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Investigation of factors that effect energy intensity in selected Organization for Economic Cooperation and Development (OECD) member countries provides suggestions for more efficient use of energy and greater energy security in these countries. It can also help developing countries to find ways to reduce energy consumption. To this end, we investigate the effects of government size and quality on energy intensity in OECD countries from 2002 to 2014.  We study the nonlinear effect of government size and quality on energy intensity using panel smooth transition model (PSTR).  Our findings do not support the hypothesis of a linear relationship between government size and energy intensity. They rather indicate the existence of a two-regime model with one threshold. Up to a certain threshold of government size, government size and industrial value added have positive and significant effect on energy intensity, and government quality and energy price have negative and significant effect. Beyond this threshold, government size, industrial value added and energy price have positive and significant effect and government quality has negative and significant effect on energy intensity. We can thus conclude that while government size tends to increase energy intensity, quality of government can counteract this effect and this positive contribution becomes more marked the larger the size of government.  
JEL Classification: Q40, Q43, Q48.
 

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Among the important factors that cause differences in energy intensity between countries and amongst regions in a country is their geographical location.  Inter-provincial and cross-country empirical studies can correctly model energy intensity by relying on spatial characteristics and eliminating estimation biasses.  Energy intensity in Iranian province is influenced by such spatial factors as climate, size and existence of industrial poles. This study investigates the factors that affect the energy intensity index in Iranian provinces and estimates spatial autocorolation over the period 2000-2013. For this purpose, we estimate an emprical model using panel data and determine the relevant coefficients by applying spatial panel econometric techniques and the quasi-maximum likelihood (QMLE) method.  Our model estimates the regional spatial elasticity of energy intensity to be 0.55. Therefore, to reduce energy intensity at the  provincial level we need to act regionaly. The most important policy recommendations of this study for scholars and policymakers are detailed in the paper.
JEL Classification: Q43, R11, O14, C33.
 

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The importance of improving energy efficiency in the industry and its sub-sections is that reduce the cost of production at the macro level, Pay less subsidies and reduce the cost of industrial products. In this way, enhanced the value added of these sectors and increase competitiveness, enhance product quality, and ultimately, reduce imports some of important goods and increase exports of some products that made. This study examines the effect of eliminating energy subsidies on the energy intensity in iran industry using the approach of seasonal time series data in during 1385-1392 with Cobb-Douglas cost function that negative correlation between energy intensity and energy prices approved. Also results show that over time with advances in technology, energy intensity is decreased. Then energy price liberalization scenario, assuming a steady rise in nominal prices for the period 1393-1389 is studied. The results show that after the liberation of energy prices, energy intensity is decreased so that the highest reduction in the first year of liberalization and in the years following the reduction of energy intensity has decreased.

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In this paper have been introduced an approach which refer to as the attribution analysis of index to the IDA and energy studies. This approach extends the methodology of IDA by quantifying the contribution of each individual attributes to the overall percent change of factors, such as the real energy intensity. As has been shown in this study, the method can be used as a tool to assess and monitoring changes of industrial energy efficiency in greater depth compared to what has been reported in the literature. It can similarly apply the technique to analyze the structural change index in a symmetrical way.

In this study have been applied the proposed method to the real energy intensity index in the multiplicative Logarithmic Mean Divisia Index ­(M-LMDI)­ approach,a major IDA technique. Since the M-LMDI is based on geometric mean type indices and chain computation,we need some appropriate method to cope with the difficulties that arise.

This study is based on a standard model of two factors such that the aggregate energy intensity index is the product of the real energy intensity index and the structural change index. The proposed attribution analysis, however, is not restricted to the number of factors. It can be similarly employed in other IDA studies, such as energy-related carbon dioxide emissions where the number of factors is often more than two. This approach can be defined as long as these factors are expressed in either geometric mean or arithmetic mean indices.

This study present a numerical illustration of the proposed method using the energy consumption and real value added data of the Iranian manufacturing industry.

