Economic Growth and Inflation Analysis

This assignment requires an analysis of economic growth and inflation trends from 1995 to 2012. The provided data includes annual figures for two primary indicators: a measure of economic growth (likely GDP or a similar metric) and a measure of inflation (potentially CPI or a comparable index). Students are expected to examine these trends over time, identify patterns or shifts, and potentially draw conclusions about the relationship between economic growth and inflation during this period.

POLICY AND PLANNING OF ENERGY
CONSERVATION
(Energy Planning and Policy Program)
Spring Semester 2017
Assignment # 1
By
<Student Name>
(student ID)
University of Technology, Sydney

Table of Contents
1. Introduction 1
2. Mathemetical Formulation of LMDI Method 1
Formula of logarithmic mean Divisia index (LMDI) 1
3. Calculation from LMDI: 3
4. Findings of Analysis using LMDI method 5
5. Calculation of energy intensity trends 6
6. Philosophical Perspective 7
References 8
Appendix A

List of Figures
Figure 1 Total additive changes (rolling base) during 1980-2012..................................................4
Figure 2 Contribution of four effects in total additive changes (rolling base) during 1980-2012...4
Figure 3 Total multiplicative changes (rolling base) during 1980-2012.........................................5
Figure 4 Contribution of four effects in total multiplicative changes (rolling base) during 1980-
2012.................................................................................................................................................5
Figure 5 Törnqvist index during 1980-2012....................................................................................6

1. Introduction
Energy efficiency improvement is considered as one of the most significant aspects for lessening
the greenhouse gas emissions and energy imports of countries. Many theoretical and empirical
literatures have described the association the variation in energy intensity with the country’s
development of economy by decomposing the energy intensity into its elements (Xu, He, &
Long, 2014). It is very crucial to recognize the economic activities, due to their special effect on
energy, and fundamental characteristics to lessen consumption of energy, as well as potential
measures which can enhance the energy efficiency (Chang, Ries, & Wang, 2010). Many research
papers have made extensive analysis of combined economy by utilizing sectoral data (Wu,
2012). In this study, we have employed a Divisia index method, as LMDI is the best
decomposition method furnishing comprehensive decomposition outputs with no residual effects
within different alternative methods. This study decomposes the factors which influence
consumption of the energy from four fuel sources, for five sectors using the logarithmic mean
Divisia index (LMDI) method and examines the specific trend of consumption energy from 1980
to 2012, and aims to study specific characteristics of energy intensity during this period. This
study uses not only additive LMDI methods but also multiplicative methods to understand which
aspects influence on consumption and intensity of energy. This decomposition of the factors is
mainly associated with the activity, structure, intensity, and substitution effects.
1

2. Mathemetical Formulation of LMDI Method
The identity of total final energy consumption can be expressed as:
E=∑
i=1
5
∑
j=1
4
E ji=∑
ij
A . Ai
A . Ei
Ai
. Eij
Ei
=∑
ij
A . Si . Ii . M ij ----------------Equation 1
Where, A: total output (activity effect), S= Ei
Ai
= sectoral composition of output (structure
effect), I = Ei
Ai
=sectoral energy intensity (intensity effect), and M = Eij
Ei
= fuel mix (substitution
effect).
Formula of logarithmic mean Divisia index (LMDI)
Additive Form
∆ Eact =∑
ij
Wij . ln ( AT
A0 ) -------------------Equation 2
∆ Estr =∑
ij
Wij . ln ( Si
T
Si
0 ) -------------------Equation 3
∆ Eint =∑
ij
Wij . ln ( Ii
T
Ii
0 ) -------------------Equation 4
∆ Emix =∑
ij
Wij . ln ( M ij
T
M ij
0 ) -------------------Equation 5
Here, Wij= Eij
T−Eij
0
ln Eij
T−ln Eij
0 -------------------Equation 6
2

