The Impact of Oil Shocks on the Economic Growth in the Middle East and North Africa and its Implications

Transcription

1 The Impact of Oil Shocks on the Economic Growth in the Middle East and North Africa and its Implications By: Hudab Faleh Al-Kobaisi, Ph.D. International Economic Relations

2 The Impact of Oil Shocks on the Economic Growth in the Middle East and North Africa and its Implications Abstract 1. Introduction 1.1 Research Problem 2. The recent drop in oil prices comparing with the previous oil shocks, along with the change in OPEC objectives 2.1 The feathers of the three past oil shocks 2.2 Recent drop in oil prices: The returns of the present to the past 3. The impact of oil price in the MENA Countries and its implications 3.1 Monetary issues: Cause and effects 3.2. Fiscal aspects: Challenges and opportunities 3.3 The role of MENA oil importers in strengthening a dual economic growth 4. The reliability of oil price in affecting the gross domestic product in MENA countries 4.1. The Levin Lin Chu 4.2. Im Pesran chin 4.3. Kao Cointegrating Model Residual 4.4. Augmented Dickey Fuller (ADF) 4.5. Panel Dynamic Least Squares (PDOLS) 5. Conclusions 6. References Annex

3 Tables 1. Levels of American crude oil stock movements m/b ( ) 2. World Oil Demand, Production (mb/d) Inflation rate in the MENA Countries (%) and oil price ( ) 4. Deficit / Surplus General Budget as a percentage of GDP MENA Countries + oil prices ( ) 5. Real GDP Growth, Government, External Debt MENA Countries % 6. Gross domestic product % and oil demand in the MENA Countries mb/d ( ) 7. The Levin Lin Chu 8. The Im Pesran chin 9. Kao Cointegrating and Augmented Dickey Fuller (ADF) 10. Panel Dynamic Least Squares (PDOLS) Annex

4 The impact of Oil Shocks on the Economic Growth in the Middle East and North Africa and its Implications Dr.Hudab Al-Kobaisi International Economic Relations-Petroleum Economics Tel: Abstract This paper seeks to investigate the relationship between oil prices and economic growth in the Middle East and North Africa (MENA) region. Since these countries are experiencing the fluctuation of oil price and its effect on economic growth. Which leads to destabilizing in the economic performance and, the relation receives a great deal of attention. Therefore, this paper addresses three questions with particular emphasis on the MENA region. How does the recent drop in oil prices compare with the previous oil shocks, and the significant change in OPEC objectives? How does the oil price impact these economies, on the exporters to adjust the fiscal and monetary policies? For the importers, by strengthening the dual economic growth. How much reliable in oil price to estimate the fluctuation in gross domestic product (GDP)? The framework of this paper is designed in such way to combine the descriptive frame of (Economical theory and its implication) along with the quantitative analysis. The results of time series model, observed oil shocks, from has proven the role of oil price in economic stability, as well as, the influence of oil price in demand. However, from , oil price factor disappeared in affecting OPEC oil. Besides, non-conformity with the economic theory. This paper concludes that the effects of oil price have completely different behavior in each oil shock. 1

5 1. Introduction In the history, the economic and noneconomic factors caused oil price instability at the beginning of the 1970s; mostly, the relationship between oil prices and economic growth, was working on the bases of supply and demand and its effects on the economic activity, this followed by the high growth in oil demand after the two oil shocks 1973 and In the mid- 1980s, speculative oil markets have begun to emerge known as Future Markets, these markets deals with future contract to ensure a low oil price not to be changed in the future. Therefore, energy markets became complex and unpredictable. Over the past four decades, seven oil shocks have been appearing. Oil prices are characterized by strong fluctuations, these determents appears to be dependent on many political and economical factors; oil prices might reflect or even forecast changes in the intercontinental stability in the world economy and in the Middle East and North Africa as well. This paper has chosen the Middle East and North Africa to compare their GDP sensitiveness to oil price volatility. As these fluctuations in oil prices creates a changeable matter in the oil markets. This consequence would take a place in different economic and financial channels, especially, as these MENA countries are considered to be emerging economies. The quantitative analyses covers a sample of *17 MENA countries from , and approached a different statistical tests, the purpose of this paper is to explore if the economic growth in the Middle East and North Africa can be explained by the changes in the oil prices. This paper also approached the ordinary least squares (OLS) model to investigate the track of oil prices. This paper is organized in four sections besides the conclusions and references.. * See the Annex 1.1 Research Problem 2

