L.A. Greening et al. r Energy Economics 23 2001 153᎐178 154
1. Introduction
The residential sector uses between 20 and 25 of final energy consumed in the Ž
. OECD IEA, 1997 . Energy using activities such as space conditioning, water
heating, the use of major appliances, and the ‘other’ category, which includes the use small household and personal appliances, account for energy consumption in
this sector. Changes in the consumption of final energy for residential purposes vary by country. For example, final energy consumption in Denmark has decreased
by 28 or approximately 1.6 per year, while final energy consumption in Japan has increased by 170 or approximately 4.4 per year over the period of analysis
Ž
. Ž
. 1970᎐1993 . As with transport personal transportation and freight , where energy
consumption has been increasing annually at slightly less than 1, these increases Ž
. are attributable to changes in behavior Greening et al., 1996, 1998c . These
changes in behavior have included increases in population and the numbers of households, an increase in the square footage of the average dwelling, and
decreases in the average number of occupants. Along with increased penetration and usage of energy-using technologies, these factors should continue to drive
increases in energy consumption for the majority of countries and increases in global carbon emission levels.
More than any other sector, we can directly link changes in residential energy Ž
. consumption to changes in human activity Schipper et al., 1992 . Analysis of these
1
Ž .
changes have been approached by a variety of disciplines Lutzenhiser, 1992 .
However, no single approach has provided an indisputable framework for analysis. For this discussion, we will emphasize the role of economics in determining
changes in levels of energy consumption. Under this paradigm, changes in energy prices and income are a primary driver of changes in energy consumption. How-
ever, other factors such as climate, household demographics, life-style, culturaliza- tion and governmental policy, also, play a role in determining the choices of types,
Ž sizes and amounts of energy-using equipment and household living areas Haas,
. 1997 . Using micro-level data, the contribution of these other factors to changes in
Ž .
levels of energy consumption can be evaluated Greening et al., 1998b . However, with aggregate data, we are limited to the observed changes in the average number
of dwellings, the average number of occupants, the average square footage of a dwelling, penetration rates of general classes of energy-consuming equipment, and
Ž .
average climate heating and cooling degree days . This severely limits the types of Ž
. inferences we can draw from the analysis Golove and Schipper, 1997 .
As with the decomposition efforts for other sectors, a primary issue is the identification of the appropriate activity measure to use as a basis for development
1
Those disciplines include energy technologists, whose primary emphasis has been on the role of a given technology without consideration of the factors that lead to adoption, anthropologists, sociologists,
psychologists, architects, economists, and others. A good overview of these various lines of approach to Ž
. the problem, and the major results are presented in Lutzenhiser 1992 .
L.A. Greening et al. r Energy Economics 23 2001 153᎐178 155
Ž .
of measures of aggregate carbon intensity Greening and Greene, 1998 . Con- sumers demand energy services, of which energy is only one input.
2
Ideally, carbon emissions should be disaggregated on a per unit basis of energy service. However,
unlike either personal transportation or freight, where passenger-kilometers or Ž
. tonne-kilometers, are routinely measured for different modes activities , residen-
tial end uses do not have a similar common measure of activity. For example, in the case of space conditioning, consumers are really demanding thermal comfort. As a
measure of thermal comfort, the thermostat set point could be used, or the ambient temperature of the living space. Likewise, for water heating services, the
number of gallons of hot water provides an activity measure. However, with the exception of a few isolated, metered studies of an end use, these measures have not
been routinely collected. Also, since these measures have different units, different end uses are difficult to combine. Therefore, proxy measures must be determined
for each service or end use. To combine them, measures of carbon emissions, structure and energy intensity are usually normalized by population, resulting in
Ž .
per capita measures Schipper et al., 1985 . Several previous studies have been performed attributing changes of carbon
emissions and energy to changes in fuel mix, energy intensity, and activity mix Ž
. structure . However, in comparison to either manufacturing or personal
Ž .
transportation this number is much smaller Greening et al., 1996, 1997, 1998a . This smaller number is the result of the difficulties in obtaining good time series
for the relevant data, and then the assignment of energy consumption to various Ž
end uses Schipper and Ketoff, 1985; Shinbaum and Schipper, 1993; Schipper et al., .
1996 . Therefore, valid comparisons between previous studies and our work are difficult, and in some cases impossible. For this discussion of previous decomposi-
tion efforts of residential energy and carbon, we will focus on the most contribu- Ž
. tion to the literature by Schipper et al. 1998 . That work was performed with the
same data set, which underlies our analysis, and the same assumptions concerning allocation of energy consumption by end use.
Ž .
Schipper et al. 1998 decomposed carbon emissions from the residential sector for the period 1973 through 1991 for the same 10 OECD countries included in this
analysis. Using a Laspeyre’s index specification with a fixed base year, the authors attributed changes in absolute emissions levels to five different factors, including
changes in population, changes in primary mix for the generation of electricity, changes in the final fuel mix, changes in energy intensity and changes in structure.
Schipper found that structural changes induced by changes in human behavior resulted in increases in levels of carbon emissions. With the exception of Norway,
structural shifts towards more carbon-intensive activities resulted in increases of carbon emissions of between 15 and 65. These shifts in structure partially offset
the reductions in emissions levels achieved through decreases in energy intensity
2
Energy services are produced by the use of fuel, capital, labor and management expertise by Ž
. households or firms Greening and Greene, 1998 .
L.A. Greening et al. r Energy Economics 23 2001 153᎐178 156
Ž .
17᎐41 for nine of the countries . These two terms are most comparable with the analysis presented here, and patterns of change for both terms for each of the
countries are the same between the two studies. However, the magnitudes vary as a result of the specification of five terms and the indexing method used.
The work presented here analyzes development of carbon emission trends from residential energy consumption in 10 OECD countries: Denmark, Finland, France,
Ž .
Germany West , Italy, Japan, Norway, Sweden, the UK, and the US. Decomposi- tion of aggregate carbon intensity allows attribution of changes in this measure to
changes in the primary fuel mix for the generation of electricity, changes in final fuel mix for all residential end uses, and changes in energy intensity and end use
Ž
. activity mix structure. As with our previous analyses of sectoral emissions trends,
we use a modified Adaptive Weighting Divisia index specification. As with our other sectoral studies, declines in energy intensity made a substantial contribution
to declines in residential carbon intensity in the majority of countries in this analysis. In addition, declines in aggregate carbon measures also result from
significant shifts towards a less carbon-intensive mix for both primary fuels used in the generation of electricity and final fuels. However, for the majority of countries,
shifts in the activity mix or structure of end uses offset either partially or totally those declines in aggregate carbon intensity resulting from changes in these other
measures. As a result, cumulative changes in per capita carbon emissions, our measure of aggregate carbon intensity, show a great deal of variability. Six of the
countries exhibit declines ranging from almost 8 for the US to almost 72 for Sweden. The other four countries exhibit increases of less than 1 to well over
94.
The remainder of this paper is organized into several sections. Section 2 provides an overview of the parametric framework for the carbon decomposition index and
discusses the data used in the analysis. The complete technical development of the index decomposition method is presented in Appendix A. Section 3 of the main
body of the text discusses the results of our analysis. The final section provides brief concluding remarks.
2. Specification of the index decomposition method and data
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