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Price, Environmental Regulation, and Fuel Demand: Econometric Estimates for Japanese Manufacturing Industries

Isamu Matsukawa, Yoshifumi Fujii and Seishi Madono

Year: 1993
Volume: Volume14
Number: Number 4
DOI: 10.5547/ISSN0195-6574-EJ-Vol14-No4-3
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In this paper, we analyze interfuel substitution according to Japanesemanufacturing sectors. We examine the impact of environmental regulations and technical changes on fuel choice, and the effects of price on fuel substitution, using pooled data on fuel consumption and purchase price for 58 regions in the period 1980-88. The empirical results, based on the estimation of translog unit fuel cost functions by sector, indicate that (1) substitution possibilities were found for most combinations of fuel types in every sector; and (2) environmental regulations and technical changes significantly impact fuel consumption for most sectors, but their effects on fuel demand differ both across sectors and fuel types.

The Determinants of Sulfur Emissions from Oil Consumption in Swedish Manufacturing Industry, 1976-1995

Henrik Hammar and Asa Lofgren

Year: 2001
Volume: Volume22
Number: Number 2
DOI: 10.5547/ISSN0195-6574-EJ-Vol22-No2-5
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Using a structural decomposition analysis, we analyze the causes of a reduction in sulfur emissions originating from oil consumption in the manufacturing industry in Sweden during 1976-1995. The Swedish case is of interest since Sweden has pursued an ambitious policy to combat the precursors of acid rain. Between 1989 and 1995, about 59 percent of the reduction in sulfur emissions from manufacturing can be attributed to the announcement and implementation of a Swedish sulfur tax. Two thirds of the reduction during 1976-1995 is captured by substitution between oil and other energy sources. The price of electricity also has had a significant effect via substitution between oil and electricity. Furthermore, one third of the reduction during 1976-1995 is explained by decreased energy intensity.

The Capital-Energy Controversy: An Artifact of Cost Shares?

Manuel Frondel and Christoph M. Schmidt

Year: 2002
Volume: Volume23
Number: Number 3
DOI: 10.5547/ISSN0195-6574-EJ-Vol23-No3-3
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Any serious empirical study of factor substitutability has to allow the data to display complementarity as well as substitutability. The standard approach reflecting this idea is a translog specification-this is also the approach used by the majority of studies analyzing the substitutability of energy and capital. Yet, the substitutability between capital and energy and the source of discrepancies in the results still remain controversial. This paper offers a straightforward explanation for at least the divergent results provided by the translog studies: Using a translog approach reduces the issue of factor substitutability to a question of cost shares. Our review of translog studies demonstrates that this argument is empirically far more relevant than the distinction between time-series and panel studies being favored in the literature. More generally, we provide ample empirical evidence for our argument that the magnitudes of cross price elasticity estimates of two factors gleaned from static approaches like the translog functional form are mainly driven by the cost shares of these factors.

Estimating Plant Level Energy Efficiency with a Stochastic Frontier

Gale A. Boyd

Year: 2008
Volume: Volume 29
Number: Number 2
DOI: 10.5547/ISSN0195-6574-EJ-Vol29-No2-2
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A common distinguishing feature of engineering models is that they explicitly represent best practice technologies, while parametric/statistical models represent average practice. It is more useful to energy management or goal setting to have a measure of energy performance capable of answering the question, �How close is observed performance from the industry best practice?� This paper presents a parametric/statistical approach to measure best practice. The results show how well a plant performs relative to the industry. A stochastic frontier regression analysis is used to model plant level energy use, separating energy into systematic effects, inefficiency, and random error. One advantage is that physical product mix can be included, avoiding the problem of aggregating output to define a single energy/output ratio to measure energy intensity. The paper outlines the methods and gives an example of the analysis conducted for a non-public micro-dataset of wet corn milling plants.

Addressing Key Drivers of Regional CO2 Emissions of the Manufacturing Industry in Japan

Ken’ichi Matsumoto, Yosuke Shigetomi, Hiroto Shiraki, Yuki Ochi, Yuki Ogawa, and Tomoki Ehara

Year: 2019
Volume: Volume 40
Number: The New Era of Energy Transition
DOI: 10.5547/01956574.40.SI1.kmat
View Abstract

This study investigated the factors behind the historical changes in CO2 emissions of the Japanese manufacturing industry as a whole and by sector at the prefectural level. We decomposed the changes of CO2 emissions in 47 prefectures from 1990 to 2013 into four factors (carbon intensity, energy intensity, structure, and activity effects) using the logarithmic mean Divisia index method. We found that energy intensity, structure, and activity effects were more influential in the changes of emissions than the carbon intensity effect, although the most influential factor varied by prefecture. Among the eight considered industrial sectors of Japan's manufacturing industry, the changes in the chemistry and metal sectors were particularly complex. Thus, improvements of the energy intensity and production in these two sectors should be prioritized. We also conducted detailed analysis of the decomposed factors in three selected prefectures based on cluster analysis.

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