جستجوی مقالات مرتبط با کلیدواژه « تقاضای انرژی » در نشریات گروه « اقتصاد »

Evaluating the energy demand of the industrial sector is important and necessary for policy making in order to increase production and improve efficiency in this sector. The purpose of this study is to estimate the demand for major energy consumption in the industrial sector, including natural gas energy, electric energy, and petroleum products energy (gas oil and mazut) in the form of a system of equations during the period 1988-2019. The results of this research, based on seemingly unrelated regression equations, show that the demand for natural gas and oil products is inelastic, and natural gas energy input is substituted by electricity and oil product energy is substituted by natural gas. Also, the increase in the added value of the industrial sector has a positive and significant effect on the demand for natural gas energy and petroleum products. In addition, the increase in the ratio of capital to labor in the industrial sector is accompanied by a decrease in the demand for natural gas energy and petroleum products and an increase in the demand for electric energy. In addition, the increase in the ratio of capital to labor in the industrial sector has led to a decrease in the demand for natural gas energy and petroleum products and an increase in the demand for electric energy.

In this paper, we employ the locally flexible normalized quadratic (NQ) cost function to estimate the demand for electricity, gasoil, and kerosene in the agricultural sector of Iran. We use the price and quantity of the forenamed energy resources being consumed in the agricultural sector between the years 1971 to 2017. To provide credible results, consistent with microeconomic theories, we examine and impose the regularity conditions, namely, we examine the positivity and monotonicity of the cost function and impose curvature. We find that own-price elasticities are negative, income elasticities are positive, and Morishima elasticities of substitution are in general positive, and all elasticities are generally statistically significant. An exception is electricity which does not provide statistically significant own-price and income elasticities and cannot easily be replaced by the other energy inputs.

Examining the factors affecting changes in energy demand can help economic policymakers to adopt energy saving approaches. One method of examining these factors is factor analysis of energy demand. Given the high share of industry, especially energy-intensive industries in Iran's energy consumption, the purpose of this article is to analyse the factors affecting changes in energy consumption in all industrial industries and energy-intensive industries. For this purpose, the methods of analysis of Laspers, Division and Fisher index in the period 1397-1385 have been used. The results of factor analysis show that the energy consumption of all industries increased in the period under review and these findings are confirmed by real energy consumption statistics. The results also show that the main effective factor in increasing energy consumption of industries (year-on-year or in the whole period) is related to the effect of activity and other factors sometimes have an increasing effect and mainly a decreasing effect on energy consumption. Findings indicate the maximum role of energy intensity in reducing energy consumption of industries (including energy-intensive industries) and the positive role of structural effect in increasing energy consumption compared to the effect of activity is very small.

The present study examines the long-term relationship between energy demand, financial development and economic growth using data from the period 1349 to 1396. In order to reduce the bias of the estimates, the variables of foreign direct investment, free trade and gross fixed capital formation are also considered in the proposed model. To estimate the desired long-run relationship from generalized least squares regression, The Bayer-Hank combined co-integration method has been used. The results of this study showed that the increase in energy demand due to financial development is negligible and the impact of trade, gross fixed capital formation and real GDP on positive energy demand is positive. Also, the results of the asymmetric causality test showed that real GDP, free trade and gross fixed capital formation are the cause of long-term energy demand. Finally, the results of this study indicate that the impact of economic growth on energy consumption is much greater than the impact of financial development on this variable

Considering the importance of urbanization and its relationship with energy sources, it is necessary to examine the relationship between these two variables for policy making. Accordingly, this paper reinvestigates the relationship between urbanization and energy consumption in case of Iran for the period of 1375-1393 by employing the STIRPAT (Stochastic Impact by Regression on Population, Affluence and Technology) model and autoregressive distribution lag (ARDL) Bound Test. Long-term results show that logarithms of urbanization and its square have a positive effect on energy consumption. The positive effect of transportation on energy consumption is shown that energy is the technology used in this industry. The increase in GDP per capita has increased energy consumption. The relationship between technology and energy consumption suggests the function of return effects. Short-term results also confirm the positive impact of urbanization. Short-term relationships between economic growth and energy consumption are positive. Technology has negative effect and transportation will positively affect energy consumption in the short term. Our empirical results indicate that the short run deviations stem in energy demand function is corrected by 15.39% in each quarter and will take 1 year and 2 months to achieve stable long run equilibrium path. Based on the Granger causality results, energy consumption is a major cause of urbanization.

