پژوهش ها و چشم اندازهای اقتصادی

پژوهش ها و چشم اندازهای اقتصادی

تأثیر نامتقارن تکانه‌های مقیاس‌بندی‌شده قیمت نفت بر ضریب ظرفیت بار (LCF) زیست‌محیطی در ایران به کمک رویکرد NARDL چندآستانه‌ای نامتقارن (MATNARDL)

نویسنده
دانش‌آموخته دکتری اقتصاد بخش عمومی، گروه اقتصاد، دانشکده‌ اقتصاد و علوم اداری، دانشگاه لرستان، خرم‌آباد، ایران
چکیده
طی سال‌های گذشته، اثرگذاری نامتقارن تکانه‌های قیمت نفت بر شاخص‌های زیست‌محیطی در کشورهای واردکننده و صادرکننده نفت، مورد توجه خاصی در بین پژوهشگران قرار گرفته است. در این راستا، هدف اصلی از پژوهش حاضر، بررسی تأثیر نامتقارن و غیرخطی تکانه‌های مقیاس‌بندی شده قیمت نفت بر ضریب ظرفیت بار به‌عنوان شاخص پایداری زیست‌محیطی در ایران طی دوره زمانی 2022-1961 می‌باشد. براین‎اساس، برآورد مدل با دسته‌بندی تکانه‌های مثبت و منفی قیمت نفت در سه مقیاس کوچک (کوانتایل کمتر از آستانه τ30)، متوسط (کوانتایل بین آستانه‌های τ30 و τ70) و بزرگ (کوانتایل بیشتر از آستانه τ70) در قالب رویکرد خودرگرسیون با وقفه‌های توزیعی غیرخطی چند آستانه‌ای نامتقارن (MTANARDL) انجام شده است. نتایج حاکی از آن است که در بلندمدت، تکانه‌های مثبت (منفی) قیمت نفت در مقیاس کوچک، اثر مثبت (منفی) و معناداری بر ضریب ظرفیت بار داشته است؛ درحالی‌که این تکانه‌ها در بلندمدت در دو مقیاس متوسط و بزرگ، اثر منفی بر ضریب ظرفیت بار داشته‌اند. براین‎اساس، می‌توان گفت که اثر قیمت نفت بر ضریب ظرفیت بار در ایران، نامتقارن است و در بین تکانه‌های مثبت، تنها با افزایش در مقیاس کوچک قیمت نفت، می‌توانیم شاهد افزایش ضریب ظرفیت بار و پایداری محیط‎‌زیست در کشور باشیم. تکانه‌های مثبت قیمت نفت در دو مقیاس متوسط و بزرگ نیز با اولویت بخشیدن به دستاوردها و فعالیت‌های اقتصادی بر مسائل زیست‌محیطی، به افزایش ناپایداری زیست‌محیطی می‌انجامد. براساس سایر نتایج، مصرف انرژی، اثر منفی و معنادار بر ضریب ظرفیت بار داشته و فرضیه زیست‌محیطی منحنی ظرفیت بار (LLC) در ایران، تأیید می‌شود
کلیدواژه‌ها

موضوعات


عنوان مقاله English

The Asymmetric Impact of Scaled Oil Price Impulses on the Environmental Load Capacity Factor (LCF) in Iran A Multiple Asymmetric Thresholds NARDL (MATNARDL) Approach

نویسنده English

abolghasem golkhandan
Ph.D. in Public Sector Economics, Department of Economics, Faculty of Economics and Administrative Sciences, Lorestan University, Khoram Abad, Iran.
چکیده English

