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Energy efficiency and consumption — the rebound effect — a survey

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TLDR
In this paper, a review of some of the relevant literature from the US offers definitions and identifies sources including direct, secondary, and economy-wide sources and concludes that the range of estimates for the size of the rebound effect is very low to moderate.
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This article is published in Energy Policy.The article was published on 2000-06-01. It has received 1867 citations till now. The article focuses on the topics: Rebound effect (conservation) & Energy consumption.

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Citations
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Quantifying the rebound effects of energy efficiency improvements and energy conserving behaviour in Sweden

TL;DR: In this paper, the authors derived a general expression of the rebound effects of household consumption in a parameterised form where available data can be tested and analyzed how different parameter assumptions affect the quantification of rebound effects and what may be reasonable ranges.
Journal ArticleDOI

Including second order effects in environmental assessments of ICT

TL;DR: Information and Communication Technology (ICT) can have both negative and positive impacts on the environment.
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Known unknowns: indirect energy effects of information and communication technology

TL;DR: While the overall net effect of ICT is likely to remain unknown, this review suggests several guidelines for improving research quality in this area, including increased data collection, enhancing traditional modeling studies with sensitivity analysis, greater care in scoping, less confidence in characterizing aggregate impacts, more effort on understanding user behavior, and more contextual integration across the different levels of the effect taxonomy.
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Energy rebound effect in China's Industry: An aggregate and disaggregate analysis

TL;DR: Wang et al. as discussed by the authors investigated the impact of output growth on energy consumption in China's industrial sectors with an index decomposition model and the energy rebound effect in the industrial sectors using a panel data model using the annual data during 1994-2012.
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The impact of energy efficiency on carbon emissions: Evidence from the transportation sector in Chinese 30 provinces

TL;DR: Wang et al. as mentioned in this paper investigated carbon emissions caused by the transport sectors of 30 Chinese provinces from 2005 to 2019, and combined the decoupling index with a panel threshold analysis, showing that the inhibitory effect of energy efficiency on carbon emissions in the transportation industry is increasing as energy efficiency improves.
References
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Book

Economics and consumer behavior

TL;DR: Deaton and Muellbauer as mentioned in this paper introduced generations of students to the economic theory of consumer behaviour and used it in applied econometrics, including consumer index numbers, household characteristics, demand, and household welfare comparisons.
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Technology, Prices, and the Derived Demand for Energy

TL;DR: In this article, an industrial demand for energy is essentially a derived demand: the firm's demand for the energy is an input, derived from demand for a firm's output, which is an output.
Journal ArticleDOI

Individual Discount Rates and the Purchase and Utilization of Energy-Using Durables

TL;DR: In this article, a model of individual behavior in the purchase and utilization of energy-using durables is presented, where the tradeoff between capital costs for more energy efficient appliances and operating costs for the appliances is emphasized.
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Economic Implications of Mandated Efficiency in Standards for Household Appliances

TL;DR: In this article, the authors argue that the indiscriminate use of mandated standards will backfire, but a mix of selective standards and reliance on prices as a restraint can be effective.
Posted Content

Qualitative Choice Analysis: Theory, Econometrics, and an Application to Automobile Demand

TL;DR: In this article, the authors present a detailed study of automobile demand and use, presenting forecasts based on the powerful new techniques of qualitative choice analysis and standard regression techniques, which are combined to analyze situations that neither alone can accurately forecast.
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