How Dependent Is Growth From Primary Energy?

An Empirical Answer on 33 Countries

www.theshiftproject.org

Gael GiraudCNRS, PSE, CES, Labex REFI

Zeynep KahramanThe Shift Project

IntroductionWhy is this relationship important ?

• Mainstream economic models do not include energy as a factor that could foster economic growth.

• Ecological economists, often ascribe to energy the central role in economic growth.

• Is energy an important driver of economic growth ?

• If so, what is the magnitude of the dependency of growth from energy ?

IntroductionWhy is this relationship important ?

Sources: BP statistical Review, 2012, Shilling et al. 1977, EIA, 2012, and World Bank (GDP), 2012.

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GD

P b

illio

n c

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stan

t $

Oil Price per barrel in constant 2011 $

World Oil prices and GDP (1965 – 2011)

IntroductionWhy is this relationship important ?

Source : BP statistical review, 2012, Shilling et al. 1977, EIA, 2012, and World Bank (GDP), 2012.

y = 0.6548x + 0.0103

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rld

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ss D

om

esti

c P

rod

uct

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wth

Primary Energy Consumption Growth

Comparison of the World Gross Domestic Product growth with the World Primary Energy Consumption Growth

IntroductionWhy is this relationship important ?

Source: EIA, http://www.eia.gov/totalenergy/data/annual/pdf/sec1_13.pdf

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U.S Energy Expenditures as Share of GDP

Empirical methodologyEstimation of the long run relation

lnYi,t = βi,0+ βi,1 lnCi,t+ βi,2 lnEi,t-1+ βi,3 lnKi,t+εi,t

*All the variables are per capita

The main equation:

Empirical methodologyEstimation of the long run relation

An ECM approach:

∆𝑦it= ϕi𝑦i,t−1 +β′1𝑐it +β′2𝑒it−1 +β′3𝑘it+

𝑗=1

𝑝−1

𝜆∗ ij∆𝑦i,t−j +

𝑗=0

𝑞−1

𝛿 ∗′ 1j∆𝑐i,t−j

+

𝑗=1

𝑞−1

𝛿 ∗′ 2j∆𝑒i,t−j +

𝑗=0

𝑞−1

𝛿 ∗′ 3j∆𝑘i,t−j + μi + αit +ε

"ϕi" is the error correction term, "βi" is long-run coefficients

Empirical methodologyThe Data

Variables under scrutiny is:

- Primary energy consumption (million tons of oil equivalents)

- GDP (in 2000 U.S dollars)

- Gross Fixed Capital Formation (in 2000 U.S dollars)

- Population (millions)

World Bank, World

Development Indicators

Estimation of the long run relationThe Data

The analysis is based on a panel data covering the period from 1970 to 2011 for

33 countries.

Algeria France Netherlands

Argentina Germany Norway

Australia Greece Philippines

Austria Hungary Portugal

Belgium Iran South Korea

Brazil Ireland Spain

Canada Italy Sweden

Chile Japan Thailand

China Luxembourg United States

Costa Rica Malaysia United Kingdom

Denmark Mexico Venezuela

Time series properties of the dataCross section dependence, Unit Root and Co-integration tests

1. Cross Section Dependence Test of Pesaran

2. Unit Root Tests:• First Generation:

• Levin, Lin and Chu test • Breitung• Im, Pesaran and Shin• ADF-Fisher • Philips Perron – Fisher

• Second Generation:• CIPS test

3. Co-integration Tests:• Pedroni’s residual co-integration tests• Westerlund test

common

unit root process

Individual

unit root process

Emprical ResultsCo-integration tests results

Deterministic intercept and trend

No deterministic intercept and trend

Alternative hypothesis: common AR coefs. (within-dimension)

Statistic Prob.

Panel v-Statistic 19.10098 0.0000

Panel rho-Statistic -5.165067 0.0000

Panel PP-Statistic -10.56038 0.0000

Panel ADF-Statistic -9.640764 0.0000

Statistic Prob.

Panel v-Statistic 12.12852 0.0000

Panel rho-Statistic -12.66436 0.0000

Panel PP-Statistic -17.26987 0.0000

Panel ADF-Statistic -16.24284 0.0000

Alternative hypothesis: individual AR coefs. (between-dimension)

Statistic Prob.

Group rho-Statistic -2.675141 0.0037

Group PP-Statistic -9.576716 0.0000

Group ADF-Statistic -8.976859 0.0000

Statistic Prob.

Group rho-Statistic -12.03752 0.0000

Group PP-Statistic -20.42889 0.0000

Group ADF-Statistic -18.09532 0.0000

Pedroni Residual Cointegration Test

Value Z value P value Robust p value

Gt -4.130 -13.580 0.000 0.000

Ga -18.174 -9.531 0.000 0.000

Pt -22.424 -11.338 0.000 0.000

Pa -18.275 -12.740 0.000 0.000

Westerlund panel cointegration test results

Emprical ResultsEstimation of the long run relation

Model: PMG MG CCEP

Dependent variable: ∆Yit

Energy consumption per capita

(Cit)

0.6543

(0.053)***

0.8083

(0.105)***

0.5195

(0.213)***

Energy efficiency

(Eit-1)

0.5860

(0.064)***

0.8090

(0.164)***

0.5164

(0.214)***

Capital formation per capita

(Kit)

0.1018

(0.016)***

0.0716

(0.016)

0.269

(0.016)***

Convergence coefficient

(Yit-1)

-0.5540

(0.085)***

-0.8433

(0.085)**

-0.5724

(0.214)***

Hausman test p value 0.2304

Results of long-run estimations

Emprical ResultsGranger Causality

Dependent Variable

Sources of causation (independent variables)

Short run Long runΔY ΔE ΔC ΔK ECT

ΔY - 10.93** 26.38*** 299.26*** -0.554***

ΔE 1754.6*** - 9526.42*** 8.37** -1.196***

ΔC 4.07 3.20 - 1.59 -0.533 ΔK 5.14 4.90 63.35*** - -0.273***

Panel causality test results

Conclusion

• Primary energy is a key factor that drives GDP growth: its long-run output elasticity evolved around 0.6.

• Capital accumulation has played a minor role compared to energy : long-run elasticity for capital around 0.2.

• These estimations are also robust to the choice of various sub periods of time and subsamples of countries.

• There are good reasons to believe that, the output elasticity of energy is decoupled from its GDP share.

• Our inquiry does not suggest that energy use be the sole first-order factor driving growth. Efficiency plays a dual, almost comparable role.

• Energy and GDP cointegrate and energy use univocally Granger causes GDP in the long-run

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