# Analysis of Oil Price Effect on Economic Growth of ASEAN Net Oil Exporters

^{*}

## Abstract

**:**

## 1. Introduction

## 2. Literature Review

## 3. Results

#### 3.1. Empirical Model

_{t}represents the white noise residuals.

^{2}to λ

^{5}normalise on λ

^{1}for Equation (3). However, the long-run estimates are meaningful only if cointegration can be established. There are three separate tests to establish the existence of cointegration among the variables, namely, the F-test for joint significance of lagged variables and the t-test on the lagged level of the dependent variable as suggested by Pesaran et al. [52] and another additional F-test on the lagged levels of the independent variable(s) as suggested by McNown et al. [54].

#### 3.2. Data and Sources

## 4. Empirical Results

#### 4.1. Unit Root Tests

#### 4.2. ARDL Results: Linear Model

^{2}value is reported to determine the goodness of fit, which in this case is good for all three countries. To determine whether the short-run and long-run coefficient estimates are stable, the CUSUM and CUSUM

^{2}are utilised following Pesaran et al. [52]. For all three countries, the estimates are stable for both CUSUM and CUSUM

^{2}, which is unsurprising given that the inclusion of a dummy variable, to account for the structural break, would lead to a stable estimate. Among the three countries being studied, the dummy variable is only significant for Brunei, which means that the exclusion of a dummy variable for Brunei will lead to a biased result and the CUSUM or CUSUM

^{2}test might be unstable. Surprisingly, despite the Zivot and Andrews [58] unit root tests indicating the existence of a structural break, both the ARDL model for Malaysia and Vietnam do not suffer from any structural break.

#### 4.3. ARDL Results: Nonlinear Model

^{2}, suggesting goodness of fit. CUSUM and CUSUM

^{2}results suggest the estimates are stable within the 5% confidence band for Brunei and Malaysia. For the case of Vietnam, the parameters are stable for CUSUM but unstable for the CUSUM

^{2}test. Furthermore, the RAMSEY reset test indicates misspecification error for the case of Vietnam only.

