پژوهشنامه اقتصاد انرژی ایران
پیاپی 5 (زمستان 1391)

The main purpose of this study is to develop a model for determining the optimal shares of renewable and non-renewable sources of energy in a sustainable growth model. We develop an optimal control model in which nonrenewable and renewable sources of energy are inputs of production. The model allows us to determine the optimal shares of renewable and nonrenewable energy inputs. Finally، we use the model to determine these shares for Iran. Genetic algorithms technique is used to estimate the coefficient for production and utility functions. We also estimate the pollution equation. Using these parameters، we derive the optimal paths for consumption، output and renewable and nonrenewable energy shares in Iran. The results show that the optimal share of renewable energy in total energy consumption is about 0. 8 percent in 2010. While the actual share of renewable energy in Iran was 0. 4 percent. Moreover، our model predicts this share should rise to 2. 1 percent of total energy consumption by 2021 to be able to stay on sustainable growth path. This requires an average growth rate of 26 percent in renewable energy production each year.

Global Demand for Natural Gas has exhibited a considerable growth during the first decade of the 21 century. During this period، the trade in natural gas via pipeline has increased by 65 percent. The establishment of Gas Exporting Countries Forum (GECF) and its policies has been regarded، by many leading exporters and importers of natural gas، as a turning point in the development of natural gas market. This is due to the fact that currently the GECF member countries possess nearly half of the global trade in natural gas and over 40% of the global trade via the pipeline. We consider، in this paper، the possibility of competition or cooperation amongst member countries in exporting natural gas via pipeline. It is concluded that the feasibility of competition or cooperation in GECF member countries is not only very weak but is possible only in three cases and between six member countries.

GDP growth rate as a measure of economic progress is estimates on the basis of national accounts. Since the national accounts are recorded regardless of natural resource depletion، by estimating depreciation in the oil، gas، coal and other parts of the environment، depletion of natural resources can be accounted for which will provide the access to green GNP index. Green GNP shows increased economic growth stability. Among all natural resources، oil is the most important source of revenue for oil exporting countries and fluctuations in its price is a major factor for economic crisis in both the oil-exporting and importing countries. The main purpose of the present paper is to examine the impact of oil price shocks on green GNP. For this study، the first oil price shock are calculated using hoodrick - Prescott Filter method and then the effects of oil price shocks on green manufacturing was estimated using self regressing pattern. Based on the estimation results in the short term، oil price shocks have a negative impact on the green production. This is due to the oil extraction، depletion of natural resource is increased and it leads to decreasing the green production، and it has negative impact on green production in the long-run because an increase in oil production will lead to real growth of other sectors so that this growth offsets the depreciation.

Crude oil prices are influenced by many factors. Inclusion of all these determinants in a single model is complex and inefficient. In this case، using time series approach might be appropriate. In the later method past behavior of oil prices is used to forecast its future volatility. Several time series studies were conducted to forecast oil prices using methods such as autoregressive integrated moving average (ARIMA) models and artificial neural networks (ANN). All these methods need a large volume of data to have accurate forecasting. One way to overcome this limitation is to use fuzzy regression (FA) models which can give more accurate forecasting with less data. In this study، the three methods، fuzzy regression، ARIMA and fuzzy autoregressive integrated moving average (FARIMA) were applied using the daily oil price in order to forecast oil prices. To compare the forecast accuracy of the model، the prediction error criteria was used. The results showed that the performance of FARIMA is much better than the other two models.

Since the first inception in 1992 that the debate was started on the relationship between environment and growth، the Environmental Kuznets Curve hypothesis has been subject of intense scrutiny. The most recent line of investigation criticizes the EKC hypothesis for the lack of sufficient statistical testing of existence. Specially by introducing co-integration concept in time series data it is asked whether econometric estimations can show long-run inverted U shaped relationship between income and environmental pollution. On the basis of panel integration and co-integration tests، Stern (2004) and Perman and Stern (1999، 2003) have presented evidence and forcefully stated that the EKC hypothesis does not exist. In this paper by using fractional co-integration test، EKC is evaluated for 27 low middle income countries. The conclusions show according to classical co-integration test there is no co-integrated EKC based on HADRI statistics. Using fractional co-integration، evidences support a common EKC for countries: El Salvador، Nicaragua، Iran، Pakistan، Paraguay، Tunisia but our data does not give useful information about EKC existence.

The causal relation between energy consumption and economic growth، as an imperative issue in energy economics، has been a well-studied topic. Previous studies in Iran have ignored the nonlinear behavior which could be caused by structural breaks. In this study، both linear and nonlinear causality test are applied to examine the causal relationship between energy consumption and economic growth in Iran. The nonlinear causality test، applied here، is based on the conception of correlation integral (an estimator of spatial probability across time). In this study، we find evidence on a unidirectional linear and nonlinear causality running from energy consumption to economic growth.

This paper investigates the relationship between energy consumption، foreign trade and human development index and environment pollution with emphasis on role of institutions quality according to Environmental Kuznets Curve (EKC). Based on the EKC hypothesis there is an inverted-U-shaped relationship between different pollutants and per capita income. Although، studies about EKC have grown in recent period but in most of these studies the effect of institutions quality on carbon emissions has not been considered. This case has been tested for members of organization of the Islamic Conference (OIC) using the time series data for the period of 1996- 2007. The results from estimation of static and dynamic panel data models show that (i) the EKC hypothesis isn’t empirically supported for members of OIC; (ii) the elasticity of pollution relative to institutions quality is (-0. 24) that indicates when institutions، quality increases by 1%، pollution decreases by 0. 24%; (iii) energy consumption، foreign trade، human development index have significant and positive effect on pollution; (iv) The results of static and dynamic models estimation are consistent together، although quantity of coefficients in dynamic model are smaller than static model. In dynamic model، the elasticity of pollution relative to institutions quality is (-0. 2)، which indicates dynamic effects of institutions quality on pollution is smaller than its static effects.

Financial development is an important factor in economic growth، particularly in developing economies. Financial development can increase the efficiency of the financial system and on the other hand it can affect the energy demand. This paper investigates the relationship between financial development and energy demand in Iran، Using the ARDL and ECM model in 1359 to 1386. The paper seeks to answer the question whether there is a positive statistical relationship between two variables، financial development and energy demand. Finally، the existence of such a relationship was established in a statistical analysis both for short term and long term. Elasticity of the indicators of financial development in the long were obtained greater than 1. This indicates that the index of long term impact of financial development on energy demand is relatively high.