Single Equation Models for the Projection of Energy Demand in the United Kingdom 1954‐80*

Westoby, Richard; Pearce, David

doi:10.1111/j.1467-9485.1984.tb00476.x

Cited by 10 publications

(6 citation statements)

References 15 publications

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“…Consequently a simple log-linear model for price and income incorporating a lag term to account for the dynamic adjustment is employed. The use of a lagged term overcomes the potential model breakdown in periods of unstable energy prices (Westoby and Pearce, 1984). The model postulated by Pindyck (1979) has been used in many estimations of income and price elasticity of oil (e.g., Dargary, 1992 Huntington, 2002;Cooper, 2003).…”

Section: Methodological Advancementsmentioning

confidence: 99%

Price volatility and demand for oil: A comparative analysis of developed and developing countries

Jobling

Jamasb

2017

Economic Analysis and Policy

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Section: Methodological Advancementsmentioning

confidence: 99%

Price volatility and demand for oil: A comparative analysis of developed and developing countries

Jobling

Jamasb

2017

Economic Analysis and Policy

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“…[Bhattacharyya and Timilsina, 2009]. In the 1980s, simplified methods of energy demand forecasting had been documented in numerous countries, including reliance on energy intensities or an elasticity of energy demand with respect to national income or GDP [Westoby and Pearce, 1984;Codoni et al, 1985]. For example, simple measures of GDP elasticity and energy intensities have been used to forecast energy demand and develop energy policies in China and India [GOI, 2006;Berrah et al, 2007].…”

Section: Evolution and Challenges Of Forecasting Energy Marketsmentioning

confidence: 99%

Evolution of Forecasting Techniques for Dynamic Energy Markets

Carey¹,

Eryilmaz²

2020

Handbook of Energy Finance

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We are in a very dynamic period in our domestic and global energy markets. Market forces are at work in both the shale oil and gas revolution and the development of renewable energy, which are dramatically impacting the energy industry. Transformation of global energy markets highlights the importance of understanding various forecasting methods and technical methods to accurately forecast in such a dynamic market structure. This chapter provides a comprehensive review of the forecasting techniques for energy markets and illustrates them through a case study. This chapter can potentially be utilized by academics and industry practitioners for understanding the evolution of the energy market dynamics.

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“…Grover & Chandra [7] stated that the simple approaches are also applied by Indian state agencies, where the income elasticity is used to forecast primary energy and electricity demand. Although the simple approach is appealing due to its ease of use, it could not explain the driver of changes and relies highly on the subjective judgements of the modeller [4,29].…”

Section: Review Of Literaturementioning

confidence: 99%

Modelling Energy Consumption of the Republic of Serbia using Linear Regression and Artificial Neural Network Technique

2019

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The objectives of the study are twofold. First, we aim to examine the most influential socio-economic indicators to explain energy consumption in Republic of Serbia. The second objective is to develop models that are able to predict the future energy consumption in the Republic of Serbia. This could be the first important step towards proper energy management in the country. Several potential socio-economic indicators are selected to be the independent variables. Regression analysis is conducted to select the most relevant independent variables as well as building the multiple linear regression (MLR) models. In addition, an artificial neural networks (ANN) model is developed as a comparison. Finally, the energy demand is projected to the year 2022. It is found that both models show the declining trend with respect to the current level of energy consumption.

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Single Equation Models for the Projection of Energy Demand in the United Kingdom 1954‐80*

Cited by 10 publications

References 15 publications

Price volatility and demand for oil: A comparative analysis of developed and developing countries

Price volatility and demand for oil: A comparative analysis of developed and developing countries

Evolution of Forecasting Techniques for Dynamic Energy Markets

Modelling Energy Consumption of the Republic of Serbia using Linear Regression and Artificial Neural Network Technique

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