mohamadnabi ShahakiTash; Ali Norouzi
Volume 3, Issue 10 , April 2014, , Pages 93-130
Abstract
In this study, we perform a parametric analysis of the energy structure, estimating the demand function of natural gas as well as assessing the factors affecting the short-run and long-run intensity of natural gas in Iran's energy-intensive industries during 2003-2010. The energy-intensive industries ...
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In this study, we perform a parametric analysis of the energy structure, estimating the demand function of natural gas as well as assessing the factors affecting the short-run and long-run intensity of natural gas in Iran's energy-intensive industries during 2003-2010. The energy-intensive industries consume on average 94.5 percent of total energy and over 97.5 percent of natural gas of entire industry. Findings indicate that the intensity of natural gas consumption in short-run and long-run is equal to 0.1493 percent and 0.1144 percent, respectively, and the energy-intensive industries have approximately operate efficiently in natural gas consumption. Assessing the trend of contribution and intensity of natural gas of energy-intensive industries indicates that total share of natural gas of 10 industries has been increased in the whole period and the amount of natural gas intensity (on average) has been decreased in short and long-run. The most important factor in increaseing efficiency in long-run is the reduction of substitution effect, and the important factor in the overall reduction of intensity of natural gas in short-term is reduction of positive budget effect. Accordingly, we can conclude that the change in prices of all production inputs is an important factor in the change of the intensity of natural gas and the other components (production and technology) have far less influence in determining the intensity of natural gas.
Mohammad Nabi Shahiki Tash; Ali Norouzi; Ghulam Ali Rahimi
Volume 2, Issue 6 , April 2013, , Pages 75-105
Abstract
In this Study, We applied Translog cost function with four Input (Labor, Capital, Energy and Material) and ISUR[1]method for analysis of the cost structure of 11 most Energy intensive sub sector industries (With 4 Digit ISIC[2]code) of Manufacture of other Non-Metallic Mineral Products (Code26) and Manufacture ...
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In this Study, We applied Translog cost function with four Input (Labor, Capital, Energy and Material) and ISUR[1]method for analysis of the cost structure of 11 most Energy intensive sub sector industries (With 4 Digit ISIC[2]code) of Manufacture of other Non-Metallic Mineral Products (Code26) and Manufacture of Basic Metals (Code 27) during the period 1375-87. Input Share, Economies of Scale, Minimum Efficient Scale, Own-cross price elasticity and Morishima elasticity of substitution were calculated. The important results of this study is the detection of Scale effects, which reveals possibilities for increasing Scales (products) and reducing costs. The result of Cross-price and Morishima Elasticity of substitution shows that all Input substitution elasticities areElastic. This case indicates that the Firm's Manager of Energy intensive industries have a lot of options to substitute one input for the other inputs.
[1]. Iterative Seemingly Unrelated Regressions
[2]. International Standard Industrial Classification
