Determinants Of Household Energy Consumption Research Articles

Investigating the determinants of household energy consumption in Nigeria: insights and implications

BackgroundThe present study draws motivation from the United Nations Sustainable Development Goals and explores the nexus between access to modern cooking energy sources, responsible energy consumption, climate change mitigation, and economic growth. Using 2018 demographic and health survey data, the study examines the influence of key socioeconomic and demographic factors on household choice of cooking energy in Nigeria.ResultsThe empirical results show that traditional energy sources are dominant among Nigerian households (74.24%) compared to modern energy sources (25.76%). Regarding energy demographics, male-headed households show more usage of modern energy sources (19.86%) compared to female-headed households (5.90%). Regional analysis reveals that the northwest region predominantly uses traditional energy sources (18.60% of the share of total traditional energy sources), while the southwest region shows the greatest usage of modern energy sources (10.52% of the share of total modern energy sources). Binary logistic regression analysis reveals the positive and statistically significant influence of wealth index, education, and geopolitical region on the likelihood of utilizing modern energy sources. Conversely, household size and place of residence indicate an inverse relationship with the likelihood of adopting modern energy sources.ConclusionsThese findings have important policy implications for energy efficiency, environmental sustainability, and improving the quality of life in Nigeria, which is currently plagued with significant energy poverty, especially in rural communities.

The structural changes and determinants of household energy choices and energy consumption in urban China: Addressing the role of building type

Understanding the energy use and choice behaviors in urban China is essential to curb its energy consumption and air pollutant emissions. Current energy consumption estimates for urban households in China rarely account for the effects of building types on energy choice behavior, thus may lead to biased policy implications. In this paper, we estimate the determinants of household energy consumption for different energy choice scenarios through the Seemingly Unrelated Regression (SUR) model, using urban household data. The empirical results show that household use of various energy carriers is driven by household income, fuel price, demographics, building attributes and lifestyles. Results show building types have a significant effect on household energy consumption behaviors. Households living in old houses have less access to clean energy, such as piped gas. Income and price elasticities of energy consumption vary with energy type in each scenario, and there exist certain substitution effects among different types of energy carriers. In particular, inter-fuel substitute elasticities between coal and clean energy are asymmetric. Our study highlights the significance of city planning and infrastructure expansion policies and also offers a better basis for coordinating and designing energy policies in urban China and other developing countries.

Daily Habits and Energy Consumption: Go to Bed Earlier for Environmental Protection

Energy consumption reduction in the residential sector is crucial for mitigating global warming. This has prompted researchers to investigate the determinants of household energy consumption from various aspects. However, previous studies have not examined the impact of time allocation on energy consumption, primarily because of the lack of surveys that simultaneously examine time allocation and energy consumption. We conducted an original survey of 547 Japanese households to examine whether time allocation affects their electricity consumption. We divided a 48-hour period into 192 time slots and asked the households to choose one of the 20 types of actions listed for each slot. We also collected information on the socioeconomic background and electricity consumption of the households. After controlling for various factors that affect household electricity consumption, we examined whether time allocation determines electricity consumption. The empirical result of our study revealed that while a married male’s bedtime does not affect electricity consumption, a married female’s bedtime does. This suggests that it is essential to understand the daily habits of consumers for proposing effective energy conservation measures.Keywords: Electricity Usage, Household, Time Allocation

Local and national determinants of household energy consumption in the Netherlands

The policies of Third National Energy Efficiency Action Plan for the Netherlands, regarding the reduction of household energy consumption (HEC), were made based on the unwritten presumption that the stimuli of HEC are similar in each and every location of the Netherlands, and that it therefore is possible to formulate an identical set of incentives and regulations that are optimally suitable in all the locations of the country. The objective of this study is to examine the validity of this presumption by formulating two research questions: what are the national determinants of HEC, i.e. the stimuli that trigger the same response across the whole country? What are the local determinants of HEC, i.e. the stimuli which trigger different responses across the country? To identify local and national determinants of HEC, the impact of nine determinants of HEC in 2 462 neighbourhoods of the Netherlands is assessed by employing the geographical variability test. The results show that two of the determinants are national: (1) the number of frost-days, (2) wind speed. The results indicate that seven of the determinants are local: (1) income, (2) household size, (3) building age, (4) surface-to-volume ratio, (5) population density, (6) number of summer days, and (7) land surface temperature. By employing a semi-parametric geographically weighted regression analysis, the impact of the local and global determinants of HEC is estimated and mapped.