6 The difficulties in collecting a perfectly data specification for all MENA countries, especially, these countries are a combination of oil exporters and importers. 2. The recent drop in oil prices comparing with the previous oil shocks, along with the change in OPEC objectives 2.1 The feathers of the three past oil shocks The oil market passed through several economical changes during the seventies. Resulting mainly in sudden and abnormal increases in crude oil prices which took place in Consequently leading later on to international economical changes. The Research following the main oil shocks, which covered the period , explained by OLS OPEC time series model indicating the major factors involved into the oil market. The results of the time series model from the non linear relationship indicated the impact of economic variables on oil production and OPEC oil demand as well: The nonlinear relationship represents the increasing in oil demand in particular on OPEC oil production after the first shock 1973, this was in terms of building * the strategic oil stock of the US, not because the purpose of consumption *The Energy Policy and Conservation Act: An Act to increase domestic energy supplies and availability; to restrain energy demand; to prepare for energy emergencies; and for other purposes. This was established in December 1975 which came after the oil embargo, and led to the deterioration in the US economy 3

7 that caused and led to increase in oil prices. Furthermore, it is clear from the relationship that the relation below; between oil demand and its price is positively related which it means (non-conformity with the economic theory) while the price of oil should be inversely related to the demand. (Y2= OPEC production, X1= oil price, X2= world oil demand, X3= time variable) logy2= logx logx logx1 (-5.57) (6.70) (2.66) R² = While the liner relationship from ( ) illustrates that the changes in oil OPEC has been done regardless to the role of oil price. The increases in world oil demand by 1.16 led to increased OPEC production about 31.7 m b/d especially in 1979 the second oil shock. At that time was on the peak of building the strategic oil stock in the industrial countries. (Y2) production as dependent variable explained (%98.08) by the independent variables, (world oil x2 demand, time variable x3) Y2= x x2 (-22.05) (10.33) R² = The Ordinary least squares (OLS) model of OPEC time series from 1973 to1992, has proven, that the nonlinear relationship is an elastic demand on OPEC production estimated (2.60) while the oil price was $ b/d declined to $b/d 14 especially for the period although the world oil demand was mb/d increased to mb/d respectively. Y2= OPEC production, X1= Oil price, X2= World oil demand, X3= Time variable Y2= logx logx2+ 8.4logx1 (-10.51) (8.55) (3.15) R² = Thus concludes that the fall in oil price was %54, while the increase in world oil demand was %107. 4

8 41.8 Following the results of the second period of OPEC time series has proven the contradiction of decreasing and increasing in OPEC production Log Y2 = x log x3 (6.14) (-241) R²= In the mid-1980s, speculative oil markets have begun to emerge known as (Future Markets). These markets deals with future contract (Hedge) to ensure a low oil price not to be changed in the future (Hedging against falling crude oil). At that time OPEC give up from controlling the determents of reference basket price, in front of to maintain the production ceiling, this has led to expansion of speculative (oil markets exchanges) in New York, London and Singapore which it deals with (Paper Barrels) more than (Wet Barrels) (Hussein Abdullah 2000). This debate has not been stopped in 2006; a US Senate subcommittee published a report titled The Role of Market Speculation in Rising Oil and Gas Prices : Among its conclusions was a call for lawmakers and regulators to update and reform regulation of the financial energy markets. To the extent that energy prices are the result of market manipulation or excessive speculation, it should be highlighted that the new rules do not target excessive speculation directly. Instead, they seek to remove some of the conditions that have allowed excessive speculation to flourish (OPEC World Oil Outlook 2015). Moreover, this was raised a question is it fundamentals or trading that primarily drive oil prices? (John Kingston, 2015). Table 1 Q4 Levels of American crude oil stock movements m/b ( ) Oil price $b/d Q3 Q Source: OAPEC Report, 2015, P91 OAPEC Report, 2016, P11 Journal of Oil and Industry News, United Arab Emirates, Abu Dhabi 273 May

9 The outcomes of the future oil market would work to pushing and pulling up the strategic oil stock, on the bases of the future oil price in case is higher than current prices or towards shrinkage the oil stock (Backwardation) when the future price is less than the current price. The USA would go for this option which is buying the oil in terms of future price if it is lower than the current. The level of the oil stock in 1990 was 921 m/d at the price b/$ 22 and reduced to 885 b/d at the price b/$18 (The World Oil Market 2003; IEA2000). Also the table represents the old levels of oil stock in the 1990s which indicated a huge difference in boosting up%77 from 885 m/b in 1992 to1566 m/bin Furthermore, the American oil stock movement reveals that, changes in decline levels in 2013 compeered with the upward levels for the last quarter of While the commercial crude oil stocks rose in October 2015, 26.4%, above the same time in 2014 and 30.9%, above the latest five-year average. This change in oil stock levels caused another change in OPEC Reference Basket from $44.83 to $ in September-October 2015 (OPEC Monthly Report 2015) respectively. 2.2 Recent drop in oil prices: The returns of the present to the past In the present, the world is witnessing sudden and fast changes which influenced the oil market and led to serious changes in the growth rates of oil demand. Other shocks subsequent oil shocks were primarily driven by weakening global demand following U.S. recessions ( and 2001); the Asian crisis ( ); and the global financial crisis ( ). The latest shock (June 2014-January 2015) constitutes the third largest price drop (Understanding the plunge2015) The latest oil shock has some significant parallels with the price collapse in the Oil price drop in has two key parallels to 1980s, as both oil shocks followed a period of rapid growth in the oil supply from non-opec countries besides shifting in OPEC policy (World Bank, January 2015) and the eventual decision by forgo price targeting and increase production. 6

