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 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

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.

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

Energy Omission E/GDP influenced by energy mix Different energy types have different CO2 emissions Statistical effects of omitted variable bias

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)

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

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.

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

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

Tests of predictive accuracy (Diebold and Mariano, 1995)

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

Relation between income and energy consumption (corrected for changes in energy mix) Quadratic Model Semi Log Model Double Log Model

Relation between income and CO2 emissions (corrected for changes in energy mix) Quadratic Model Semi Log Model Double Log Model

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

Why do Energy Mix Variables Effect Turning Points? Fraction Coal Petroleum Electricity GDP 0.00443 (2.89) -0.031 (8.3) 0.00197 (8.2) GDP2 -46.53E-04 (1.7) 0.00127 (0.8) -- Turning point $3,390 $12,070 Panel ADF -3.14 -5.45 -6.51 Group ADF -4.40 -7.13 -9.12

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