An econometric analysis of domestic fuel consumption in Ghana: Implications for poverty reduction

The study looks at the determinants of household energy consumption and how that relates to general poverty and energy poverty. It extends the Multidimensional Energy Poverty Index (MEPI) by estimating the rural-urban differentials in MEPI. The study employed multinomial logistic regression on household adoption of energy for cooking and lighting. The Ghana Demographic and Health Survey—GDHS 2014 data were used for the regression and three waves (2003, 2008 and 2014) of the data were used to estimate the MEPI as well as the rural-urban contributions to the MEPI over time. The paper provides empirical insights that household energy consumption is affected by socioeconomic variables and rural households are more deprived than urban households in terms of access to and use of modern energy. The most popular energy for cooking is wood and main electricity is the most popular energy for lighting. The wealth status of household, nature of residence (rural or urban) and the size of the household are key socioeconomic variables that affect energy consumption. An estimation of the MEPI showed that it has been declining from a severely deprived energy poverty rate in 2003 to a moderately deprived energy poverty rate in 2014. Also, rural homes (57%) are more energy poor than urban (43%) households. The study includes implications for the provision of clean and better energy sources for household consumption policies. This study fulfills an identified need to look at general poverty in relation to energy poverty and to look at the rural-urban differentials in energy consumption.

Local determinants of household gas and electricity consumption in Randstad region, Netherlands: application of geographically weighted regression

The previous studies on household energy consumption (HEC) are based on an implicit assumption: the impact of geographic determinants on HEC is uniform across a given region, and such impacts could be unveiled regardless of geographic location of households in question. Consequently, these studies have searched for global determinants which explain HEC of all areas. This study aim at examining validity of this assumption in Randstad region by putting forward a question regarding households’ gas and electricity consumption: are the determinants global, stationary across all the areas of the region, or local, varying from one location to another? By application of geographically weighted regression, impact of socioeconomic, housing, land cover and morphological indicators on HEC is studied. It is established that the determinants of HEC are local. This result led to second question: what are the main determinants of gas and electricity consumption in different neighborhoods of Randstad? The results show that variety of factors could be the most effective determinant of gas consumption in different neighborhoods: building age, household size and inhabitants’ age, inhabitants’ income and private housing tenure, building compactness. Whereas, in case of electricity consumption the picture is more deterministic: in most of the neighborhoods the most effective factors are inhabitants’ income and private tenure.

Households energy consumption and transition toward cleaner energy sources

The paper investigates the factors influencing households’ energy choices, and the drivers of switching toward cleaner energy. We first present a theoretical framework to determine the factors that explain households’ energy consumption and highlight the motivations underlying their transition towards less polluting sources, including their environmental preference. Using French household data from ADEME, we provide an econometric test of qualitative variables following studies by Dubin and McFadden (1984). Our results show that income and prices are the main determinants of household energy consumption. Environmental considerations seem to influence the choice of energy sources more than consumption. We also find evidence that income and relative capital cost are the most important variables for household energy switching.

An economic model for residential energy consumption, generation, storage and reliance on cleaner energy

Economic models that provide a framework for understanding determinants of household energy consumption and the rate of reliance on cleaner energy are not available, despite the growing number of residential solar houses. This study presents a theoretical framework for understanding the relationship between energy consumption, generation, storage and the reliance on cleaner energy. Our findings suggest that, (i) households which generate energy could consume more energy than households which do not generate energy, (ii) the economically optimal reliance on solar energy depends on energy prices, income and the slope of the marginal energy storage cost, (iii) there is no relationship between reliance on cleaner energy (or energy demand) and the efficiency level of energy-conversion technologies, and (iv) when buy-back rates are equal to the retail rate of electricity, reliance on generated energy could be zero and energy demand of a generating household may be identical to its non-generating counterpart.