10 Hence, when oil prices dropped sharply between June 2014 and January 2015, bringing to an end a four year period of relative price stability. The decline in oil prices has been much larger than that of other commodity prices. This collapse in prices was driven by a marked slowdown in oil demand growth and record increases in supply particularly tight oil from North America, as well as the decision by the OPEC countries in November 2014 not to try to rebalance the market through cuts in output, the point of view was made that OPEC decision to leave the production target unchanged was then generated for further price falls (David Hough, Cassie Barton 2016). In order to understand these contradictions Perspectives, by reviewing the figures in the coming table which point out a regular growing in oil world demand from While OPEC production in 2015 under the price $b/d 41.8 was at the same level of 2013 under the price $b/d A question is raised: why this falling in oil prices, while the sum of OPEC oil shares in 2014 was less than other previous years? Table2 World Oil Demand, Production oil mb/d Years World Demand 87,33 88,19 89,01 90,36 91, World Production OPEC Production OPEC % 69,8 70,4 72,7 72,9 73, ,24 30,12 32,42 31,60 30,68 31, Source OPEC, Annual Statistical Bulletin 2015, 50 th edition OPEC Monthly oil market Report18 January

11 Therefore, with regard to oil shares from non-opec, this should be taken in consideration, especially from the US growth in oil supply reached mb/d in 2015 compare to mb/d in 2014 (OPEC Monthly Report, Jan 2016) As it mentioned that, this latest oil shock is parallels with the price collapse in the , it should be noted that the results of OLS world oil demand indicates, the liner relationship from included the most important oil shocks, point out that, an increase in world oil demand about 1.11mb/d, this should meet the boosts in oil production about one million barrel a day to maintain the stability in oil prices. As: Y1word oil production, X2 world oil demand. Y1= x x3 (7.51) (-4.64) R² =77.31 Back to the table 2, the world oil production has indicated an extra amount reached to 15.2 mb/d in 2015 camper to2014, while the oil demand increased about one million barrel a day, at this point of exceeded oil production, obviously, price would be collapsed sharply. Although was pointed to OPEC that, this non action marked a change from the decision of when deep production cuts were made to prevent prices from falling further, this was translated that OPEC s decision to maintain output may be a strategic one, intended to drive high cost producers out of the market and maintain market shares, Saudi Arabia has said it will not cut production regardless of price levels, be it $40, $30 or $20 per barrel (Zhenbo Hou, Jodie Keane, 2015). Hence, both oil shocks meets the similarity in oil supply glut and but the difference is in the first time was by OPEC but the last one done by non-opec countries and several years of upward in the production of unconventional oil as well! 8

12 3. The impact of oil price in the MENA Countries and its implications Fluctuations in Oil prices and inflation have been positively related; the decline in oil prices will leads a considerable income shift from oil exporters to oil importers in MENA countries over the medium term. On the other hand, it would affect oilexporting countries adversely by weakening fiscal and external positions and reducing economic activity. 3.1 Monetary issues: Cause and effects The decline in oil prices has extensive macroeconomic effects and policy implications. The drop in oil price, would effects direct through trade or indirect through growth and investment and changes in inflation While For oil exporters, falling oil prices would support activity and reduce inflation in the MENA countries. In fact, lower oil prices reduce energy costs since oil is feedstock for various sectors, including petrochemicals, paper, and aluminum, the decline in price directly impacts a wide range of processed or semi-processed inputs (Global Economic Prospects 2015.P162). In general the positive side in the lower oil prices tends to lower overall inflation. The negative side, lower oil prices reduce the extraction and drilling incentive for producers, which has become more important in recent years as the United States has become a large crude oil producer. Kevin L. Kliesen, Are Oil Price Declines Good for the Economy? Federal Reserve Bank, 2015, No. 3. Table 3 represents the fluctuation in oil price and inflation has been positively correlated, Even though this relationship has varied widely across countries. Large decreases in oil prices during the 9

13 last three years were often followed by cycles of low inflation for instance, Jordan as in many other countries, Sustained low oil prices are likely to have significant implications. Table 3 Inflation rate in the MENA Countries % & oil price ( ) Country Oil price$/b Jordan UAE Bahrain Tunisia Algeria Djibouti Saudi Arabia Sudan Iraq Oman Qatar Qumran Kuwait Lebanon Libya Egypt Morocco Mauritania Yemen MENA Source: The prospects of the Arab Economy Report Fiscal aspects: Challenges and opportunities The decline in oil prices will have major effects in fiscal and external debts, in oilexporting and importing countries. 10

