Regional Evidence regarding U.S. Residential Electricity Consumption

Regional economic, demographic, and climatic data are used to analyze residential electricity demand in the United States. Results indicate that electricity is an inferior good for households in the United States. This confirms earlier research compiled using data for less geographically extensive regional and metropolitan markets. The results imply that demographic growth may place fewer pressures on electricity generation capacity than was previously assumed.Residential Electricity Demand, Regional Economics

Residential electricity consumption and economic growth in Algeria

Within the framework of the COP21 (Conference of the Parties) agreement, Algeria submitted its Intended Nationally Determined Contribution pledging to reduce carbon emissions by at least 7% by 2030. However, it will be a difficult task to reach this target as total final energy consumption has increased 32% from 2010 to 2014, with the major energy increases being related to electricity use in the residential sector. In this context, the relationship between residential electricity consumption and income is analyzed for Algeria in the period 1970–2013, by estimating a residential electricity consumption per capita demand function which depends on GDP per capita, its squared and cubed terms, the electricity prices, and the goods and services imports. An extended Autoregressive Distributed Lag model (ARDL) was adopted to consider the different growth patterns registered in the evolution of GDP. The estimate results show that the relationships between electricity use and GDP (in per capita terms) present an inverted N-shape, with the second turning point having been reached. Therefore, promoting growth in Algeria could be convenient to reduce the electricity consumption, as a higher income level may allow the use of more efficient appliances. Additionally, renewable energies may be adequate to increase the electricity production in order to cover the increasing residential demand.Junta de Andalucía proyecto SEJ-132Ministerio de Economía y Competitividad de España, Cátedra de Economía de la Energía y del Medio Ambiente (Cátedra de Energía y Economía Ambiental) ECO2014-56399-

Consumption-Driven Environmental Impact and Age Structure Change in OECD Countries

This paper examines two environmental impacts for which population has a substantial demonstrated influence: transport carbon emissions and residential electricity consumption. It takes as its starting point the STIRPAT framework and disaggregates population into four key age groups: 20-34, 35-49, 50-69, and 70 and older. Population age structure’s influence was significant and varied across cohorts, and its profile was different for two dependent variables. For transport, young adults (20-34) were intensive, whereas the other cohorts had negative coefficients. For residential electricity consumption, age structure had a U-shaped impact: the youngest and oldest had positive coefficients, while the middle cohorts had negative coefficients.demography, environment, FMOLS panel cointegration, GHG emissions projections, IPAT, STIRPAT

Examining the Feedback Response of Residential Electricity Consumption towards Changes in its determinants: Evidence from Malaysia

Residential electricity consumption in Malaysia is increasing rapidly and poses a threat to energy security. Therefore, it is very important to understand the way residential electricity consumption responds to its determinants so that effective measures to contain its rapid growth can be undertaken. The current study aims to examine the responsiveness of residential electricity consumption towards real disposable income, price of electricity, price of electrical appliances population and foreign direct investment in Malaysia for 1978-2013 period. Residential electricity consumption is only elastic towards real disposable income. The magnitude of own price elasticity is larger than cross elasticity of complements. The study shed some light on the responsiveness of residential electricity consumption, which can help Malaysia in developing new policies to control energy consumption without affecting economic growth adversely. Keywords: residential electricity consumption; complements; co-integration; elasticities; Malaysia. JEL Classifications: C32; N7; Q41; Q4

Short run and long run dynamics of residential electricity consumption: Homogeneous and heterogeneous panel estimations for OECD

The purpose of this paper is to reveal the short run and long run dynamics of residential electricity consumption for 11 OECD countries within annual period 1979-2006. To this end, this paper first explores the findings from related literature evidence and, later, follows panel cointegration equations (CEs) and panel error correction models (ECMs). CEs give long run relations of the variables in residential electricity demand function. ECMs include both long run and short run parameter estimates of the per capita residential electricity demand in terms of residential electricity price, residential light fuel oil price, residential natural gas price and per capita income. For both ECs and ECMs, the techniques of panel OLS, panel adjusted OLS and panel dynamic OLS are utilized. Finally, this paper yields short term and long term elasticities of residential electricity consumption together with error correction terms through homogeneous and heterogeneous variance structures.electricity consumption, elasticities, homogeneous and heterogeneous variance structures, panel error correction model, panel dynamic ordinary least squares

A system dynamics analysis of the growth in Virginia\u27s residential electricity consumption trends, 1980-2010.

