1. 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

2. Talk Overview Omitted variable bias Model specification
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
The EKC hypothesizes that the relation between income and the use of natural resources and/or the emission of wastes has an inverted U-shape.
Describe graph
Reasons for this inverted U-shaped relation include income driven changes in: (1) the composition of production and consumption; (2) the preference for environmental quality; (3) institutions that are needed to internalize externalities; and/or (4) increasing returns to scale associated with pollution abatement.
EKC attractive to policy makers because it suggests that economic growth improves both living standards and environmental quality.
The World Bank World Development Report (IBRD, 1992): environmental degradation can be slowed by policies that protect the environment and promote economic development.
Concern about climate change has prompted several analysts to examine the relation between economic activity and energy consumption and/or carbon emissions (de Bruyn et al., 1998; Schmalensee et al., 1998; Holtz-Eaken et al., 1995).
Results consistent with EKC. However, turning point often is well beyond the largest value for income in the sample.

4. Turning Points
Natural Resources
Use
and\ or
Emission of Wastes
Income

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
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
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 Quadratic Specification:
EKC if β1 > 0 and β2 < 0
Turning point = –(β1/ 2β2)
Semi Log Specification:
Diminishing returns
Double Log Specification:
Constant elasticity 1. 3. 2.

9. Omitted Variable Bias: Fuel Share
PCTCOAL = ln(FINCOAL/TE)
PCTPET = ln((FINOIL+FINGAS)/ TE) PCTELC = ln((HYRDO+NUCLEAR)/TE)
Expect coefficient associated with PCTCOAL to be positive and coefficients associated with PCTPET and PCTELC to be negative.
Diminishing Returns

10. Estimation Techniques
Regression techniques:
Pooled OLS
Fixed Effects or Random Effects Estimator
Random Coefficient Model (Swamy, 1970)
Cointegration (Pedroni, 1999)

11. Tests of predictive accuracy (Diebold and Mariano, 1995)

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)
Quadratic Model
Semi Log Model
Double Log 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?
Fraction
Coal
Petroleum
Electricity
GDP
(2.89)
-0.031
(8.3)
(8.2)
GDP2
-46.53E-04
(1.7)
(0.8) --
Turning
point
$3,390
$12,070
Panel ADF
-3.14
-5.45
-6.51
Group ADF
-4.40
-7.13
-9.12

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