THE DEVELOPMENT AND CRITICAL REVIEW OF ANNUAL STOCK
AND GROSS INVESTMENT DATA FOR RESIDENTIAL
ENERGY-USING CAPITAL
Ralph Braid
June 1978
MIT ENERGY LABORATORY REPORT No. MIT-EL-78-036
2
ABSTRACT
The purpose of this paper is to develop pooled time-series
cross-sectional stock and gross investment data for residential
energy-using capital by state over the period 1960 to 1974.
In the
process of doing so, it is necessary to examine theoretical issues and
empirical techniques, and to evaluate the accuracy of data sources
currently available.
One section of the paper is devoted to a careful
theoretical and empirical discussion of appliance depreciation rates and
their relationship to average appliance lifetimes.
Another discusses
benchmarking techniques and the conditions under which they are liable to
be effective.
The remainder of the paper concerns the development and
evaluation of the actual data series.
Whereas most of the discussion
focuses on household appliances, the techniques discussed, evaluated, and
utilized should be of wider interest.
Similar techniques will allow
construction of accurate gross investment data for household heating
equipment.
3
ACKNOWLEDGMENTS
The research discussed in this paper reflects work undertaken by the
author as part of a larger analysis of the potential markets for solar
photovoltaics.
That
larger
analysis
has been and is being
by
conducted
the MIT Energy Laboratory for the United States Department of Energy.
The author would like to express gratitude to Ray Hartman for many
helpful conversations, and many helpful suggestions on revising the paper
for clarity.
Bob Schmitt and Alix Werth carried out much of the work
preliminary to this research while studying related areas of the larger
analysis of energy demand.
The author would also like to express
gratitude for the valuable computer advice of Dick Startz and David E.
White, and the very helpful comments and suggestions of Jerry Hausman,
David Wood, and Richard Tabors.
The author
is a graduate
student
of Economics
assistant at the MIT Energy Laboratory.
at MIT and a research
4
TABLE OF CONTENTS
Page
INTRODUCTION AND OVERVIEW
A) NATIONAL APPLIANCE STOCK DEPRECIATION
5
8
B) TECHNIQUES FOR THE DEVELOPMENT OF APPLIANCE STOCK
DATA BY STATE
23
C) TECHNIQUES FOR THE DEVELOPMENT OF GROSS INVESTMENT
34
DATA BY STATE
D) BENCHMARKING
TECHNIQUES
41
CONCLUSIONS
47
REFERENCES
50
APPENDIX 1: GROSS INVESTMENT DATA FOR HOUSEHOLD
HEATING EQUIPMENT
51
APPENDIX 2: THE STOCHASTIC NATURE OF THE ELECTRIC
APPLIANCE GROSS INVESTMENT DATA
APPENDIX 3: THE DATA BASE
54
57
5
INTRODUCTION AND OVERVIEW
The existing body of residential energy demand models is
characterized by two types of difficulties:
specifications and inadequate data.
specifications
of past modeling
inadequate theoretical
Inadequacies in the theoretical
attempts
are discussed
in some detail
Hartman [8], along with suggestions for future modeling attempts.
in
The
purpose of this paper is to introduce some of the data sources currently
available, to assess critically their quality, and to indicate desirable
extensions and improvements.
This paper discusses the appliance stock and gross investment data
developed for the MIT Energy Laboratory study of residential energy
demand.
Annual appliance stock data were needed for the short run
analysis of energy demand ([13] and [8 ).
investment
Annual appliance gross
data were needed for the long run analysis
([2] and [8]).
of energy
demand
Both analyses use pooled time series cross-sectional data
for states over the period 1960 to 1974.
The principal sources of data considered in this paper are as follows.
*
Merchandising Week (MW). The statistical issues of this
magazine furnish survey information concerning appliance
saturation
rates and sales.
In addition,
information
is
provided about expected appliance lifetimes, and appliance
shipments
a
at the national
level.
U.S. Census of Housing. The census provides estimates of
appliance stocks and housing stocks for the census years 1960
and 1970.
*
Association of Home Appliance Manufacturers (AHAM)
Gas Appliance Manufacturers' Association (GAMA. These
organizations provide survey information about manufacturers'
shipments of appliances, disaggregated to the state level. The
former covers electric and gas dryers (and washers), while the
6
latter covers gas ranges, gas water heaters, and residential
gas-fired heating equipment.
I
Electric Power Research Institute (EPRI).
Data Resources, Inc. (DRI).
DRI developed a wealth of
information in the study it carried out for EPRI [3]. For the
electric appliances, its data base includes census data, MW
survey data aggregated to the state level, and estimated annual
appliance stocks. Furthermore, DRI estimates housing stocks by
state and year, broken down according to heating fuel.
*
Midwest Research Institute (MRI). This organization provides
data on appliance choice at the household level. These data are
not discussed in this paper, but are mentioned because of their
potential importance. The MRI data will be incorporated into
the MIT Energy Laboratory data base.