## 5. Conclusions and Policy Implications

## Author Contributions

## Funding

## Acknowledgments

## Conflicts of Interest

## References

- Lang, K.; Auer, B.R. The economic and financial properties of crude oil: A review. N. Am. J. Econ. Financ.
**2019**. [Google Scholar] [CrossRef] - Amano, R.A.; van Norden, S. Oil prices and the rise and fall of the US real exchange rate. J. Int. Money Financ.
**1998**, 17, 299–316. [Google Scholar] [CrossRef] - Dawson, J.C. The effect of oil prices on exchange rates: A case study of the Dominican Republic. The Park Place Economist.
**2004**, 14, 23–30. [Google Scholar] - Uddin, G.S.; Tiwari, A.K.; Arouri, M.; Teulon, F. On the relationship between oil price and exchange rates: A wavelet analysis. Econ. Model.
**2013**, 35, 502–507. [Google Scholar] [CrossRef] - Salisu, A.A.; Isah, K.O. Revisiting the oil price and stock market nexus: A nonlinear Panel ARDL approach. Econ. Model.
**2017**, 66, 258–271. [Google Scholar] [CrossRef] - Wang, Y.; Wu, C.; Yang, L. Oil price shocks and stock market activities: Evidence from oil-importing and oil-exporting countries. J. Comp. Econ.
**2013**, 41, 1220–1239. [Google Scholar] [CrossRef] - Wei, Y.; Guo, X. Oil price shocks and China’s stock market. Energy
**2017**, 140, 185–197. [Google Scholar] [CrossRef] - Aydın, L.; Acar, M. Economic impact of oil price shocks on the Turkish economy in the coming decades: A dynamic CGE analysis. Energy Policy
**2011**, 39, 1722–1731. [Google Scholar] [CrossRef] - Humbatova, I.S.; Hajiyev, Q.N. Oil Factor in Economic Development. Energies
**2019**, 12, 1578. [Google Scholar] [CrossRef] - Nusair, S.A. The effects of oil price shocks on the economies of the Gulf Co-operation Council countries: Nonlinear analysis. Energy Policy
**2016**, 91, 256–267. [Google Scholar] [CrossRef] - Hamilton, J.D. Oil and the Macroeconomy since World War II. J. Political Econ.
**1983**, 91, 228–248. [Google Scholar] [CrossRef] - Su, X.; Zhu, H.; You, W.; Yinghua, R. Heterogeneous effects of oil shocks on exchange rates evidence from a quantile regression approach. SpringerPlus
**2016**, 5, 1187. [Google Scholar] [CrossRef] [PubMed] - Kuboniwa, M. A comparative analysis of the impact of oil prices on oil-rich emerging economies in the Pacific Rim. J. Comp. Econ.
**2014**, 42, 328–339. [Google Scholar] [CrossRef] - Qianqian, Z. The Impact of International Oil Price Fluctuation on China’s Economy. Energy Procedia
**2011**, 5, 1360–1364. [Google Scholar] [CrossRef] - Mehrara, M.; Mohaghegh, M. Macroeconomic Dynamics in the Oil Exporting Countries: A Panel VAR study. Int. J. Bus. Soc. Sci.
**2011**, 2, 288–295. [Google Scholar] - Rautava, J. The role of oil prices and the real exchange rate in Russia’s economy—A cointegration approach. J. Comp. Econ.
**2004**, 32, 315–327. [Google Scholar] [CrossRef] - U.S. Energy Information Administration. International Energy Statistics; U.S. Energy Information Administration: Washington, DC, USA, 2019. [Google Scholar]
- Ministry of Finance Malaysia. Estimates of Federal Government’s Revenue 2015; Ministry of Finance Malaysia: Putrajaya, Malaysia, 2016.
- General Statistics Office of Vietnam. National Accounts and State Budget; General Statistics Office of Vietnam: Hanoi, Vietnam, 2018.
- International Monetary Fund. Brunei Darussalam—Statistical Appendix; International Monetary Fund: Washington, DC, USA, 2016. [Google Scholar]
- Moshiri, S.; Banihashem, A. Asymmetric Effects of Oil Price Shocks on Economic Growth of Oil-Exporting Countries. 2012. Available online: http://dx.doi.org/10.2139/ssrn.2006763 (accessed on 10 April 2019).
- Donayre, L.; Wilmot, N.A. The Asymmetric Effects of Oil Price Shocks on the Canadian Economy. Int. J. Energy Econ. Policy
**2016**, 6, 167–182. [Google Scholar] [CrossRef] - Mork, K.A. Oil and the Macroeconomy When Prices Go Up and Down: An Extension of Hamilton’s Results. J. Political Econ.
**1989**, 97, 740–744. [Google Scholar] [CrossRef] - Shin, Y.; Yu, B.; Greenwood-Nimmo, M. Modelling Asymmetric Cointegration and Dynamic Multipliers in a Nonlinear ARDL Framework. In Festschrift in Honor of Peter Schmidt: Econometric Methods and Applications; Sickles, R.C., Horrace, W.C., Eds.; Springer: New York, NY, USA, 2014; pp. 281–314. [Google Scholar] [CrossRef]
- Aziz, M.I.A.; Dahalan, J. Oil Price Shocks and Macroeconomic Activities in Asean-5 Countries: A Panel VAR Approach. Eurasian J. Bus. Econ.
**2015**, 8, 101–120. [Google Scholar] [CrossRef] - Sun, Q.; Tong, W.; Yu, Q. Determinants of foreign direct investment across China. J. Int. Money Finance
**2002**, 21, 79–113. [Google Scholar] [CrossRef] - Burbidge, J.; Harrison, A. Testing for the Effects of Oil-Price Rises using Vector Autoregressions. Int. Econ. Rev.
**1984**, 25, 459–484. [Google Scholar] [CrossRef] - Darby, M.R. The Price of Oil and World Inflation and Recession. Am. Econ. Rev.
**1982**, 72, 738–751. [Google Scholar] - Rasche, R.H.; Tatom, J.A. Energy price shocks, aggregate supply and monetary policy: The theory and the international evidence. Carnegie-Rochester Conf. Ser. Public Policy
**1981**, 14, 9–93. [Google Scholar] [CrossRef] - Farzanegan, M.R.; Markwardt, G. The effects of oil price shocks on the Iranian economy. Energy Econ.
**2009**, 31, 134–151. [Google Scholar] [CrossRef][Green Version] - Granger, C.W.J.; Terasvirta, T. Modelling non-linear economic relationships; Oxford University Press: Oxford, UK, 1993. [Google Scholar]
- Ghalayini, L. The Interaction between Oil Price and Economic Growth. Middle East. Finance Econ.
