پژوهشنامه اقتصاد انرژی ایران
پیاپی 37 (زمستان 1399)

In recent years, privatization in the downstream industries of oil and gas , has been one of the most important measures taken to change and improve the business environment and remove barriers of production, as well as to implement of the general policies of Article 44 of the Constitution. This study intends to check out eleven variables related to the performance of six companies: Isfahan Oil Refinery, Bandar Abbas Oil Refinery, Tehran Oil Refinery, Lavan Oil Refinery, Shiraz Oil Refinery and Tabriz Oil Refinery by DID (fuzzy) method and compare it with control groups in order to Assess the privatization status of these companies. The results of this study show that two variables out of the eleven variables -, the ratio of general administrative and sales costs to revenues and the number of staff before and after the transfer, were significant for the control group. In other words, the employment situation and general administrative and sales costs in the companies under review were more unsatisfactory than the control group and in this regard, they had poor performance. This shows that in practice, the transfer of these companies has not affected the employment situation, positively.

Due to the strategic role of volatility and instability of crude oil prices and its effects on all countries of the world, different methods of modeling and forecasting are necessary. Over the past two decades, extensive literature has emerged on various approaches to empirically modeling volatility in the crude oil market. In this research, WTI crude oil price volatility modeling, which is one of the most important types of crude oil in the market of this strategic commodity, is examined with six flexible stochastic volatility (SV) models. Then the experimental performance of these models is compared with each other using Bayesian methods. The findings of this study show that adding jump in efficiency and leverage effect to the stochastic volatility (SVLJ) model greatly improves its performance compared to other models. According to the findings of this model, the stability of volatility in the WTI market is very high and on average one jump occurs in this market every year. However, this model shows that in 2020, two jumps in WTI returns occurred in April and May, which is a unique event. In addition, the correlation between the return jump component and the volatility jump (Merton correlation jump) is not confirmed in the WTI data. Also, due to the negative leverage effect, negative shocks have stronger volatility effects than positive shocks in the crude oil market.

It is necessary to develop the photovoltaic industry due to the criticality of reducing economic dependence on fossil fuels and mitigating air pollution. Therefore, the present study aims to propose a financing model for this industry in Iran.

This is an applied-developmental study, In terms of purpose. It is developmental because it provides a framework for financing the industry. On the other hand, it is of an applied nature, as its results find direct application in developing this industry. The modeling draws on a mixed-method approach combining the qualitative methodology of grounded theory and the quantitative method of artificial neural networks. The study's population comprises the financial, economic, and technical experts of the photovoltaic industry. Semi-structured interviews took place with 25 experts chosen through targeted sampling, combining maximum variation with snowball sampling methods.

The findings indicate that the investment funds (one of the primary strategies of community financing), bank loans (one of the private financing strategies), power purchase agreements (a government incentive), public funding by modifying the fossil power tariffs, along with guarantees and insurances are among the strategic priorities for financing this industry.

In sum, the financing model of the photovoltaic industry demonstrates that based on the current context in Iran, it is possible to create a profitability perspective and a supportive atmosphere for the photovoltaic industry by adopting diverse strategies.

Considering the increasing use of storage as one of the effective methods of peak demand management and increasing the reliability of the electricity network, it is necessary to prioritize the use of storages.The purpose of this study was to prioritize selected sub-distributive substations of Tehran for peak load, curve leveling and economic criteria using battery storage. First, we introduce different types of storage and considering the location of the storage in this study, the substations are power distribution. After prioritizing the posts and identifying the first priority posts, we determine the appropriate size of the storage and determine the delay time and the amount of benefit from delaying the development of the post when using the electrical energy storage. The method used is based on multi-criteria decision making with Shannon entropy weighting method and SAW implementation method. In this study, we used real data obtained from Tehran Regional Electricity and the data used for the 63 to 20 kW substations Ekbatan, Azadi, Azerbaijan, Abuzar, Sina, Depo and Yakhchi Abad on July 20, 2016. It is the hottest day of the year. The results of this study show that the maximum installed storage capacity calculated for the first priority post is 119.66 MWh and the maximum storage capacity is 18MW. the most suitable storage size for installing is 120MWh / 18MW. Using the storage at the selected post will delay the development of the post for 7 years and the benefit of underdevelopment is 40% of the investment cost.

The global trend towards natural applications in the fields of production and transportation is growing rapidly, and factors such as low cost, safety, availability, environment, and the development of technology and its application, especially in gas turbines, have made the product an alternative to petroleum fuels. Be. Many of the technological ways on the market explore the challenges and opportunities of using natural gas with the aim of identifying relevant productivity paths. As one of these solutions, in this article, a model for selecting the best fuel in the natural value chain in Iran is introduced from four options: compressed natural gas, natural gas, dimethylator and Gas- To- Liquid (GTL). First, based on a comprehensive study, fuel selection indicators were identified. Then, using Delphi technique and with the help of relevant experts, the indicators were screened and the final 20 cases were selected. In the next step, the indices were ranked, which was achieved through a group agreement between experts with a Kendall matching coefficient of 0.808. In order to convert rank into weight, a Rank Order Centroid (ROC) technique was used. Finally, with the weights of the indicators as well as the four options mentioned above, the CoCoSo technique is taken to determine the superior fuel. According to the results, liquefied natural gas is currently the best option for the country. And in the next rank, compressed natural gas is placed. The facts of the world confirm the accuracy of the results obtained.

Environmental degradation is one of the most important concerns in the developing countries. One of the most important indicators whose study helps to understand the extent of the world's support for improving the quality of the environment is the ecological footprint (EF). EF is an indicator that shows the environmental constraints and the extent of human encroachment on these constraints. Numerous factors such as energy consumption, etc. are effective on the EF, but on the one hand due to the effective role of economic freedom and governance in the EF and on the other hand due to the lack of interaction between these two variables on the EF in any study, Internally. The purpose of this paper is to investigate the interaction of economic freedom and governance on the EF of selected developing countries during the period 1971-2017 and two econometric models (The first model: the effect of economic freedom and governance as independent variables on the EF and the second model: the interaction of economic freedom and governance on the EF) in the form of panel data method have been used. The results of the first model indicate that the effect of economic freedom and governance on the EF of selected developing countries are positive (and significant) and negative (and significant), respectively, but the results of the second model estimate It indicates that the interaction of economic freedom and governance on the EF of selected developing countries is negative and significant.