The above list does not cover all potentially valuable data sources, nor
all of the data sources
used in the long and short
residential energy demand ([2] and[13]).
run analyses
Furthermore, not all data
provided by the listed organizations are referred to above.
list is intended
discussed
to introduce
the sources
of
of data
actually
Rather, the
used and
in this paper.
Section A is devoted to a careful theoretical and empirical
discussion of appliance depreciation rates and their relationship to
average appliance lifetimes . In section B, the quality of
the EPRI annual stock data for electric appliances is assessed, and
alternative methods are used to generate new annual stock data for both
electric and gas appliances.
In section C, annual gross investment data
are developed for both electric and gas appliances.
Section D outlines
the benchmarking techniques used in sections B and C, and discusses their
probable effectiveness.
are three appendices.
Following the conclusions and references, there
The first examines briefly some of the problems
encountered in trying to construct gross investment data for household
7
heating equipment.
The second examines the stochastic nature of the
electric appliance gross investment data developed in section C.
Finally, Appendix 3 provides printouts of the series discussed and
developed
in this paper.
Whereas most of the discussion focuses on household appliances, the
techniques discussed, evaluated, and utilized should be of wider
interest.
summarize
The conclusions
the discussion
illustrate
and results
this
implicitly,
of the paper.
as well
as
8
A.
NATIONAL APPLIANCE STOCK DEPRECIATION
The purpose of this section is to estimate national depreciation
rates (more precisely, deterioration rates) for the various electric and
gas appliances.
Appliance depreciation rates are of interest for two
reasons.
(i) Appliance stocks Kt are related to gross investment It through
the formula
Kt+
where
= I t + (1 -
)K t
6 is the appliance
(1)
depreciation
rate.
One use of this formula
(discussed later in this section) is the construction of accurate yearly
national appliance stocks from census national appliance stocks and
yearly national appliance shipments.
A related use of equation (1)
(discussed in section C) is the construction of state appliance gross
investment data from annual state appliance stock data.
(ii) The depreciation
rate of an appliance
is closely
related
to its
average lifetime, which in turn affects the annualized capital cost of
owning the appliance.
The raw data for estimating national appliance depreciation rates are
as follows.
For each appliance, 1960 and 1970 stocks are found in the
Census of Housing [12].
Week
National shipments are reported by Merchandising
[10].
Assuming census stocks (and other annual stocks) are mid-year
estimates, and manufacturer's shipments lag behind retail sales by six
months, the appropriate relationship between stocks and flows, repeated
from above, is
9
Kt+l = It + (1 - 6)Kt
(1)
where Kt represents national stocks, It represents national
shipments,
and
represents
6
the depreciation
represent 1960 and 1970, so that K
rate.
Letting
0 and 10
and K 10 are census stocks, and
K1 through K9 are unobserved intercensus stocks,
K 10
=
19 +
(1 -
)K9
=
19 + (1 - 6)I8 + (1 -
)2K8
and so on until
= 19 + (1 -
K 10
)I8 + ... + (1 - 6)9I
+ (1 - 6)10K
In summation notation,
9
K10
It(1-
E
) 9- t + (1 - 6)10 K
(2)
t=O
Equation (2) is used in estimating appliance depreciation rates.
The appropriate value of 6 is calculated by estimating the roots of
equation (2).
Specifically, a Newton-Raphson algorithm is used to find
the values of x for which
9
g(x)
Itx9 - t + KOx1 0 - K10
=
=0
t=O
where x = 1 - 6 represents the percentage of the stock surviving from one
year to the next.
is easily
Remembering that all the I's and K's are positive, it
seen that g(O) < 0, and that g'(x)
for all x > 0.
It immediately
root, which represents
it should
lie between
follows
the correct
0 and 1.
that
value
and g"(x) are both positive
g(x) has only one positive
of x = 1 - 6.
Graphically,
Assuming
6 >
g(x) has the following
0,
shape.
10
g(x)
1.0
x
As a consequence of its curvature, the Newton-Raphson algorithm should
converge
directly
the initial
to the unique
positive
root of g(x) if 1.0 is chosen
as
guess for x.
Estimated results of equation (2) for several appliances are shown in
Table
1.
(All appliances
are electric
unless
designated
as gas.)
Depreciation rates for the electric appliances agree with those
calculated by DRI [3].
Average lifetimes are calculated as reciprocals
of depreciation rates, an identity which holds if exponential
depreciation is assumed (see following discussion).
For some appliances,
average life expectancies are listed in Merchandising Week [11].
are listed in column 5.
These
In some cases, the calculated lifetimes seem
high, in comparison with either intuition or (where available) the MW
figures.
