IDEAS home Printed from https://ideas.repec.org/a/eco/journ2/2016-03-2.html
   My bibliography  Save this article

Uncertainty of Oil Proved Reserves and Economic Growth in Iran

Author

Listed:
  • Elaheh Asadi Mehmandosti

    (Department of Economics, Alzahra University, Tehran, Iran)

  • Fatemeh Bazazan

    (Department of Economics, Alzahra University, Tehran, Iran,)

  • Mir Hossein Mousavi

    (Department of Economics, Alzahra University, Tehran, Iran)

Abstract

The relationship between the oil and the level of economic activity is a fundamental empirical issue in macroeconomics. Also, a part of major debates between the pessimists and the optimists approaches about economic growth is how uncertainty of proved reserves of non-renewable energy resources as a one of main inputs, effects on the economic growth; in other words, on the base of some optimistic new economic growth models, the uncertainty through positive shocks positively effects on the economic growth. So, to find some evidences about it, in this research we try to find experimentally direct effects of uncertainty of oil proved reserves on macroeconomics of Iran by using annually data from 1980 to 2013 by using Multivariate generalized auto-regressive conditional heteroskedasticity in-mean vector auto-regression (VAR) model. We find that uncertainty in oil proved reserves has not had statistically significant effect on aggregate output and the responses to positive and negative shocks are symmetric.

Suggested Citation

  • Elaheh Asadi Mehmandosti & Fatemeh Bazazan & Mir Hossein Mousavi, 2016. "Uncertainty of Oil Proved Reserves and Economic Growth in Iran," International Journal of Energy Economics and Policy, Econjournals, vol. 6(3), pages 374-380.
    • Handle: RePEc:eco:journ2:2016-03-2
    as