14 With regard to the fiscal matters, the loss in oil revenues for exporters will damage public finances, while savings among oil importers could help rebuild fiscal space. Current account balances are expected to improve in oil-importing countries and deteriorate in oil-exporting countries. Table 4 Deficit / Surplus General Budget as a percentage of GDP In the MENA Countries + oil prices ( ) Country Oil price$/b Jordan UAE Bahrain Tunisia Algeria Djibouti Saudi.Arabia Sudan Iraq Oman Qatar Kuwait Lebanon Libya Egypt Morocco Mauritania Yemen MENA Source: The prospects of the Arab Economy Report

15 A number of MENA countries provide large fuel subsidies totheir populations. In some cases, the cost of subsidies exceeds %5 of GDP, which leads to Savings on subsidies (Energy subsidies2014) Although Fiscal deficits are expected to remain high with MENA importers countries in the medium-term. While lower oil prices presents an opportunity to implement structural reforms (World Bank March, 2015).The revenue structure of oil exporting countries is dominated large oil sectors. Table 4 represents that, both oil exporters and importers have been affected by the recent sharp drop in oil prices, for some importers, the deficit was lower in 2015 after the oil shock than before. In general the table indicated, the MENA countries in 2015 was suffering from high deficit except Qatar was estimated a surplus and mostly due to the large dependence in producing natural gas. In order to understand other fundamental economic indicators of the MENA countries from the view of government net debt and external debt related to the economic growth and the effects of oil price, which classified differently oil importers from exporters. Table 5 represents that, MENA exporters in the period of oil drop this has not affected on the economic growth as well as the government dept but the External Debt would be increased in the short run. While the GDP for the MENA importers were increasing by the lower oil prices, this would be considered as economic activity to the importers and could be activated their growth. While for the importers on the long run would reduce the External Debt. The impact of the low oil prices for the exporters on long time may dampen economic activity. Table 5 12

16 Real GDP Growth, Government, External Debt MENA Countries % Oil price $/b MENA GDP Oil exporters Total Government Net Debt Total Gross External Debt MENA GDP Oil importer Total Government Net Debt Total Gross External Debt Source:IMF, Statistical Appendix, 2015 In several oil exporters that have not been able to accumulate substantial resources, will face substantial pressures on their budgets, for instance Iraq and the severe damage in the budget because of dependency on oil sector. 3.3 The role of MENA oil importers in strengthening a dual economic growth The impact of the MENA countries and the economic growth on oil price can be seen in the light of GDP as one of the main determinants of oil demand, in the MENA countries, oil prices tend to be fluctuating, due to the differences in the business cycle, unexpected economic growth has an important impact on oil demand 13 In the Middle East and North Africa, the potential gross domestic product improvements in the region offer some upside in oil demand. Egypt one of the region s largest

17 economies is forecast to recover well in the medium-term and support regional growth. Ongoing challenges, the domestic oil demand also would be affecting due to the geopolitical developments in the region. Hence, average GDP growth rates scenarios for the period is estimated the higher economic growth is %3.6 and increase the oil demand to 12.8 mb/d (World Oil Outlook 2015). Oil prices then, tend to be fluctuating, due to differences in the business cycle for that reason, unexpected economic events have an important impact on oil demand this can be viewed in the fact that the most recent global financial crisis has had significant implications on oil demand projections. Back in 2008, before the severity of the crisis became evident, oil demand projections for 2015 in the *WOO were at around 96 mb/d. However, demand projections for 2015 in the WOO 2009 and the WOO 2010, which assumed significantly lower GDP growth, were reduced to 90 mb/d and 91 mb/d, respectively (World Oil Outlook 2015). Table 6 Gross domestic product % and oil demand in the MENA Countries 14

18 mb/d ( ) MENA GDP Oil Demand Oil price $/b by the researcher/ based on: - AOPEC, the secretary-general's Annual report 40 - OPEC Monthly Oil Market Report November OPEC Monthly Oil Market Report January OPEC World Oil Outlook 2015 Prepared Therefore, the Impact of drop oil price, should be strengthening the economic growth in importers since economic activity in these countries would generate more oil demand, thus would furthermore enhancing another economic growth to the exporting countries. In this case the impact of low oil price would work as dual effects by stimulating the economic growth in both sides Table 6 represents that GDP is increasing in each oil price drop; it would generates more oil demand from the MENA countries especially from oil importers. Although the projection of oil price predicted to be $80b/d but there is a trend that GDP would be 3.6 more than the previous period. 4. The reliability of oil price in affecting the gross domestic product in MENA countries During the half quarter of 2014, the world has experience low oil prices the extreme fluctuation of what is consider of an oil shock in the global economy. This has been raised a very fundamental question? How much is reliable oil price in affecting economic growth in MENA countries, and led predicting variation in GDP growth remains a 15 controversial issue. Several models have been developed targeting different relations between oil price and GDP growth according to its effects on oil markets. Other variables