**2011**, 13, 127–141. [Google Scholar] - Corden, W.M.; Neary, J.P. Booming Sector and De-Industrialisation in a Small Open Economy. Econ. J.
**1982**, 92, 825–848. [Google Scholar] [CrossRef] - Ito, K. Dutch disease and Russia. Int. Econ.
**2017**, 151, 66–70. [Google Scholar] [CrossRef] - Korhonen, I.; Mehrotra, A.N. Real Exchange Rate, Output and Oil: Case of Four Large Energy Producers. SSRN Electron. J.
**2009**. [Google Scholar] [CrossRef][Green Version] - Kose, N.; Baimaganbetov, S. The asymmetric impact of oil price shocks on Kazakhstan macroeconomic dynamics: A structural vector autoregression approach. Int. J. Energy Econ. Policy
**2015**, 5, 1058–1064. [Google Scholar] - Xavier, S.I.X. I Just Ran Two Million Regressions. Am. Econ. Rev.
**1997**, 87, 178–183. [Google Scholar] - Loayza, N.V.; Oviedo, A.M.; Servén, L. The Impact of Regulation on Growth and Informality—Cross-Country Evidence, Vol. 1 Of 1; The World Bank: Washington, DC, USA, 2005; p. 22. [Google Scholar] [CrossRef]
- Levine, R.; Renelt, D. A Sensitivity Analysis of Cross-Country Growth Regressions. Am. Econ. Rev.
**1992**, 82, 942–963. [Google Scholar] - Campos, N.F. Will the Future Be Better Tomorrow? The Growth Prospects of Transition Economies Revisited. J. Comp. Econ.
**2001**, 29, 663–676. [Google Scholar] [CrossRef][Green Version] - Azman-Saini, W.N.W.; Baharumshah, A.Z.; Law, S.H. Foreign direct investment, economic freedom and economic growth: International evidence. Econ. Model.
**2010**, 27, 1079–1089. [Google Scholar] [CrossRef] - Fattouh, B. An Anatomy of the Crude Oil Pricing System; Oxford Institute for Energy Studies: Oxford, UK, 2011. [Google Scholar]
- Boldanov, R.; Degiannakis, S.; Filis, G. Time-varying correlation between oil and stock market volatilities: Evidence from oil-importing and oil-exporting countries. Int. Rev. Financ. Anal.
**2016**, 48, 209–220. [Google Scholar] [CrossRef][Green Version] - Lv, X.; Lien, D.; Chen, Q.; Yu, C. Does exchange rate management affect the causality between exchange rates and oil prices? Evidence from oil-exporting countries. Energy Econ.
**2018**, 76, 325–343. [Google Scholar] [CrossRef] - Hajamini, M.; Falahi, M.A. Economic growth and government size in developed European countries: A panel threshold approach. Econ. Anal. Policy
**2018**, 58, 1–13. [Google Scholar] [CrossRef] - Qadri, F.S.; Waheed, A. Human capital and economic growth: A macroeconomic model for Pakistan. Econ. Model.
**2014**, 42, 66–76. [Google Scholar] [CrossRef][Green Version] - Romer, P.M. Increasing Returns and Long-Run Growth. J. Political Econ.
**1986**, 94, 1002–1037. [Google Scholar] [CrossRef][Green Version] - Weil, D.N.; Mankiw, N.G.; Romer, D. A Contribution to the Empirics of Economic Growth. Q. J. Econ.
**1992**, 107, 407–437. [Google Scholar] [CrossRef] - Bloom, D.E.; Canning, D.; Sevilla, J. The Effect of Health on Economic Growth: A Production Function Approach. World Dev.
**2004**, 32, 1–13. [Google Scholar] [CrossRef] - Frankel, M. The Production Function in Allocation and Growth: A Synthesis. Am. Econ. Rev.
**1962**, 52, 996–1022. [Google Scholar] - Sharma, S.S. The relationship between energy and economic growth: Empirical evidence from 66 countries. Appl. Energy
**2010**, 87, 3565–3574. [Google Scholar] [CrossRef] - Pesaran, M.H.; Shin, Y.; Smith, R.J. Bounds testing approaches to the analysis of level relationships. J. Appl. Econom.
**2001**, 16, 289–326. [Google Scholar] [CrossRef] - Pesaran, M.H.; Shin, Y. An Autoregressive Distributed-Lag Modelling Approach to Cointegration Analysis. In Econometrics and Economic Theory in the 20th Century: The Ragnar Frisch Centennial Symposium; Strøm, S., Ed.; Cambridge University Press: Cambridge, UK, 1999; pp. 371–413. [Google Scholar] [CrossRef]
- McNown, R.; Sam, C.Y.; Goh, S.K. Bootstrapping the autoregressive distributed lag test for cointegration. Appl. Econ.
**2018**, 50, 1509–1521. [Google Scholar] [CrossRef] - Narayan, P.K. The saving and investment nexus for China: Evidence from cointegration tests. Appl. Econ.
**2005**, 37, 1979–1990. [Google Scholar] [CrossRef] - Sam, C.Y.; McNown, R.; Goh, S.K. An augmented autoregressive distributed lag bounds test for cointegration. Econ. Model.
**2019**, 80, 130–141. [Google Scholar] [CrossRef] - Goh, S.K.; Yong, J.Y.; Lau, C.C.; Tang, T.C. Bootstrap ARDL on energy-growth relationship for 22 OECD countries. Appl. Econ. Lett.
**2017**, 24, 1464–1467. [Google Scholar] [CrossRef] - Zivot, E.; Andrews, D.W.K. Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis. J. Bus. Econ. Stat.
**1992**, 10, 251–270. [Google Scholar] [CrossRef] - Perron, P. The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis. Econometrica
**1989**, 57, 1361–1401. [Google Scholar] [CrossRef] - Sturm, M.; Gurtner, F.; Alegre, J.G. Fiscal Policy Challenges in Oil-Exporting Countries—A Review Of Key Issues; European Central Bank: Frankfurt, France, 2009. [Google Scholar]
- Cherif, R.; Hasanov, F. Soaring of the Gulf Falcons: Diversification in the GCC Oil Exporters in Seven Propositions; Working Paper No. 14/177; IMF: Washington, DC, USA, 2014. [Google Scholar]