The role of risk and trust attitudes in explaining residential energy demand: Evidence from the United Kingdom

Recent research into the determinants of household energy consumption has aimed to incorporate findings from economics, sociology and psychology in order to obtain a more comprehensive understanding of the factors determining energy demand. The current paper contributes to this nascent stream of literature by studying the relationship between risk attitudes, trust propensity and energy consumption at the household level. Drawing on the British Household Panel Survey, a well-known data set in the context of energy studies, I show that trust is negatively correlated with household energy demand, while higher risk tolerance leads to increases in residential energy use. Potential explanations for these findings are investigated, suggesting that risk preferences may be related with overall appliance stock and the size of the rebound effect.

Understanding the spectrum of domestic energy consumption: Empirical evidence from France

This article focuses on residential energy consumption in France. Using a bottom-up statistical approach, this analysis explores determinants of household energy consumption using data from the most recent National Housing Survey. The primary objective is to tease out the impacts of various factors on the domestic energy consumption spectrum across different population groups. The aim of this approach is to neutralize conventional factors affecting energy consumption (age of house, total area, etc.) to finely analyze the impact of other determinants including those relating to household characteristics and other control variables.First, we define homogeneous consumption groups of households by using multivariate statistical techniques, namely the Multiple Correspondence Analysis and Ascending Hierarchical Classification. Second, we use standard OLS regression to explore the effects of various factors on domestic energy consumption among homogeneous groups of households. This multivariate analysis exercise has led us to identify four main consumption typologies. Results revealed that energy prices were the most important factors determining domestic energy consumption. In addition, this study showed that occupant characteristics significantly affect domestic energy use. Results of this research call for combine all efforts, multiple strategies and smart policies, to incorporate household and consumption behaviors in managing domestic energy consumption.

Emisiones de CO2 en hogares urbanos. El caso del Distrito Federal

La intensificación de la actividad humana en el ámbito productivo y el quehacer cotidiano ha generado un aumento significativo en la emisión de gases de efecto invernadero, conduciendo al cambio climático o calentamiento global; este fenómeno de origen antropogénico ha sido estudiado desde diversas perspectivas, entre ellas el análisis con enfoque microsocial. Atendiendo a ello, en este trabajo se estudian los principales determinantes del consumo de energía en los hogares y se estima un proxy del volumen de emisiones de dióxido de carbono asociado, usando datos de la Encuesta Nacional de Ingresos y Gastos de los Hogares para el Distrito Federal

An analysis of monthly household energy consumption among single-family residences in Texas, 2010

Demographic, socioeconomic, and housing characteristics influence variation in household energy consumption. By combining household-level utility, public, and proprietary data, we examine predictors of household energy consumption in a Texas urban area. Using quantile regression, this analysis assesses the relationship between energy consumption and predictors at the middle and both ends of the distribution (10th and 90th percentiles). Results indicate potential opportunities to lower consumption among the highest energy-consuming households including those with pools, with non-central cooling, with people working from home, those built on pier/post foundation, and those that are renter-occupied. These findings suggest significant opportunities to reduce consumption and demand as in the study area, almost 10% of housing units are renter-occupied, 18% percent are without central cooling, and 7% have pools. Capturing a significant portion of these homes for retrofit conservation efforts through marketing has potential to produce substantial results. Producing a better understanding of determinants of household energy consumption using the methods presented has potential to assist development and implementation of strategies to reduce consumption and increase efficiency.

Determinants of household energy consumption in India

Improving access to affordable modern energy is critical to improving living standards in the developing world. Rural households in India, in particular, are almost entirely reliant on traditional biomass for their basic cooking energy needs. This has adverse effects on their health and productivity, and also causes environmental degradation. This study presents a new generic modelling approach, with a focus on cooking fuel choices, and explores response strategies for energy poverty eradication in India. The modelling approach analyzes the determinants of fuel consumption choices for heterogeneous household groups, incorporating the effect of income distributions and traditionally more intangible factors such as preferences and private discount rates. The methodology is used to develop alternate future scenarios that explore how different policy mechanisms such as fuel subsidies and micro-financing can enhance the diffusion of modern, more efficient, energy sources in India.