∆ Etot =∆ Eact +∆ Estr + ∆ Eint+ ∆ Emix -------------------Equation 7
Multiplicative Form
∆ Dact = exp (∑
ij
ˇW ij . ln ( AT
A0 ) ) -------------------Equation 8
∆ Dstr = exp (∑
ij
ˇW ij . ln ( Si
T
Si
0 )) -------------------Equation 9
∆ Dint = exp (∑
ij
ˇW ij . ln ( Ii
T
I i
0 ) ) -------------------Equation 10
∆ Dmix = exp (∑
ij
ˇW ij . ln ( M ij
T
Mij
0 )) -------------------Equation 11
Here, ˇW ij=(Eij
T−Eij
0 )/( ln Eij
T−ln Eij
0 )
( ET−E0)(ln Eij
T −ln Eij
0 ) -------------------Equation 12
∆ Dtot =∆ Dact . ∆ Dstr . ∆ Dint . ∆ Dmix -------------------Equation 13
3. Calculation from LMDI:
To calculate the total change in final energy consumption, chaining decomposition method was
implemented on a yearly and rolling basis. Using every two consecutive years data, i.e. “year 0
& 1”, “1 & 2”, till “T -1 and T”. Total T subsets of decomposition outcomes have been found
3

which can be “chained” to attain the timeseries for the complete time period (Ang, 2015).
Subsets of additive decomposition outcomes have been additively chained, and subsets of
multiplicative decomposition outcomes have been multiplicatively chained, to get the total
change in energy consumption.
Total additive change in energy conversation during 1980-2012: Final ∆ Etot=¿ 1644.9, figure 1
highlights total additive changes (rolling base) during 1980-2012. Contribution of four effects in
total additive changes: Final ∆ Eact=2832.59, Final ∆ Estr=−300.39, Final ∆ Eint=−894.5,
Final ∆ Emix =7.21. Figure 2 denotes the contributions of four effects on total additive changes
(rolling base) during 1980-2012.
1980-1981
1982-1983
1984-1985
1986-1987
1988-1989
1990-1991
1992-1993
1994-1995
1996-1997
1998-1999
2000-2001
2002-2003
2004-2005
2006-2007
2008-2009
2010-2011
-150.000
-100.000
-50.000
0.000
50.000
100.000
150.000
200.000
250.000
Figure 1 Total additive changes (rolling base) during 1980-2012
4

1980-1981
1982-1983
1984-1985
1986-1987
1988-1989
1990-1991
1992-1993
1994-1995
1996-1997
1998-1999
2000-2001
2002-2003
2004-2005
2006-2007
2008-2009
2010-2011
-150.000
-100.000
-50.000
0.000
50.000
100.000
150.000
200.000
∆Eact ∆Estr ∆Eint ∆Emix
Figure 2 Contribution of four effects in total additive changes (rolling base) during 1980-2012
Total multiplicative change in energy conversation: Final ∆ Dtot=1.86, figure 3 highlights total
multiplicative changes (rolling base) during 1980-2012. Contribution of four effects in total
multiplicative changes: ∆ Dact=2.94, ∆ Dstr= 0.88, ∆ Dint= 0.72, ∆ Dmix= 1.00. Figure 4 denotes
the contributions of four effects on total multiplicative changes (rolling base) during 1980-2012.
1980-1981
1981-1982
1982-1983
1983-1984
1984-1985
1985-1986
1986-1987
1987-1988
1988-1989
1989-1990
1990-1991
1991-1992
1992-1993
1993-1994
1994-1995
1995-1996
1996-1997
1997-1998
1998-1999
1999-2000
2000-2001
2001-2002
2002-2003
2003-2004
2004-2005
2005-2006
2006-2007
2007-2008
2008-2009
2009-2010
2010-2011
2011-2012
0.850
0.900
0.950
1.000
1.050
1.100
Figure 3 Total multiplicative changes (rolling base) during 1980-2012
5

1980-1981
1982-1983
1984-1985
1986-1987
1988-1989
1990-1991
1992-1993
1994-1995
1996-1997
1998-1999
2000-2001
2002-2003
2004-2005
2006-2007
2008-2009
2010-2011
0.900
0.920
0.940
0.960
0.980
1.000
1.020
1.040
1.060
1.080
1.100
∆Dact ∆Dstr ∆Dint ∆Dmix
Figure 4 Contribution of four effects in total multiplicative changes (rolling base) during 1980-2012
4. Findings of Analysis using LMDI method
 Activity effect has the highest positive contribution (2832.59 and 2.940) to the increase
of energy consumption for both the cases (Additive and Multiplicative), whereas intensity
effect has the highest negative contribution in energy consumption (-894.508).
 Negative additive changes were observed for 1981-1982, 1982-1983, 1990-1991, 2000-
2001, and 2008-2009. Total additive change was lowest (i.e. -106.7) during 1982-83,
during this period energy consumption was mainly reduced by the “activity effect” and
“structure” effect. Early 1980’s recession affected the economy during this period, and it
resulted into fall in energy consumption. Second lowest additive change was observed
during 2008-09, energy consumption was mainly reduced by the intensity effect. It was
also the effect of the global recession during that period.
6

