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ZEF Discussion Papers on Devlopment Policy 7
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Bog'liq zef dp07ZEF Discussion Papers on Devlopment Policy 7
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Similarly, a study conducted in El Salvador in 1977 also shows that including the
consumer surplus results in substantially higher benefits than are indicated by estimates that
include only telephone revenues.
Another way of estimating the benefits associated with telephones is to examine the costs
saved through their use. In this genre of studies, authors usually calculate the alternative costs of
communicating as an estimate of consumers’ willingness to pay. The gap between the
willingness to pay and actual telephone costs is a measure of the consumer surplus associated
with telephone use. Several studies of this nature have been carried out on developing countries.
These studies are reviewed in detail in Saunders
et al.
(1983). Although these studies suffer
from data problems and some questionable assumptions, a common finding across countries is
that savings exceed expenditure quite substantially. Depending on the country, region and
sample group analyzed, these savings may range from 1.5 to 5.5 times the costs.
4.2.3.2 Consumer surplus and computers
The literature on consumer surplus associated with computers is relatively thin (as
compared to that on telephones) and deals mostly with developed countries.
Brynjolfsson (1994) uses data from the US to estimate the increase in consumer surplus
associated with the decline in computer prices during the 1975-1987 period. He computes four
different measures of consumer surplus, i.e. Marshallian surplus, exact surplus based on
compensated demand curves (Hicksian demand curves), a non-parametric estimate and a value
based on the theory of index numbers. These will now be described in some detail.
The most common method of estimating consumer surplus is based on the ordinary or the
Marshallian demand curve. Given a specification of the demand curve, one can directly evaluate
the Marshallian consumer surplus by integrating it between any two prices. Brynjolfsson relies
on a log-linear specification of the demand function, i.e.
δ
α
γ
y
p
e
Q
=
(8)
where
Q
is quantity,
p
is price,
y
is income and
γ
,
α
, and
δ
are parameters to be estimated.
Integrating the demand curve from the initial price
p
0
to the final price
p
1
yields:
)
1
(
/
)
(
1
0
1
1
α
α
α
δ
γ
+
−
=
+
+
p
p
y
e
CS
(9)
Given prices, income and estimates of the parameters, consumer surplus can be calculated.
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