How Dependent Is Growth From Primary Energy?

An Empirical Answer on 33 Countries

www.theshiftproject.org

Gael GiraudCNRS, PSE, CES, Labex REFI

Zeynep Kahraman The Shift Project

Outline

• Introduction• Empirical methodology• The data• Time series properties of the data• Conclusion

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 ?

Oil prices and World GDP (1965 – 2011)Sources: BP statistical Review, 2012, Shilling et al. 1977, EIA, 2012, and World Bank (GDP), 2012.

IntroductionWhy is this relationship important ?

Primary Energy Consumption and GDP (1965 – 2011)Source : BP statistical review, 2012, Shilling et al. 1977, EIA, 2012, and World Bank (GDP), 2012.

IntroductionWhy is this relationship important ?

The GDP share of primary energy, U.S., 1970-2010.Source: EIA, http://www.eia.gov/totalenergy/data/annual/pdf/sec1_13.pdf

Empirical methodology

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

The data

The analysis is based on a panel data covering the period from 1970 to 2011 for 33 countries.

Algeria France NetherlandsArgentina Germany NorwayAustralia Greece PhilippinesAustria Hungary PortugalBelgium Iran South KoreaBrazil Ireland SpainCanada Italy SwedenChile Japan ThailandChina Luxembourg United States Costa Rica Malaysia United KingdomDenmark Mexico Venezuela

Estimation of the long run relation

lnGDPi,t = βi,0+ βi,1 lnNRGi,t+ βi,2 lnEFFi,t-1+ βi,3 lnKi,t+εi,t

All the variables are per capita

The main equation:

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

commonunit root process

Individualunit 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

Table 5. Pedroni Residual Cointegration Test

  Value Z value P value Robust p valueGt -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

Table 6. Westerlund panel cointegration test results

Emprical ResultsEstimation of the long run relation

Can we quantify this long-run relationship ? The short-run speed of convergence towards the equilibrium relation ?An ECM approach:

"ϕi" is the error correction term, "βi" is long-run coefficients, δ incorporates short-run information

Emprical ResultsEstimation of the long run relation

Model: PMG MG CCEPDependent 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

Table 7. 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***

Table 8. 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