We undertook a sensitivity analysis of the key demand factors leading to changes of energy consumption in the competitive market, using a Leontief demand-driven approach. We applied the Leontief model to previous research results to study the most sensitive factors leading to the change of energy demand in different economic sectors. Based on the 2011 Iranian symmetrical input–output table, the results show that the secondary energy sector, transportation, wholesale and retail, manufacturing of basic metal and fabricated metal products and non-metallic mineral products respectively have the highest direct and indirect average technologically normalized elasticities of energy demand.
Our results indicate that we can reduce energy demand substantially through technological innovations in the above mentioned sectors.

Valid estimates of price elasticity of energy demand lead to a better understanding of the economic, environmental and distributive impacts of energy price changes, and enable policymakers to make efficient energy management decisions. This study aims to investigate the effectiveness of pricing policies for the modification of energy consumption patterns among Iran’s provinces. In this regard, price elasticities of energy demand ‎are estimated for selected energy carriers and total energy price index during 2000-2015. For this purpose, a dynamic panel model is used and the price elasticities of energy demand are estimated by Arellano-Bover (1995) and Blundell-Bond (1998) approaches. When total energy price index is applied in the model, the results show that the short-run and long-term price elasticities of energy demand are -0.038 and -0.567 on average, respectively. However, regarding energy carriers, the highest price elasticities of the aggregate energy demand belong to electricity and gasoline, respectively. The effect of climate change (as a proxy for heating and cooling needs) on energy demand is significant, and the average climate elasticity of energy demand is 0.15 in the short run and 2.30 in the long run. Since price elasticity of energy demand is less than one, and its climate elasticity is greater than one in the long run, non-tariff policies are proposed for energy conservation in the country.

Energy-intensive industries in Iran are responsible for a significant share of energy consumption, especially oil products. Therefore, there is a major focus on promoting energy efficiency in such industries. Energy efficiency improvement results in rebound and backfire effects. In this paper we estimate the effects of fuels, electricity and energy efficiency improvement in energy intensive industries based on computational general equilibrium model. Simulation is done for six scenarios, including 3. 1% efficiency improvement of electricity, fuels and energy for energy intensive industries and all sectors of economy. Results show that the rebound effects in chemical and basic metal industries are considerable (For instance, there are rebound effects of 79%, 94% and 92% in the last third scenarios in chemical industry). In addition, efficiency improvement will result in production cost decrease. Chemical and non- metallic mineral industries experiencing the most decreases of production cost around 0. 9% and 0. 6%, respectively.
JEL Classification: C68، Q41، Q43

In this study, we estimate the demand for natural gas in the subsection manufacture of basic metals of Iran using structural time series model (STSM) over the period of time 1981-2013. Such model contains unobservable elements which have been transported to state space model with the use of kalman filter and is estimated by implementing maximum likelihood approach. Also, because the Targeting of Subsidies Plan was approved by the Iranian parliament at the end of 2010, so we evaluate the role of this plan on energy demand of industrial subsectors. Finding of the research is that, first of all the nature of the trend is smooth one. Secondly, it is changing on a nonlinear basis. The estimated demand function shows that price elasticity for natural gas in the long and short run, correspondingly, are (-0.30) and (-0.79) and production elasticities of natural gas in the short and long run, correspondingly, are (0.17) and (0.38). Furthermore, Cross elasticity for electricity and gasoline in the long and short run, correspondingly, are substitute and complementary goods. In addition, the result of evaluating effect of the Targeting of Subsidies Plan show that estimated natural gas demand functions can explain the impact of this policy.