Errors in the data might be the reason, but another quite
11
Table
1
(
APPLIANCE DEPRECIATION RATES AND AVERAGE LIFETIMES
4-
`0
O0
I
o
S.-
C,
O
.0 a)
E U
.3-
a" o
o
0r
a)
4- c
0 o
.r030.
-I-' (0
-a
CD
.-
C4,
U
11
a-
E
0
cD
S. (
S4-\
V
C
II
aE
a)
II'-
U
>
rd
-i-)
CO
Cj
E
-- 0
-I
>EE
O
o
o 0
.-
(
0
Q
-3
O C
U
O -- )
CD 0
r-V
O 4O
-
koSW
LC)
1
refrigerators
.0603
16.6
1.196
63440
2
freezers
.0215
46.5
1.836
17900
4
electric ranges
.0483
20.7
15
1.576
25760
gas ranges
.0599
16.7
15
1.145
31244
electric water heaters
.0433
23.1
1.491
16100
gas water heaters
.0582
17.2
1.358
34667
electric dryers
.0130
76.9
14
2.957
18630
gas dryers
.0330
30.3
14
2.823
7840
6
washers (auto/semi-auto)
.0632
15.8
11
1.834
37990
7
washers (wringer &
spinner)
.1350
7.4
0.406
7110
10
5
11
8
12
Data sources for Equation (2): National Shipments It from Merchandising
Week [10]; Census stocks K, K1 0 from the Census of Housinq [12].
12
plausible explanation is explored below.
The identity between average appliance lifetimes and reciprocals of
depreciation rates depends on the assumption of exponential
depreciation.
Only under exponential depreciation is there a
well-defined constant depreciation rate 6 independent of the age
structure of the stock, a feature which makes exponential depreciation
quite convenient and hence often used in both theoretical and empirical
Under exponential depreciation, the fraction of
economic work.
(of a given type)
appliances
t years
operating
installed
in year
0 which
will
still
be
later is
F(t) = -e 6t
The probability
density
function
for how long a given
unit will
last
before decaying is
f(t)
= - F'(t)
The depreciation
)
=
e6 t
=
rate for appliances
f(t)
6t
F~t>
i t) e-6
of age t is hence given
by
6
which is a constant, independent of age, as mentioned earlier.
Average
appliance lifetime is
AL =
J
t f(t) dt
which
is the formula
Table
1, column
=
t(Se-6t)dt
= 1/6
that was used in estimating
average
lifetimes
in
4.
However, it does not seem completely realistic that the depreciation
rate of an appliance
should be independent
of its age.
Consider
two
13
dryers,
one 2 years old and the other
12 years
old, which
good working condition at the beginning of the year.
are both
in
Under exponential
depreciation, the two dryers are equally likely to survive the year in
good working condition.
Intuitively, however, it would seem that the
older dryer has a greater chance of breaking down during the year.
Furthermore, the relevant depreciation rate is not the percentage chance
an appliance will break down, but rather the percentage chance it will be
retired from service during the year.
The older dryer has a smaller
chance of being repaired if it does break down, and a larger chance of
being retired due to obsolescence even it if doesn't break down.
depreciation
rates would
be expected
to increase with
Thus
the age of an
appliance, not remain constant as predicted by the exponential model of
depreciation.
Before discussing a realistic pattern of stock depreciation, it is
worthwhile mentioning another model of depreciation sometimes used in
economics ( see [6] for example1 ).
This is the "one hoss shay"
assumption, according to which all appliances of a given type last the
same number of years before falling apart.
The "one hoss shay"
assumption and the exponential depreciation assumption are compared
graphically
in Figure
1.
Intuitively, the actual pattern of stock depreciation should be
somewhere between these two, as illustrated in Figure 2.
Algebraically, the function
F(t)
1 + e-
1
1 + ea(t
T)
e aT+
e
ea
1
+ e at
-
1
discussed
in section
2 of DRI [3].
14
1A: fraction of appliances still in operation t years after installation
I
F(t)
F(t)
F(t) = e -
1.
at
__
1.0
iw
to
t
lB:
t
probability density function of appliance lifetime
f(t
f(t)'
e- t
f(t) =
t
C:
depreciation
to
rate as a function
6(t)
of age =
t
f(t)
F(t)
6(t)
6(t) = 6
6
t
EXPONENTIAL
DE'PR'ECIATION
Figure 1:
to
" ONE HOSS SHAY" DEPRECIATON
TWO ALTERNATIVE DEPRECIATION PATTERNS
t
15
2A:
fraction of appliances still in operation t years after installation
F(t)
t
2B:
probability density function of appliance lifetime
f(tI
t
2C:
depreciation rate as a function of age
=
f(t)
F(t)
6(t)
t
Figure 2:
A REALISTIC PORTRAYAL OF APPLIANCE
DEPRECIATION
16
might be appropriate to approximate Figure 2A.
