Siberia's fuel-energy complex
In: Problems of economics: selected articles from Soviet economics journals in English translation, Band 26, S. 15-24
ISSN: 0032-9436
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In: Problems of economics: selected articles from Soviet economics journals in English translation, Band 26, S. 15-24
ISSN: 0032-9436
International audience ; The residential energy demand is growing steadily and the trend is expected to continue in the near future. At the same time, under the impulse of economic crises and environmental and energy policies, many households have experienced reductions in real income and higher energy prices. In the residential sector, the number of fuel-poor households is thus expected to rise. A better understanding of the determinants of residential energy demand, in particular of the role of income and the sensitivity of households to changes in energy prices, is crucial in the context of recurrent debates on energy efficiency and fuel poverty. We propose a panel threshold regression (PTR) model to empirically test the sensitivity of French households to energy price fluctuations-as measured by the elasticity of residential heating energy prices-and to analyze the overlap between their income and fuel poverty profiles. The PTR model allows to test for the non-linear effect of income on the reactions of households to fluctuations in energy prices. Thus, it can identify specific regimes differing by their level of estimated price elasticities. Each regime represents an elasticity-homogeneous group of households. The number of these regimes is determined based on an endogenously PTR-fixed income threshold. Thereafter, we analyze the composition of the regimes (i.e. groups) to locate the dominant proportion of fuel-poor households and analyse their monetary poverty characteristics. Results show that, depending on the income level, we can identify two groups of households that react differently to residential energy price fluctuations and that fuel-poor households belong mostly to the group of households with the highest elasticity. By extension, results also show that income poverty does not necessarily mean fuel poverty. In terms of public policy, we suggest focusing on income heterogeneity by considering different groups of households separately when defining energy efficiency measures. We also suggest paying particular attention to targeting fuel-poor households by examining the overlap between fuel and income poverty.
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International audience ; The residential energy demand is growing steadily and the trend is expected to continue in the near future. At the same time, under the impulse of economic crises and environmental and energy policies, many households have experienced reductions in real income and higher energy prices. In the residential sector, the number of fuel-poor households is thus expected to rise. A better understanding of the determinants of residential energy demand, in particular of the role of income and the sensitivity of households to changes in energy prices, is crucial in the context of recurrent debates on energy efficiency and fuel poverty. We propose a panel threshold regression (PTR) model to empirically test the sensitivity of French households to energy price fluctuations-as measured by the elasticity of residential heating energy prices-and to analyze the overlap between their income and fuel poverty profiles. The PTR model allows to test for the non-linear effect of income on the reactions of households to fluctuations in energy prices. Thus, it can identify specific regimes differing by their level of estimated price elasticities. Each regime represents an elasticity-homogeneous group of households. The number of these regimes is determined based on an endogenously PTR-fixed income threshold. Thereafter, we analyze the composition of the regimes (i.e. groups) to locate the dominant proportion of fuel-poor households and analyse their monetary poverty characteristics. Results show that, depending on the income level, we can identify two groups of households that react differently to residential energy price fluctuations and that fuel-poor households belong mostly to the group of households with the highest elasticity. By extension, results also show that income poverty does not necessarily mean fuel poverty. In terms of public policy, we suggest focusing on income heterogeneity by considering different groups of households separately when defining energy efficiency measures. We also suggest paying particular attention to targeting fuel-poor households by examining the overlap between fuel and income poverty.
BASE
International audience ; The residential energy demand is growing steadily and the trend is expected to continue in the near future. At the same time, under the impulse of economic crises and environmental and energy policies, many households have experienced reductions in real income and higher energy prices. In the residential sector, the number of fuel-poor households is thus expected to rise. A better understanding of the determinants of residential energy demand, in particular of the role of income and the sensitivity of households to changes in energy prices, is crucial in the context of recurrent debates on energy efficiency and fuel poverty. We propose a panel threshold regression (PTR) model to empirically test the sensitivity of French households to energy price fluctuations-as measured by the elasticity of residential heating energy prices-and to analyze the overlap between their income and fuel poverty profiles. The PTR model allows to test for the non-linear effect of income on the reactions of households to fluctuations in energy prices. Thus, it can identify specific regimes differing by their level of estimated price elasticities. Each regime represents an elasticity-homogeneous group of households. The number of these regimes is determined based on an endogenously PTR-fixed income threshold. Thereafter, we analyze the composition of the regimes (i.e. groups) to locate the dominant proportion of fuel-poor households and analyse their monetary poverty characteristics. Results show that, depending on the income level, we can identify two groups of households that react differently to residential energy price fluctuations and that fuel-poor households belong mostly to the group of households with the highest elasticity. By extension, results also show that income poverty does not necessarily mean fuel poverty. In terms of public policy, we suggest focusing on income heterogeneity by considering different groups of households separately when defining energy efficiency measures. We also suggest paying ...
