Document Type : Research Paper
Authors
1 Ph.D. Student in Oil and Gas Economics, Allameh Tabataba'i University, Tehran, Iran.
2 Associate Professor, Energy Economics, Allameh Tabataba'i University, Tehran, Iran.
3 Professor, Department of Theoretical Economics, Allameh Tabataba'i University, Tehran, Iran
Abstract
Global greenhouse gas emissions have risen from 31,553 million tons of CO2 equivalent in 1990 to 46,187 million tons in 2022. According to the United Nations Intergovernmental Panel on Climate Change (IPCC), since the late 19th century, the Earth’s average temperature has increased by 1.1 degrees Celsius.
Every decade since 1960 has been warmer than the previous one, with the last decade being the hottest on record. The warming caused by human activities and greenhouse gas emissions has currently reached about 1 degree Celsius above pre-industrial levels. Over the past two decades, global scientific and political communities have increasingly focused on the issue of global warming and its associated climate changes. The historic Paris Agreement, signed on December 12, 2015, during the 21st Conference of the Parties (COP21) to the UN Climate Change Convention, was a significant step toward combating climate change and addressing the challenges of reducing emissions and investing in a low-carbon, resilient, flexible, and sustainable economy. The agreement, signed by 195 countries, came into force on November 4, 2016. Under the Paris Agreement, countries committed to reducing greenhouse gas emissions to prevent the global average temperature from rising more than 2 degrees Celsius above pre-industrial levels, and to pursue efforts to limit the increase to 1.5 degrees Celsius above pre-industrial levels.
Following the agreement, countries through the UN Climate Change Convention asked the IPCC to provide a special report on the impacts of global warming of 1.5 degrees Celsius above pre-industrial levels and related global greenhouse gas pathways. In the IPCC report, supported by 133 researchers, various greenhouse gas emission pathways to achieve the 1.5-degree goal were outlined. Achieving this goal will require significant reductions in greenhouse gas emissions, with a major focus on the energy sector. Four proposed scenarios, which aim to reach net-zero carbon emissions by 2050, predict a sharp decline in the use of fossil fuels. However, the type of fuel and the speed of the transition in fuel consumption vary considerably, especially for coal, oil, and gas, through 2030. Coal faces the most severe reductions, with consumption needing to decrease by 59% to 78% by 2030 compared to 2010. Natural gas has a better outlook, with predictions ranging from a one-third increase to a one-quarter decrease in different scenarios. Oil has the most uncertain future, with the fourth scenario, based on bioenergy combined with carbon capture and storage (BECCS), predicting an 86% increase in oil consumption compared to 2010. Given the uncertain future of oil in these scenarios, analyzing the impact of implementing each of the IPCC's proposed scenarios on OPEC member countries, whose economies are heavily reliant on oil revenues, is crucial. The innovation of this research lies in examining the effects of climate change policies on oil-producing and exporting OPEC countries, including Iran, using a time-series econometric approach, co-integration equations, and a vector error correction model.
Methods and Material
In this research, to examine the effects of the IPCC scenarios, which are based on reducing global fossil fuel consumption, on OPEC’s oil demand and supply, a time-series econometric approach was used. Co-integration equations were employed to estimate long-term relationships, and the vector error correction model was applied for short-term estimates. Given the significance of reduced demand for OPEC countries, which are economically dependent on oil export revenues, data on the production and price of OPEC oil were used. Additionally, the long-term effects of environmental actions under the IPCC scenarios, which replace fossil fuels with renewable energy by 2030 and 2050, were incorporated into the model using renewable energy price variables. Variables used in the supply and demand functions include OPEC oil production, OPEC oil prices adjusted for the U.S. consumer price index, industrial production indices for developed and emerging countries, and renewable energy price indices. The research data were gathered monthly from 1986 to 2022. OPEC oil price and production statistics were obtained from OPEC, and the U.S. consumer price index data were sourced from the World Bank. The industrial production index (IP) for developed countries was calculated as a weighted average of IP from the U.S., Japan, Germany, France, the U.K., Italy, Canada, Spain, the Netherlands, Sweden, Norway, Belgium, Austria, Denmark, Finland, Greece, Ireland, Portugal, and Luxembourg, with weights based on the GDP share of each country in total GDP. For emerging countries, the IP index was similarly calculated for China, Brazil, India, South Korea, Mexico, Turkey, and Indonesia. The GDP data were obtained from the World Bank, and IP data from the International Monetary Fund. Renewable energy prices were based on the weighted average levelized cost of energy (LCOE) for renewable sources such as concentrated solar power, offshore and onshore wind power, and photovoltaic solar energy. The weights were based on each energy type's share of total renewable energy production, and the LCOE data were published by the International Renewable Energy Agency. Initially, the industrial production indices for developed and emerging countries, as well as the renewable energy price index, were seasonally adjusted.
Table 1. Long-term supply and demand relationships for oil based on Johansen's method.
variables
OPEC Oil Supply function
OPEC Oil Supply function
OPEC oil production
1
1
Real price of OPEC oil
0.22
(0.05)
-0.05
(0.02)
Non-OPEC oil production
1.56
(0.41)
0
IP(Advanced economic)
0
0.76
(0.16)
IP(Emerging economic)
0
0.58
(0.07)
Renewable energy price
0
0.26
(0.06)
Error correction term
0.03-
)0.009)
0.08-
(0.003)
Results and Discussion
OPEC adopts two approaches in the global oil market: a strategic approach, where OPEC acts similarly to non-OPEC producers and amplifies the effect of price shocks, and an adaptive approach, where OPEC seeks to balance non-OPEC production changes and stabilize oil price fluctuations. The estimated coefficients indicate that during the study period, OPEC countries, alongside the increase in non-OPEC production, attempted to maintain their market share, often increasing production to force high-cost producers out of the market. This finding is consistent with those of Bog, Pal, and colleagues (2016), who viewed OPEC as a dominant producer seeking to protect market share by limiting competitors like shale oil producers.
The results of the model estimation indicate a direct relationship between OPEC oil supply and real oil prices, with a price elasticity of oil supply of 0.22. Additionally, a 1% increase in non-OPEC production leads to a 1.56% increase in OPEC oil production. The price elasticity of oil demand is negative at -0.05, with demand from developed countries having a more significant impact on OPEC oil demand than demand from emerging countries. Furthermore, a 1% decrease in renewable energy prices reduces OPEC oil demand by 0.26%. Therefore, in the pessimistic IPCC scenario, where oil consumption declines by 37%, OPEC’s oil supply could decrease by 40% by 2030.
Based on the findings, it is recommended that OPEC regularly monitor the pace of renewable energy development up to 2030 and adjust its strategies accordingly. Although the growth of industrial production in developed countries has a more significant effect on OPEC oil demand, trends in oil imports from China and India, which accounted for about 40% of OPEC’s exports in 2019, versus declining imports from the U.S. and European OECD countries, which have dropped by 40%, should also be considered by OPEC.
Keywords
- Crude oil demand
- Crude oil supply
- Renewable energies
- structural cointegration
- vector error correction model (VECM)
Main Subjects
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