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Published in: Energy Efficiency 7/2019

03-09-2019 | Original Article

The potential for short-term energy efficiency improvement in Canadian industries

Authors: Samuel Gamtessa, Jason Childs

Published in: Energy Efficiency | Issue 7/2019

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Abstract

Canada has joined the few countries that have adopted carbon tax in an effort to mitigate CO2 emissions. Since consumption of fossil fuels is the primary source of CO2 emissions, the key mechanism for business to reduce their carbon tax liabilities without reducing their productive activities is through energy savings. While businesses could achieve this goal in the long-run by investing in new energy-efficient technologies, the short-run response is normally to engage in energy conservation and minimization of inefficiencies. The potential for such improvements is, however, unknown. We employ a stochastic energy intensity frontier model to separate energy demand driven by energy prices, other input prices, and indicators of the level of technology from energy demand due to inefficiency. We used the Canadian KLEMS data set covering all business sector industries for the period 1961–2014. We find an average transient energy inefficiency of approximately 8.5%. Inefficiency is particularly high in energy-intensive sectors such as oil and gas extraction. The trend shows that inefficiency has declined substantially over time, particularly after the early 1970s oil price shock. Comparing the trend in energy intensity to the trend in energy inefficiency reveals that reductions of energy inefficiency have contributed to the decline in energy intensity. Our results suggest the potential to further reduce energy inefficiency and, thereby reducing energy consumption and CO2 emissions without reducing output. Existence of such potential is important in determining the economic and environmental impact of a carbon tax.

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Appendix
Available only for authorised users
Footnotes
1
The estimated aggregate energy inefficiency of the Canadian economy is 62% in this study.
 
2
It is important to note that Filippini and Hunt (2011) stated that their estimates for the energy inefficiency using the underlying energy demand approach represents energy intensity. Clearly, in industries, energy intensity cannot be used to measure energy efficiency; energy intensity changes due to changes in relative price of energy, improvements in production technologies, and efficiency improvements. Our study attempts to find the contribution of energy inefficiency to energy intensity.
 
3
This specification implicitly assumes a constant returns to scale cost function. This assumption fits the nature of the data used in this study. The KLEMS dataset is constructed assuming a constant returns to scale Cobb-Douglas production function.
 
4
That is, \( \frac{I_{it}}{{I_{it}}^{\ast }}=\frac{E_{it}/{Y}_{it}}{E_{it}^{\ast }/{Y}_{it}}=\frac{E_{it}}{E_{it}^{\ast }} \). Thus, the inefficiency term measured in our model is equal and consistent with Filippini and Hunt (2012).
 
5
See Kumbhakar et al. (2014) for comparison of panel data stochastic frontier models.
 
6
There are two different approaches proposed to address the incidental parameter problem, the pair-wise difference (time-differencing within each group) approach proposed by Belotti and Illardi (2018) and the within transformation (mean-deviations) approach proposed by Chen et al. (2014).
 
7
Statistics Canada. Table 38-10-0097-01. Physical flow account for greenhouse gas emissions.
 
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Metadata
Title
The potential for short-term energy efficiency improvement in Canadian industries
Authors
Samuel Gamtessa
Jason Childs
Publication date
03-09-2019
Publisher
Springer Netherlands
Published in
Energy Efficiency / Issue 7/2019
Print ISSN: 1570-646X
Electronic ISSN: 1570-6478
DOI
https://doi.org/10.1007/s12053-019-09821-y

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