BASE
International audience ; The residential energy demand is growing steadily and the trend is expected to continue in the near future. At the same time, under the impulse of economic crises and environmental and energy policies, many households have experienced reductions in real income and higher energy prices. In the residential sector, the number of fuel-poor households is thus expected to rise. A better understanding of the determinants of residential energy demand, in particular of the role of income and the sensitivity of households to changes in energy prices, is crucial in the context of recurrent debates on energy efficiency and fuel poverty. We propose a panel threshold regression (PTR) model to empirically test the sensitivity of French households to energy price fluctuations-as measured by the elasticity of residential heating energy prices-and to analyze the overlap between their income and fuel poverty profiles. The PTR model allows to test for the non-linear effect of income on the reactions of households to fluctuations in energy prices. Thus, it can identify specific regimes differing by their level of estimated price elasticities. Each regime represents an elasticity-homogeneous group of households. The number of these regimes is determined based on an endogenously PTR-fixed income threshold. Thereafter, we analyze the composition of the regimes (i.e. groups) to locate the dominant proportion of fuel-poor households and analyse their monetary poverty characteristics. Results show that, depending on the income level, we can identify two groups of households that react differently to residential energy price fluctuations and that fuel-poor households belong mostly to the group of households with the highest elasticity. By extension, results also show that income poverty does not necessarily mean fuel poverty. In terms of public policy, we suggest focusing on income heterogeneity by considering different groups of households separately when defining energy efficiency measures. We also suggest paying ...
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In: Current history: a journal of contemporary world affairs, Band 58, S. 330-336
ISSN: 0011-3530
In: Nami , H , Butera , G , Campion , N J B , Frandsen , H L & Hendriksen , P V 2021 , MarE-fuel: Energy efficiencies in synthesising green fuels and their expected cost, MarE-fuel project report 9/9-2021, DTU Energy . Technical University of Denmark .
Several replacement fuel to today's fossil based ship propulsion fuels have been addressed in MarEfuel. Key ones are; pyrolysis oil (blend in fuel), methanol and ammonia. These were singled out among many possible fuels from a preliminary analysis that indicated that they could play a key role in fulfilling the emission targets set politically and by the sector in the most cost effective manner. In the following they shall be treated in turn in some detail. Costs of several "blue" fuels have also been assessed. The projected costs are used in other parts of the MarEfuel project (e.g. for assessing the total cost of ownership).
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In: The Palgrave Handbook of the International Political Economy of Energy, S. 641-660
In: Problems of economics, Band 26, Heft 5, S. 15-24
In: Transportation research record no. 2572
In: The current digest of the Soviet press: publ. each week by The Joint Committee on Slavic Studies, Band 27, S. 7-9
ISSN: 0011-3425
Authors consider possible development ways of the Russia coal industry. Researchers recognize that the world economic crisis had an essential negative impact on the coal industry in general. Research relevance consists in resource analysis of the East Donbass coal basin, whose social and economic situation represents a particular interest in connection with a political situation in the Ukraine border regions, in the Donetsk national republic. East Donbass (160 billion t) is in the west of the Rostov region. Basin coals, as well as in the main Donbass have high quality. The predominant energy, anthracite coal with a high calorific value, there are almost no coking coal. The small power of layers (the majority from several centimeters to 1 m), a deep water of development (on average 350 m, the greatest - over 1000 m) do an expensive coal rather. The coal industry state and development are defined by the following factors: size of mineral reserves; coal quality; mining-and-geological conditions; mine fund; scientific-technical progress; working conditions; economic factors. DOI:10.5901/mjss.2015.v6n3s6p329
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In: Journal of policy analysis and management: the journal of the Association for Public Policy Analysis and Management, Band 3, Heft 1, S. 141
ISSN: 1520-6688
In: The Australian economic review, Band 55, Heft 4, S. 503-514
ISSN: 1467-8462
AbstractThe Ukraine war has increased coal and gas prices during 2022. Consequently, spot prices in Australia's National Electricity Market rose from $75 to $225/MWh, year‐on‐year. Households are shielded from spot prices, but as energy retailer hedge contracts mature, they are replaced by higher cost contracts, and end‐use retail tariffs will then rise. In this article, fuel poverty levels in Queensland are analysed. Model results forecast that fuel poverty rises from 6.8 per cent to 10.5 per cent of households. However, changes to energy concessions policy in 2016‒2017 materially enhanced horizontal and vertical efficiency, with successful targeting rising from 51 per cent to 69 per cent of vulnerable households.