19 may have dominated role and led to consequences in gross domestic product. Policy makers face a dual challenge one in adjusting to lower oil prices and dealing with security risks in the short run, and boost growth and employment in the long run, moreover, the large role played by governments in these economies, make economic adjustment more difficult.(global-economic-prospects2015) The research approached different statistical test, Panel-data unit-root tests, cointegration model, and Panel Dynamic Least Squares (PDOLS) are taken part of this section. The sample was extended to include (17) countries of the Middle East and North Africa, data of the research is from 2009 to The causality relationship between different time series is based on: GDP = F (P, K, L) While: P is to explain the oil price, K for the fixed capital and L for the labor are explained as independent variable, while GDP is the dependent variable. to investigate the relationship between the variables that mentioned the research approached different tests to search for stationarity or non-stationarity of the cross section time series, different tests of the unit root and the cointegrating model were applying, to avoid the problematic which related in the explanatory variables in explaining their impacts on GDP through the oil shocks 4.1. The Levin Lin Chu 4.2. Im Pesran chin 4.3. Kao Cointegrating Model Residual 4.4. Augmented Dickey Fuller (ADF) 4.5. Panel Dynamic Least Squares (PDOLS) 16

20 4.1. The Levin Lin Chu (2002) Started with *GDP variable the estimation which has been indicated, the null hypothesis which means that, the series contains a unit root: Since H0: series imply a unit root ( ) under the probability ( ) So the hypothesis would be rejected. And the series is stationary. This should go to the alternative hypothesis H1: to confirm the relation between the variables and its efect. The Levin Lin Chu test assumes a common autoregressive parameter for all panels, so this test does not allow, the dependent variable GDP explains the changes would happen into independent variables, in other words to expose the causality of oil prices, labor and fixed capital on gross domestic product in the MENA at short time, there might be structural breaks that are causing the problem with the unit root test due to the Probability that some countries within the sample contain unit roots, while other countries do not, since the sample of the data imply exporters and importers 4.2. Im Pesran chin test where applied to the MENA countries data to examine whether the series contains a unit root or not; the results were in the same direction of the first root test that also it contains a unit root. Moreover, the research runs the same previous tests for fixed capital (K) as well as for the labor (L), where both are in the direction of H0: hypothesis, the series also contains a unit root, and for the exporters. Except that the labor force would not change in the short run in spite of lower oil price. While the results in the table 7 of The Levin Lin Chu test for the oil price (P) proved that the oil price is affecting the (GDP) in the MENA countries * See the Annex 17

21 Table 7 Null Hypothesis: Unit root (common unit root process) Series: P Date: 01/01/16 Time: 14:14 Sample: Exogenous variables: Individual effects User-specified lags: 1 Newey-West automatic bandwidth selection and Bartlett kernel Total (balanced) observations: 85 Cross-sections included: 17 Method Statistic Prob.** Levin, Lin & Chu t* ** Probabilities are computed assuming asympotic normality Intermediate results on P Cross 2nd Stag... Varianc... HAC of Max Bandsection Coefficie... of Reg Dep. Lag Lag width Obs Algeria Bahrain Egyby Iran Israel Jordan Kuwait Lebanon Libya Mouritania Morocco Oman Qatar Saudi Arabia Tunisia Turkey United (UAE) Coefficie... t-stat SE Reg mu* sig* Obs Pooled Although, the Im Pesran chin proved it with semi non-stationary at the level where the probability of the null hypothesis of unit root is as in the table 8, especially, after the first difference where taken, which is a common behavior would happen to the explanatory variable within the time of the cross section. So the price is integrated as a first-class variable and affects the GDP. 18 Table 8

22 Null Hypothesis: Unit root (individual unit root process) Series: P Date: 01/01/16 Time: 14:15 Sample: Exogenous variables: Individual effects User-specified lags: 1 Total (balanced) observations: 85 Cross-sections included: 17 Method Statistic Prob.*... Im, Pesaran and Shin W-stat ** Probabilities are computed assuming asympotic normality Intermediate ADF test results Cross Max section t-stat Prob. E(t) E(Var... Lag Lag Obs Algeria Bahrain Egyby Iran Israel Jordan Kuwait Lebanon Libya Mouritania Morocco Oman Qatar Saudi Arabia Tunisia Turkey United (UAE) Average Warning: for some series the expected mean and variance for the given lag and observation are not covered in IPS paper 4.3. Kao Cointegrating Model Residual By using the Kao cointegration test the table represents that, this statistical method represents a successful integrated where the tests indicated the presence of cointegration between the variables (P, K, L) are affecting GDP. In spite of it might be co-integrated about (0.0548) Augmented Dickey Fuller (ADF) 19