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Climate change cannot control unless by reduction of GHG emissions to secure level, therefore it is important to identify driving forces and possible scenarios based on targets.
In this research, the Logarithmic Mean Divisia Index decomposition approach in combination with Extended Kaya Identity (EKI) are applied to investigate five factors could affect emissions during 1971-2012 in Iran. These factors include population, GDP_capita, energy and carbon intensity and share of fossil fuels. Chaining, non-chaining methods and three emission reduction scenarios (4, 8 and 12%) based on Iran INDC forms the other parts of research.
Based on results, carbon intensity, activity effect, and population contribute to increase and share of fossil fuels has a decreasing effect on emissions. The future targets of government should emphasis on change of fuel type and economic development toward low carbon. Chaining analysis could be used as a calendar, show the effect of events on parameters while non-chaining present a clear image by deleting noises. Among proposed reduction scenarios, the best and logical option emphasize on reduction of fossil fuel share (up to 40% compared to 2020) and development of renewable energies. Improvement of carbon and energy intensity (each as 50% compared to 2020) are the next options.
JEL Classification: Q54, Q01
Keywords: Climate Change, LMDI, Population, Activity Effect, Carbon Intensity, Energy Intensity.     

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In today's world, given limited fossil fuel resources and growing population, it is imperative to consider energy efficiency. In this regard, due to the spread of information and communication technology, using its capabilities to reduce energy consumption & intensity is worth consideration.  In this study we assess the effect of Information and communications technology on energy intensity in Iranian provinces during the period 2008-2017, using panel data techniques and generalized method of moments (GMM). The results show that ICT deployment has a negative and significant impact on energy intensity in Iran’s provinces. However, this effect is different among developed and less- developed provinces. The results imply that information and communication technology does not have significant effect on energy intensity in less- developed provinces. Besides,  relative energy prices and real per capita income have a negative and significant effect and number of vehicles, employment rate, and air temperature have a positive and significant effect on energy intensity.
‎: Information and Communication Technology‌) ‌ICT), energy intensity Index,‎‌) ‌ICT) ‎Development Index.‎
JEL Classification: D83 ،Q43، R11، O14

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In recent years, attention to the importance of optimal energy consumption has significantly increased. Meanwhile, the manufacturing sector is one of the most energy consuming sectors and its energy intensity index has always been high. In this study, we use a seemingly unrelated regression estimator to estimate factors that affect energy intensity in manufacturing industries with ten or more employees in Iran. We compare energy-based industries and non-energy-based industries. The results of this study show that while energy prices are inversely related to energy intensity in both groups of industries, the effect of rising energy prices on reducing energy intensity in energy-intensive industries is much greater. The ownership structure and industrial concentration are also inversely related to the energy intensity of industry. More privatization and increased  industrial concentration will reduce energy intensity, especially in the energy-based industries. The effect of research and development costs on energy intensity was either not significant or, contrary to expectations, was directly related to energy intensity.
JEL Classification: O13, Q47, C33
Keywords: Energy intensity, Manufacturing industries, Seemingly unrelated regression, Cobb-Douglas cost function, Energy-intensive industries

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The Impact of Uncertainty in Economic Policies on Energy Intensity in Iran
Feyzollah Morad
MA student of Economics, Department of Economic Development and Planning, Tarbiat Modares University, moradi.sbu@gmail.com
Lotfali Agheli
Associate Professor of Economics, Institute of Economics, Tarbiat Modares University, aghelik@modares.ac.ir
Abbas Asari Arani
Associate Professor of Economics, Department of Economic Development and Planning, Tarbiat Modares University, Assari_a@modares.ac.ir

