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Erschienen in: Social Network Analysis and Mining 1/2018

01.12.2018 | Original Article

Emissions abating technology adoption in a coal trading network

verfasst von: Germán G. Creamer, Bernardo Creamer

Erschienen in: Social Network Analysis and Mining | Ausgabe 1/2018

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Abstract

This paper demonstrates that an investment decision such as the acquisition of a new technology that affects a particular asset is associated with the dynamic trading network of this asset. Therefore, the exogenous variables of this trading network can be used to identify the determinant factors of the investment decision and their final effect on the dynamic trading network. Using a coal trading network among the different US states between 1990 and 2005, this research studies the factors that affect the corporate strategies to adopt emission abating technology. Typically, these companies improve their processes and equipment to lower emissions, pay the news costs of emissions, or use less contaminating low-sulfur coal (high-quality inputs). Efficiency increases when more sub-bituminous coal is used because of its lower level of emissions in comparison with bituminous coal and when the electric power sector is deregulated. This research indicates that firms select strategies that simultaneously control emissions and minimizes costs. The firms reduce their pollution using higher-quality inputs (sub-bituminous coal), investing in new emission abating technology or a combination of both approaches.

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Fußnoten
1
In 2008, electric power plants generated 83.3% of the total sulfur emissions.
 
2
Zhu (2003) does not recommend to use production variables with an adverse effect as inputs; however, in our tests, there was not much difference between using emissions as inputs or outputs, and the convergence improved slightly when \(\hbox {SO}_2\) emissions were used as inputs.
 
3
\(\hbox {SO}_2\) emissions are calculated from the content of sulfur in coal, assuming that all reported sulfur from the input coal would be poured into the air in the form of emissions.
 
4
FERC Form No. 423 provides information about the content of sulfur in coal purchased by electric power plants expressed as a percentage of the coal bought, types of fuel purchased, fuel cost, fuel origin, fuel quantity and fuel quality by electric power plants.
 
5
Form EIA 767 contains data on coal-based electric power plants with a generator nameplate rating of 100 megawatts or more through 2000, and 10 megawatts or more after that.
 
6
Regions 1 and 9 were not included because they had very few coal-based electric power plants reporting to FERC.
 
7
Information about R is at <http://​cran.​r-project.​org>.
 
8
SO2sBit is not significant in the longitudinal network model.
 
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Metadaten
Titel
Emissions abating technology adoption in a coal trading network
verfasst von
Germán G. Creamer
Bernardo Creamer
Publikationsdatum
01.12.2018
Verlag
Springer Vienna
Erschienen in
Social Network Analysis and Mining / Ausgabe 1/2018
Print ISSN: 1869-5450
Elektronische ISSN: 1869-5469
DOI
https://doi.org/10.1007/s13278-018-0498-x

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