In this study, we estimate the demand for energy in the industrial subsectors of Iran in terms of double-digit ISIC classification using structural time series model (STSM) over the period of 13601981-20091388. As a case study, we alsoAlso, as a case study we estimated the demand for energy in subsection subsectors of textile, apparel and leather products. Furthermore, we try to determine considered the role of different climates in energy demand of the industrial subsectors. Because Since the Targeting of Subsidies Plan was approved by the Iranian parliament at the end of 13892010, so we evaluated the role of this plan on energy demand of industrial subsectors too.
By estimating the demand functions of electricity, natural gas, gas oil and mazut in subsection textile, apparel and leather products, it is found thatThe estimation results of demand for electricity, natural gas, gas oil and mazut fuel oil in three subsectors show that the estimated short-run price elasticities of these energy carriers are inelastic. The estimated long-run price elasticity of electricity is inelastic and long-run price elasticity of natural gas, gas oil and fuel oil mazut are more than unit. The estimated short-run output elasticities of these energy carries are inelastic and long- run output elasticities of electricity, gas oil and fuel oil mazut are inelastic and long- run output elasticitiy of natural gas are elastic. The result shows that the best climate for manufacture in textile sector is mild and humid climate. The results suggest that the nature ofAlso the trend of natural gas and fuel oil mazut demand are not linear and deterministic but stochastic in form andbut for electricity demand isn linear and deterministic. In aAdditionally, the result of evaluating effect of the Targeting of Subsidies Plan shows that the estimated demand for natural gas and fuel oil mazut demand functions can explain the impact of this policy.

Underlying Energy Demand Trend (UEDT) is tried to be introduced through Structural Time Series Model (STSM) in this paper in order to estimate Iran electricity demand function in residential and industrial parts during 1976-2012. Applying mentioned method to estimate the electricity demand functions، led to consider UEDT as an intangible and non-measurable variable and hence modeling it as a stochastic procedure via maximum likelihood approach and the kalman filter. Therefore skewed estimations are avoided in price and income elasticity. Results show that nature of the Underlying Energy Demand Trend in residential electricity demand function، is smooth trend model and it is local model with drift in industrial electricity demand function. Furthermore، the estimated price and income elasticities in residential and industrial sectors are indicative of inelastic for both short term and long term during the estimated period. Therefore، non pricing policies such as increasing efficiency of electrical energy applications and also determining the range of price elasticity and then the pricing based on subscribers consumption as a pricing policies is suggested to reduce electricity consumption in residential and industrial electricity sectors of Iran.

Energy demand prediction is very important to adopt appropriate policies. The reliability of intelligence and non-linear methods، particularly neural networks and evolutionary algorithms on energy demand prediction، hasbeenproved in numerous studies. This is due to volatility and non-linearity of energy demand and the affecting variables. Despite their lot of strengths، these techniques are faced with important issues such as imposing specific forms in evolutionary algorithmor necessity of large samples in neural networks. The purpose of this study is to exhibit a combined algorithm for more accurate energy demand prediction to overcome the disadvantages of individual techniques and to use their benefits simultaneously. To this purpose،the performance of various techniques in energy demand prediction has been investigated during 1967-2011. The results indicate that the neural networks learned by evolutionary algorithms in terms data limitations have desired outcomes، and the neural network base on the combination of genetic and particle swarm algorithms combination provides very good results. Comparisonof the results of this study with those of other studies in this field indicates the higher ability ofthe proposed algorithm and further confirms the high explanatory power of the used variables. Moreover، future energy demand projection indicates that the energy demand is going to be 1817، 1643 and 1457 million barrelsof oil equivalent (BOE) in 2025 under three different scenarios.

The industry as one of the most productive sectors is one of the most applicants energy especially natural gas. In this study using structural time series model (STSM) for evaluating demand for natural gas in the industrial sector of Iran is the focus of the analysis. Such model contains unobservable elements which have been transported to state space model with the use of kalman filter and is estimated by implementing maximum likelihood approach for the period of 1981-2011. Finding of the research is that، first of all the nature of the trend is smooth one. Secondly، it is changing on a nonlinear basis. The estimated demand function shows that price elasticity for natural gas in the long and short run is less than unit، correspondingly، (-0. 33) and (-0. 16). So، natural gas price in the short and long term is inelastic and even the time horizon which is one of the effective factors on the value of elasticity، have no influence on this good. Hence، it is suggested using nonpricing policies like induce production sector through tax-deductible depreciation and financing industries through the banking system. However، production elasticities of natural gas in the short and long run، correspondingly، are 2. 08 and 0. 99. These findings show that in the short term to keep pace with increased production in the manufacturing sector، the more intensive use of natural gas is observed. Cross elasticity for electricity is estimated to be 1. 64 in the long run and 0. 76 in the short run. This result suggests that in the long run the possibility of changing or replacing devices is high. The result of considering the implementation of the Targeting of Subsidies Plan shows that this policy has no influence on natural gas demand in industrial sector of Iran.