During the past years, researchers have been particularly interested in the asymmetric impact of oil price impulses on environmental indicators in oil-importing and oil-exporting countries. In this regard, the main purpose of this research is to investigate the asymmetric and non-linear impact of scaled oil price impulses on load capacity factor as an indicator of environmental sustainability in Iran from 1961-2022. Based on this, the estimation of the model has been performed by categorizing the positive and negative impulses of the oil price in three small scales (quantiles less than the τ30 threshold), medium (quantiles between the τ30 and τ70 thresholds) and large (quantiles greater than the τ70 threshold) in the form of Multiple Asymmetric Thresholds Non-linear Autoregressive Distributed Lag (MATNARDL) approach. The results indicate that in the long term, small-scale positive (negative) oil price impulses had a positive (negative) and significant effect on the load capacity factor; While these impulses have a negative effect on the load capacity factor in the long term in both medium and large scales. Based on this, it can be said that the effect of oil price on the load capacity factor in Iran is asymmetric. Among positive impulses, only with a small-scale increase in oil price, we can see an increase in load capacity factor and environmental sustainability in the country. Also, the positive impulses of the oil price on both medium and large scales lead to the increase of environmental instability by prioritizing economic achievements and activities over environmental issues. Based on other results, energy consumption has a negative and significant effect on the load capacity coefficient, and the environmental hypothesis of the load capacity curve (LLC) in Iran is confirmed.

Aim and Introduction

Ecological footprint accounting is composed of two metrics, the “demand-side” (ecological footprint) and the “supply-side” (biocapacity). While the ecological footprint calculates the demand for natural assets in global hectares, biocapacity symbolizes the supply capacity of nature to meet this demand with the same unit of measurement. Ecological deficit also shows the difference between ecological footprint and biological capacity. Globally, the degree of ecological deficits continued to expand over the last decade due to the increase in EF and reduction in biocapacity, which is caused by the following: increasing consumption of fossil fuel energy, overexploitation of natural resources, unsustainable production methods, and economic activities.

Iran is one of the countries that has a weak environmental performance. According to the Global Footprint Network, Iran's ecological footprint exceeded 333% of its biological capacity in 2022. Iran's ecological deficit, which was - 0.55 global per capita hectares in 1961, has increased by 554% to 2.50 global per capita hectares in 2022, and the destruction and pollution of the environment in Iran have reached unsustainable levels. Therefore, the analysis of the determinants of environmental quality can provide insights into the design of appropriate environmental policies in Iran.

In this regard, the environmental effects of dependence on crude oil have attracted considerable attention. Crude oil is an important and largest source of energy, especially for developing countries such as Iran. It is a fossil-based fuel and a major source of carbon emissions in the world. Hence, many studies have linked oil price shocks to environment quality. In contrast to oil-importing economies, where oil price increases encourage a shift to cheaper and cleaner alternative energy sources, the environmental policy issue in oil-exporting countries is entirely different. Indeed, a fall in oil prices may be associated with a decreased investment in environmentally friendly energy sources. By comparison, an increase in oil prices revealed a reluctance to diversify the economy away from its reliance on non-eco-friendly fossil fuel energy.

Based on the explanations above, the main purpose of this article is to investigate the asymmetric impact of scaled oil price impulses on the environmental Load Capacity Factor (LCF) in Iran using the Non-linear Autoregressive Distributed Lag (MATNARDL) approach. The paper intends to make the following contributions to the literature. Firstly, this article is the first to look into the effect of oil prices on the LCF in Iran by applying asymmetric methodologies. Secondly, it is the first study with a reverse load capacity factor as an environmental sustainability indicator. Thirdly, this paper applied the advanced and newly developed MATNARDL for asymmetric and nonlinear analysis to provide a more robust result that exhibits relevant policy implications. Finally, this innovative study investigated the effects of oil prices on the LCF in Iran between 1961 and 2022 in the framework of the LCC hypothesis.

Methodology

The study compiles annual data for the period 1961-2022 for Iran from three different sources. According to Statista, OP represents average annual OPEC crude oil price (in US dollars per barrel). The data are obtained from the World Bank, GDP per capita, (constant 2015 dollars), Energy Consumption (EC) as kg of oil equivalent per capita, Ecological Footprint (per capita, gha) and LCF (the load capacity factor) are obtained from Global Footprint Network. Because the LCF includes biocapacity in the numerator and EF in the denominator, it allows for simultaneous environmental assessment on the supply and demand sides. A higher LCF indicates a better environment. The current paper's economic functions are illustrated in Equations (1):

LnLCFt=fLnOPt, LnGDPt,LnGDPt2,LnECtt (1)

The main objective of this study is to examine the major, medium and minimal scales of positive and negative changes in oil price on the environmental quality index in Iran. For this purpose, the MATNARDL is used as an estimator to examine the effect of minor to major adverse shocks and minor to major positive surprises in the explanatory variable on the explained variable.