Residential electricity consumption in the Commonwealth of Virginia has more than doubled in three decades, between 1980 and 2010. Per capita and per household consumption rates have grown faster than many other states including New York and California. The following dissertation applies systems dynamics methodology to explore the causes of growth in Virginia’s per capita and per household residential electricity consumption rates in relative contrast to New York and California over the past several decades. Major databases used in the study were accessed from the United States Energy Information Administration and the Census Bureau. Qualitative modelling applying system dynamics principles is used to understand the general dynamics that drive residential electricity consumption across U.S households. The extent to which these dynamics prevail in Virginia is then analyzed using the state’s historical data. Further comparative analysis with benchmark states of New York and California helps identify if those dynamics uniquely prevail in Virginia or are common across the benchmark states too. The study finds that a combination of economic and lifestyle factors among Virginia’s residents, compounded by a low-cost high-volume ‘business as usual’ strategy by the state’s power utility sector with negligible investments in demand side management efforts, have worked relentlessly to cause per capita and per household residential electricity consumption rates to rise in the Commonwealth during the three decades. The results of this study are intended to support in better management of residential electricity consumption rates in the Commonwealth of Virginia. Public educational programs, Government tax credits and rebates, and stronger utility demands side management are key recommendations in the interest of addressing the issue. A successful future reduction in consumption rates will help lessen pressures on the state’s economy as well as the environment

Determining the efficiency of residential electricity consumption

Increasing energy efficiency is a key global policy goal for climate protection. An important step toward an optimal reduction of energy consumption is the identification of energy saving potentials in different sectors and the best strategies for increasing efficiency. This paper analyzes these potentials in the household sector by estimating the degree of inefficiency in the use of electricity and its determinants. Using stochastic frontier analysis and disaggregated household data, we estimate an input requirement function and inefficiency on a sample of 2000 German households. Our results suggest that the mean inefficiency amounts to around 20%, indicating a notable potential for energy savings. Moreover, we find that household size and income are among the main determinants of individual inefficiency. This information can be used to increase the cost-efficiency of programs aimed to enhance energy efficiency

Analysing the Residential Electricity Consumption using Smart Meter

A massive amount of electricity usage may be accessed on an everyday and hourly basis due to the advancement of smart power measuring technology. Electricity demand management and utility load management are made easier by energy usage forecasts. The majority of earlier studies have concentrated on the power consumption of business clients or residential buildings, or they have experimented with individual household electricity usage using behavioral and occupant sensor information. This study used smart meters to examine energy usage at a single household level to enhance residential energy services and gather knowledge for developing demand response strategies.The power usage of various appliances in a single household is estimated, by utilizing Autoregressive Integrated Moving Average (ARIMA) modeling technique, which is applied to daily, weekly, and monthly information granularity. To select the household’s energy consumption dataset for this study, a multivariate time-series dataset describing the four-year electricity usage of a household is provided. The use of Exploratory Data Analysis (EDA) is utilizedfor the selection of features and data visualization. The correlation coefficients with the daily usage of the household have been computed for the characteristics prepared for the forecast. The top three major determinants with the top three positive significance are "temperature," "hour of the day," and "peak index." A single household's usage is inversely related to the variables having negative coefficients. It should be noticed that the correlations among a household's attributes with usage vary from one another. Finally, the power prediction is analyzed in a single household

Increase of Residential Electricity Consumption in Urban and Rural China by Province

We have developed a projection model to investigate the inter-regional and intra-regional urban-rural characteristics of the current residential electricity demand in China. We have specifically focused on residential electricity demand pertaining to three major appliances; refrigerator, color-TVs and air-conditioners for cooling. The model integrates factors such as population and income growth, and urban-rural disparity of individual factors are also reflected. The relationship between income growth and appliance penetration is investigated and future residential electricity demand is projected for urban and rural areas of individual province. We postulated three scenarios i.e. 1) Base Line scenario 2) Rural Growth Scenario 3) Energy EfficiencySc enario by 2020 and conducted scenario analysis. The Base Line case projected that the total urban REC will approximately triple and the total rural REC will almost five times by 2020. The expected population growth and falling household membership will increase urban REC, whereas the penetration increase is the main driving force for rural REC growth. The Rural Growth Scenario resulted in the largest total REC among all Scenarios, suggesting rural growth plays a key role in determining the future REC in China.Resource /Energy Economics and Policy,