data. Coefficient of variances has applied to corroborate the
most consistent years. Moreover, statistical tests like ANOVA, LSD and Regression has
applied to validate the results.
Limitations
Some consumption variables were in Barrels and some in Tons. Moreover, data of
consumption commodities of some countries were not given for few years.
Proceedings of 5th Annual American Business Research Conference
6 - 7 June, 2013, Sheraton LaGuardia East Hotel, NY, USA, ISBN: 978-1-922069-24-5
Empirical Results
Prior to moving toward testing of hypothesis and inferential study of data, there is
graphical representation for a precise review of data. Following is the Line chart for
GDP including all regions:
Chart No. 1: GDP (in million Dollars) of all Regions
25000000
GDP of all Regions (1980-2008)
GDP africa
20000000
GDP Asia
15000000
GDP Central America
GDP Europe
10000000
GDP North America
5000000
GDP Oceania
GDP South America
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
0
The above chart no. 1 shows the GDP of all Africa, Asia, Europe, Oceania and Central, North
and South America from 1980-2008. The line of this chart shows that Central America had least
GDP as compared to other regions. GDP of Africa and Oceania was overlapping and had
approximately same growth. GDP of South America had slightly greater growth as compared to
Oceania, Africa and Central America. However, GDP growths of North America, Asia and
Europe were far above the ground. Asia had some appreciated GDP growth as it slashes the
GDP of Europe after year 2000.
Chart No. 2: Total Average Consumption of Regions
Total Average Consumption of Regions (19802009)
4000
3000
2000
1000
0
Consumption
Africa
Asia
C.
Europe
N.
Oceania
S.
America
America
America
Region
Proceedings of 5th Annual American Business Research Conference
6 - 7 June, 2013, Sheraton LaGuardia East Hotel, NY, USA, ISBN: 978-1-922069-24-5
The Chart no. 2 shows the total average consumption of all regions for two decades. The
commodities of consumption includes Coal, Crude oil, Distillate fuel, Dry natural gas,
hydroelectric power, Jet Fuel, Kerosene, Liquefied Petroleum gases, Motor Gasoline, Nuclear
electrical power, Geothermal, Solar, Wind, Wood waste, Other Petroleum and Residual fuel.
The bars of this chart show that South America had leading consumption and Europe had
nominal energy usage as compared to other regions which are made known in table above.
Measuring Consistency with Co-efficient of Variance
Co-efficient of variance has applied to be acquainted with consistent years regarding
consumption of energy. C.V. can be evaluated by using following formula:
Table No. 1: Consistency measure for consumption
Year
s
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
Coal
181.9
7
179.9
5
180
178.7
6
178.5
7
178.6
7
177.2
1
176.6
8
175
177.3
8
178.7
3
181
180.5
4
182.2
8
181.6
2
179.8
4
134.9
4
C. Oil
70.19
2
68.51
9
65.87
3
65.87
3
66.15
4
66.66
7
66.91
2
66.91
2
64.49
3
65.49
3
65.97
2
65.97
2
66.43
8
69.59
5
68.18
2
68.59
81.02
2
D.
Fuel
138.2
2
138.5
9
138.7
4
139.5
9
140.0
2
140.8
3
216.6
3
216.6
5
217.0
4
216.8
8
217.3
3
217.5
7
217.8
2
218.3
3
218.1
6
217.8
7
153.0
8
D. N.
G.
102.38
98.889
102.86
97.945
96.575
95.333
94.805
H. P.
55.0
7
54.2
5
57
56.3
4
55.5
1
55.1
5
85.714
54.9
54.1
3
53.3
9
52.6
3
51.8
6
51.2
5
84.659
49
85.714
47.9
48.6
3
48.4
1
67.8
1
92.208
92.208
91.772
89.157
85.484
82.653
98.802
J.
Fuel
110.2
4
111.2
5
167.7
6
171.9
6
116.2
9
175.7
2
175.3
8
173.6
168.9
4
173.0
5
161.5
4
158.0
7
134.5
4
134.5
5
134.7
9
134.8
2
108.2
7
Kerosen
e
147.707
4
143.595
4
74.0217
4
71.0526
3
65.0519
61.2903
2
63.8636
4
58.4146
3
57.5547
9
58.0801
9
76.7103
3
76.2228
3
81.1617
78.0219
8
83.8351
8
83.0275
2
87.1359
2
L.
