Dutch sectoral energy intensity developments in international perspective, 1987–2005

Mulder, Peter; Groot, H.L.F. de

doi:10.1016/j.enpol.2012.09.072

Cited by 14 publications

(4 citation statements)

References 44 publications

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“…Therefore, the empirical analysis should identify changes due exclusively to EE (i.e., the efficiency component) from other changes related to sectoral changes (i.e., the activity component). The Index Decomposition Analysis (IDA) is the methodology commonly used to separate out structural shifts in the economy from more fundamental improvements in the use of energy (see Metcalf, 2008;Mulder & De Groot, 2012;Marrero & Ramos-Real, 2013), among others). However, this approach is very dependent on the availability of sectoral energy demand and economic activity data, which can lead to unreliable decompositions (Alghandoor et al 2008;Zahur 2013;Grossi & Mussini 2017).…”

Section: Methodology: the Stochastic Frontier Analysismentioning

confidence: 99%

Energy Efficiency and Energy Governance: A Stochastic Frontier Analysis Approach

Marrero¹,

Ramos–Real²

2022

The Energy Journal

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This work analyzes the impact of energy governance on energy efficiency in a set of 29 OECD countries. A Stochastic Frontier Analysis (SFA) approach is conducted to estimate the energy efficiency levels in this sample of countries between 2000 and 2015. Energy governance is measured by an Energy Efficiency Governance Index (EEGI) constructed in Barrera-Santana et al. (2020). The results suggest that increasing the average quality of energy governance by 10% could raise energy efficiency levels by around 9.20%, according to the estimate of our preferred SFA model. To achieve this outcome there are two key requirements: set quantified and achievable targets, and carry out an extensive evaluation of the results of energy policies. Our results are robust to different econometric approaches and variations of the EEGI.

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Section: Methodology: the Stochastic Frontier Analysismentioning

confidence: 99%

Energy Efficiency and Energy Governance: A Stochastic Frontier Analysis Approach

Marrero¹,

Ramos–Real²

2022

The Energy Journal

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“…The modifications in energy intensity are contributed mostly in two ways: alterations in the manufacturing decomposition of an economy, and change in its energy manufacture intensities. In European countries, different studies [40][41][42][43][44] analyzed the decomposition and determines factors of energy intensity in various sectors such as residual, commercial, electricity, transportation, and manufacturing in European countries in recent decades [45][46][47][48][49][50].…”

Section: Empirical Backgroundmentioning

confidence: 99%

Bioenergy Intensity and Its Determinants in European Continental Countries: Evidence Using GMM Estimation

Alsaleh

Abdul‐Rahim

2019

Resources

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This study contributes to the existing literature by examining bioenergy intensity and its related factors in European continental countries (ECC). Through its focus on European continental (EC), this study extends the existing literature, which mainly covers nationwide studies. The current paper aims to investigate the variables of bioenergy intensity in the ECC during the term 2005–2013, construct its economic variables, and evaluate the volume and significance level of the impact of each variable on bioenergy intensity. To successfully achieve this analysis, a generalised method of moments estimator (GMM) was designed for ECC. The estimated models show that available bioenergy for final consumption has a positive impact on bioenergy intensity in ECC. The largest influence on bioenergy intensity was evaluated for the annual growth of Gross Domestic Product (GDP), followed by the investment and referral that the scale and construction of this economic variable should be taken into consideration and applied as a precious bioenergy regulation and policy instruments for developing bioenergy intensity and efficiency.

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“…This technique has recently been applied in works that analyse the evolution of energy consumption and energy efficiency in different countries, such as: Australia (Sandu and Petchey, 2009);China (Ma and Stern, 2008;Liao et al, 2007 andZhao et al, 2010); Greece (Hatzigeorgiou et al, 2011); Holland (Mulder and Groot, 2013); Lithuania (Balezentis et al, 2011); South Africa (InglesiLotz and Pouris, 2012); Turkey (Ediger and Huvaz, 2006); and the OECD (Mulder and Groot, 2012). However, this same technique has been used for the analysis of the energy consumption and efficiency of some specific economic sectors, as in the following works: the industrial sector (Cahill and Gallachóir, 2010;Salta et al, 2009;Bhattacharyya and Ussanarassamee, 2005); the transport sector (Zhang et al, 2011;Sorrell et al, 2009); the residential sector (Rogan et al, 2012); the services sector (Mairet and Decellas, 2009); the electricity sector (Inglesi-Lotz and Blignaut, 2011); and, the domestic sector (Hojjati and Wade, 2012).…”

Section: Methodsmentioning

confidence: 99%

LMDI decomposition analysis of energy consumption in Andalusia (Spain) during 2003–2012: the energy efficiency policy implications

Carmona

Collado

2015

Energy Efficiency

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ABSTRACT:The LMDI decomposition analysis of the evolution of the final energy consumption in Andalusia during the period 2003-2011, leads to the conclusion that the increase of final energy consumption (3%) produced in this period was due to economic growth (83.4%) and the decrease in energy efficiency (16.6%). Industry was the sector that most increased energy efficiency (1.9%), while that of the energy sector reduced by 2.6%.

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Dutch sectoral energy intensity developments in international perspective, 1987–2005

Cited by 14 publications

References 44 publications

Energy Efficiency and Energy Governance: A Stochastic Frontier Analysis Approach

Energy Efficiency and Energy Governance: A Stochastic Frontier Analysis Approach

Bioenergy Intensity and Its Determinants in European Continental Countries: Evidence Using GMM Estimation

LMDI decomposition analysis of energy consumption in Andalusia (Spain) during 2003–2012: the energy efficiency policy implications

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