Assessing energy price induced improvements in efficiency of capital in OECD manufacturing industries

Steinbuks, Jevgenijs; Neuhoff, Karsten

doi:10.1016/j.jeem.2014.07.003

Cited by 58 publications

(9 citation statements)

References 65 publications

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“…The use of the translog functional form in this literature is well-established. Earlier papers that employ this functional form include Halvorsen (1977) and Hall (1986), while more recent examples include Steinbuks and Neuhoff (2014) and Bardazzi et al (2015).…”

Section: Factor and Fuel Elasticities Of Substitutionmentioning

confidence: 99%

Firm-level Estimates of Fuel Substitution: An Application toCarbon Pricing

Hyland¹,

Haller²

2018

The Energy Journal

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We estimate partial-and total-fuel substitution elasticities between electricity, gas and oil, using firm-level data. We find that, based on the partial elasticity measure, electricity is the least-responsive fuel to changes in its own price and in the price of other fuels. The total elasticity measure, which adjusts the partial elasticity for changes in aggregate energy demand induced by individual fuel price changes, reveals that the demand for electricity is much more price responsive than the partial elasticity suggests. Our results illustrate the importance of accounting for the feedback effect between interfactor and interfuel substitution elasticities when considering the effectiveness of environmental taxation. We use the estimated elasticities to simulate the impact of a e15/tCO 2 carbon tax on average energyrelated CO 2 emissions. The carbon tax results in a small reduction in CO 2 emissions from oil and gas use, but this reduction is partially offset by an increase in emissions due to increased electricity consumption by some firms.

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Section: Factor and Fuel Elasticities Of Substitutionmentioning

confidence: 99%

Firm-level Estimates of Fuel Substitution: An Application toCarbon Pricing

Hyland¹,

Haller²

2018

The Energy Journal

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“…However, a related endogeneity issue could occur at the individual sector/firm level since some large industries/firms negotiate prices directly with regulators. Steinbuks and Neuhoff (2014) argued that this potential endogeneity is mitigated when one uses prices that are aggregated at the entire industry/manufacturing sector level (as we do).…”

Section: Model and Methodsmentioning

confidence: 95%

“…Energy efficiency improvements do affect energy demand. Indeed, there is a separate literature that aims to model the price-induced and autonomous improvements of the energy efficiency of capital stock (e.g., Sue Wing 2008;Steinbuks and Neuhoff 2014). However, this literature employs substantially different models, methods, and data than the present paper.…”

Section: Model and Methodsmentioning

confidence: 97%

Industry electricity price and output elasticities for high-income and middle-income countries

Liddle

Hasanov

2021

Empir Econ

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Energy planning and climate policy require understanding long-run energy demand patterns. Electricity demand further is important because energy services derived from electricity typically do not have substitution possibilities from other fuels. By employing dynamic panel models, we estimate the long-run price and output elasticities of aggregate industrial electricity demand for high-income (mostly OECD) and middle-income (mostly non-OECD) countries. The unbalanced data span 1978–2016 and include 35 high-income countries and 30 middle-income countries. Our dynamic panel estimates address nonstationarity, heterogeneity, and cross-sectional dependence. We believe these are the first such panel estimates for middle-income/non-OECD countries and among the few such estimates for high-income/OECD countries to appear in the literature. The output elasticity for high-income countries typically was significantly below unity, around 0.5, and the price elasticity was around − 0.25 (and was statistically significant). For middle-income countries, the output elasticity was greater than unity and was likely significantly larger than the output elasticity for high-income countries, whereas the price elasticity was small and insignificant for middle-income countries.

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“…Industrial energy demand, leading to 2030, is expected to increase at a rate of 1.3 per cent annually, primarily in emerging economies (IEA, 2015a). Decision making priorities differ significantly between the building and industry sectors where short-term energy prices for industries often have a large impact on energy efficiency decisions, particularly at the point of in-plant investment (Steinbuks and Neuhoff, 2014).…”

Section: Industrymentioning

confidence: 99%

Pre-2020 action: trends, progress and urgency

Fransen

Elzen

Kuramoch

et al. 2016

The Emissions Gap Report 2016

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The use of information from this document for publicity or advertising is not permitted. Trademark names and symbols are used in an editorial fashion with no intention on infringement of trademark or copyright laws.The views expressed in this publication are those of the authors and do not necessarily reflect the views of the United Nations Environment Programme. We regret any errors or omissions that may have been unwittingly made.

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Assessing energy price induced improvements in efficiency of capital in OECD manufacturing industries

Cited by 58 publications

References 65 publications

Firm-level Estimates of Fuel Substitution: An Application toCarbon Pricing

Firm-level Estimates of Fuel Substitution: An Application toCarbon Pricing

Industry electricity price and output elasticities for high-income and middle-income countries

Pre-2020 action: trends, progress and urgency

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