 Top 5 positive changes were observed for 1987-1988, 1988-1989, 1994-1995, 2002-
2003, 2006-2007. Maximum change (i.e. 216.70) was observed in 2002-03, it was mainly
contributions of active and intensity effect. Second highest positive change was observed
for 1987-88 i.e. 119.1.
5. Calculation of energy intensity trends
Energy intensity trend has been calculated using Törnqvist index method. Overall price index is
1.348406888 and overall quantity index is 1.93. Graphical representation of both the energy
intensity trends (price index and quantity index) have been show below in figure 5.
1980-1981
1982-1983
1984-1985
1986-1987
1988-1989
1990-1991
1992-1993
1994-1995
1996-1997
1998-1999
2000-2001
2002-2003
2004-2005
2006-2007
2008-2009
2010-2011
0
0.2
0.4
0.6
0.8
1
1.2
1.4
Törnqvist-Theil price index Törnqvist quantity index
Figure 5 Törnqvist index during 1980-2012
7

Findings
 Highest price index (i.e. 1.143) was observed during 1999-2000, it was mainly due to rise
in energy prices, and lowest price index (i.e. 0.87) was observed in 2008-09, it was
mainly due to decrease in energy prices.
 Highest quantity index was observed during 1987-88, and lowest quantity index was
observed in 1982-1983. During, 1980-2012, movement of quantity index is flatter than
the price index.
6. Philosophical Perspective
 The logarithmic mean Divisia index (LMDI) method has been chosen for the study. In
this method sets and subsets can be grouped together in either additive or multiplicative
decomposition method. It is mostly preferred due of its benefits in achieving the factor-
reversal test and it does not leave any unexplained residual (Shahiduzzaman &Alam,
2013).
 Aggregation of energy types can be made by combining either in physical units or in
thermal units or in energy unit, which is purely quantitative method. Associating price of
energy and non-energy and inputs on productivity with those, helps to build a framework,
which would quantify energy intensity trend and can also capture qualitative attributes.
8

References
Ang, B.W., 2015. LMDI decomposition approach: a guide for implementation. Energy
Policy, 86, pp.233-238.
Chang, Y., Ries, R.J. and Wang, Y., 2010. The embodied energy and environmental
emissions of construction projects in China: an economic input–output LCA model. Energy
Policy, 38(11), pp.6597-6603.
Shahiduzzaman, M. and Alam, K., 2013. Changes in energy efficiency in Australia: a
decomposition of aggregate energy intensity using logarithmic mean Divisia approach.
Energy Policy, 56, pp.341-351.
Wu, Y., 2012. Energy intensity and its determinants in China's regional economies. Energy
Policy, 41, pp.703-711.
Xu, S.C., He, Z.X. and Long, R.Y., 2014. Factors that influence carbon emissions due to
energy consumption in China: Decomposition analysis using LMDI. Applied Energy, 127,
pp.182-193.
9