Gases
130.892
1
137.413
1
155.879
2
150
162.195
1
161.410
4
162.108
3
153.790
6
149.053
2
157.084
149.006
6
146.382
1
145.140
4
143.764
9
149.597
1
143.333
3
132.573
7
M. G.
138.4
7
137.1
7
137.2
5
138.4
1
138.9
2
139.1
6
141.8
141.7
9
140.6
2
140.1
5
216.1
3
216.5
2
135.9
1
136.0
8
135
135.6
9
109.4
6
N. E.
P.
99.80
6
102.2
3
107.1
3
147.2
5
103.9
5
144.2
9
142.4
6
138.7
4
138.5
9
140.7
3
140.6
5
139.7
9
140.5
4
141.2
3
139.9
6
138.7
4
156.5
1
O. E.
132.9
128.0
2
121.3
3
120.5
4
116.0
3
107.3
4
104.7
2
99.45
7
96.42
9
94.96
4
92.76
3
90.29
5
91.58
9
92.09
6
95.03
9
96.75
1
108.7
8
O. P.
164.2
1
168.4
169.1
170.0
7
170.5
8
163.7
7
154.5
2
161.8
8
165.8
4
166.9
7
160.3
4
164.0
9
212.4
8
168.5
4
162.2
3
159.6
154.7
6
R.
Fuel
136.0
1
135.9
2
135.2
2
135.8
8
135.7
6
135.0
2
135.0
6
135.1
135.1
2
135.4
2
135.2
1
135.1
5
135.1
135.7
6
135.4
2
135.2
1
123.8
9
To evaluate the above results, firstly S.D. and Means of all consumption variables has
determined and then C.V. for all years has calculated. Table no. 1 shows C.V. from year
1990-2006. Results show that Distillate Fuel and Nuclear Electric Power were
consistent in year 1990, Crude Oil and Kerosene in year 1998 and Coal, Jet Fuel, Motor
Gasoline and Residual Fuel shows consistency in 2006. Other consumption variables
with consistent years can be reviewed in the table.
Proceedings of 5th Annual American Business Research Conference
6 - 7 June, 2013, Sheraton LaGuardia East Hotel, NY, USA, ISBN: 978-1-922069-24-5
ANOVA
ANOVA has applied to analyze the variances and to compare the means for all regions.
The hypothesis for this test can be as follows:
H0: Africa=Asia=Central America and the Caribbean= Europe= North America= Oceania= South
America
H1: At Least one Region has different Means
ANOVA for GDP
Taking GDP as dependent variable following is the table for ANOVA:
Table no. 2: ANOVA for GDP
SS
df
MS
Between
Groups
Within Groups
Total
F
3894071735936400.00
4.00 973517933984100.00 125.27
1095746888800420.00 141.00
7771254530499.48
4989818624736830.00 145.00
P-val
0.00
Table no. 2 shows highly significant value that is 0.00, which is less than 0.05. Hence, it
can be concluded for this test that H1 can be accepted. It means there is at least one
region that have different mean, in case of GDP. However, to hit upon the different
means, LSD has applied.
LSD is Post Hoc test to determine the difference in means. Following is the LSD table
for GDP:
Table no. 3: LSD test for GDP
Dependent Variable:
GDP
(I) Regions
Africa
Asia
Central America
& the Caribbean
Europe
(J) Regions
Asia
Europe
North America
Central
America
& the
Caribbean
Europe
North America
Europe
North America
North America
Mean Difference (IJ)
-10102394.33
-11959964.89
-6800593.39
Std. Error
725958.75
732085.10
732085.10
10832768.73
-1857570.56
3301800.94
725958.75 0.00
725958.75 0.01
725958.75 0.00
-12690339.29
-7530967.79
5159371.50
732085.10 0.00
732085.10 0.00
732085.10 0.00
Sig.
0.00
0.00
0.00
Table no. 3 shows that Africa has significantly different mean while contrasting with
Asia, Europe and North America. Similarly, Asia has different mean values with Central
Proceedings of 5th Annual American Business Research Conference
6 - 7 June, 2013, Sheraton LaGuardia East Hotel, NY, USA, ISBN: 978-1-922069-24-5
America, Europe and North America. Central America has different means with Europe
and North America. Moreover, Mean difference value of Europe with North America is
also specified.