Findings

The bounds cointegration test results confirm a long-term relationship in the asymmetric model. The estimation of the model has been performed by categorizing the positive and negative impulses of the oil price in three small (quantiles less than the τ30 threshold), medium (quantiles between the τ30 and τ70 thresholds), and large (quantiles greater than the τ70 threshold) scales in the form of MATNARDL approach. The results indicate that in the long term, small scale of positive (negative) oil price impulses had a positive (negative) and significant effect on the load capacity factor; while these impulses have a negative effect on the load capacity factor in the long term in both medium and large scales. Based on other results, energy consumption has a negative and significant effect on the load capacity coefficient, and the environmental hypothesis of the load capacity curve (LLC) in Iran is confirmed.

Discussion and Conclusion

Based on the obtained results, it can be said that the effect of oil price on the load capacity factor in Iran is asymmetric. Among positive impulses, only with increase in small scale of oil price, we can see an increase in load capacity factor and environmental sustainability in the country. Moreover, the positive impulses of the oil price on both medium and large scales lead to the increase of environmental instability by prioritizing economic achievements and activities over environmental issues

کلیدواژه‌ها English

oil price
Load Capacity Factor
Asymmetric impact
Iran
Multiple Asymmetric Thresholds NARDL
Achuo, E. D. (2022). The nexus between crude oil price shocks and environmental quality: empirical evidence from sub-Saharan Africa. SN Business & Economics, 2(7). DOI: 10.1007/s43546-022-00264-9
Alizadeh, M. & Golkhandan, A. (2017). Investigating and comparing the asymmetric impact of oil price shocks on food prices in oil-exporting and oil-importing countries, Economy and Regional Development, 14, 121-147. [In Persian]
Ayad, H., Ben-Salha, O. & Ouafi, M. (2023). Do oil prices predict the exchange rate in Algeria? Time, frequency, and time-varying Granger causality analysis. Econ. Change Restrict. 1-22. https://doi.org/10.1007/s10644-023-09545-1
Bhutto, N.A. & Chang, B.H. (2019). The effect of the global financial crisis on the asymmetric relationship between exchange rate and stock prices. High Frequency, 2(3-4), 175-183. doi:10.1002/hf2.10033
Cao, H., Sun, P. & Guo, L. (2020). The asymmetric effect of oil price uncertainty on corporate investment in China: evidence from listed renewable energy companies. Front. Energy Res. 8, 47. https://doi.org/10.3389/fenrg.2020.00047
Cashin, P., Mohaddes, K., Raissi, M. & Raissi, M. (2014). The differential effects of oil demand and supply shocks on the global economy. Energy Economics, 44, 113-134.
Chang, B.H., Derindag O.F., Hacievliyagil, N. & Mehmet Canakci, M. (2022). Exchange rate response to economic policy uncertainty: evidence beyond asymmetry. Humanities and Social Sciences Communications, 9(1), 358. doi: 10.1057/s41599-022-01372-5
Daliri, H. (2020). Relationship between ecological footprint and economic growth in D8 countries: Testing the Kuznets Environmental Hypothesis using PSTR model. The Journal of Economic Modeling Research, 11(39), 81-112. [In Persian]
Djedaiet, A., Ayad, H. & Ben-Salha., O. (2024). Oil prices and the load capacity factor in African oil-producing OPEC members: Modeling the symmetric and asymmetric effects. Resources Policy, 89. https://doi.org/10.1016/j.resourpol.2023.104598
Dogan, A., Pata, U. K. (2022). The role of ICT, R&D spending and renewable energy consumption on environmental quality: testing the LCC hypothesis for G7 countries. Journal of Cleaner Production. 380, 135038
Ebaid, A., Lean, H. H. & Al-mulali, U. (2022). Do Oil Price Shocks Matter for Environmental Degradation? Evidence of the Environmental Kuznets Curve in GCC Countries. Frontiers in Environmental Science, 10. DOI: 10.3389/fenvs.2022.860942