Note that if
T
is large
and negative,
F(t)
e-at
-
eT+
1
1
T
+ eat
eat
e
so that exponential depreciation results.
value to and a
is large and positive,
F(t)
- +e
F~t)
={1
t)
for
t
1+ea(t-to)
1+ e
Also, if
then
+e
0
o
1 + e
has the positive
0 for t > to
so that "one hoss shay" depreciation results.
With finite positive
values of both a and t, the graph of the function looks much as in Figure
2A, intermediate between exponential and "one hoss shay" depreciation.
Consider now an arbitrary pattern of depreciation.
F(t) represents
the fraction of appliances still in operation t years after
installation.
will
The probability density function for how long a given unit
last before
decaying
is related
to F(t) by
f(t) = - F'(t)
The depreciation
6(t)
rate for appliances
by
(3)
X
=
of age t is given
Average appliance lifetime is
co
AL =
f
0
co
t f(t) dt =
I
0
F(t)dt
(4)
17
where the second equality follows from integration by parts.1
How does this average appliance lifetime relate to the observed
depreciation rate?
To answer this, let g(t) represent gross investment
(the number of appliances installed) t years ago.
should
The current stock
be
0
and the current
rate of appliance
decay
should
be
co
D =
g(t)
f(t)dt
The appliance depreciation rate currently observed is thus
1
Let u(t) = t and v'(t) = f(t).
Then u'(t) = 1 and v(t) = - F(t).
Hence
00
00
t f(t)dt - tF(t)
It is necessary
+
only to demonstrate
clearly allowable assumption that
bound
n, it follows
that
:
.
atd log F(t)
rr)
(t)
=
-
(t)
F(t)dt
that tF(t)
+
0 as t
+
A.
Making
(t) has a positive greatest lower
>
_
nn
all
t > 0.
Integrating and then exponentiating shows that
F(t)
<
exp(
-
nt),
all
t
> 0
for some constant value of . It immediately follows by use of
1'Hopital's rule that tF(t) - 0 as t
.
the
18
g(t)
g(t) f(t)dt
d =D
=
F(t)
6(t)dt
=
/
K
(5)
g(t) F(t)dt
g(t) F(t)
0
dt
0
where the second equality follows from equation (3).
Now let d
be the depreciation
rate observed
where g(t) = go forever into the past.
gO
gof(t)dt
d
_
=
__;
_
gO
-= _
f(t)dt
J
go
0
(6)
1
=[
F(t)dt
0
state
Then
0
-
F(t)dt
in the steady
J
F(t)dt
0
where the last equality follows from equation (4).
In this steady state
situation, average appliance lifetime is the reciprocal of the observed
depreciation rate, no matter what the actual pattern of stock
depreciation.
What happens out of steady state?
Copying part of equation (5), the
appliance depreciation rate currently observed is
00
J
d
g(t) F(t)
6(t) dt
0
:
r
g(t) F(t)
dt
The steady state depreciation rate may be written as
J
u0-
F(t) 6(t) dt
c
F(t) dt
F(t) dt
19
by use of equations
averages of
(t).
(3) and (6).
Both d and d
are thus weighted
Suppose gross investment (and hence the stock of the
appliance) has been increasing over time.
Then inclusion of g(t) in the
formula for d will give newer appliances relatively more weight than in
the formula
for d.
is as depicted
Assuming
the actual
pattern
in Figure 2, so that newer
of stock depreciation
appliances
have lower
depreciation rates, the observed depreciation rate d will be smaller than
the steady state rate d.
Forming
the average
appliance
lifetime
as
the reciprocal of the observed depreciation rate will, therefore,
overstate the actual average appliance lifetime.
The predictions of the above paragraphs are borne out by Table 1.
For appliances whose ratio of 1970 to 1960 stock is close to unity, the
estimated average lifetimes (column 4) correspond reasonably well with
intuition and/or the Merchandising Week figures.
For appliances whose
ratio of 1970 to 1960 stock is high, the estimated average lifetimes seem
too high.
In order to estimate average appliance lifetimes more accurately from
census stock and yearly shipment data, one could perhaps estimate
coefficients a and
for the depreciation formula
F(t)- 11
++eea't -T-t
The average
lifetime
AL
1
See equation
of an appliance
1= +e
T
01
+e(tT)
(4).
dt
would
then be given
by the integral 1
20
which could be solved by numerical integration.
and
T
might
not be possible.
Since
However, estimation of a
two parameters
must be estimated,
it
would be necessary to have at least three census years of stock data,
together with national shipment data for all years in between.
It is
unlikely that all these data are available (prior to the 1980 census).
Of what
value then are the depreciation
rates
calculated
in Table
1?
Certainly they should be used with caution in computing average appliance
lifetimes.
For this purpose, educated guesses by people familiar with
the industry may be better, such as the MW estimates.