Table no. 4: ANOVA for Consumption
Dependent
variable
(Consumption)
Coal
Crude Oil
Distillate Fuel
Dry Natural Gas
Hydroelectric
Power
Jet Fuel
Kerosene
Liquefied
Petroleum
Gases
Motor Gasoline
SS
Between
Groups
Within Groups
Total
Between
Groups
Within Groups
Total
Between
Groups
Within Groups
Total
Between
Groups
Within Groups
Total
Between
Groups
Within Groups
Total
Between
Groups
Within Groups
Total
Between
Groups
Within Groups
Total
Between
Groups
Within Groups
Total
Between
Groups
Within Groups
df
MS
F
P-val
5874213.83
6.00
9664579.65 201.00
15538793.48 207.00
979035.64
48082.49
20.36
0.00
6422727.87
6.00
5259117.94 201.00
11681845.82 207.00
1070454.65
26164.77
40.91
0.00
10202815.83
6.00
7380933.29 156.00
17583749.12 162.00
1700469.30
47313.67
35.94
0.00
2607305.37
6.00
5338494.83 201.00
7945800.20 207.00
434550.89
26559.68
16.36
0.00
11372314.59
6.00
2013948.65 182.00
13386263.25 188.00
1895385.77
11065.65
171.29
0.00
4107449.40
6.00
5365616.96 156.00
9473066.35 162.00
684574.90
34394.98
19.90
0.00
1145792.97
6.00
4198650.20 156.00
5344443.17 162.00
190965.49
26914.42
7.10
0.00
2113109.35
6.00
5417663.04 156.00
7530772.40 162.00
352184.89
34728.61
10.14
0.00
12126525.34
6.00
2505199.00 156.00
2021087.56
16058.97
125.85
0.00
Proceedings of 5th Annual American Business Research Conference
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Nuclear
Electric
Power
Other
Electric
Power
Other
Petroleum
Residual Fuel
Total
Between
Groups
Within Groups
Total
Between
Groups
Within Groups
Total
Between
Groups
Within Groups
Total
Between
Groups
Within Groups
Total
14631724.34 162.00
9995300.44
6.00
4521831.33 182.00
14517131.77 188.00
1665883.41
24845.23
67.05
0.00
114860.88
6.00
120279.97 182.00
235140.85 188.00
19143.48
660.88
28.97
0.00
5831954.81
6.00
3392788.34 156.00
9224743.15 162.00
971992.47
21748.64
44.69
0.00
1059667.66 2106.41
503.07
0.00
6358005.96
6.00
78478.80 156.00
6436484.76 162.00
Above table no. 4 shows ANOVA table presuming energy consumption as dependent
variable. The results of this test show highly significant values for all variables. All
consumption variables are less than 0.05. Consequently, it can be said that at least one
region has different mean from others. For further proceedings of result LSD has
concerned.
Since the LSD table for consumption was so extensive, therefore it has segregated into
three parts.
Table no. 5: LSD for Coal, Crude Oil, Distillate Fuel, Dry Natural Gas and Hydroelectric Power
Dependent Variable
(I) Country codes
(J) Country codes
Coal
Africa
Asia
Asia
Central America
Europe
Mean Difference (I-J)
Std. Error
Sig.
171.00
56.62
0.00
Central America
-289.55
56.62
0.00
Europe
171.80
56.62
0.00
North America
-182.63
56.62
0.00
South America
142.73
57.62
0.01
Central America
-460.55
56.62
0.00
North America
-353.63
56.62
0.00
Oceania
-138.93
56.62
0.02
Europe
461.35
56.62
0.00
Oceania
321.62
56.62
0.00
South America
432.28
57.62
0.00
North America
-354.43
56.62
0.00
Oceania
-139.73
56.62
0.01
Proceedings of 5th Annual American Business Research Conference
6 - 7 June, 2013, Sheraton LaGuardia East Hotel, NY, USA, ISBN: 978-1-922069-24-5
Africa
182.63
56.62
0.00
Asia
353.63
56.62
0.00
Europe
354.43
56.62
0.00
Oceania
214.70
56.62
0.00
South America
325.36
57.62
0.00
Africa
Central America
-508.39
41.77
0.00
Central America
Asia
490.42
41.77
0.00
Europe
494.19
41.77
0.00
North America
489.39
41.77
0.00
Oceania
508.82
41.77
0.00
South America
507.29
42.50
0.00
Asia
569.97
64.20
0.00
Central America
448.82
65.58
0.00
Europe
647.76
64.20
0.00
North America
649.25
63.59
0.00
South America
271.36
65.58
0.00
Oceania
-497.54
62.79
0.00
South America
-298.61
64.20
0.00
Europe
198.94
64.20
0.00
North America
200.42
63.59
0.00
Oceania
-376.40
64.20
0.00
South America
-177.47
65.58
0.01
Oceania
-575.33
62.79
0.00
South America
-376.40
64.20
0.00
North America
South America
-377.89
63.59
0.00
Africa