Year | Brunei | Cambodia | Indonesia | Laos | Malaysia | Myanmar | Philippines | Singapore | Thailand | Vietnam |
---|---|---|---|---|---|---|---|---|---|---|

2002 | 187.9 | 0 | 277.9 | 0 | 232.6 | −6.9 | −250.1 | −816.4 | −682.2 | 322.1 |

2003 | 196.0 | 0 | 192.1 | 0 | 235.6 | 0.6 | −238.8 | −938.2 | −709.1 | 337.0 |

2004 | 186.5 | 0 | 103.3 | 0 | 217.7 | 0.0 | −189.6 | −1114.3 | −815.7 | 388.6 |

2005 | 196.0 | 0 | 81.5 | 0 | 212.2 | 6.3 | −199.7 | −1176.8 | −762.1 | 369.7 |

2006 | 196.9 | 0 | −7.5 | 0 | 188.0 | 2.2 | −202.0 | −1150.1 | −763.9 | 340.2 |

2007 | 171.2 | 0 | 56.5 | 0 | 144.7 | 2.9 | −189.0 | −1162.5 | −752.2 | 328.9 |

2008 | 163.9 | 0 | 46.1 | 0 | 126.1 | 0.8 | −172.5 | −1158.0 | −765.7 | 308.0 |

2009 | 141.9 | 0 | 46.5 | 0 | 158.3 | 0.9 | −117.0 | −871.8 | −762.3 | 296.6 |

2010 | 147.6 | 0 | 76.1 | 0 | 164.0 | 0.0 | −165.0 | −944.0 | −786.2 | 216.6 |

2011 | 135.4 | 0 | 96.2 | 0 | 49.9 | −0.1 | −171.5 | −973.9 | −761.7 | 182.4 |

2012 | 139.0 | 0 | 61.5 | 0 | 27.1 | 2.7 | −162.5 | −966.2 | −819.2 | 183.0 |

2013 | 117.0 | 0 | 6.8 | 0 | 47.1 | 2.7 | −140.1 | −939.8 | −843.2 | 165.7 |

2014 | 107.6 | 0 | −40.8 | 0 | 38.6 | 2.8 | −160.0 | −942.0 | −798.2 | 180.6 |

2015 | 115.5 | 0 | −69.8 | 0 | 150.4 | 1.8 | −197.9 | −977.9 | −818.3 | 183.6 |

2016 | 109.7 | 0 | −61.8 | 0 | 192.5 | 2.7 | −222.1 | −1029.9 | −842.2 | 148.9 |

Cointegration Test | Null Hypothesis | Alternative Hypothesis |
---|---|---|

F-bound test | ${\lambda}_{1}={\lambda}_{2}={\lambda}_{3}={\lambda}_{4}={\lambda}_{5}=0$ | $any{\lambda}_{1},{\lambda}_{2},{\lambda}_{3},{\lambda}_{4},{\lambda}_{5}\ne 0$ |

t-test on lagged dependent variable | ${\lambda}_{1}=0$ | ${\lambda}_{1}\ne 0$ |

F-test on lagged independent variable | ${\lambda}_{2}={\lambda}_{3}={\lambda}_{4}={\lambda}_{5}=0$ | $any{\lambda}_{2},{\lambda}_{3},{\lambda}_{4},{\lambda}_{5}\ne 0$ |

Outcome | F-Bound Test | t-Test on Lagged Dependent Variable | F-Test on Lagged Independent Variable | Conclusion |
---|---|---|---|---|

1 | ✓ | ✗ | ✓ | Not cointegrated (Degenerate case #1) |

2 | ✓ | ✓ | ✗ | Not cointegrated (Degenerate case #2) |

3 | ✗ | Not necessary | Not necessary | Not cointegrated |

4 | ✓ | ✓ | ✓ | Cointegrated |

Variables | Descriptions | Measurement | Sources | Expected Sign |
---|---|---|---|---|