Appendix
Appendix 1 (LMDI) factor decomposition analysis of energy consumption (rolling base year). During
1980-2012
Year ∆Eact ∆Estr ∆
Eint
∆
Emix
∆
Da
ct
∆
Dstr
∆
Dint
∆
Dmi
x
∆Etot ∆
Dto
t
1980-1981 66.029 12.189 -75.703 -0.014 1.035 1.006 0.961 1.000 2.500 1.001
1981-1982 58.365 -11.545 -49.638 0.119 1.031 0.994 0.974 1.000 -2.700 0.999
1982-1983 -66.208 -51.075 10.581 0.002 0.965 0.973 1.006 1.000 -106.700 0.944
1983-1984 86.256 -6.493 1.706 0.032 1.048 0.997 1.001 1.000 81.500 1.045
1984-1985 119.789 15.237 -62.949 0.023 1.064 1.008 0.968 1.000 72.100 1.038
1985-1986 90.806 -8.533 -38.162 0.388 1.047 0.996 0.981 1.000 44.500 1.023
1986-1987 55.715 -32.062 23.643 0.004 1.028 0.984 1.012 1.000 47.300 1.024
1987-1988 153.698 -25.952 -8.980 0.334 1.075 0.988 0.996 1.000 119.100 1.058
1988-1989 103.826 18.001 -25.273 0.346 1.048 1.008 0.989 1.000 96.900 1.045
1989-1990 92.023 -42.086 -0.755 0.018 1.041 0.982 1.000 1.000 49.200 1.022
1990-1991 3.687 -20.510 14.423 0.000 1.002 0.991 1.006 1.000 -2.400 0.999
1991-1992 22.153 -38.572 43.819 0.001 1.010 0.984 1.019 1.000 27.400 1.012
1992-1993 63.951 -16.511 18.560 0.701 1.027 0.993 1.008 1.000 66.700 1.028
1993-1994 114.665 3.138 -34.244 0.241 1.048 1.001 0.986 1.000 83.800 1.035
1994-1995 128.095 -16.565 4.168 0.003 1.051 0.994 1.002 1.000 115.700 1.046
1995-1996 114.165 30.754 -85.555 0.135 1.044 1.012 0.968 1.000 59.500 1.023
1996-1997 101.466 -17.660 -60.104 -0.102 1.039 0.993 0.978 1.000 23.600 1.009
1997-1998 115.368 -18.929 -25.549 0.010 1.043 0.993 0.991 1.000 70.900 1.026
1998-1999 134.886 -38.679 -69.358 0.051 1.050 0.986 0.975 1.000 26.900 1.010
1999-2000 113.563 -15.513 -40.800 0.250 1.041 0.995 0.986 1.000 57.500 1.021
2000-2001 71.995 -42.226 -42.641 -0.029 1.026 0.985 0.985 1.000 -12.900 0.995
2001-2002 66.077 10.865 -62.858 2.117 1.023 1.004 0.978 1.001 16.200 1.006
2002-2003 92.675 55.674 67.305 1.051 1.032 1.019 1.023 1.000 216.706 1.076
2003-2004 114.717 -14.918 -36.246 -0.021 1.038 0.995 0.988 1.000 63.532 1.021
2004-2005 107.364 9.839 -55.666 0.010 1.034 1.003 0.983 1.000 61.547 1.020
2005-2006 102.418 -6.738 -62.799 0.008 1.032 0.998 0.981 1.000 32.889 1.010
2006-2007 136.908 6.625 -41.979 0.006 1.043 1.002 0.987 1.000 101.559 1.031
2007-2008 133.044 27.652 -116.325 -0.001 1.040 1.008 0.966 1.000 44.371 1.013
2008-2009 58.208 -45.494 -60.974 -0.051 1.018 0.987 0.982 1.000 -48.311 0.986
A

2009-2010 77.910 -10.086 -11.625 0.003 1.023 0.997 0.997 1.000 56.203 1.017
2010-2011 76.656 -3.989 18.113 1.554 1.023 0.999 1.005 1.000 92.335 1.027
2011-2012 122.319 -6.231 -28.643 0.025 1.035 0.998 0.992 1.000 87.469 1.025
Overall
Chage
(Additive
and
Multiplicat
ive)
2832.589 -300.395 -894.508 7.214 2.940 0.879 0.717 1.003 1644.900 1.857
Appendix 2 Törnqvist Index (Price and Quanity) during 1980-2012
Year Törnqvist-Theil price index Törnqvist quantity index
1980-1981 1.046172209 0.989305008
1981-1982 1.031136542 1.00549317
1982-1983 1.07516953 0.954275455
1983-1984 0.960325057 1.052316216
1984-1985 1.021862906 1.030431777
1985-1986 0.903304908 1.019014505
1986-1987 0.958404496 1.027761661
1987-1988 0.886754895 1.059280043
1988-1989 1.022146755 1.049916607
1989-1990 1.032163535 1.019408594
1990-1991 1.050896213 1.002056627
1991-1992 1.00329466 1.0098523
1992-1993 1.012226042 1.032576338
1993-1994 0.99111428 1.027846349
1994-1995 0.973950462 1.046027361
1995-1996 1.010192861 1.027588652
1996-1997 0.982218338 1.006591897
1997-1998 0.949607458 1.03074016
1998-1999 1.018566971 1.019879004
1999-2000 1.142948748 1.027657143
2000-2001 0.973961416 1.007126199
2001-2002 0.943138326 1.006775204
2002-2003 1.018567032 1.037638439
2003-2004 1.050604943 1.034779469
2004-2005 1.133451823 1.027041158
B

2005-2006 1.070998956 1.01164579
2006-2007 0.962421778 1.031368677
2007-2008 1.140080563 1.020047734
2008-2009 0.874539625 0.992246646
2009-2010 1.000172971 1.007743589
2010-2011 1.099322805 1.026641989
2011-2012 1.028127127 1.027618749
Overall 1.348406888 1.92610234
C