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,LnECt,εt (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
