brant liddle centre for strategic economic studies victoria university australia
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The importance of energy quality in energy intensive manufacturing: Evidence from panel cointegration and panel FMOLS. Brant Liddle Centre for Strategic Economic Studies Victoria University Australia. Overview. - PowerPoint PPT PresentationTRANSCRIPT
The importance of energy quality in energy intensive manufacturing: Evidence from panel cointegration and panel FMOLS
Brant LiddleCentre for Strategic Economic Studies
Victoria UniversityAustralia
Overview
• Use panel cointegration & Pedroni FMOLS to analyze C-D production function (VA, L, K, E)
• Consider disaggregated data (ISIC-two digit)– Chemicals– Iron & steel– Nonferrous metals– Nonmetallic minerals– Pulp & paper
• Consider quality weighted index of energy consumption– Stern (1993 & 2000), Oh & Lee (2004)
Data
• IEA Energy Balances– Energy consumption– Energy prices
• OECD Structural Analysis Database (STAN)– Value added– Labor employed– Physical capital (gross fixed capital formation)
Panels
• Chemicals– 11 countries, 1990-2006
• Iron & steel– 7 countries, 1980-2006
• Nonferrous metals– 6 countries, 1980-2006
• Nonmetallic minerals– 11 countries, 1980-2006
• Pulp & paper– 12 countries, 1978-2007
Manufacturing Energy IntensitiesIron and Steel 1.548Non-ferrous metals 0.672Non-metallic minerals 0.438Chemical and chemical products 0.344Paper, pulp, and printing 0.268Wood and wood products 0.200Food and tobacco 0.123Textile and leather 0.099Transport equipment 0.044Fabricated metal products including machinery 0.034Construction 0.014
Chemicals Iron & steel
Non-ferrous metals
Non-metallic minerals
Pulp & paper
Total for 5
Australia 3.9% 2.2% 3.4% 2.6% 7.0% 19.1%Austria 6.4% 4.8% 1.8% 5.2% 7.0% 25.3%Belgium 17.6% 5.3% 1.4% 4.5% 6.6% 35.4%Denmark 9.9% 0.5% 0.3% 3.0% 6.5% 20.3%Finland 5.6% 3.9% 1.1% 3.1% 15.4% 29.2%France 9.1% 2.5% 0.9% 4.4% 7.1% 24.0%Germany 9.4% 2.8% 1.3% 2.7% 6.3% 22.5%Hungary 7.9% 1.3% 1.3% 3.5% 4.4% 18.3%Italy 6.1% 2.3% 0.8% 5.2% 5.4% 19.9%Japan 6.8% 5.8% 1.7% 2.6% 6.7% 23.5%Korea 8.0% 8.3% 1.5% 3.2% 3.8% 24.7%Poland 5.4% 2.0% 0.5% 4.7% 5.7% 18.3%Portugal 4.6% 1.5% 0.7% 9.4% 8.0% 24.1%Spain 8.1% 3.7% 1.4% 7.2% 8.0% 28.5%Sweden 10.7% 3.7% 1.1% 1.8% 10.0% 27.4%Switzerland 17.0% 2.3% 6.8% 26.1%UK 8.7% 1.0% 0.7% 2.8% 10.1% 23.3%USA 9.7% 1.7% 1.0% 2.5% 11.5% 26.4%
OECD 9.4% 3.0% 1.2% 3.7% 7.6% 23.5%
Models
titititi LEKVA ,,,,
titititi LEQKVA ,,,,
titititititi LEKbaVA ,,,,, lnlnlnln
titititititi LEQKbaVA ,,,,, lnlnlnln
Energy Quality
• Some forms of energy produce more work than others– Electricity > Oil > Natural gas > Coal
• Prices of the different forms tend to reflect that difference in quality (Berndt 1978)
Energy Quality
• Stern (1993): “quality weighted final energy use … is likely to be a superior measure of the energy input to economic activity as it will reflect better the productivity of the uses to which energy is put.”
