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09-05-2019 | Original Article

Home appliances’ rebound effects estimated by a modified nonlinear model: an empirical study in South Korea

Author: Sang-Hyeon Jin

Published in: Energy Efficiency | Issue 8/2019

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Abstract

Energy efficiency improvement is an important measure in the age of climate change. However, efficiency improvement also has severe side effects, known as the rebound effect. In this context, to improve the accuracy of estimates of rebound effects, this study attempts to modify the previous nonlinear model by including an income variable. Data from the “Survey of Electricity Consumption Characteristics of Home Appliances” were utilized. The hypothetical targets for efficiency improvement include the following four major home appliances: televisions, refrigerators, washing machines, and air conditioners. The analysis results show a reasonable positive value of the income effect. Therefore, rebound effects become marginally smaller owing to the elimination of this confounding factor. Additionally, rebound effects vary considerably at the level of individual home appliances. In conclusion, policymakers should prudently consider rebound effects to ensure the success of energy efficiency policies.

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Khazzoom and Brookes developed the theory on the rebound effect in the 1980s. Saunders (1992) synthesized and named this theory the “Khazzoom–Brookes postulate.” Details on the rebound effect are provided in the second section.

In fact, a number of studies have shown that there is interaction between income and rebound effects (Saunders 2013, Chakravarty et al. 2013).

Rebound effects are classified into three categories: direct effects, indirect effects, and economy-wide effects. First, “direct rebound effects” are related to the part taken back in the same energy service. For example, oil consumption increases when consumers possess highly efficient cars. Such rebound effects are caused by cost savings arising from efficiency improvement. Second, “indirect rebound effects” are secondary effects of efficiency improvement. The cost savings that consumers of efficient cars realize due to efficiency improvement increase their energy consumption of other goods or services. Third, “economy-wide rebound effects” refer to the ultimate effects of efficiency improvement. Efficient cars lead to a change in not only the cost of the service offered as a commodity feature but also the cost of intermediate and final commodities. This might lead to an expansion of rebound effects throughout the economy (Dimitropoulos 2007, Sorrell and Dimitropoulos 2008). This study is restricted to the scope of direct effects because policymakers considering efficiency improvement programs focus on the energy consumption of only target appliances. In fact, numerous studies have focused on direct rebound effects (Yu et al. 2013).

Recently, besides the earlier focus on energy issues, studies related to the rebound effect have broadened, and they are now considering environmental problems (Barker et al., 2007, Brannlund et al. 2007, Druckman et al. 2011, Turner and Hanley 2011, Hong et al. 2013, Thomas and Azevedo 2013, Koesler et al. 2016, Vivanco et al. 2016).

The rebound effect for personal automotive transport is 10~30%, and the number of studies on the subject is 17. Meanwhile, the effect for space cooling is 1~26%, and the number of studies on the subject is only 2. Therefore, the evidence on the rebound effect for personal automotive transport is trustworthy, while the effect of space cooling is unreliable due to the lack of studies on the subject (Sorrell et al. 2009).

To summarize, researchers with interest in the rebound effects of home appliances have adopted various methods such as direct relative measure, elasticity parameter measure, life cycle analysis, almost ideal demand model, and coefficient estimation of the log form of the energy consumption function (Chakravarty et al. 2013).

The following three methods are used to estimate the rebound effect: direct measurement, indirect estimation, and direct estimation (Jin 2007). “Direct measurement” is considered the easiest method for measuring the rebound effect, while the other methods are used for estimation. “Indirect estimation” does not use the relationship between energy use and efficiency but utilizes price elasticity. “Direct estimation”, by contrast, uses the relationship between energy use and efficiency directly. Certainly, a different classification of estimation methods is possible (Yu et al. 2013). However, this classification of three methods is simpler and clearly understandable when compared to other classifications.

These four appliances account for 48.7% of the total electricity consumption per household. Namely, televisions, refrigerators, washing machines, and air conditioners account for 10.4%, 23.8%, 2.0%, and 12.4% respectively (KPX 2011).

In this model for televisions, the p value is less than 0.000, and the adjusted R² is 0.669.

In this model for refrigerators, the p value is less than 0.000, and the adjusted R² is 0.956.

In this model for washing machines, the p value is less than 0.000, and the adjusted R² is 0.6.

In this model for air conditioners, the p value is less than 0.000, and the adjusted R² is 0.343.

In the former case, which succeeded in efficiency improvement, the reduction in greenhouse gas emissions was additionally registered as the “Clean Development Mechanism” (Jin 2013).

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Title: Home appliances’ rebound effects estimated by a modified nonlinear model: an empirical study in South Korea
Author: Sang-Hyeon Jin
Publication date: 09-05-2019
Publisher: Springer Netherlands
Published in: Energy Efficiency / Issue 8/2019
Print ISSN: 1570-646X
Electronic ISSN: 1570-6478
DOI: https://doi.org/10.1007/s12053-019-09795-x

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