On the other hand,
whenever the formula
Kt+
= It + (1 - &)Kt
is used to convert
between
appliance
stocks
and gross
investment,
it is
the actual depreciation rate rather than the steady state depreciation
rate that should be used.
To what extent
is the actual depreciation
rate d of the preceding
theoretical discussion equivalent to the calculated depreciation rates of
Table 1?
Equation (2), which was used to calculate depreciation rates,
implicitly assumes the depreciation rate 6 is constant over time.
Under
the restrictive assumption of exponential depreciation, the actual
depreciation
rate is always constant
the steady state depreciation rate d
appliance lifetime.
over time,
and is always
equal
to
whose reciprocal is average
For a general pattern of depreciation, neither of
these conditions is guaranteed to hold, except under special
circumstances.
For example, if gross investment has been increasing or
decreasing at a steady exponential rate forever into the past, then the
21
actual depreciation rate will be exactly constant over time. 1 ,2
The best that can be stated
confidently
is that the appliance
depreciation rates calculated from equation (2) are averages of the
actual appliance depreciation rates over the period 1960 to 1970.
Given
this caveat, the depreciation rates calculated in Table 1 are appropriate
for two purposes
mentioned
in the introduction
to this
section:(a)
the
construction of accurate yearly national appliance stocks (discussed in
the next paragraph), and (b) the construction of yearly state by state
gross investment data from yearly state by state appliance stock data
(discussed
in Section
C).
It should
be noted
in reference
to the latter
that actual appliance depreciation rates may vary among states, since
some states may have relatively steady state numbers of an
1
Let g(t) = Ae-t.
Using equation
(5), the current
depreciation
rate
is
J
Ae - t f(t) dt
r
Ae-tF(t)
dt
rate T periods
The depreciation
4
Ae
jAe
This
-Y (t
-Y
(t -
)
T
}
hence
is
f(t) dt
F(t) dt
is seen equal to the current
depreciation
rate upon cancellation
the constant factor eYT from both numerator and denominator.
20nly if the steady exponential rate is actually zero, however, will
this constant actual depreciation rate equal the steady state
depreciation rate do whose reciprocal is average appliance lifetime.
of
22
appliance, and others may have rapidly increasing numbers of the
appliance (and hence comparatively lower actual depreciation rates).
depreciation
rates calculated
in Table
1 are still the best single
The
set of
depreciation rates to use, since they should be national averages of the
actual state depreciation rates.
Once appliance depreciation rates were estimated, they were used to
calculate yearly national appliance stocks from 1960 to 1974.
appliance,
the 1960 stock was set equal
to the census value,
For each
and stocks
in all following years were calculated recursively by the formula
Kt+l = I t + (1 - 6)Kt
where Kt represents national stocks, It represents national
shipments, and 6 is the estimated depreciation rate.
The way
6
was
calculated ensures that the 1970 stock thus generated should equal the
value given in the census.
23
B.
TECHNIQUES FOR THE DEVELOPMENT OF APPLIANCE STOCK DATA BY STATE
The development of annual appliance stock data by state has been
necessary for the short-run analysis of energy demand ([13] and [8]).
The EPRI study [3] is one source of annual stock data for the electric
appliances.
A different method was used to generate annual stock data
for the gas appliances.
Problems with the EPRI data and uncertainties
about the original gas appliance stock data led to construction of yet
another set of annual appliance stock data, this time for both the
electric
and gas appliances.
The EPRI stock data for electric appliances (and some of their
problems) are discussed in the first part of this section.
The
alternative method of constructing stock data for both electric and gas
appliances is discussed in the second part of this section.
comparative merit of the two methods is considered.
original
section
set of gas appliance
stock
data
is postponed
Finally, the
Discussion of the
to the end of
C.
The two basic sources of raw data used by DRI in the construction of
the EPRI appliance stock data are Merchandising Week [10] and the Census
of Housing [12].
1960 and 1970.
companies
The census reports state by state appliance stocks for
Merchandising Week (MW) surveys electric utility
each year and reports
the results
in its statistical
issues.
Usually only some of the utilities in a state reply to the MW survey.
The utilities that do reply make estimates of appliance saturation rates
and appliance sales within their districts.
These are printed in
Merchandising Week, along with the number of customers served by each
utility.
24
DRI tabulates the survey information for the electric appliances and
includes it in their dataset.
their appliance
in section
Only the saturation rate data are used in
B.
stock estimates,
For each state
and that
and year,
is all that will be discussed
DRI reports
the total
number
of
customers served by utilities which report saturation rates for a given
appliance.
It then computes a statewide saturation rate by taking a
weighted average of the saturation rates of the reporting utilities.
DRI computes
a first approximation
to the stock
of a given
appliance
(by state and year) by multiplying the saturation rates computed above
times the values of the housing stock calculated elsewhere in their data
set.