23 The result of Augmented Dickey Fuller (ADF) method, this test detects the presence or absence of a unit root. In other words indicated that, this is non-stationary statistical series. As the three independent variables (P, K, L) were verified and affected the dependent variable (GDP), this concludes the return causality feedback causality between the variables. As in the table 9. Table 9 Kao Residual Cointegration Test Series: GDP K L P Date: 01/01/16 Time: 14:30 Sample: Included observations: 119 Null Hypothesis: No cointegration Trend assumption: No deterministic trend User-specified lag length: 1 Newey-West automatic bandwidth selection and Bartlett kernel t-statistic Prob. ADF Residual variance HAC variance Augmented Dickey-Fuller Test Equation Dependent Variable: D(RESID) Method: Least Squares Date: 01/01/16 Time: 14:30 Sample (adjusted): Included observations: 85 after adjustments Variable Coefficient Std. Error t-statistic Prob. RESID(-1) D(RESID(-1)) R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Akaike info criterion Sum squared resid Schwarz criterion Log likelihood Hannan-Quinn criter Durbin-Watson stat The ²R estimated as an appropriate result, more than %72 of independent variables of (P, K, L) explained the change in dependent variable of GDP. With acceptance of null hypothesis, (T-statistic and Durbin-Watson) as well Panel Dynamic Least Squares (PDOLS) 20

24 In the light of the previous results and by using the Panel Dynamic Least Squares (PDOLS) method in order to describe the change of the independent variables over time, by considering a constant and non constant, linear trend and Quadratic trend to explain a long term tendency. The results-table 10 indicated that the coefficient of the MENA variables are statistically significant in all regressions the variable of oil price and its impact was negative in all regressions agreed with economic theory and statistically was significant in the Quadratic trend. Table 10 Dependent Variable: GDP Method: Panel Dynamic Least Squares (DOLS) Date: 01/02/16 Time: 13:33 Sample: Periods included: 7 Cross-sections included: 17 Total panel (balanced) observations: 119 Panel method: Pooled estimation Cointegrating equation Static OLS leads and lags specification Coefficient covariance computed using sandwich method Long-run variances (Bartlett kernel, Newey-West fixed bandwidth) used for coefficient covariances No d.f. adjustment for standard errors & covariance Variable Coefficient Std. Error t-statistic Prob. K L P R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Sum squared resid Durbin-Watson stat Long-run variance This concludes that, the effects of oil price in GDP would appears on the long run in the MENA countries, but it should be noted that, as this has not yet translated into stronger economic growth. 5. Conclusion 21

25 This paper has estimated the effects of oil price shocks on the economic activity of the Middle East and North Africa, and focuses on the relationship between oil price and GDP growth, which analyzed in terms of, Panel-data unit-root tests, cointegration model, and Panel Dynamic Least Squares (PDOLS). This relationship examined by the unit-root approach, in which oil prices are assumed to have consistent impacts on economic growth and this came to conclusion that, the oil prices affected the gross domestic product, which explains the effective role of the oil price as an independent variable on the GDP as a dependent variable. Moreover, it concluded that, by the (ADF) method the interaction between oil variable and other macroeconomic variables, as fixed capital and labor are found to be fundamental factors by explaining the change in GDP. While the further statistic methods such as, Levin Lin Chu and the Im Pesran chin, they have not shown a clear impact from fixed capital and labor on GDP and vice versa. As the consequences of the continuation effects of oil prices, have a completely different behavior in each oil shock, the results of the Ordinary least squares (OLS) of OPEC model as well as world oil demand and oil production models, indicates the action of oil price throughout the 1970s and its effects on world oil demand was positively related, which is completely contrary to the economic theory. While in the 1980s world oil demand led the OPEC production done, regardless, of oil price role. In other words oil price factor disappeared in affecting OPEC oil. Besides, non-conformity with the economic theory and despite of that OPEC production was acceded, thus led to a series of declines in oil prices till-1990s. While the cause of the fall in oil prices it was similar to the oil shock in due to the estimation, caused by the supply glut as well, but differed this time as it is from non-opec countries. While the cause of the fall in oil prices , due to the estimation, it is similar to the oil shock in , caused by the supply glut as well, but this time differed from the past since it is for non-opec countries 22