Central America
-269.16
42.08
0.00
Asia
Central America
-328.93
42.08
0.00
Oceania
-111.59
42.08
0.01
Europe
317.07
42.08
0.00
North America
318.97
42.08
0.00
Oceania
217.34
42.08
0.00
South America
340.71
42.82
0.00
Europe
Oceania
-99.73
42.08
0.02
North America
Oceania
-101.63
42.08
0.02
Oceania
South America
123.37
42.82
0.00
Africa
Asia
-379.16
28.63
0.00
Europe
-544.88
28.63
0.00
North America
-543.53
28.63
0.00
South America
-340.42
28.63
0.00
Central America
428.69
28.63
0.00
North America
Crude oil
Distillate Fuel
Africa
Asia
Central America
Europe
Dry Natural Gas
Central America
Hydroelectric
Power
Asia
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Central America
Europe
North America
Oceania
Europe
-165.72
28.63
0.00
North America
-164.37
28.63
0.00
Oceania
395.65
28.63
0.00
Europe
-594.41
28.63
0.00
North America
-593.06
28.63
0.00
South America
-389.95
28.63
0.00
Oceania
561.37
28.63
0.00
South America
204.46
28.63
0.00
Oceania
560.02
28.63
0.00
South America
203.11
28.63
0.00
South America
-356.91
28.63
0.00
Table above (table no. 5) includes LSD test for energy consumption variable. In case of,
Coal consumption Africa has mean difference values comparing with Asia, Central
America, Europe, North America and South America. Other comparison has done and
showed in the table with significant different means. Assuming Crude Oil consumption
as dependent variable, Africa has significant different means with Central America and
Central America has difference with Asia, Europe, North America, Oceania and South
America. Analysis of Distillate Fuel, Dry Natural Gas and Hydroelectric Power
consumption has also mentioned in the table with mean difference between different
regions.
Table no. 6: LSD for Jet Fuel, Kerosene, Liquefied Petroleum Gases and Motor Gasoline
Dependent Variable
(I) Country codes
(J) Country codes
Jet Fuel
Africa
Asia
Std. Error
Sig.
-387.07
54.74
0.00
North America
125.77
54.21
0.02
Central America
469.30
54.74
0.00
Europe
305.29
53.54
0.00
North America
512.84
53.00
0.00
Oceania
391.41
53.54
0.00
South America
407.45
54.74
0.00
Central America
Europe
-164.00
54.74
0.00
Europe
North America
207.55
53.00
0.00
North America
Oceania
-121.43
53.00
0.02
Africa
Asia
-183.59
48.42
0.00
Asia
Central America
279.82
48.42
0.00
Europe
188.18
47.36
0.00
North America
219.23
46.88
0.00
Oceania
152.36
47.36
0.00
South America
244.09
48.42
0.00
Oceania
-127.46
48.42
0.01
Asia
Kerosene
Central America
Mean Difference (I-J)
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Liquefied Petroleum
Gases
Africa
123.27
56.19
0.03
North America
168.28
54.48
0.00
South America
-204.30
56.19
0.00
Central America
121.60
55.01
0.03
North America
166.62
53.26
0.00
South America
-205.96
55.01
0.00
Europe
-178.89
55.01
0.00
South America
-327.57
56.19
0.00
North America
223.90
53.26
0.00
Oceania
129.13
53.80
0.02
South America
-148.68
55.01
0.01
North America
South America
-372.58
54.48
0.00
Africa
Asia
476.64
37.40
0.00
Central America
344.24
38.21
0.00
Europe
529.53
37.40
0.00
North America
524.02
37.04
0.00
South America
-181.91
38.21
0.00
Central America
-132.40
37.40
0.00
Oceania
-473.88
36.58
0.00
South America
-658.55
37.40
0.00
Europe
185.30
37.40
0.00
North America
179.78
37.04
0.00
Oceania
-341.48
37.40
0.00
South America
-526.14
38.21
0.00
Oceania
-526.78
36.58
0.00
South America
-711.44
37.40
0.00
Oceania
-521.26
36.21
0.00
South America
-705.92
37.04
0.00
South America
-184.67
37.40
0.00
Asia
Central America
Europe
Motor Gasoline
Asia
Central America
Europe
North America
Oceania
Central America
Resuming LSD test for consumption variables, first one is about Jet Fuel consumption
in table no. 6. Results show that Africa has mean difference with Asia and North
America, Asia with Europe, Oceania and Whole America, Central America with Europe,
Europe with North America and last but not least North America with Oceania.