Erdogan, S. (2023). Linking natural resources and environmental sustainability: A panel data approach based on the load capacity curve hypothesis. Sustainable Development, 1-13. https://doi.org/10.1002/sd.2836
Erdogan, S. (2024). On the impact of natural resources on environmental sustainability in African countries: A comparative approach based on the EKC and LCC hypotheses. Resources Policy, 88. https://doi.org/10.1016/j.resourpol.2023.104492
Fang, Z., Wang, T. & Yang, C. (2024). Nexus among natural resources, environmental sustainability, and political risk: Testing the load capacity factor curve hypothesis, Resources Policy, 90. https://doi.org/10.1016/j.resourpol.2024.104791
Granger, C.W. & Yoon, G. (2002). Hidden Co-integration, University of California, Working Paper.
Grossman, G. M., & Krueger, A. B. (1991). Environmental impacts of a North American free trade agreement. NBER.
Hamilton, J. D. (1983). Oil and the macroeconomy since World War II. J. Polit. Econ, 91(2), 228-248. https://doi.org/10.1086/261140
Hassan, F. & Mhlanga, D. (2023). The asymmetric effect of oil price on ecological footprint: evidence from oil-producing African countries, Sustainable Energy Research, 10(1). DOI: 10.1186/s40807-023-00087-8
Ibrahim, R. L. & Ajide, K. B. (2021). The dynamic heterogeneous impacts of nonrenewable energy, trade openness, total natural resource rents, financial development and regulatory quality on environmental quality: Evidence from BRICS economies. Resources Policy. https://doi.org/10.1016/j.resourpol.2021.102251
Joof, F., Samour, A., Ali, M., Tursoy, T., Haseeb, M., Hossain, M. E. & Kamal, M. (2023). Symmetric and asymmetric effects of gold, and oil price on the environment: The role of clean energy in China, Resources Policy, 81. https://doi.org/10.1016/j.resourpol.2023.103443
Kassouri, Y., Bilgili, F. & Kuşkaya, S. (2022). A wavelet-based model of world oil shocks interaction with CO2 emissions in the US. Environ. Sci. Policy, 127, 280-292. doi:10.1016/j.envsci.2021.10.020
Kazerouni, A., Asgharpour, H., Aghamohamadi, A. & Zokaei alamdari, E. (2019). Corruption and the environmental Kuznets Curve in developed and developing countries. The Journal of Economic Modeling Research, 10(37), 7-38. [In Persian]
Li, Y. & Guo, J. (2022). The asymmetric impacts of oil price and shocks on inflation in BRICS: a multiple threshold nonlinear ARDL model, Applied Economics, 54(12), 1377-1395. DOI: 10.1080/00036846.2021.1976386
Molaei, H., Golkhandan, A., & Golkhandan, D. (2014). An analysis of asymmetry effects of oil shocks on economic growth of the oil-exporting countries: A non-liner hidden panel cointegration. Iranian Energy Economics, 3(10), 201-229. [In Persian]
Okwanya, I., Abah, P. O., Amaka, E-O. G., Ozturk, I., Alhassan, A. & Bekun, F. V. (2022). Does carbon emission react to oil price shocks? Implications for sustainable growth in Africa, Resources Policy, 82. https://doi.org/10.1016/j.resourpol.2023.103610
Pal, D. & Mitra, S.K.. (2015). Asymmetric impact of crude price on oil product pricing in the United States: an application of Multiple Threshold Nonlinear Autoregressive Distributed lag model. Economic Modelling, 51: 436-443. doi:10.1016/j. econmod.2015.08.026
Pal, D. & Mitra, S. K. (2016). Asymmetric oil product pricing in India: evidence from a Multiple Threshold Nonlinear ARDL model. Economic Modelling, 59: 314-328. doi:10.1016/j.econmod.2016.08.003
Pata, U. K. (2021). Do renewable energy and health expenditures improve load capacity factor in the USA and Japan? A new approach to environmental issues. The European Journal of Health Economics, 22(9), 1427-1439. https://doi.org/10.1007/s10198-021-01321-0
Pata, U.K. & Ertugrul, H.M. (2023). Do the Kyoto Protocol, geopolitical risks, human capital and natural resources affect the sustainability limit? A new environmental approach based on the LCC hypothesis. Resources Policy, 80. https://doi.org/10.1016/j.resourpol.2023.103352
