Contribution of price/expenditure factors of residential energy consumption in China from 1993 to 2011: A decomposition analysis

2015 ◽  
Vol 98 ◽  
pp. 401-410 ◽  
Author(s):  
Zengming Liu ◽  
Tao Zhao
Keyword(s):  
Energy Consumption ◽  
Decomposition Analysis ◽  
Residential Energy ◽  
Residential Energy Consumption

scholarly journals Spatiotemporal Patterns and Influencing Mechanism of Urban Residential Energy Consumption in China

Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3864
Author(s):  
Qiucheng Li ◽  
Jiang Hu ◽  
Bolin Yu
Keyword(s):  
Energy Consumption ◽  
Energy Use ◽  
Decomposition Analysis ◽  
Theil Index ◽  
Residential Energy ◽  
Residential Energy Consumption ◽  
Index Method ◽  
Inequality Measures ◽  
Influencing Mechanism ◽  
Per Capita

The residential sector has become the second largest energy consumer in China. Urban residential energy consumption (URE) in China is growing rapidly in the process of urbanization. This paper aims to reveal the spatiotemporal dynamic evolution and influencing mechanism of URE in China. The spatiotemporal heterogeneity of URE during 2007–2018 is explored through Kernel density estimation and inequality measures (i.e., Gini coefficient, Theil index, and mean logarithmic deviation). Then, with several advantages over traditional index decomposition analysis approaches, the Generalized Divisia Index Method (GDIM) decomposition is employed to investigate the impacts of eight driving factors on URE. Furthermore, the national and provincial decoupling relationships between URE and residential income increase are studied. It is found that different provinces’ URE present a significant agglomeration effect; the interprovincial inequality in URE increases and then decreases during the study period. The GDIM decomposition results indicate the income effect is the main positive factor driving URE. Besides, urban population, residential area, per capita energy use, and per unit area energy consumption positively influence URE. By contrast, per capita income, energy intensity, and residential density have negative effects on URE. There is evidence that only three decoupling states, i.e., weak decoupling, strong decoupling, and expansive negative decoupling, appear in China during 2007–2018. Specifically, weak decoupling is the dominant state among different regions. Finally, some suggestions are given to speed up the construction of energy-saving cities and promote the decoupling process of residential energy consumption in China. This paper fills some research gaps in urban residential energy research and is important for China’s policymakers.

scholarly journals Analysis of the EU Residential Energy Consumption: Trends and Determinants

Energies ◽  
2019 ◽  
Vol 12 (6) ◽  
pp. 1065 ◽  
Author(s):  
Sofia Tsemekidi Tzeiranaki ◽  
Paolo Bertoldi ◽  
Francesca Diluiso ◽  
Luca Castellazzi ◽  
Marina Economidou ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Complex Dynamics ◽  
Decomposition Analysis ◽  
Weather Conditions ◽  
The European Union ◽  
Residential Energy ◽  
Residential Energy Consumption ◽  
The Impact ◽  
The Eu

This article analyses the status and trends of the European Union (EU) residential energy consumption in light of the energy consumption targets set by the EU 2020 and 2030 energy and climate strategies. It assesses the energy efficiency progress from 2000 to 2016, using the official Eurostat data. In 2016, the residential energy consumption amounted to 25.71% of the EU’s final energy consumption, representing the second largest consuming sector after transport. Consumption-related data are discussed together with data on some main energy efficiency policies and energy consumption determinants, such as economic and population growth, weather conditions, and household and building characteristics. Indicators are identified to show the impact of specific determinants on energy consumption and a new indicator is proposed, drawing a closer link between energy trends and policy and technological changes in the sector. The analysis of these determinants highlights the complex dynamics behind the demand of energy in the residential sector. Decomposition analysis is carried out using the Logarithmic Mean Divisia Index technique to provide a more complete picture of the impact of various determinants (population, wealth, intensity, and weather) on the latest EU-28 residential energy consumption trends. The article provides a better understanding of the EU residential energy consumption, its drivers, the impact of current policies, and recommendations on future policies.

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