1 Intelligent Well Technology: Status and Opportunities for Developing Marginal Reserves SPE

Household Energy Spending and Income Groups:

The Case of Great Britain 1991-2007

Helena Meier, Faculty of Economics, University of Hamburg, +49 (0)40 42838 4632,

Tooraj Jamasb, Faculty of Economics, University of Cambridge, +44 (0)1223 335271,

Overview

Analysing household energy expenditures is important for understanding the domestic energy consumption and spending and addressing equity issues in energy consumption. This paper investigates the determinants of household energy spending in different income groups. We explore the shape of Engel curves for energy spending and estimate income and price elasticities. We focus on energy expenditures of British households and use a panel data of approximately 5,000 British households from 1991 to 2007.

Several studies using micro data focus on energy consumption of different groups of households. Nesbakken (1998) analyses Norwegian residential energy consumption in two income groups, higher or lower than the mean income. The findings suggest that the income elasticity hardly depends on the income groups. In the analysis of US energy consumption, Poyer and Williams (1993) have households broken down by race/ethnicity. Dresner and Ekins (2006) compare the impacts of policy measures to reduce carbon emissions on households within different income groups. They show that households within the lowest income groups have rather heterogeneous energy consumption patterns.

We hypothesize that households on different incomes adjust their energy expenditure patterns to changes in their income. We also expect that households on lower incomes to be more sensitive to external changes than those with higher incomes. Our analysis shows that there is an S-shaped relationship between average energy expenditures and average income levels of different income groups as discussed in Bradshaw et al. (1987). We also discuss that there exists an inflection point at which energy spending flattens/decreases while income still increases. Thus, the income elasticity of energy spending declines at this point. We are interested in the income levels at which energy spending tunrs over. We then calculate energy expenditure elasticities of income and prices (gas and electricity) for different income groups and analyse the influence of further factors on energy spending.

Methods

We analyse the effect of building characteristics, regional differences, energy prices, and several socio-economic characteristics on houseld energy expenditures. We distinguish between the following house types: detached and semi-detached houses, terraced and end-terraced houses and flats. In addition, we control for the number of rooms in buildings. In order to capture the effect of regional differences we control for households living in rural areas. We use annual gas, electricity and oil prices from the IEA (2008). Within the group of socio-economic characteristics we control for the household’s annual income and the number of children. We use a fixed effects econometric model. A Hausmann test rejects the use of the random effects model.

We first analyse energy expenditures of all households and then examine households within five different income groups. The subgroups consist of approximately 10,000 households each. We estimate short-run income and price elasticities for these income groups as we do not consider any technological adjustments over time and assume technologies to be fixed.

Results

The results show positive significant income elasticities of energy expenditure for all households as well as for different income subgroups. Elasticities are smaller than unity and differ for different income groups. With increasing income levels, i.e. moving from the lowest income group to the highest, income elasticities of energy expenditures seem to increase. This result is in line with our hypothesis. Concerning adjustments of energy expenditures to price changes, we find positive and significant price elasticities of energy expenditures for gas and electricity. Again, we find that the elasticities are increasing across income groups.

According to official statistics, the lowest average household income levels are found in the North East while households in London were on average the richest within Great Britain. Our results do not show a clear tendency of higher energy expenditures in rural areas, Coefficients vary according to income group.Regional variations may also be due to differences in weather conditions (as shown in Meier and Rehdanz, 2008), And not to differences in rural or urban areas in general.

Conclusions

In this paper we show that households on different income levels adjust their energy spending differently to changes in prices and income. In particular changes in income elasticities show that Engel expenditure curves of energy are not linear. Our analysis further suggests that next to income, other socio-economic factors such as the number of children also drive energy spending.. As differences in adjustment processes of income groups persist, we suggest to develop targeted policy measures supporting these income groups differently.

References

BERR, Department for Business Enterprise and regulatory Reform, Defra, Department for Environment Food and Rural
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Bradshaw, J., Mitchell, D., Morgand, J., 1987. Evaluating adequacy: the potential of budget standards. Journal of Social Policy
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Dresner, S., Ekins, P., 2006. Economic instruments to improve UK home energy efficiency without negative social impacts.
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IEA, International Energy Agency, 2008. Energy Prices and Taxes, Quartlerly statistics, Fourth quarter 2008.

Meier, H., Rehdanz, K. 2008. Determinants of residential space heating expenditures in Great Britain. Kiel Working Papers,
1439, Kiel Institute for the World Economy, Kiel; FNU-163.

Nesbakken, R., 1999. Price sensitivity of residential energy consumption in Norway. Energy Economics 21(6), 493-515.

Office for National Statistics, 2008. Regional Trends 40: 2008 edition. www.statistics.gov.uk

Office for National Statistics, 2009. CPI INDEX: Average 2005=100. www.statistics.gov.uk.

Poyer, D.A., Williams, M., 1993. Residential energy demand: additional empirical evidence by minority household type.
Energy Economics 15(2), 93-100.