Pata, U. K. & Isik, C. (2021). Determinants of the load capacity factor in China: A novel dynamic ARDL approach for ecological footprint accounting. Resources Policy, 74(C). https://doi.org/10.1016/j.resourpol.2021.102313
Pata, U. K. & Tanriover, B. (2023). Is the load capacity curve hypothesis Valid for the top ten tourism destinations? Sustainability, 15(2), 960. https://doi.org/10.3390/su15020960
Pesaran, M. H., Shin, Y. & Smith, R.J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(20), 289-326. doi:10.1002/jae.616
Sanjari Konarsandal, N., Elyaspour, B. & Babaki, R. (2022). The asymmetric effects of economic policy uncertainty and oil price on carbon dioxide emissions in Iran. The Economic Research, 22(4), 233-260. [In Persian]
Shin, Y., Yu, B. & Greenwood-Nimmo, M. (2014). Modeling Asymmetric Co-integration and Dynamic Multipliers in a Nonlinear ARDL Framework, In W. Horrace, & R. Sickles (Eds.), The Festschrift in Honor of Peter Schmidt.: Econometric Methods and Applications (pp. 281-314). Springer. https://doi.org/10.1007/978-1-4899-8008-3__9
Sam, C., McNown, R. & Goh, S. (2019). An Augmented Autoregressive Distributed Lag Bounds Test for Co-integration. Economic Modelling, 80, 130-141. doi:10.1016/j.econmod.2018.11.001.
Siche, R., Pereira, L., Agostinho, F., & Ortega, E. (2010). Convergence of ecological footprint and emergy analysis as a sustainability indicator of countries: Peru as a case study. Communications in Nonlinear Science and Numerical Simulation, 15(10), 3182-3192. https://doi.org/10.1016/j.cnsns.2009.10.027
Sun, A., Bao, K., Aslam, M., Gu, X., Khan, Z. & Uktamofv, K. F. (2023). Testing load capacity and environmental Kuznets curve hypothesis for China: Evidence from novel dynamic autoregressive distributed lags model. Gondwana Research. https://doi.org/10.1016/j.gr.2023.07.018
Tambari, I., Failler, P. & Jaffry, S. (2024). Understanding the Interplay: Oil price and renewable energy investment in Africa's net oil importing and net oil exporting countries, Resources Policy, 91. https://doi.org/10.1016/j.resourpol.2024.104875
Tayebi, S. K., Aghili, F. S., & Allahdadian, L. (2018). Trade liberalization, oil shocks and environmental quality: The case study of oil exporting and importing countries. Environmental Sciences, 16(1), 159-172. [In Persian]
Uche, E., Chang, B.H. & Effiom, L. (2022). Household consumption and exchange rate extreme dynamics: Multiple asymmetric threshold non‐linear autoregressive distributed lag model perspective. International Journal of Finance & Economics. https://doi.org/10.1002/ijfe.2601
Uche, E. & Effiom, L. (2021). Financial development and environmental sustainability in Nigeria: fresh insights from multiple threshold nonlinear ARDL model. Environmental Science and Pollution Research, 28(29), 39524-39539. doi: 10.1007/s11356-021-12843-8
Uche, E. & Ngepah, N. (2024). How green-technology, energy-transition and resource rents influence load capacity factor in South Africa. International Journal of Sustainable Energy, 43. https://doi.org/10.1080/14786451.2023.2281038
Ullah, S., Chishti, M.Z., Majeed, M.T., 2020. The Asymmetric Effects of Oil Price Changes on Environmental Pollution: Evidence from the Top Ten Carbon Emitters. https:// doi.org/10.1007/s11356-020-09264-4/.
Verheyen, F. (2013). Exchange rate nonlinearities in EMU to the US. Econ. Model. 32, 66-76.
Wang, S., Zafar, M. W., Vasbieva, D. G. & Yurtkuran, D. G. (2023). Economic growth, nuclear energy, renewable energy, and environmental quality: Investigating the environmental Kuznets curve and load capacity curve hypothesis, Gondwana Research. https://doi.org/10.1016/j.gr.2023.06.009
Zhang, W., Huang, Y. & Wu, H. (2022). The symmetric and asymmetric effects of economic policy uncertainty and oil prices on carbon emissions in the USA and China: evidence from the ARDL and non-linear ARDL approaches. Environmental Science and Pollution Research, 29, 26465-26482. DOI: 10.3389/fenvs.2022.860942