The Rebound Effect in Energy-Intensive Industries:A Factor Demand Model with Asymmetric Price Response

Dahlqvist, Anna; Lundgren, Tommy; Marklund, Per-Olov

doi:10.5547/01956574.42.3.adah

Cited by 13 publications

(4 citation statements)

References 45 publications

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“…During this period, the total spillovers fluctuated between 60% and 70%, with cross-market spillovers showing a high and stable situation. Realising that clean energy is key to mitigating the problem of global climate change, many countries are combining economic policies with incentive measures and supporting the development of clean energy through taxation and subsidies (Abdmouleh et al, 2015;Asl et al, 2021;Dahlqvist et al, 2021). As predicted by the market supply and demand theory, the energy and metal markets show an increased connectedness.…”

Section: Dynamic Spillover Resultsmentioning

confidence: 99%

Time-Frequency Spillovers and the Determinants among Fossil Energy, Clean Energy and Metal Markets

Ding¹,

Huang²,

Chen³

2023

The Energy Journal

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Using the frequency-domain spillover index method, we investigate time-frequency spillovers and their underlying drivers among fossil energy, clean energy and metal markets. We find that short-term spillovers are stronger than long-term spillovers. Global clean energy markets are powerful spillover transmitters that can have strong impacts on fossil energy and metal markets. Rare earth metals are most vulnerable to spillover effects from clean energy and base metal markets, particularly in the long term. Different clean energy sources and metal markets have heterogeneous connectedness, e.g., the impact of wind energy on rare earth market is greater than that of solar energy. The short-term spillovers are mainly driven by policy changes, while the long-term spillovers are mainly affected by stock market uncertainty and economic fundamentals. Our findings have important implications for the construction of optimal diversification strategies and the design of policy incentives to promote clean energy investments across different time horizons.

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Section: Dynamic Spillover Resultsmentioning

confidence: 99%

Time-Frequency Spillovers and the Determinants among Fossil Energy, Clean Energy and Metal Markets

Ding¹,

Huang²,

Chen³

2023

The Energy Journal

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“…The estimated size of rebound effects is influenced by various factors, including the model parameters used, the types of responses considered, and the time frame under examination (Chakravarty et al, 2013). There are several reasonable explanations for these variations in rebound effect estimates (Dahlqvist et al, 2021). One key factor is that studies employ diverse methods and operate on distinct underlying assumptions.…”

Section: Assessing the Scale Of The Rebound Effectmentioning

confidence: 99%

The “energy rebound effect” within the framework of environmental sustainability

Özsoy

2024

WIREs Energy & Environment

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The energy rebound effect, characterized by increasing energy use despite enhanced efficiency, has emerged as a complex interdisciplinary topic in the literature, reflecting its significance in both production and consumption sustainability. Recognizing the pivotal role of academic research in shaping energy management strategies and policies, this study conducted a comprehensive bibliometric review, accessing 530 articles from major citation indexes. This analysis provides insights into the evolution of the energy rebound field and potential future directions. Understanding the existing literature on the rebound effect serves as a valuable foundation for forthcoming research endeavors, addressing the intricate challenge of reconciling energy efficiency with sustainable energy consumption and production. The review explores the extensive literature on the energy rebound effect, highlighting a predominant focus on residential (e.g., cooling, heating, lighting, transportation) and industrial energy consumption in the majority of studies. Empirical applications primarily emphasize the measurement of the energy rebound effect, with a notable trend of increasing research concentration in China in recent years. Additionally, there is a growing body of economy‐wide analyses in this field. However, the literature exhibits complexity in both the analyses conducted and the methods employed for measuring the rebound effect. Research gaps are apparent, numerous studies tend to concentrate solely on the rebound effect at the overall energy consumption level, neglecting variations in energy types and the behavioral patterns of economic actors. Furthermore, despite consistent findings of a higher rebound effect in developing nations, there is a noticeable lack of scholarly literature addressing this issue about these countries.This article is categorized under: Sustainable Energy > Energy Efficiency Human and Social Dimensions > Behavioral Science Policy and Economics > Governance and Regulation

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“…The data includes firm-specific capital gross investments, which enabled us to create a firm-specific capital stock by applying the perpetual inventory method (Berndt 1991). 9 Specifically, we compute the capital stock at time t as K it = I it + (1 − θ)K it−1 where K it denotes capital at time t, I it denotes gross investments in inventories and machinery, and θ is the depreciation rate which we, following Dahlqvist et al (2021), assume to be 0.087. Statistics Sweden also provided data on an investment good price index and a long-term interest rate, both at the national level, together with a sector-specific Producer Price Index (the output price), which are used to calculate the user cost of capital as follows: p K = p I /p Y (r + δ) where p I and p Y denote the investment good price index and the output price (sectorspecific Producer Price Index), respectively, r denotes the long-term market capital interest rate and θ = 0.087 the depreciation rate as before.…”

Section: Datamentioning

confidence: 99%

Efficiency in electricity distribution in Sweden and the effects of small-scale generation, electric vehicles and dynamic tariffs

Lundgren,

Vesterberg

2024

J Prod Anal

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We measure the cost of technical inefficiency for local electricity distribution firms in Sweden using Stochastic Frontier Analysis, and explore how small-scale generation, the number of electric vehicles and the introduction of dynamic pricing schemes affects the transient inefficiency and efficiency scores. Our results show little to no effect of these environmental variables on the cost of technical inefficiency of electricity distribution grids in Sweden.

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The Rebound Effect in Energy-Intensive Industries:A Factor Demand Model with Asymmetric Price Response

Cited by 13 publications

References 45 publications

Time-Frequency Spillovers and the Determinants among Fossil Energy, Clean Energy and Metal Markets

Time-Frequency Spillovers and the Determinants among Fossil Energy, Clean Energy and Metal Markets

The “energy rebound effect” within the framework of environmental sustainability

Efficiency in electricity distribution in Sweden and the effects of small-scale generation, electric vehicles and dynamic tariffs

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