1. Leila Dagher American University of Beirut National Renewable Energy Lab, Research Fellow AN INVESTIGATION OF THE ENERGY CONSUMPTION- GROWTH NEXUS IN THE ARAB COUNTRIES

2. 1.E→ Y growth hypothesis 2.Y → E conservation hypothesis 3.E ↔Y feedback hypothesis 4.E ↮ Y neutrality hypothesis MOTIVATION & POLICY IMPLICATIONS (1)

3.  Conflicting results  GHG mitigation activities: low ghg emissions but high on emissions per capita  New energy conservation targets: NEEAP (e.g. Egypt 5% reduction in electricity consumption 2012-2015)  External oil shocks  Electricity rationing MOTIVATION & POLICY IMPLICATIONS (2)

4.  Kraft and Kraft (1978)  100s of studies  Renewed interest (climate change and mitigation)  Variables used  Bivariate versus multivariate models  Kuznets curve framework  Conflicting results LITERATURE REVIEW (1)

5. LITERATURE REVIEW (2) StudyAlgeriaEgyptMoroccoOmanSASudanSyriaTunisia Akinlo 2008 E---Y (SR) E↔Y (LR) Al-Iriani 2006Y → E Apergis and Payne 2010a NG↔Y (SR & LR) Apergis and Payne 2010b C↔Y (SR & LR) Belloumi 2009 E → Y (SR) E↔Y (LR) Chontanawat et al. 2006Y → EE → YE↔YE → YY → EE↔Y Dagher and Yacoubian 2012 Mahadevan and Asafu- Adjaye 2007 E↔Y (SR) p:Y → E (LR) i:E↔Y (LR)

6. StudyAlgeriaEgyptMoroccoOmanSASudanSyriaTunisia Mehrara 2007a E → Y (SR) E → Y (LR) Mehrara 2007b Y → E (SR & LR) Narayan and Smyth 2009 EL → Y (SR) EL↔Y (LR) Narayan et al. 2010EL↔Y Y → EL EL↔YY → ELEL↔Y Ozturk et al. 2010 E↔Y (SR & LR) Y →E (SR) E↔Y (LR) E↔Y (SR & LR) Sharma 2010E → Y Wolde-Rufael 2006 E---Y EL↔Y E---Y EL → Y Wlde-Rufael 2009E → YY → E LITERATURE REVIEW (3)

7.  Unit root testing (ADF or IPS)  Testing for cointegrating relationship (Johansen or Pedroni)  Granger causality METHODOLOGY (1)

8.  “if y t causes x t, then x t+1 is better forecast if the information in y t-j is used than if it is not used.” (Granger, 1988)  Major drawbacks:  Series should be stationary  Results are sensitive to lag length METHODOLOGY (2)

9.  Hsiao test uses Akaike’s Final Prediction Error  Compare FPE(n,0) to FPE(n,m)  Compare FPE(s,0) to FPE(s,r)  Strengths: valid whether series are stationary or not METHODOLOGY (3)

10.  Toda and Yamamoto: modified Wald test on an augmented VAR METHODOLOGY (4)

11.  Estimator: seemingly unrelated regression (SUR) procedure  Wald test ignoring m  Strengths:  valid whether series are stationary or not  Avoids biases relating to pretesting  Size is acceptable  Drawbacks: inefficient due to overfitting METHODOLOGY (5)

12.  Granger on VECM METHODOLOGY (6)

13.  Panel causality tests  Holtz-Eakin et al., 1988  Dumitrescu and Hurlin, 2012  Very good small sample properties  Can be used with unbalanced panels and different lag orders METHODOLOGY (7)

14. METHODOLOGY (8)

15.  Panel of 9 countries: Algeria, Egypt, Mauritania, Morocco, Oman, Saudi Arabia, Sudan, Syria, and Tunisia.  N=9, T=41 (1970-2010)  E from OAPEC and Y from WDI DATA (1)

16. DATA (2)

17. DATA (3)

18. RESULTS (TIME SERIES) AlgeriaE---Y EgyptY → E MauritaniaE---Y MoroccoE---Y OmanY → E Saudi ArabiaE↔Y SudanE↔Y SyriaE---Y TunisiaE↔Y

19.  E is I(0) and Y is I(1)  Dumitrescu-Hurlin: no causality in either direction RESULTS (PANEL)