GDPPC | Real Gross Domestic Product Per Capita | Constant US Dollar 2010 | UNSD, WDI | |

BRENT | Brent crude oil price (USD/Barrel) | Constant US Dollar 2010 | WBC | + |

LE | Life Expectancy | Years | WDI | + |

POP | Total Population | Total number | WDI | − |

GFCF | Gross Fixed Capital Formation | Constant US Dollar 2010 | UNSD | + |

Variable | Mean | Min | Max | Std. Dev |
---|---|---|---|---|

Brunei | ||||

GDPPC | 39,588.59 | 31,430.74 | 72,437.55 | 8,450.31 |

BRENT | 47.34 | 15.48 | 101.58 | 26.19 |

LE | 74.38 | 69.94 | 77.37 | 2.31 |

POP | 313,146.36 | 187,656.00 | 428,697.00 | 74,438.09 |

GFCF | 2.80 × 10^{9} | 9.23 × 10^{8} | 6.39 × 10^{9} | 1.40 × 10^{9} |

Malaysia | ||||

GDPPC | 6,673.06 | 3,194.60 | 11,528.34 | 2,481.98 |

BRENT | 47.34 | 15.48 | 101.58 | 26.19 |

LE | 72.07 | 67.73 | 75.45 | 2.23 |

POP | 22,179,506.21 | 13,460,201.00 | 31,624,264.00 | 5,634,228.05 |

GFCF | 4.09 × 10^{10} | 9.12 × 10^{9} | 9.27 × 10^{10} | 2.39 × 10^{10} |

Vietnam | ||||

GDPPC | 817.49 | 309.52 | 1,834.65 | 462.11 |

BRENT | 47.34 | 15.48 | 101.58 | 26.19 |

LE | 72.35 | 66.88 | 76.45 | 2.79 |

POP | 76,286,359.77 | 53,169,673.00 | 95,540,800.00 | 12,601,992.94 |

GFCF | 1.67 × 10^{10} | 1.39 × 10^{9} | 5.42 × 10^{10} | 1.59 × 10^{10} |

Variable | Mean | Min | Max | Std. Dev |
---|---|---|---|---|

Brunei | ||||

LnGDPPC | 10.57 | 10.36 | 11.19 | 0.18 |

LnBRENT | 3.71 | 2.74 | 4.62 | 0.57 |

LnLE | 4.31 | 4.25 | 4.35 | 0.03 |

LnPOP | 12.62 | 12.14 | 12.97 | 0.25 |

LnGFCF | 21.63 | 20.64 | 22.58 | 0.51 |

Malaysia | ||||

LnGDPPC | 8.73 | 8.07 | 9.35 | 0.39 |

LnBRENT | 3.71 | 2.74 | 4.62 | 0.57 |

LnLE | 4.28 | 4.22 | 4.32 | 0.03 |

LnPOP | 16.88 | 16.42 | 17.27 | 0.26 |

LnGFCF | 24.24 | 22.93 | 25.25 | 0.67 |

Vietnam | ||||

LnGDPPC | 6.55 | 5.74 | 7.51 | 0.57 |

LnBRENT | 3.71 | 2.74 | 4.62 | 0.57 |

LnLE | 4.28 | 4.20 | 4.34 | 0.04 |

LnPOP | 18.14 | 17.79 | 18.38 | 0.17 |

LnGFCF | 22.92 | 21.05 | 24.72 | 1.26 |

Variable | LnGDPPC | LnBRENT | LnLE | LnPOP | LnGFCF |
---|---|---|---|---|---|

Brunei | |||||

LnGDPPC | 1.000 | ||||

LnBRENT | −0.062 | 1.000 | |||

LnLE | −0.833 *** | 0.370 ** | 1.000 | ||

LnPOP | −0.833 *** | 0.374 ** | 0.998 *** | 1.000 | |

LnGFCF | −0.793 *** | 0.172 | 0.831 *** | 0.846 *** | 1.000 |

Malaysia | |||||

LnGDPPC | 1.000 | ||||

LnBRENT | 0.429 *** | 1.000 | |||

LnLE | 0.988 *** | 0.365 ** | 1.000 | ||

LnPOP | 0.992 *** | 0.420 *** | 0.997 *** | 1.000 | |

LnGFCF | 0.969 *** | 0.329 ** | 0.945 *** | 0.941 *** | 1.000 |

Vietnam | |||||

LnGDPPC | 1.000 | ||||

LnBRENT | 0.540 *** | 1.000 | |||

LnLE | 0.975 *** | 0.384 ** | 1.000 | ||

LnPOP | 0.961 *** | 0.329 ** | 0.998 *** | 1.000 | |

LnGFCF | 0.984 *** | 0.459 *** | 0.986 *** | 0.978 *** | 1.000 |

**Table 8.**Zivot and Andrews [49]’s breakpoint unit root test results.

Variable | Level Variables | First Differenced Variables | ||||
---|---|---|---|---|---|---|

