Is there an Environmental Kuznets Curve for Energy Use and Carbon Emissions?
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Is there an Environmental Kuznets Curve for Energy Use
and Carbon Emissions?
Amy K. Richmond and Robert K. Kaufmann
US Association for Ecological EconomistsSaratoga Springs, NY
May 22, 2003
http://cybele.bu.edu/people/arr.html
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Talk Overview
• Omitted variable bias– Energy Mix
• Model specification– Quadratic, Semi-Log, Double-Log
• Tests of predictive accuracy• Questions
– Does the inclusion of energy mix influence turning points?
– Is there a turning point?• Conclusion
– Omission of energy variables effects turning point– Quadratic specification is best
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Environmental Kuznets Curve
• Reasons for EKC include income driven changes in: – composition of
production and consumption;
– preference for environmental quality;
– institutions that are needed to internalize externalities;
– increasing returns to scale associated with pollution abatement
Income
Natural Resources Use and\ or Emission of Wastes
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Turning Points
Income
Natural Resources Use and\ or Emission of Wastes
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Energy Omission
• E/GDP influenced by energy mix
• Different energy types have different CO2 emissions
• Statistical effects of omitted variable bias
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Methodology: Data• Panel of International Data
– 36 nations• 20 developed countries• 16 developing countries
– 1973-1997• Total Economic activity measured by GDP
in 1996 US dollars, converted using PPP indices
• Carbon emissions (kg/ million BTU)• Total energy use (BTU’s)• Final energy consumption (BTU’s)
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Basic Model
ittjitit ZXY )ln(
• Yij is a measure of energy per capita (TE/Pop) or carbon emissions per capita (CO2/Pop) by nation i at time t
• X is per capita GDP
• Z is a vector of fuel shares (PCTCOAL, PCTPET, PCTELC)
• µ is the regression error
• α, β, Φ, are regression coefficients
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Model Specifications
itititit ZXY )ln()ln(
Quadratic Specification:
ititititit ZXXY )ln(221
• EKC if β1 > 0 and β2 < 0• Turning point = –(β1/ 2β2)
Semi Log Specification:
• Diminishing returns
itititit ZXY )ln()ln()ln(Double Log Specification:
• Constant elasticity
1.
3.
2.
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Omitted Variable Bias: Fuel Share
• Expect coefficient associated with PCTCOAL to be positive and coefficients associated with PCTPET and PCTELC to be negative.
• Diminishing Returns
PCTCOAL = ln(FINCOAL/TE) PCTPET = ln((FINOIL+FINGAS)/ TE) PCTELC = ln((HYRDO+NUCLEAR)/TE)
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Estimation Techniques
• Regression techniques:– Pooled OLS – Fixed Effects or Random Effects Estimator
– Random Coefficient Model (Swamy, 1970)
• Cointegration (Pedroni, 1999)
itititit ZXY
Yit i Xit Zit it
Yit i iX it iZit it
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Tests of predictive accuracy (Diebold and Mariano, 1995)
S2a I dt 0.5N
t1
N
0.25N
S3a I dt rank( dt )
N N 1 4t1
N
N N 1 (2N 1)24
I(dt ) 1 if dt 00 otherwise
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Results
• Variables generally have correct sign and statistically significant
• GDP variables have correct sign, quadratic term not statistically significant
• All variables contain stochastic trend (indicates modeling variables using time trends is not sensible)
• Quadratic specification cointegrates• Energy shares allow diminishing returns
specifications to cointegrate
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Relation between income and energy consumption
(corrected for changes in energy mix)
Quadratic Model Semi Log Model Double Log Model
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Relation between income and CO2 emissions
(corrected for changes in energy mix)
Semi Log Model Double Log ModelQuadratic Model
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Effect of Energy Mix on Turning Points
• Energy use– Turning point without fuel shares: $43,767*– Turning point with fuel shares: $52,296*
• CO2 emissions
– Turning point without fuel shares: $110,600– Turning point with fuel shares: $29,700
* Calculated even though quadratic term not statistically significant
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Why do Energy Mix Variables Effect Turning Points?
FractionCoal
FractionPetroleum
FractionElectricity
GDP 0.00443(2.89)
-0.031(8.3)
0.00197(8.2)
GDP2 -46.53E-04(1.7)
0.00127(0.8)
--
Turningpoint
$3,390 $12,070 --
Panel ADF -3.14 -5.45 -6.51
Group ADF -4.40 -7.13 -9.12
Sit 1Xit 2Xit2 it
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Conclusion• Omission of energy variables effects turning
point
• Quadratic specification generates a more accurate out of sample forecast
• Modeling relationship between energy use and income using time trends is not sensible
http://cybele.bu.edu/people/arr.html