Energy poverty indicators

2019 ◽  
pp. 127-141
Author(s):  
Ivan Faiella ◽  
Luciano Lavecchia
Keyword(s):  
Energy Poverty ◽  
Poverty Indicators

scholarly journals Expenditure-Based Indicators of Energy Poverty—An Analysis of Income and Expenditure Elasticities

Energies ◽  
2020 ◽  
Vol 14 (1) ◽  
pp. 8
Author(s):  
Johannes Thema ◽  
Florin Vondung
Keyword(s):  
Energy Expenditure ◽  
Micro Data ◽  
European Union Policy ◽  
Energy Poverty ◽  
Union Policy ◽  
Depth Sensitivity ◽  
Policy Agendas ◽  
Poverty Indicators ◽  
Specific Country ◽  
The Eu

Energy poverty is high up on national and European Union policy agendas. A number of possible indicators to measure the issue have been identified in the literature, but comparable data with European coverage is scarce. The EU Commission thus proposes four independent indicators on the “EU Energy Poverty Observatory” based on self-reported items from the pan-European surveys on income and living conditions (SILC) and household budgets (HBS). It is of increasing public interest to analyse social impacts of energy policies, and quantify energy poverty indicators also from modelling. This paper first shortly outlines how the expenditure-based indicators using HBS micro data may be directly linked to existing macroeconomic models through their defining variables (energy expenditure and income). As endogenous modelling based on micro data is difficult, the link may be country-specific elasticities. The main contribution of the paper is a systematic in-depth sensitivity analysis of the two indicators to changes in income and energy expenditure following varying patterns in the underlying distributions of the micro data. The results may be used by future soft links to models. The results display sometimes counterintuitive effects. We find that whether these indicators increase/decrease after a change of income or energy expenditure largely depends on the specific country-wise income and energy expenditure distribution between households on a micro-level. Due to their definition, the examined indicators are especially sensitive, when income changes alter the indicator threshold values, which in these cases are the median values in underlying distributions. We discuss these findings and relate them to several indicator shortcomings and potential remedies through changes in indicator definition.

Energy poverty indicators: Inconsistencies, implications and where next?

2021 ◽  
Vol 103 ◽  
pp. 105551
Author(s):  
David Deller ◽  
Glen Turner ◽  
Catherine Waddams Price
Keyword(s):  
Energy Poverty ◽  
Poverty Indicators

Energy poverty indicators: A systematic literature review and comprehensive analysis of integrity

2021 ◽  
Vol 67 ◽  
pp. 102756
Author(s):  
Indre Siksnelyte-Butkiene ◽  
Dalia Streimikiene ◽  
Vidas Lekavicius ◽  
Tomas Balezentis
Keyword(s):  
Literature Review ◽  
Systematic Literature Review ◽  
Comprehensive Analysis ◽  
Energy Poverty ◽  
Poverty Indicators

The policy implications of energy poverty indicators

Energy Policy ◽  
2018 ◽  
Vol 115 ◽  
pp. 98-108 ◽  
Author(s):  
José Carlos Romero ◽  
Pedro Linares ◽  
Xiral López
Keyword(s):  
Policy Implications ◽  
Energy Poverty ◽  
Poverty Indicators

Measuring the Energy Poverty and the Accuracy in Korea

2019 ◽  
Vol 27 (4) ◽  
pp. 41-74
Author(s):  
Hahyun Jo ◽  
Hyungwoo Lim ◽  
Haedong Kim
Keyword(s):  
Energy Poverty

Green Sukuk, Energy Poverty, and Climate Change: A Roadmap for Sub-Saharan Africa

2018 ◽  
Author(s):  
Dalal Aassouli ◽  
Mehmet Asutay ◽  
Mahmoud Mohieldin ◽  
Tochukwu Chiara Nwokike
Keyword(s):  
Climate Change ◽  
Sub Saharan Africa ◽  
Energy Poverty ◽  
Sub Saharan

Comparative Assessment of Poverty Indicators in the European Part of the CIS and the European Union as a Social Criterion of Economic Security

2020 ◽  
Vol 26 (9) ◽  
pp. 924-939
Author(s):  
V. A. Tsvetkov ◽  
K. Kh. Zoidov ◽  
K. S. Yankauskas ◽  
Sh. Kobil
Keyword(s):  
European Union ◽  
Comparative Analysis ◽  
Poverty Reduction ◽  
Economic Security ◽  
Actual State ◽  
The European Union ◽  
Poverty Dynamics ◽  
Subsistence Level ◽  
Strategic Objectives ◽  
Poverty Indicators

The presented study comparatively analyzes indicators of the level of poverty and social inequality in Belarus, Ukraine, Moldova, and the European Union (EU) as a criterion of national economic security.Aim. The study aims to examine existing approaches to determining the level of poverty and its dynamics and to consider suggestions for improving this methodology.Tasks. The authors examine and comparatively analyze approaches and methods for determining the level of poverty and its dynamics in the European Union and the CIS countries that are not members of the Eurasian Economic Union (EAEU).Methods. This study uses the methods of systems analysis, evolutionary-institutional theory, and historical approach.Results. Determining the level of poverty based on the number of citizens with incomes below the subsistence level can lead to misrepresentation of the actual state of this phenomenon. Calculation of poverty indicators based on consumer spending provides more accurate data on the level of poverty in a country where a significant share of the population’s income is generated by remittances from individuals living abroad, which are not reflected in official income statistics. A comparative analysis of poverty dynamics shows that in 2013 the level of poverty in all four examined countries decreased compared to 2006. Poverty dynamics in Russia and Belarus is more synchronized than in Ukraine and Moldova. A common methodology for calculating the level of poverty in all EU countries makes it possible to conduct a more thorough comparative analysis of poverty dynamics and to formulate more accurate recommendations in the field of anti-poverty policies. Based on the identified poverty dynamics in the EU and Russia, it is highly possible that strategic objectives on poverty reduction in the European Union and Russia will not be completed.Conclusions. To exclude the possibility of interested authorities influencing the dynamics of the poverty indicator by changing its threshold values depending on the current economic or political situation, it is necessary to switch to comprehensive assessment of this indicator in Russia. For comparative cross-country data analysis, it is advisable to consider the possibility of creating a Eurasian Statistics Service within the EAEU that would collect statistics and standardize statistical methods among the EAEU member states.

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