    Download full text from publisher

    File URL: http://www.econjournals.com/index.php/ijeep/article/download/1749/1643
    Download Restriction: no
    File URL: http://www.econjournals.com/index.php/ijeep/article/view/1749/1643
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Engle, Robert F. & Kroner, Kenneth F., 1995. "Multivariate Simultaneous Generalized ARCH," Econometric Theory, Cambridge University Press, vol. 11(1), pages 122-150, February.
    2. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-1072, June.
    3. Kevin B. Grier & Ólan T. Henry & Nilss Olekalns & Kalvinder Shields, 2004. "The asymmetric effects of uncertainty on inflation and output growth," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(5), pages 551-565.
    4. Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-836, July.
    5. Hartwick, John M, 1977. "Intergenerational Equity and the Investing of Rents from Exhaustible Resources," American Economic Review, American Economic Association, vol. 67(5), pages 972-974, December.
    6. John Elder & Apostolos Serletis, 2010. "Oil Price Uncertainty," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 42(6), pages 1137-1159, September.
    7. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    8. Anderson, Curt L., 1987. "The production process: Inputs and wastes," Journal of Environmental Economics and Management, Elsevier, vol. 14(1), pages 1-12, March.
    9. Elder, John, 2003. "An impulse-response function for a vector autoregression with multivariate GARCH-in-mean," Economics Letters, Elsevier, vol. 79(1), pages 21-26, April.
    10. Elder, John, 2004. "Another Perspective on the Effects of Inflation Uncertainty," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 36(5), pages 911-928, October.
    11. Harold Hotelling, 1931. "The Economics of Exhaustible Resources," Journal of Political Economy, University of Chicago Press, vol. 39, pages 137-137.
    12. Gerlagh, Reyer & Keyzer, Michiel A., 2004. "Path-dependence in a Ramsey model with resource amenities and limited regeneration," Journal of Economic Dynamics and Control, Elsevier, vol. 28(6), pages 1159-1184, March.
    13. Engle, Robert F & Lilien, David M & Robins, Russell P, 1987. "Estimating Time Varying Risk Premia in the Term Structure: The Arch-M Model," Econometrica, Econometric Society, vol. 55(2), pages 391-407, March.
    14. Dasgupta, Partha & Stiglitz, Joseph, 1981. "Resource Depletion under Technological Uncertainty," Econometrica, Econometric Society, vol. 49(1), pages 85-104, January.
    15. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Rahman, Sajjadur, 2016. "Another perspective on gasoline price responses to crude oil price changes," Energy Economics, Elsevier, vol. 55(C), pages 10-18.
    2. Efimova, Olga & Serletis, Apostolos, 2014. "Energy markets volatility modelling using GARCH," Energy Economics, Elsevier, vol. 43(C), pages 264-273.
    3. Zoundi Zakaria, 2017. "Crude Oil Price Volatility and Domestic Price Responses in Developing Countries, Accounting for Asymmetry and Uncertainty," Economics Bulletin, AccessEcon, vol. 37(4), pages 2466-2482.
    4. Rahman, Sajjadur & Serletis, Apostolos, 2012. "Oil price uncertainty and the Canadian economy: Evidence from a VARMA, GARCH-in-Mean, asymmetric BEKK model," Energy Economics, Elsevier, vol. 34(2), pages 603-610.
    5. Amélie Charles & Chew Lian Chua & Olivier Darné & Sandy Suardi, 2020. "On the pernicious effects of oil price uncertainty on US real economic activities," Empirical Economics, Springer, vol. 59(6), pages 2689-2715, December.
    6. Mehmet Balcilar & Zeynel Abidin Ozdemir, 2020. "A re-examination of growth and growth uncertainty relationship in a stochastic volatility in the mean model with time-varying parameters," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 47(3), pages 611-641, August.
    7. Dimitrios Kartsonakis-Mademlis & Nikolaos Dritsakis, 2022. "Asymmetric volatility transmission in Japanese stock market in the presence of structural breaks," The Japanese Economic Review, Springer, vol. 73(4), pages 647-677, October.
    8. Jinan Liu & Apostolos Serletis, 2019. "Volatility in the Cryptocurrency Market," Open Economies Review, Springer, vol. 30(4), pages 779-811, September.
    9. Sajjadur Rahman, 2018. "The Lucas hypothesis on monetary shocks: evidence from a GARCH-in-mean model," Empirical Economics, Springer, vol. 54(4), pages 1411-1450, June.
    10. Don Bredin & John Elder & Stilianos Fountas, 2009. "Macroeconomic Uncertainty and Performance in Asian Countries," Review of Development Economics, Wiley Blackwell, vol. 13(2), pages 215-229, May.
    11. Haigh, Michael S. & Bryant, Henry L., 2000. "Price And Price Risk Dynamics In Barge And Ocean Freight Markets And The Effects On Commodity Trading," 2000 Conference, April 17-18 2000, Chicago, Illinois 18934, NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    12. Chia-Lin Chang & Michael McAleer & Guangdong Zuo, 2017. "Volatility Spillovers and Causality of Carbon Emissions, Oil and Coal Spot and Futures for the EU and USA," Sustainability, MDPI, vol. 9(10), pages 1-22, October.
    13. Kris Boudt & Hong Anh Luu, 2022. "Estimation and decomposition of food price inflation risk," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(2), pages 295-319, June.
    14. Committee, Nobel Prize, 2003. "Time-series Econometrics: Cointegration and Autoregressive Conditional Heteroskedasticity," Nobel Prize in Economics documents 2003-1, Nobel Prize Committee.
    15. Hartmann, Matthias & Roestel, Jan, 2013. "Inflation, output and uncertainty in the era of inflation targeting – A multi-economy view on causal linkages," Journal of International Money and Finance, Elsevier, vol. 37(C), pages 98-112.
    16. Chang, Chia-Lin & McAleer, Michael, 2019. "The fiction of full BEKK: Pricing fossil fuels and carbon emissions," Finance Research Letters, Elsevier, vol. 28(C), pages 11-19.
    17. repec:fgv:epgrbe:v:66:n:3:a:3 is not listed on IDEAS
    18. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654, January.
    19. Matos, Paulo & Beviláqua, Giovanni & Filho, Jaime, 2012. "Previsão do câmbio real-dólar sob um arcabouço de apreçamento de ativos," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 66(3), October.
    20. Menelaos Karanasos & Ning Zeng, 2013. "Conditional heteroskedasticity in macroeconomics data: UK inflation, output growth and their uncertainties," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 12, pages 266-288, Edward Elgar Publishing.
    21. Kushal Banik Chowdhury & Kaustav Kanti Sarkar & Srikanta Kundu, 2021. "Nonlinear relationships between inflation, output growth and uncertainty in India: New evidence from a bivariate threshold model," Bulletin of Economic Research, Wiley Blackwell, vol. 73(3), pages 469-493, July.

    More about this item

    Keywords

    Uncertainty; Oil Proved Reserves; Time Allocation of Resources; Vector Auto-regression Multivariate Generalized Auto-regressive Conditional Heteroskedasticity-in-Mean Vector Auto-regression;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E10 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - General
    • Q32 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - Exhaustible Resources and Economic Development

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eco:journ2:2016-03-2. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Ilhan Ozturk (email available below). General contact details of provider: http://www.econjournals.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.