26 6. References Global-Economic-Prospects, 2015 June, Middle-East-and-North-Africa-analysis, P5 Hussein Abdullah, 2000, the future of the Arab oil magazine, Beirut, November, PP28-31 John Kingston 2015 September7, Paper and barrels, pushing and pulling oil prices: Petrodollars Hedging against Falling Crude Oil Prices using Crude Oil Futures, The OptionsGuide.com, The World Oil Market Current Conditions and Immediate Prospects, September 2003 Report to the100 th Meeting of the Economic Commission Board, OPEC Secretariat, P.32. Prices Glossary, 2000, International Energy Agency, August, p44 OPEC Monthly Oil Market Report November 2015, PP OPEC, World Oil Outlook 2015, PP John Baffes; AyhanKose, 2015 January understanding the plunge in oil prices: Sources and implications, World Bank, Global Economic Prospects P159 World Bank Group, 2015 March, The Great Plunge in Oil Prices: Causes, Consequences, and Policy Responses, PP5-6. David Hough; Cassie Barton, 14 January 2016, No 04153, House of Commons, p5. OPEC Monthly oil market Report18 January 2016 OPEC Monthly Report, Jan P46 OPEC, Annual Statistical Bulletin 2015, 50 th edition PP42-28 Zhenbo Hou, Jodie Keane, March 2015, the oil price shock of 2014 Drivers, impacts and policy implication. Working paper 415, P11 Kevin L. Kliesen, 2015, Are Oil Price Declines Good for the Economy? Federal Reserve Bank, No. 3. The prospects of the Arab economy report, 2015, PP55-57 IMF, Statistical Appendix, 2015 AOPEC, the secretary-general's Annual report 40 OPEC Monthly Oil Market Report November

27 Energy subsidies in the Middle East and North Africa lessons for reform March, OPEC World Oil Outlook 2015 PP Journal of Oil and Industry News, United Arab Emirates, Abu Dhabi 273 Issue, May 1993, P2 Unified Arab Economic Report , 1990 OAPEC Reports 1988, 1991 Follow up activities of the energy sources of Arab and International World oil trends, Cambridge Energy Research, World Economic Form The global Competitiveness Report, ( ) ( ),( ),( ),( ), ( ) ( ) International Monetary Fund April 2015 World Economic Situation and prospects 2015 OAPFC, the Secretary Generals 41 Annual Report, 2014 World Economic situation and prospects 2012 ESCWA, National Accounts studies of the Arab Region, Bulletin No.33, New York,

28 Annex Function Type Table 1 Years world oil demand model The mathematical form of the function R² (%) Rˉ² (%) F D.W Linear Half logarithmic Double logarithmic Y2= x3 Y2= logx3 logy2= logx3 (-4.01) (-4.39) Linear Half logarithmic Double logarithmic Linear Half logarithmic Double logarithmic Y2= x3+1.57x2 (-11.84) (8.15) Y2= logx3+1.88logx2 (-10.25) (6.49) lohy2= logx3+3.60logx2 (-9.59) (6.38) Y2= x3+1.45x2-0.11x1 (-10.74) (7.87) (-2.12) Y2= logx3+2.28logx2+8.4logx1 (-10.51) (8.55) (3.15) logy2= logx3+4.36logx logx1 (-9.76) (8.25) -(3.02) Source: computed Time X3 oil demand X2 oil price X1 OPEC production Y Linear Half logarithmic Double logarithmic Linear Double logarithmic Double logarithmic Table 2 OPEC oil demand model Y1= *3 (-4.01) Y1= log x2 (4.19) logy1= log x2 (4.22) Y1= x x3 (7.51) (-4.64) logy1= logx2-4.8logx3 (5.8) (-3.07) logy1= logx2-0.35logx3 (5.87) (-3.11) Source: Author calculation Oil production Oil demand Time variables R²(%) Rˉ²(%) F D.W

29 Table 3 OPEC oil production model Type of the function Linear Half logarithmic Double logarithmic Linear Half logarithmic Double logarithmic Half logarithmic Double logarithmic Years OPEC oil production model Mathematical function form Y2= x3 (-6.16) Y2= logx3 (-3.49) logy2= logx3 (-3.41) Y2= x3+1.16x2 (-22.05) (10.33) Y logx logx2 (-7.04) (4.88) logy2= logx3+3.95logx2 (-6.85) (4.33) Y2= logx3+2.52logx2+1.3logx1 (-5.32) (6.20) (2.24) logy2= logx3+4.70logx2+0.30logx1 (-5.57) (6.70) (2.66) R² (%) Rˉ² (%) F D.W Source: Computed Y2= OPEC production X1= Oil PriceX2= World oil demand X3=Time variables Table 4 OPEC oil production model R² (%) Rˉ²% F DW Linear Half logarithmic Double logarithmic Half logarithmic Double logarithmic Y2= x2 (13.07) Y2= logx2 (12.25) logy2= logx2 (13.79) Y2= logx2-5.4logx3 (5.15) (-2.09) LogY2= x logx3 (6.14) (-241)