Model A | Model B | Model C | Model A | Model B | Model C | |

Brunei | ||||||

LnGDPCC | −5.75(0) ^{a} [1986] | −4.52(0) ^{b} [2011] | −4.87(0) ^{c} [1986] | −6.07(0) ^{a} [1987] | −6.59(0) ^{a} [1992] | −6.49(0) ^{a} [1991] |

LnBRENT | −3.12(0) [1986] | −2.95(0) [1987] | −3.21(0) [1986] | −6.61(0) ^{a} [2009] | −6.69(0) ^{a} [2006] | −6.99(0) ^{a} [1999] |

LnLE | 0.41(2) [2005] | −3.73(2) [2002] | −3.71(2) [2001] | −6.89(2) ^{a} [2005] | −4.39(2) ^{a} [2002] | −5.51(2) ^{b} [2005] |

LnPOP | −3.15(2) [2003] | −5.20(2) ^{a} [1998] | −5.19(2) ^{b} [1998] | −2.52(2) [2002] | −1.66(2) [2008] | −2.64(2) [2002] |

LnGFCF | −4.34(0) [1999] | −2.63(0) [1992] | −4.51(0) [1999] | −7.34(0) ^{a} [1997] | −6.35(0) ^{a} [2000] | −7.22(0) ^{a} [1997] |

Malaysia | ||||||

LnGDPCC | −3.46(0) [1991] | −2.54(0) [1996] | −3.40(0) [1991] | −6.35(0) ^{a} [1998] | −5.16(0) ^{a} [1992] | −6.31(0) ^{a} [1998] |

LnBRENT | −3.12(0) [1986] | −2.95(0) [1987] | −3.21(0) [1986] | −6.61(0) ^{a} [2009] | −6.69(0) ^{a} [2006] | −6.99(0) ^{a} [1999] |

LnLE | −9.42(2) [2001] | −4.85(2) ^{b} [1993] | −4.66(2) [1990] | −3.36(2) [2008] | −6.00(2) ^{a} [2005] | −6.83(2) ^{a} [2001] |

LnPOP | −0.78(2) [1991] | −5.17(2) ^{a} [1994] | −4.70(2) [1992] | −5.84(2) ^{a} [1999] | −4.84(2) ^{b} [2011] | −5.11(2) ^{b} [2009] |

LnGFCF | −3.64(1) [2001] | −3.25(1) [1995] | −4.25(1) [1998] | −5.08(0) ^{b} [1998] | −4.28(0) ^{c} [1999] | −5.01(0) ^{c} [1998] |

Vietnam | ||||||

LnGDPCC | −3.40(2) [2000] | −4.91(2) ^{b} [1987] | −3.69(2) [1989] | −8.34(0) ^{a} [1992] | −5.95(0) ^{a} [2004] | −8.15(0) ^{a} [1992] |

LnBRENT | −3.12(0) [1986] | −2.95(0) [1987] | −3.21(0) [1986] | −6.61(0) ^{a} [2009] | −6.69(0) ^{a} [2006] | −6.99(0) ^{a} [1999] |

LnLE | −7.39(2) ^{a} [2002] | −7.11(2) ^{a} [1997] | −6.83(2) ^{a} [1996] | −2.78(2) [2011] | −4.12(2) ^{c} [2008] | −3.67(2) ^{a} [2008] |

LnPOP | −3.06(2) [1987] | −6.55(2) ^{a} [1992] | −5.20(2) ^{b} [1991] | −3.65(2) ^{b} [1993] | −3.96(2) [2002] | −3.57(2) [1998] |

LnGFCF | −5.34(0) ^{b} [1992] | −2.89(0) [2004] | −5.09(0) ^{b} [1992] | −9.73(0) ^{a} [1990] | −7.92(0) ^{a} [1994] | −9.55(0) ^{a} [1990] |

^{a},

^{b}, and

^{c}corresponds to 1%, 5%, and 10% significance level respectively. The 1%, 5% and 10% critical values: −5.34, −4.80 and −4.58 for Model A; −4.93, −4.42 and −4.11 for Model B; and −5.57, −5.08 and −4.82 for Model C.