• Stern (1993) found for US– Energy quality weighted consumption Granger-
caused GDP
Measuring Energy Quality
• Logged differences weighted by expenditure shares• P: prices & E: quantities consumed of fuels i• Electricity, oil, natural gas, coal, & combustible
renewables and waste
Ratio of Energy Quality to Conventional Energy Consumption
19781979
19801981
19821983
19841985
19861987
19881989
19901991
19921993
19941995
19961997
19981999
20002001
20022003
20042005
20062007
20080.8
0.9
1
1.1
1.2
1.3
1.4
Iron & steelPulp & paperNon-ferrous metalsChemicalsNon-metallic minerals
Methods
• Panel unit root tests– ADF-Fisher– Pesaran
• For all sectors all variables are panel I(1)• Pedroni panel cointegration test• For all sectors variables are panel cointegrated• Long-run elasticities estimated from Pedroni
panel FMOLS
Panel Variable Coefficient Variable CoefficientChemicals E 0.0367** EQ 0.190***
K 0.163*** K 0.171***
L 0.696*** L 0.549***
Iron & steel E -0.062 EQ 0.343*
K 0.042 K 0.101*
L 0.143*** L 0.241***
Non-ferrous metals E 0.316 EQ 0.568***
K 0.043 K 0.074**
L 1.307*** L 0.516***
Non-metallic minerals E 0.063*** EQ 0.197***
K 0.207*** K 0.240***
L 0.484*** L 0.215***
Pulp & paper E 0.0098*** EQ 0.301***
K 0.235*** K 0.239***
L 0.174*** L 0.251***
Panel Variable Coefficient Variable Coefficient
Chemicals E 0.0367** EQ 0.190***
K 0.163*** K 0.171***
L 0.696*** L 0.549***
Iron & steel E -0.062 EQ 0.343*
K 0.042 K 0.101*
L 0.143*** L 0.241***
Non-ferrous metals E 0.316 EQ 0.568***
K 0.043 K 0.074**
L 1.307*** L 0.516***
Non-metallic minerals E 0.063*** EQ 0.197***
K 0.207*** K 0.240***
L 0.484*** L 0.215***
Pulp & paper E 0.0098*** EQ 0.301***
K 0.235*** K 0.239***
L 0.174*** L 0.251***
Panel Variable Coefficient Variable CoefficientChemicals E 0.0367** EQ 0.190***
K 0.163*** K 0.171***
L 0.696*** L 0.549***
Iron & steel E -0.062 EQ 0.343*
K 0.042 K 0.101*
L 0.143*** L 0.241***
Non-ferrous metals E 0.316 EQ 0.568***
K 0.043 K 0.074**
L 1.307*** L 0.516***
Non-metallic minerals E 0.063*** EQ 0.197***
K 0.207*** K 0.240***
L 0.484*** L 0.215***
Pulp & paper E 0.0098*** EQ 0.301***
K 0.235*** K 0.239***
L 0.174*** L 0.251***
Panel Variable Coefficient Variable CoefficientChemicals E 0.0367** EQ 0.190***
K 0.163*** K 0.171***
L 0.696*** L 0.549***
Iron & steel E -0.062 EQ 0.343*
K 0.042 K 0.101*
L 0.143*** L 0.241***
Non-ferrous metals
E 0.316 EQ 0.568***
K 0.043 K 0.074**
L 1.307*** L 0.516***
Non-metallic minerals E 0.063*** EQ 0.197***
K 0.207*** K 0.240***
L 0.484*** L 0.215***
Pulp & paper E 0.0098*** EQ 0.301***
K 0.235*** K 0.239***
L 0.174*** L 0.251***
Panel Variable Coefficient Variable CoefficientChemicals E 0.0367** EQ 0.190***
K 0.163*** K 0.171***
L 0.696*** L 0.549***
Iron & steel E -0.062 EQ 0.343*
K 0.042 K 0.101*
L 0.143*** L 0.241***
Non-ferrous metals E 0.316 EQ 0.568***
K 0.043 K 0.074**
L 1.307*** L 0.516***
Non-metallic minerals
E 0.063*** EQ 0.197***
K 0.207*** K 0.240***
L 0.484*** L 0.215***
Pulp & paper E 0.0098*** EQ 0.301***
K 0.235*** K 0.239***
L 0.174*** L 0.251***
Panel Variable Coefficient Variable CoefficientChemicals E 0.0367** EQ 0.190***
K 0.163*** K 0.171***
L 0.696*** L 0.549***
Iron & steel E -0.062 EQ 0.343*
K 0.042 K 0.101*
L 0.143*** L 0.241***
Non-ferrous metals E 0.316 EQ 0.568***
K 0.043 K 0.074**
L 1.307*** L 0.516***
Non-metallic minerals E 0.063*** EQ 0.197***
K 0.207*** K 0.240***
L 0.484*** L 0.215***
Pulp & paper E 0.0098*** EQ 0.301***
K 0.235*** K 0.239***
L 0.174*** L 0.251***
Panel Variable Coefficient Variable CoefficientChemicals E 0.0367** EQ 0.190***
K 0.163*** K 0.171***
L 0.696*** L 0.549***
Iron & steel E -0.062 EQ 0.343*
K 0.042 K 0.101*
L 0.143*** L 0.241***
Non-ferrous metals E 0.316 EQ 0.568***
K 0.043 K 0.074**
L 1.307*** L 0.516***
Non-metallic minerals E 0.063*** EQ 0.197***
K 0.207*** K 0.240***
L 0.484*** L 0.215***
Pulp & paper E 0.0098*** EQ 0.301***
K 0.235*** K 0.239***
L 0.174*** L 0.251***
DNKES
P ITA BEL NLD FRA
USAAUT
NORSW
EFIN CAN
12
13
14
15
16
17
18
Pulp & Paper
LN (V
A/EQ
)
IREDNK
AUTES
P ITAGBR
SWE
BEL CAN FIN USANLD
12
13
14
15
16
17
18
Chemcials
LN(V
A/EQ
)
AUTES
PFR
AGBR
NLD FIN BEL12
13
14
15
16
17
18
Nonmetallic minerals
LN(V
A/EQ
)
Energy Quality Productivity
USA ITA AUT BEL SWE FIN NOR10
11
12
13
14
15
16
17
18
Iron & Steel
LN(V
A/EQ
)
USA AUT ITA BEL NOR SWE FIN12
13
14
15
16
17
18Nonferrous metals
LN(V
A/EQ
)
Energy Quality Productivity
Conclusions• Improvements in energy quality—shift to electricity
important to energy intensive manufacturing– Elasticity of energy quality >> conventionally measured
energy– Importance of energy quality relative to capital & labor
emphasized• Carbon tax’s impact on manufacturing
– Carbon intensity of electricity more important than energy intensity of sector/technology
• More flexible production function– Nonlinear transformation of I(1) terms