30 Annex for different tests Levin, lin, chu test GDP variable Null Hypothesis: Unit root (individual unit root process) Series: GDP Date: 01/01/16 Time: 14:06 Sample: Exogenous variables: Individual effects User-specified lags: 1 Total (balanced) observations: 85 Cross-sections included: 17 Method Statistic Prob.*... Im, Pesaran and Shin W-stat ** Probabilities are computed assuming asympotic normality Intermediate ADF test results Cross Max section t-stat Prob. E(t) E(Var... Lag Lag Obs Algeria Bahrain Egyby Iran Israel Jordan Kuwait Lebanon Libya Mouritania Morocco Oman Qatar Saudi Arabia Tunisia Turkey United (UAE) Average Warning: for some series the expected mean and variance for the given lag and observation are not covered in IPS paper im, pesran, chin test Null Hypothesis: Unit root (common unit root process) Series: GDP Date: 01/01/16 Time: 14:01 Sample: Exogenous variables: Individual effects User-specified lags: 1 Newey-West automatic bandwidth selection and Bartlett kernel Total (balanced) observations: 85 Cross-sections included: 17 Method Statistic Prob.** Levin, Lin & Chu t* ** Probabilities are computed assuming asympotic normality Intermediate results on GDP Cross 2nd Stag... Varianc... HAC of Max Bandsection Coefficie... of Reg Dep. Lag Lag width Obs Algeria Bahrain Egyby Iran Israel Jordan Kuwait Lebanon Libya Mouritania Morocco Oman Qatar Saudi Arabia Tunisia Turkey United (UAE) Coefficie... t-stat SE Reg mu* sig* Obs Pooled

31 Levin, lin, chu test Fixed capital Null Hypothesis: Unit root (common unit root process) Series: K Date: 01/01/16 Time: 14:09 Sample: Exogenous variables: Individual effects User-specified lags: 1 Newey-West automatic bandwidth selection and Bartlett kernel Total (balanced) observations: 85 Cross-sections included: 17 Method Statistic Prob.** Levin, Lin & Chu t* ** Probabilities are computed assuming asympotic normality Intermediate results on K Cross 2nd Stag... Varianc... HAC of Max Bandsection Coefficie... of Reg Dep. Lag Lag width Obs Algeria Bahrain Egyby Iran Israel Jordan Kuwait Lebanon Libya Mouritania Morocco Oman Qatar Saudi Arabia Tunisia Turkey United (UAE) Coefficie... t-stat SE Reg mu* sig* Obs Pooled im, pesran, chin test Null Hypothesis: Unit root (individual unit root process) Series: K Date: 01/01/16 Time: 14:10 Sample: Exogenous variables: Individual effects User-specified lags: 1 Total (balanced) observations: 85 Cross-sections included: 17 Method Statistic Prob.*... Im, Pesaran and Shin W-stat ** Probabilities are computed assuming asympotic normality Intermediate ADF test results Cross Max section t-stat Prob. E(t) E(Var... Lag Lag Obs Algeria Bahrain Egyby Iran Israel Jordan Kuwait Lebanon Libya Mouritania Morocco Oman Qatar Saudi Arabia Tunisia Turkey United (UAE) Average Warning: for some series the expected mean and variance for the given lag and observation are not covered in IPS paper 28

32 Null Hypothesis: Unit root (common unit root process) Series: L Date: 01/01/16 Time: 14:12 Sample: Exogenous variables: Individual effects User-specified lags: 1 Newey-West automatic bandwidth selection and Bartlett kernel Total (balanced) observations: 85 Cross-sections included: 17 Method Statistic Prob.** Levin, Lin & Chu t* ** Probabilities are computed assuming asympotic normality Intermediate results on L Cross 2nd Stag... Varianc... HAC of Max Bandsection Coefficie... of Reg Dep. Lag Lag width Obs Algeria Bahrain Egyby Iran Israel Jordan Kuwait Lebanon Libya Mouritania Morocco Oman Qatar Saudi Arabia Tunisia Turkey United (UAE) Coefficie... t-stat SE Reg mu* sig* Obs Pooled Null Hypothesis: Unit root (individual unit root process) Series: L Date: 01/01/16 Time: 14:13 Sample: Exogenous variables: Individual effects User-specified lags: 1 Total (balanced) observations: 85 Cross-sections included: 17 Method Statistic Prob.*... Im, Pesaran and Shin W-stat ** Probabilities are computed assuming asympotic normality Intermediate ADF test results Cross Max section t-stat Prob. E(t) E(Var... Lag Lag Obs Algeria Bahrain Egyby Iran Israel Jordan Kuwait Lebanon Libya Mouritania Morocco Oman Qatar Saudi Arabia Tunisia Turkey United (UAE) Average Warning: for some series the expected mean and variance for the given lag and observation are not covered in IPS paper 29