پژوهشنامه اقتصاد انرژی ایران
پیاپی 46 (بهار 1402)

Oil prices and other oil-products prices are connected to each other and their price volatilities are parallel. Firms which are using crude oil in their products are facing a risk of price volatility which has different reactions in each era and is known under different oil regimes. For example lubricant industry is completely connected to the oil price. With this philosophy when the economy faced volatility the market players faced loss and so to overcome this issue they began to hedge themselves with another commodity. This hedging process in different regimes has different rates. So there is a need to introduce a new model. From the work of Hamiltonian (1989) oil price has its own volatility and regimes so to this attitude there is an effort to calculate an efficient hedging ratio with regime switching dynamic constant correlation. In this article, monthly data of oil and gold prices for about 10 years from 2010 till 2020 is used and the model is programed with MATLAB. The result showed that the efficient hedge ratio for the first regime (first major change in price of two markets) is 66 percent and the second (second major change in price of two markets) one is 26 percent.

In this paper, the relationship between energy consumption and total factor productivity (TFP) in the industrial sector in Iran has been investigated using threshold-type nonlinear relationships. The results of estimating a two-threshold model in a sample including data related to 110 industrial branches during the years 2002-2019 show that the effect of energy consumption on the TFP in the industry sector is state-dependent on the energy consumption state or regime and the energy consumption variable coefficients in all regimes has a negative and significant effect on the TFP. If the energy consumption in Iran's industrial sector exceeds a certain threshold, the negative effect of energy consumption on the TFP will intensify. Also, the effect of energy consumption on the TFP in the industry sector is a state dependent on the TFP state or regime, so in low TFP regimes or states, the effect of energy consumption on the TFP of industries is considerable, but in high TFP regimes, industries with higher TFP have a much lower negative impact of energy consumption on their TFP.

The main purpose of this study is to investigate the effect of economic and social factors on the emission of carbon dioxide, which has been used as a measure of environmental pollution in Iran for the period of 1352-1397. In order to measure the economic and social factors affecting environmental pollution, it is necessary to study the short-term and long-term relationship between fuel oil consumption, urbanization, economic growth, and carbon dioxide emissions in Iran. For this purpose, the autoregression model with extended distribution intervals (ARDL) was used. The results show that the error correction coefficient obtained in this model shows that in each period, 33% of the short-term failure error can be made to achieve a long-term comparison. According to the estimate, the increase in fuel oil consumption, urbanization, and economic growth have a positive effect on carbon dioxide emissions both in the short term and in the long term. Also, the long-term results indicate that with an increase of one percent of gross domestic production, fuel oil consumption and urban population increase carbon dioxide emissions by 0.849, 0.166, and 1.566 percent, respectively. Therefore, the first step to reduce carbon dioxide emissions in the country is to pay attention to the amount of fuel oil consumption, hence policies can be made to use alternative energies such as renewable energies to reduce carbon dioxide emissions.

The main goal of this research is to design a composite economic-energy-environmental performance index (3EPI) for Iran's economy by generalizing the methodology of Khramov and Lee (2013) as well as evaluating the effect of variables on the composite performance index during the period from 1991 to 2021 using a time-varying parameters model (TVP). The 3EPI index is calculated in a weighted and unweighted form, and the trend is separated from the cyclic with the Hodrick-Prescott filter. The findings show that the long-term trend of the 3EPI index is in the range between 35 and 60 percent, which is significantly different from the base number of the index (i.e. 100 percent). The chronicle of the index shows that the worst performance is related to the implementation period of the structural adjustment policy (1994 and 1995), the first round of economic sanctions (2012), and the intensification of economic sanctions in the latest round of sanctions (2019). The best performance is related to the two periods of the relative stability of macroeconomic variables and the period of implementation of the JCPOA agreement. The results of the application of the TVP model show that, from 2011 to 2021, the variable of the budget deficit to GDP ratio had the most significant negative impact on Iran’s 3EPI performance index

During the last decade, the international price of crude oil has experienced frequent periods of volatility; which has motivated researchers to investigate how oil price uncertainty affects economic activities and financial markets. Reasonably, oil, as a direct or indirect input factor, can strongly affect the cost of production and profitability expectations of companies. Accordingly, oil price changes can change the company's decision-making and performance. In this regard, we have investigated in the present research the impact of crude oil price volatility on the leverage criteria of companies admitted to the Tehran Stock Exchange. For this purpose, we have used the data of 160 selected companies during the period of 2011 to 2019. We used the panel data method in order to analyze the collected data. The findings of the research showed that crude oil price volatility had negative and significant effects on the leverage criteria of listed companies. Therefore, we concluded that companies reduce their demand for financing to overcome the uncertainty of oil prices. Consequently, an increase in uncertainty in oil prices can motivate companies to reduce their demand for external financing and thus reduce their leverage.

Oil and natural gas production is not uniformly and homogeneously distributed across all provinces of Iran, whereas a major part of oil and gas incomes is consumed in provinces that do not have any significant role in oil and gas production. Therefore, any disruption in the production of oil and gas might expose the GDP growth of all provinces at risk. In this paper, the multiregional input-output table is calculated for the year 2015. Then, the hypothetical extraction method introduced by Dietzenbacher and Lahr (2013) is employed for estimating the effect of partial and complete extraction of oil and gas production in Khuzestan and other oil-oriented regions on the value-added of 71 economic activities in each of the regions. The findings reveal that firstly, following the extraction of oil and gas production in Khuzestan, the value added of this region reduces about %32 , while the extraction of the corresponding sector in other oil-related regions will mitigate this region’s value added by %14. Secondly, the relative reduction in the value added of economic sectors and each sector’s contribution of value-added reduction in each region depend on the economic structure of the interested region. The highest share of the total value-added reduction in each region belongs to the service sector in Tehran and agriculture in other non-oil regions. It seems that diversifying energy resources as well as supplying regions, enhancing fuel consumption efficiency, and renovating the transportation system are the most important policies to have more resilience.