This
is not the measure
empirical work.
of appliance
actually
used in their
Instead, they perform two correction procedures designed
to improve the quality of the estimates.
benchmark
stocks
the saturation
rates for a given
First, for each state, they
appliance
to the 1960 and 1970
census rates.(For a discussion of benchmarking, see section D).
They
multiply these benchmarked saturation rates by their housing stock
variable in order to form state appliance stocks.
the state appliance
stocks
are all increased
Now, for each year,
or decreased
by the same
percentage in order to make their national sum equal to the national
stock of the appliance.1,2
1
Algebraically, if K1 and KN represent state and national stocks for
a given year, corrected state stocks KCi are formed by
50
KC
= (KN/
E
Ki)Ki
i=l
2
DRI calculates
national
section A of this paper.
appliance
stocks
in an identical
manner
to
25
However, the appliance stock estimates thus generated by DRI seem
quite
inaccurate
for at least
to the next, and then jump
or two later (see Table
a year
reasons
1
It is not at all unusual
state stock of an appliance
for the estimated
from one year
some states.
for this, both relating
by 1/3 or more
to decrease
year
back up to its first
There
2 for illustration).
to the Merchandising
value
are two
Week data DRI was
First, utility companies do not always have accurate
forced to rely on.
knowledge of appliance saturation rates in their districts.
Second, the
utility companies in a state responding to the survey may vary from year
to year (see Table 3 for illustration).
years
1 and 3 each of the two large
For example, suppose that in
utilities
in a state
responds
to the
survey, but that in year 2 only the utility with the (much) smaller
Then the estimated stock of
saturation rate of electric dryers responds.
electric
dryers will
or 3, even though
seem much
in reality
smaller
in year
it was roughly
2 than in either years
Neither
constant.
1
of the
correction factors used by DRI (benchmarking to census saturation rates
and making
state stocks sum to national
stocks)
will
correct
this problem
of the MW data to any significant extent.2
Since
appliance
stocks
are to be used as right-hand
in the short run analysis
of energy demand
1
aware
DRI is at least somewhat
side variables
[13], it seemed worthwhile
of its appliance
of the inaccuracy
stock
estimates. In view of the importance of water heating in energy
consumption, DRI uses an alternate method to develop better stock data
for water heaters 3].
2
See section
D for a discussion
of the probable
effectiveness
benchmarking in improving the MW saturation data.
of
26
Annual Stocks of Electric Rangesl 1960-1974 (Thousands)
Table 2
STATEZ
YEA4
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
545
625
671
1
441
513
551
590
586
601
599
629
626
614
628
6S9
2
30
33
35
42
41
42
42
43
47
45
48
54
55
67
68
3
4
73
72
77
79
104
88
114
107
1?5
101
133
121
143
109
177
144
184
129
195
131
209
139
241
160
282
151
299
177
327
186
5
6
937 1131 1133 1252 1477 1495 1685 1821 1874 1963 2078 2789 2222 2491 2591
179 194 ?23 243 265 294 318 321 342 355 372 413 462 553 565
7
324
348
346
367
303
442
462
48B
479
504
528
541
553
649
658
8
9
46
876
85
86
81
75
73
61
58
53
52
48
47
47
45
45
1054 1128 1179 1265 1321 1378 1441 1576 1666 1831 1960 2188
927 lol1011
10
514
548
559
556
579
635
684
613
767
862
779
892
899
672 1041
11
96
104
106
109
120
123
128
132
141
144
152
157
165
170
180
12
13
14
15
16
169
580
480
246
191
173
635
531
275
219
177
694
397
?80
?27
178
541
274
246
1A2
508
557
311
261
189
559
593
313
267
189
590
549
333
276
1ou
70t
582
33~
295
189
745
611
340
293
189
802
632
357
314
194
790
654
363
315
202
902
673
379
328
201
917
682
404
335
207
933
703
472
363
211
956
745
478
344
17
18
264
69
351
77
281
88
399
135
293
152
311
141
228
152
252
154
276
172
529
171
450
178
434
193
476
213
S04
227
525
193
19
108
113
114
116
161
161
162
165
170
178
181
196
192
224 247
475 518
111
298
578
147
20
21
312
628
335
639
353
696
341
648
651
722
380
746
390
771
425
803
446
816
494
823
22
23
24
75
948 1003
380
359
86
120
354
308
26
11?
