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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 Economists Saratoga Springs, NY May 22, 2003. http://cybele.bu.edu/people/arr.html. Talk Overview. Omitted variable bias Energy Mix - PowerPoint PPT Presentation
Citation preview
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
2
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
3
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
4
Turning Points
Income
Natural Resources Use and\ or Emission of Wastes
5
Energy Omission
• E/GDP influenced by energy mix
• Different energy types have different CO2 emissions
• Statistical effects of omitted variable bias
6
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)
7
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
8
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.
9
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)
10
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
11
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
12
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
13
Relation between income and energy consumption
(corrected for changes in energy mix)
Quadratic Model Semi Log Model Double Log Model
14
Relation between income and CO2 emissions
(corrected for changes in energy mix)
Semi Log Model Double Log ModelQuadratic Model
15
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
16
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
17
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