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Appendix A
incorporating Data from Prob~em-Centered
Research on incentives and
information in Formal Demand Models
Problem-oriented studies can investigate the effect of
the size and type of incentives, of qualitative factors
in the context of the incentive, and of different ways of
offering information about energy efficiency. When such
studies produce quantitative results, those results can
be incorporated into formal energy demand models. This
appendix presents a method for using such data in discrete
choice models.
The typical state-of-the-art residential energy model
includes equations that predict household purchases of new
energy-efficient systems (appliances, heating equipment,
retrofit of existing homes, thermal performance of new
homes). Typically, these are discrete choice models to
reflect the finite number of options consumers face for
each class of purchase decision. For example, a model may
define eight choices of water heaters (the combinations
of two size classes, two fuels, and two levels of insula-
tion). The choice models that predict what fraction of
each equipment type is purchased might be of the form:
(Si/Sl) = aO + alpeUi/eff i + a2Ci +
- alpeUl/effl ~ a2C1 '
where Si is the fractional share of new water heaters
sold that are of type i, S1 is the fractional share of
type 1 water heaters, Pe is the price of electricity,
Ui is annual hours of use of type i water heaters, effi
is the energy efficiency of type i water heaters, Ci is
the cost to the consumer of type i water heaters, U1 is
the annual hours of use of type 1 water heaters, eff1 is
the energy efficiency of type 1 water heaters and C1 is
the cost of type 1 water heaters. The coefficients al
and a2 represent the weights of operating and capital
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118
costs in the choice; together, they determine the implicit
discount rate for energy efficiency in purchases of new
water heaters.
Predicted values of equipment purchases are used to
project stocks of energy-using equipment. These stocks
are then used in conditional demand models to estimate
household energy demand.2
Studies of variables that affect appliance choice yield
findings that can be used to adjust either the coefficient
a2 or the equipment cost Ci in the purchase choice
models. For example, information on consumer preference
among different levels and types of incentives, stratified
by type of consumer (e.g., by household income or educa-
tion of household head) can be used to determine indif-
ference curves, along which households are indifferent to
choices such as those between rebates and loans (Figure
A-1). These indifference curves can be converted to
implicit discount rates to yield equations of the form:
a2 = f(incentive type and level, household
characteristics).
Such equations, which may vary with the type of purchase
decision, can be used to determine the coefficient a2,
which can then be used in the purchase choice model.
Alternatively, the same kinds of findings might be
used to estimate a parameter a3 for some dummy vari-
able, such as rebate versus loan or presence of an
waif d is the implicit discount rate for choices among
water heaters with different efficiency levels, g is the
consumer's expectation of future Growth rates in fuel
· . . .
price, L is the expected lifetime of the water heater,
and U is the expected annual hours of water heater usage,
then the relationship between the coefficients and d is
a2/a1 = (d - g)/u[1 - e~(d-g)L]
.
If g is close to zero and L is large, then a2/a1 = d/U.
2 The present discussion does not incorporate possible
effects of appliance efficiency on U. subsequent appliance
usage. In practice, purchase of a more efficient piece
of equipment is likely to lead to greater use of that
equipment than would occur with purchase of a less effici-
ent unit. This occurs because higher efficiency leads to
lower operating costs.
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119
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Representative terms from entire chapter:
energy efficiency