Due to resource limitations and also due to the role and importance of energy in economic development, determining effective factors on energy demand has specific important. Financial development is often cited as a very important driver of economic growth in emerging economies and it is thus likely that financial development affects energy demand. This study uses generalized method of moments (GMM) estimation techniques to examine the impact of financial development on energy consumption in D8 countries during the period 1990-2011. Several different measures of financial development are examined. the empirical results show a positive and statistically significant relationship between financial development and energy consumption when financial development is measured using stock market variables like stock market capitalization to GDP, stock market value traded to GDP, and stock market turnover.

Due to importance of energy factor in agricultural sector and considering the increasing energy price in recent years, analysis of energy demand is very important. In this paper in order to analyse agricultural energy demand, OLS, FMOLS and Johansen cointegration method and ARDL approach has been used and results of these methods have been compared. Data on energy price index, energy consumption and agricultural value added for priod 1355-1388 were used. Results showed that long run and short run price elasticity of energy consumtion are between -0.3 to -0.327 and -0.09 to -0.102 respectively. Also income elasticity of energy consumption estimated egual to 0.7. Results of OLS estimation of Log-Log model, Johansen cointegration method and ARDL approach are very similar. Because of price inelasticity of energy consumption especially in the shortrun, price policies are not likely to reduce energy consumtion considerably. Price policies can be more effective in the longrun, but this is subject to improvemeats in the energy consumption technology.

This paper intends to estimate the energy demand function in industry section basedon the two-stage optimization approach. Consequently، it defines the substitutionelasticity between inputs. Energy demand estimation in various sections makes itfeasible to define energy policies. At the first phase the key influential factors on theenergy demand function estimation in industry section which is one of highconsumption section، were defined and at the next phase the elements of energydemand were determined through logit function and seemingly unrelated regressionestimation and price and substitution elasticity were calculated.

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.

Energy has had a determinative role in economic growth of countries and its importance has been increasing during recent decades. The global economic growth and the industrialization process is one of the main sources of increasing demand and consumption of energy. On the other hand, the residential and commercial sectors are the largest energy consumption sectors, i.e. 34% of energy consumption compared to other sectors. Thus, to plan and control the amount of energy supply and demand, predicting energy consumption of these sectors would be helpful for policy makers. In this paper, the future status of energy demand of residential and commercial sectors in Iran is predicted using variables affecting energy demand of these sectors. Using PSO algorithm, both linear and exponential forms of energy demand equations were studied under 54 different scenarios with various variables. The data from 1968 to 2011 were applied to develop model and to choose the appropriate scenario. Results show that an exponential model with inputs including total value added minus that of the oil sector, value of made buildings, total number of households and consumer energy price index is the most appropriate model. Furthermore, energy demand of residential and commercial sectors is estimated for following years up to 2032.

Usually energy demand are studied with reference to energy demands patterns. The Rotterdam and AIDS models with a longer history in this field are often used in consumer demand systems modelling. This paper analyzes the demand for energy carriers in the domestic sector in urban areas of Iran during the period of 1984-2008. A non-nested is used test to determine the appropriate model. The results indicate that First-order difference dynamic model of LA-AIDS is a better model than the Rotterdam model for studying the function of urban household energy demand in Iran during the period studied.

Given the limitation and scarcity of the natural resources and due to the important role of energy in development and growth of countries, determination of the factors affecting energy demand entails particular importance. In this paper, following the identification of the factors influencing the energy consumption, we estimate the effects of financial markets development, including development of banks and the stock market by employing variables like per capita national incomeand inflation, on the energy consumption and with using combinational data pattern of D8 countries in the period of 1988-2008. Results indicate the significant and positive effect of financial markets development on the energy consumption. The coefficients of banks development indicators obtained greater than stock development, that means the capital market is less developed in D-8 countries than the money market. The coefficients of energy intensity and urbanization are significant and positive too. But inflation has a negative effect on energy consumption. The results of this study emphasize the need for paying attention to the energy demand along with financial markets development in order to achieve planned economic growth.