**Table 9.**Linear autoregressive distributed lag model (ARDL) estimation results and diagnostic checks.

Variable | Country | ||
---|---|---|---|

Brunei | Malaysia | Vietnam | |

Panel A: Coefficient estimates of linear ARDL | |||

Selected model | (1, 1, 2, 2, 2) | (1, 1, 0, 1, 2) | (3, 0, 0, 0, 0) |

Constant | −56.32(15.80) ^{a} | 2.40(5.86) | −0.19(2.74) |

LnGDPPC_{t−1} | −0.98(0.08) ^{a} | −0.52(0.13) ^{a} | −0.04(0.03) |

LnBRENT_{t−1} | −0.03(0.02) | −0.01(0.01) | 0.004(0.01) |

LnLE_{t−1} | 26.40(5.88) ^{a} | −3.69(2.74) | −0.20(2.41) |

LnPOP_{t−1} | −3.62(0.79) ^{a} | 0.90(0.38) ^{b} | 0.05(0.43) |

LnGFCF_{t−1} | −0.05(0.03) | 0.12(0.03) ^{a} | 0.02(0.02) |

∆LnGDPPC_{t−1} | 0.56(0.17) ^{a} | ||

∆LnGDPPC_{t−2} | −0.26(0.11) ^{b} | ||

∆LnBRENT_{t} | −0.01(0.02) | 0.02(0.01) | 0.004(0.01) |

∆LnLE_{t} | 153.90(46.23) ^{a} | −3.69(2.74) | −0.20(2.41) |

∆LnLE_{t−1} | −206.89(48.57) ^{a} | ||

∆LnPOP_{t} | −44.53(10.75) ^{a} | −3.20(1.74) ^{c} | 0.05(0.43) |

∆LnPOP_{t−1} | 44.71(10.03) ^{a} | ||

∆LnGFCF_{t} | 0.03(0.02) | 0.17(0.03) ^{a} | 0.02(0.02) |

∆LnGFCF_{t−1} | 0.04(0.02) ^{c} | −0.06(0.02) ^{a} | |

DUMMY | −0.20(0.02) ^{a} | −0.02(0.02) | 0.01(0.01) |

Panel B: Diagnostic results | |||

ECT_{t−1} | −0.98(0.07) ^{a} | −0.52(0.09) ^{a} | −0.04(0.02) ^{b} |

Adj. R^{2} | 0.981 | 0.999 | 0.999 |

LM(2) | 3.77 | 4.00 | 0.82 |

RESET test | 0.52 | 0.39 | 14.28 ^{a} |

CUSUM (CUSUM^{2}) | S(S) | S(S) | S(S) |

F-statistic (overall) | 38.65 | 5.58 | 0.99 |

t-statistic (lagged DV) | −11.65 | −4.08 | - |

F-statistic (lagged IDV) | 11.18 | 6.00 | - |

^{a},

^{b}and

^{c}indicates 1%, 5%, and 10% significance level, respectively. The number in parenthesis shows the standard error for the respective coefficient. LM is the Breusch–Godfrey serial correlation test with the number of lags as stated in parenthesis. RESET test is Ramsey’s reset test for misspecification of model. For CUSUM and CUSUM

^{2}, S stands for stable, and U stands for unstable.

Cointegration Test | 10% | 5% | 1% | |||
---|---|---|---|---|---|---|

I(0) | I(1) | I(0) | I(1) | I(0) | I(1) | |

F-statistic (overall) | 2.696 | 3.898 | 3.276 | 4.630 | 4.590 | 6.368 |

t-statistic (lagged DV) | −2.570 | −3.660 | −2.860 | −3.990 | −3.430 | −4.600 |

F-statistic (lagged IDV) | 2.14 | 3.82 | 2.70 | 4.67 | 4.03 | 6.63 |

Variable | Country | ||
---|---|---|---|

Brunei | Malaysia | Vietnam | |

LnBRENT | −0.03(0.02) | −0.02(0.02) | 0.09(0.15) |

LnLE | 26.90(6.14) ^{a} | −7.15(5.13) | −4.57(55.62) |

LnPOP | −3.69(0.80) ^{a} | 1.75(0.63) ^{b} | 1.16(10.01) |

LnGFCF | −0.05(0.03) | 0.23(0.03) ^{a} | 0.41(0.50) |

^{a},

^{b}and

^{c}indicates 1%, 5%, and 10% significance level, respectively. The number in parenthesis shows the standard error for the respective coefficient.