Furthermore, Results of testing Kerosene consumption shows that Africa and Asia have
different means, Asia has different mean as compared to Europe, Oceania and entire
America. Central America is also different from Oceania. Moreover, Liquefied petroleum
gases and Motor Gasoline consumption has also analyzed and there regional
differences with mean are also given in the table.
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Table no. 7: LSD for Nuclear Electric Power, Other Electric Power, Other Petroleum and Residual Fuel
Dependent Variable
(I) Country codes
(J) Country codes
Std. Error
Sig.
Nuclear Electric
Power
Africa
Asia
-324.70
42.90
0.00
Europe
-265.53
42.90
0.00
North America
-634.62
42.90
0.00
Africa
324.70
42.90
0.00
Central America
333.47
42.90
0.00
North America
-309.93
42.90
0.00
Oceania
333.47
42.90
0.00
South America
323.50
42.90
0.00
Europe
-274.30
42.90
0.00
North America
-643.39
42.90
0.00
North America
-369.09
42.90
0.00
Oceania
274.30
42.90
0.00
South America
264.34
42.90
0.00
Oceania
643.39
42.90
0.00
South America
633.43
42.90
0.00
Asia
-25.03
7.00
0.00
Europe
-50.30
7.00
0.00
North America
-67.72
7.00
0.00
Central America
22.99
7.00
0.00
Europe
-25.28
7.00
0.00
North America
-42.70
7.00
0.00
Oceania
19.84
7.00
0.01
South America
16.85
7.00
0.02
Europe
-48.26
7.00
0.00
North America
-65.68
7.00
0.00
North America
-17.42
7.00
0.01
Oceania
45.11
7.00
0.00
South America
42.13
7.00
0.00
Oceania
62.53
7.00
0.00
Asia
Central America
Europe
North America
Other Electric
Power
Africa
Asia
Central America
Europe
North America
Other Petroleum
Africa
Asia
Mean Difference (I-J)
South America
59.55
7.00
0.00
Asia
164.12
43.53
0.00
Central America
118.54
44.47
0.01
Europe
230.46
43.53
0.00
North America
230.11
43.11
0.00
South America
-366.95
44.47
0.00
Africa
-164.12
43.53
0.00
Oceania
-88.90
42.57
0.04
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South America
-531.08
43.53
0.00
Europe
111.91
43.53
0.01
North America
111.57
43.11
0.01
South America
-485.50
44.47
0.00
Oceania
-155.23
42.57
0.00
South America
-597.41
43.53
0.00
North America
Oceania
-154.88
42.14
0.00
Oceania
South America
-442.18
43.53
0.00
Africa
Asia
466.13
6.62
0.00
Central America
115.09
6.76
0.00
Europe
467.30
6.62
0.00
North America
468.23
6.56
0.00
Oceania
316.97
6.62
0.00
South America
23.49
6.76
0.00
Africa
-466.13
6.62
0.00
Central America
-351.04
6.62
0.00
Oceania
-149.16
6.47
0.00
South America
-442.64
6.62
0.00
Europe
352.21
6.62
0.00
North America
353.15
6.56
0.00
Oceania
201.88
6.62
0.00
South America
-91.60
6.76
0.00
Oceania
-150.33
6.47
0.00
South America
-443.81
6.62
0.00
Oceania
-151.26
6.41
0.00
South America
-444.75
6.56
0.00
South America
-293.48
6.62
0.00
Central America
Europe
Residual Fuel
Asia
Central America
Europe
North America
Oceania
At this instant, there is last table (Table no. 7) of LSD applied to energy consumption. It
starts with nuclear electric power as dependent variable. Its result shows that Africa has
significantly different mean values as compared with Asia, Europe and North America.
Furthermore, Asia has mean difference with Oceania and entire America. Central
America is different from Europe and North America, Europe with North America, South
America and Oceania and lastly North America with Oceania and North America.
Additionally, other electric power, other petroleum and residual oil are also scrutinize
and there outcomes are evidently revealed in the table with p-values, S.E. and Mean
different values.
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Regression Analysis
Multiple Linear regression has manipulated ensure positive and negative effect between
GDP and energy consumption.