84
77
28
159
54
174
54
79
30
31
32
33
34
35
36
37
38
39
40
499
261 290
540 544
1026 1015 1065 1157 1200 1257 1293 1239 1252 1217 1246 1285 1331
636
498
581
487
564
530
514 555
526
472
491
548
392
302
292
265
237
258
146
151 201 215
157
107
70
86
508
516
520
488
484
438 435
400
376
377
362
364
349
R8
72 132 137 141 145 145 149 158 161 165 176
118
192
10
191
94
195
100
203
82
214
102
218
101
221
102
233
101
247
101
257
85
294
91
209
97
95
P4
99
295 1006 1119
97
348
101
278
101
399
114
369
120 128
432 443
132
470
140
486
148
507
165
542
160 174
539 1641
47
86
91
91
92
90
94
95
100
90
843
985 1105 1429 1374 1502
941
985 1017
887
914
768
138
159
148
128
95
115
983 1048 1136
963 1030
971
212
149
200
112
105
94
549
542
524
481
507
467
1038 1088 1142 1171 1150 1236
105
115
102
102
81
80
526
524
507
380
491
361
1636
1070
147
1162
187
573
1234
118
528
1829
1099
1i3
1240
16b
556
1343
124
5'5
1903
11?5
155
1322
285
586
1339
125
704
1140
1124
137
1377
215
602
1424
130
532
58
57
100
1265
1157
129
1457
231
621
145.6
131
532
269
0
94
94
980 2223
1283
1189 1209 1254
156
149
131
1468 1437 1460
365
248
244
672
651
651
1471 1452 1421
136
139
135
593
560
555
2050
1258
158
1487
371
681
1373
153
611
106
128
146
41
83
90
93
97
107
108
111
113
118
117
116
120
42
680
752
748
751
741
686
738
993
993
982
964
936 1024 1056 1099
43
44
45
424
154
43
504
163
45
543
171
29
671
178
56
58
181
50
677
183
51
726
191
49
810
194
59
860
197
73
923
201
76
960 1006 1027 1068 1056
265
22?7 254
207
206
82
80
77
83
80
46
47
469
794
521
855
544
671
56
893
610
aP5
639
913
664
936
657
959
724 708 770 818 862
993 1038 1044 1054 1082
48
158
223
167
179
191
200
181
211
202
212
215 213
224
228
357
49
475
543
;52
568
SP0
594
630
65
640
626
663
634
723
741
804
50
37
44
41
42
68
68
61
65
67
52
59
92
79
63
From EPRI
2
77
912 987
1076 1088
[4].
States are listed in alphabetical order.
listing.
See Table 5
(Appendix 3) for a
27
Table 3
Annual Coverage Rates for Electric Ranges1 1960-1974 (percent)
Year
State2
60
61
1
74
63
2
0
0
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
93
73
95
37
93
64
73
6f3
42
53
23
45
48
6
61
63
93
56
89
e2
92
63
73
62
93
56
23
37
51
56
34
62
62
63
64
65
66
67
68
69
70
71
72
73
74
62
56
63
56
7
a
q3
56
94
76
94
63
73
64
92
57
23
14
46
55
57
63
0
0
n
0
92
55
89
70
95
62
73
0
94
57
91
56
61
5S
24
67
0
0
70
57
93
67
30
70
57
95
61
49
71
55
94
65
48
72
66
55
71
61
52
58
60
23
58
60
41
57
61
6)
70
74
61
73
95
70
74
108
61
73
4
9)
4
8'4
4
94
56
A9
42
52
56
87
42
50
56
88
42
46
58
59
60
61
65
61
74
48
77
65
61
72
48
88
87
78
65
62
72
48
8a
87
65
32
62
9
23
84
88
71
19
0
0
0
75
2
21
22
23
24
25
5f6
97
83
3
4'
79
53
95
87
84
44
64
53
92
38
86
45
64
47
89
R6
14
44
68
26
2
0
2
27
0
47
46
46
0
2
52
29
30
'1
:
59
93
71
98
71
97
70
97
31
2
7
6
45
32
33
27
77
46
81
26
81
46
80
1
0
0
3
78
73
76
72
1C4
q4
29
27
35
45
77
94
49
136
79
44
71
24
28
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
1
33
29
27
29
34
81
96
5)
1 09
79
47
79
27
75
73
107
96
29
27
36
44
77
95
49
107
72
44
14
16
89
74
65
94
29
289
31
44
61
95
71
105
85
44
69
17
94
92
49
5R
87
88
69
70
95
70
69
71
67
72
64
64
86
81
56
57
74
75
57
56
34
45
58
57
54
54
62
61
90
91
48
48
91
88
86
86
94
76
49
62
71
68
66
66
47 " 47
44
43
71
73
96
86
49
';3
45
47
80
80
1
93
58
93
61
71
71
73
4
94
56
77
57
47
a7
83
59
69
65
46
46
71
63
30
58
94
23
29
31
44
77
93
24
105
85
4
44
69
20
66
19
3
4
3
4
71
0
42
45
68
63
42
45
67
65
52
45
0
0
70
96
45
48
63
64
51
47
69
96
46
96
81
3
89
32
108
93
28
96
45
49
80
3
86
1
106
82
28
70
65
51
46
70
141
46
95
80
29
30
30
13
26
75
93
71
104
87
44
70
32
56
28
74
93
24
104
83
44
31
18
57
28
68
88
24
104
86
44
69
21
42
48
80
89
0
R6
255
29
31
43
78
92
72
105
38
68
19
95
68
108
59
75
56
93
55
83
43
24
59
75
62
92
48
82
85
70
21
96
0
89
32
57
93
29
29
31
38
77
93
23
105
83
6
6
94
70
109
61
74
4
94
55
81
43
45
59
82
62
92
47
82
85
70
80
96
45
95
82
3
89
30
1O7
91
28
3
2
80
31
107
82
28
31
57
28
77
87
24
80
32
103
62
28
31
35
28
77
89
24
1 04
102
88
44
69