Received: 2021/08/12   Accepted: 2021/11/11

Abstract 2

Energy intensity in the Iranian economy has always been on the rise. In this study, the only factor affecting energy intensity is the uncertainty in economic policies. It is important to determine a comprehensive measure of economic uncertainty that reflects the overall level of uncertainty in the economy. To build the index of uncertainty in economic policies, uncertainty in foreign exchange, monetary and fiscal policies has been used using the EGARGH approach. Then, the effect of uncertainty in economic policies on energy intensity has been estimated with the self-explanatory model with distributive intervals (ARDL) model during 1973-2018. The findings show that one percent increases in the index of economic uncertainty in current period, second year, and third year have positive and significant effects on energy intensity. The magnitudes of such effects are equal to 0.12, 0.11 and 0.06 percent, respectively. These results show that uncertainty in economic policies increases energy intensity. If uncertainty in economic policies goes up, firms cannot plan to manage energy consumption properly because their production plans will be risky in the medium- and long-term. The results showed that uncertainty in economic policies has a direct positive and significant positive effect on energy intensity in the short and long term. On the other hand, the indirect effects of economic policy uncertainty through the rate of inflation, budget deficit and economic growth on the intensity of energy consumption are negative, and these negative effects are intensified despite the uncertainty in economic policies.Therefore, reducing the intensity of energy consumption is possible by controlling inflation, budget deficit and strengthening economic growth. Because the impact of these variables on energy intensity is greater than the effects of macroeconomic uncertainty on energy intensity.
JEL Classification: D80,Q4,E50,E62,O53
Keywords: Uncertainty, Energy intensity, financial policy, monetary policy, Iran.

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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.

JEL Classification: K32, O13 and Q43
Keywords: Factor Analysis, Energy demand , Industries and Energy Intensity Industries.

 

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Improving economic welfare and providing suitable conditions for the entire society is one of the main goals of the economic system of any country. The undeniable role of energy in the process of production and consumption and the high energy intensity in developing countries, including Iran, has caused the reduction of energy intensity to be considered as one of the development goals of the country's economic analysts Therefore, the aim of the current research is to analyze the effect of the intensity and price of energy carriers (electricity, non-electricity, total) on economic well-being in Iran's economy during the period of 1971-2021. In this regard, economic well-being has been calculated using the composite index of well-being. This index includes four dimensions of real consumption flow, real wealth flow, income distribution and economic security. The calculations show that firstly, during the period under review, the average welfare index is equal to 123.01. Second, although the average welfare index has fluctuated during the following periods; In such a way that the highest amount of welfare is related to the sixth plan. The results of the estimation of the research model in four formats and based on the autoregressive distributed lag

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This study examines the effect of energy price changes on the intensity of energy consumption in mineral products using a dynamic computable general equilibrium (DCGE) model with calibrated data, to simulate two scenarios (1.%5 price shock to natural gas 2.%5 oil price shock) until the time horizon of 2050, for three groups of regions and countries (Iran, Major trading partners, Rest of World) has been investigated. The simulation results of the DCGE model for Iran in the first scenario suggest a continuous improvement in energy efficiency, where the energy intensity values remain negative in general, the second scenario depicts a temporary increase in energy intensity for Iran, followed by a gradual decrease. which shows the increase in the energy sector of mineral products in the near future. Trade partners and other regions show a sharper reduction in energy intensity under the second scenario with faster rates of decline and more ambitious targets for energy efficiency. Based on the obtained results, it can be said that Iran is becoming more efficient in terms of energy consumption for the production of mineral products, which can be caused by various factors such as technological advances, improvement of production processes be which is running.

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Export diversification means the increase of export items by a country, depending on the level of growth, industrial development and economic structure of that country, it can have positive or negative effects on energy intensity in that country. The aim of this study is to investigate the threshold effect of industrialization on the relationship between export diversity and energy intensity in Iran during the period from 1965 to 2022. For this purpose, a smooth transition regression model (STAR) is estimated with a threshold level, where the level of industrialization is chosen as the transition variable. The results show that the industrialization index variable can play an important role in changing the coefficients in the energy intensity pattern as a transmission variable. Thus, in the early stages of industrialization, the increase in export diversity led to a decrease in energy intensity, and after the economy passed a certain level of industrialization, with the increase in export diversity, due to the entry of industrial products with higher energy into the export basket, energy intensity has also gone up. It was also observed that urbanization has a negative and significant effect on energy intensity.