Variable | Country | ||
---|---|---|---|

Brunei | Malaysia | Vietnam | |

Panel A: Coefficient estimates of nonlinear ARDL | |||

Selected Model | (4, 0, 0, 0, 0, 0) | (1, 0, 0, 0, 0, 0) | (3, 0, 0, 0, 0, 0) |

Constant | −6.80 (7.79) | 3.30(6.58) | 1.26(3.39) |

LnGDPPC_{t−1} | −0.68(0.10) ^{a} | −0.72(0.08) ^{a} | −0.07(0.04) ^{c} |

POS_{t−1} | −0.01(0.01) | 0.001(0.02) | 0.01(0.01) |

NEG_{t−1} | 0.10(0.03) ^{a} | 0.01(0.02) | −0.003(0.01) |

LnLE_{t−1} | −3.97(2.96) | −5.52(2.95) ^{c} | −1.03(2.35) |

LnPOP_{t−1} | −0.24(0.45) | 1.34(0.42) ^{a} | 0.16(0.41) |

LnGFCF_{t−1} | 0.003(0.02) | 0.16(0.02) ^{a} | 0.03(0.02) ^{b} |

∆LnGDPPC_{t−1} | 0.10(0.12) | 0.64(0.18) ^{a} | |

∆LnGDPPC_{t−2} | −0.15(0.08) ^{c} | −0.26(0.11) ^{b} | |

∆LnGDPPC_{t−3} | −0.13(0.08) | ||

∆POS_{t} | −0.01(0.01) | 0.001(0.02) | 0.01(0.01) |

∆NEG_{t} | 0.10(0.03) ^{a} | 0.01(0.02) | −0.003(0.01) |

∆LnLE_{t} | −3.97(2.96) | −5.52(2.95) ^{c} | −1.03(2.35) |

∆LnPOP_{t} | −0.24(0.45) | 1.34(0.42) ^{a} | 0.16(0.41) |

∆LnGFCF_{t} | 0.003(0.02) | 0.16(0.02) ^{a} | 0.03(0.02) ^{b} |

DUMMY | −0.08(0.03) ^{a} | ||

Panel B: Diagnostic results | |||

ECT_{t−1} | −0.68(0.07) ^{a} | −0.72(0.06) ^{a} | −0.07(0.01) ^{a} |

SUM POS SR | −0.01(0.01) | 0.001(0.02) | 0.01(0.01) |

SUM NEG SR | 0.10(0.03) ^{a} | 0.01(0.02) | −0.003(0.01) |

W_{LR} | −0.11(0.03) ^{a} | −0.01(0.03) | 0.01(0.02) |

W_{SR} | −0.11(0.03) ^{a} | −0.01(0.03) | 0.01(0.02) |

Adj. R^{2} | 0.967 | 0.998 | 0.999 |

LM(1) | 4.26 | 2.53 | 1.89 |

RESET test | 0.28 | 2.39 | 14.78 ^{a} |

CUSUM (CUSUM^{2}) | S(S) | S(S) | U(S) |

F-statistic (overall) | 11.40 | 17.83 | 3.27 |

t-statistic (lagged DV) | −6.95 | −11.14 | - |

F-statistic (lagged IDV) | 8.18 | 21.08 | - |

^{a},

^{b}and

^{c}indicates 1%, 5%, and 10% significance level respectively. The number in parenthesis shows the standard error for the respective coefficient. W

_{LR}is the Wald test of long-run symmetry, and W

_{SR}is the Wald test of short-run symmetry. LM is the Breusch–Godfrey serial correlation test with the number of lags as stated in parenthesis. RESET test is Ramsey’s reset test for misspecification of model. For CUSUM and CUSUM

^{2}, S stands for stable and U stands for unstable.

Variable | Country | ||
---|---|---|---|

Brunei | Malaysia | Vietnam | |

POS | −0.02(0.02) | 0.001(0.02) | 0.14(0.15) |

NEG | 0.14(0.04) ^{a} | 0.01(0.03) | −0.05(0.17) |

LnLE | 5.83(4.42) | −7.68(3.92) ^{c} | −14.12(36.22) |

LnPOP | −0.35(0.66) | 1.87(0.50) ^{a} | 2.16(6.38) |

LnGFCF | 0.01(0.02) | 0.22(0.02) ^{a} | 0.47(0.32) |

^{a},

^{b}and

^{c}indicates 1%, 5%, and 10% significance level respectively. The number in parenthesis shows the standard error for the respective coefficient.

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

## Share and Cite

**MDPI and ACS Style**

Kriskkumar, K.; Naseem, N.A.M. Analysis of Oil Price Effect on Economic Growth of ASEAN Net Oil Exporters. *Energies* **2019**, *12*, 3343.
https://doi.org/10.3390/en12173343

**AMA Style**

Kriskkumar K, Naseem NAM. Analysis of Oil Price Effect on Economic Growth of ASEAN Net Oil Exporters. *Energies*. 2019; 12(17):3343.
https://doi.org/10.3390/en12173343

**Chicago/Turabian Style**

Kriskkumar, Karunanithi, and Niaz Ahmad Mohd Naseem. 2019. "Analysis of Oil Price Effect on Economic Growth of ASEAN Net Oil Exporters" *Energies* 12, no. 17: 3343.
https://doi.org/10.3390/en12173343