• Journal of Energy Engineering
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• v.27 no.3
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• pp.10-20
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• 2018

Due to cheap electricity tariff on agricultural use, electricity consumption in agricultural sector has grown dramatically. We evaluated the negative effects of the cheap electricity tariff such as electricity over-consumption, increased dependency on electricity, decreased electricity productivity, and unequal distribution of the benefit. We also estimated the effects of agricultral output growth, structural change, and electricity intensity change on sharp electricity consumption increase in agricultural sector between 1998 and 2016 using the Log Mean Divisia Index decomposition method. The findings reinforce the necessity of raising the electricity tariff for agricultural use.

• Environmental and Resource Economics Review
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• v.16 no.3
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• pp.723-738
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• 2007

This paper draws some implications from Logarithmic Mean Weight Divisia Method (LMWDM) on the sources of $CO_2$ emission changes in the manufacturing sectors of Korea, UK, and USA. The sources of change in industrial $CO_2$ emission of a country, as manifested by production scale factor, structural factor, and technical factor, summarizes the forces behind the change in $CO_2$ emissions in each country's manufacturing sector. There are three observations. First one is that Korea's emission is increasing while USA and UK are experiencing reduction or stabilization of $CO_2$ emission in the manufacturing sector. Second implication is that the technical factor affecting $CO_2$ emission in Korea does not help much, or even hinder, the reduction of $CO_2$ emissions, comparing to USA and UK. Third one, which is the combined result of the first and the second one, is that Korea's increasing trend in aggregate $CO_2$ emission throughout the periods in consideration is mainly due to the failure in technical progress, or the deterioration in the structure of within subcategories, or both. The policy implications is clear. The obvious prescription is to launch a nation-wide policy drive which can revert these adverse trends.