Table no. 8: Coefficient of determination for Regression Model
Model
1
R
R-Square
Adjusted R Square
Std. Error of the Estimate
.960
.922
.912
1688476.43775
Table no. 8 shows the value of coefficient of determination which is 0.922. It means the
model is 92% satisfactory and up to standard.
Table no. 9: ANOVA for Regression Model
Model
1
Sum of Squares
Regression
Residual
Total
df
3298149865262857.000
Mean Square
F
13
253703835789450.600
279393362720310.900
98
2850952680819.500
3577543227983168.000
111
Sig.
88.989
.000(a)
Table no. 9 demonstrates that the value for this test is 0.00 which is highly significant
and less than the standard value of 0.05. It implies that Null Hypothesis has rejected
and alternative hypothesis has accepted.
Table no, 10: Coefficients for Regression Model
Model
Unstandardized Coefficients
B
1
(Constant)
consumption(Coal)
4407776.200
Std. Error
Standardized
Coefficients
t
Sig.
Beta
1369750.046
3.218
.002
-3643.665
652.280
-.217
-5.586
.000
500.755
1016.683
.023
.493
.623
6429.041
7663.954
.324
.839
.404
consumption(Dry Natural
Gas)
-2816.412
2126.902
-.072
-1.324
.189
consumption(Hydroelectric
Power)
14919.035
1992.349
.754
7.488
.000
consumption(Crude Oil )
consumption(Distillate Fuel)
consumption(Jet Fuel)
2773.795
797.033
.140
3.480
.001
consumption(Kerosene)
-3221.139
956.900
-.117
-3.366
.001
consumption( Liquefied
Petroleum Gases)
1562.412
898.312
.064
1.739
.085
-16428.445
12828.040
-.620
-1.281
.203
consumption( Motor Gasoline)
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consumption(Nuclear Electric
Power)
consumption(Geothermal,
Solar, Wind, and Wood
Waste)
consumption(Other
Petroleum)
consumption( Residual Fuel)
-4247.209
738.119
-.238
-5.754
.000
103.760
6815.914
.001
.015
.988
4278.880
5122.405
.101
.835
.406
-1153.557
5095.716
-.041
-.226
.821
Regression coefficients have shown in table no. 10, the last table of this study. Model
has designed by presuming GDP as dependent variable and energy consumption
commodities as independent variables. The OLS model for regression is as follows:
GDP= β0 + β1 (Coal) + β2 (CO) + β3 (DF) + β4 (DNG) + β5 (HP) + β6 (JF) + β7 (Kerosene)
+ β8 (LPG) + β9 (MG) + β10 (NEP) + β11 (OEP) + β12 (OP) + β13 (RF)
By putting values from table no. 10, a new model can be formulated which has shown
below:
GDP= 4407776.200 - 3643.665 (Coal) + 500.755 (CO) + 6429.041 (DF) -2816.412
(DNG) + 14919.035 (HP) + 2773.795 (JF) -3221.139 (Kerosene) + 1562.412 (LPG) 16428.445 (MG) -4247.209 (NEP) + 103.760 (OEP) + 4278.880 (OP) - 1153.557 (RF)
Above model shows that increase in one unit of coal consumption can decrease GDP
by 3643.665. Crude Oil, Distillate Fuel, Jet Fuel, Liquefied petroleum gas, geothermal,
wind, Solar, wood waste and other petroleum consumption has positive effect on GDP.
Additionally, Hydroelectric Power is most crucial factor effecting GDP positively, as
increase of one unit in hydroelectric consumption can increase GDP by 14919.035.
Nevertheless, Motor Gasoline has most significant negative effect on GDP, as
increasing in one unit can decrease GDP by 16428.445. Dry Natural Gas, Kerosene,
Motor Gasoline, Nuclear electric power and Residual Fuel are also negatively affecting
components.
Conclusion
It is concluded that consumption is generally the largest GDP element and this study
ensures it. There are many types of consumption though the focus of study is on energy
consumption. However, previous studies show no conformity or no relationship of gross
domestic product with personal consumption expenditure. The study substantiates that
Central America has least GDP as compared to other regions and Asia has the highest
one. South America had leading consumption and Europe had nominal energy usage
as compared to other regions.
Coal, Jet Fuel, Motor Gasoline and Residual Fuel shows consistency in year 2006.
Moreover, Analysis of variances shows different mean while comparing regions
Proceedings of 5th Annual American Business Research Conference
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presuming all variables dependent one by one. Furthermore, Hydroelectric Power
consumption has most negative and Motor Gasoline consumption has most negative
impact on gross domestic product.
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