18
70
44
69
17
6
6
77
69
84
70
77
78
69
83
86
76
6
94
69
1 09
60
75
61
94
4
4
57
95
57
93
58
82
893
82
43
43
21
61
45
62
87
48
42
21
96
45
63
91
48
81
81
85
70
85
65
46
60
55
62
9)
48
82
86
71
4
64
64
53
47
69
96
47
95
2
80
33
3
3
64
64
56
47
83
74
47
17
81
65
64
23
0
71
70
47
34
80
2
2
80
80
1
1
48
66
27
29
30
20
73
91
71
103
88
44
32
15
42
61
27
30
30
19
49
85
71
103
86
5
32
0
48
75
28
32
35
22
67
86
73
103
84
44
69
3
Coverage rates are defined by GUSTwhere
ELCR
ELCR = customers
served
by all utilities
in the state
[4]
CUST = customers served by utilities reporting saturation rates of
electric ranges [4]
2
States are listed in alphabetical order.
listing.
See Table 5 (Appendix 3) for a
28
to construct an alternative data set which would not be subject to such
large random
errors,
the estimation.
so as to reduce
any errors
in variables
problems
in
This was done as follows.
The first (and most important) step in constructing the new
appliance stock data uses only state by state census appliance stocks for
1960 and 1970.
The saturation rate for a particular appliance in the
state is assumed to satisfy the equation
SAT(t)
1
1+e
where
and
values.
+ Bt
This
are chosen so that SAT(1960) and SAT(1970) equal the census
is shown diagramatically
in Figure
3.
The particular
functional form employed for SAT(t) is identical to that used in logit
probability models (see [5]).
Its main advantage is that it combines
smoothness with the property that saturation rates are assured of being
between
0 and 1 for all t.
FIGURE 3:
A smooth curve of the form
1
1 + ea+ t
is fitted through the census saturation rates.
SAT(t)
1.0
U.U
1960
1970
tt
29
The second step involves a slightly better (but more complicated)
method than used by DRI to ensure that the sum of state stocks equals the
national
stock of a given appliance,
as calculated
in section
A.
Instead
of increasing or decreasing all state stocks by the same percentage for a
given year to ensure they
add up to the national
stock,
they are
increased or decreased by a percentage proportional to (1 - SAT).
This
has the advantage that states which already have high saturation rates
are not in danger of being upwardly corrected to have saturation rates
unreasonably close to or even greater than one.
By way of numerical example, suppose the country had only three
states, with the following housing stocks and appliance saturation rates
(before the final correction procedure):
Suppose
H 1 = 100
SAT 1 = .10
H 2 = 200
SAT 2 = .50
H 3 = 100
SAT 3 = .90
the national
stock of the appliance
already been calculated as 220.
KN in the same year
The DRI correction procedure forms
corrected saturation rates CSAT using the equation1
CSAT
i
= (.-)SAT
where K i are the uncorrected state appliance stocks
K.i = H i * SAT
1
i
has
.
Multiplying each side of this equation by the housing stock Hi
transforms it to the equivalent form KCi = (K 0
Ki)Ki which was
seen in a previous footnote.
30
For the numerical example, the DRI correction procedure works as follows:
State
CSAT
= (220/200)SAT
Hi
SAT i
Ki
1
100
.100
10
.110
.010
2
200
.500
100
.550
.050
3
100
.900
90
.990
.090
i
The correction procedure used here works as follows.
i
CAST
i
- SAT
(The details
i
of how it
works are left to the next paragraph.)
State
Hi
SAT i
CSAT.
CSATi - SATi
1
100
.100
.126
.026
2
200
.500
.574
.074
3
100
.900
.926
.026
In terms of absolute (rather than percentage) changes in saturation
rates, revisions are proportional to SAT using DRI's method, and
proportional to SAT(1 - SAT) using the method here (see the last columns
in the above two small tables).
A more precise description of how this second step works is
necessary.
For a given appliance
and year,
let HK and SATK be the
housing stock and first-round saturation rate for state K.
national
appliance
stock in the same year.
SATK
XK = ln(T-
The inverse
.T )
function
f is given
XK
SATK
e
1 +e
=
f(XK)
by
Define
XK by
Let B be the
31
Now consider the expression
~ K f(XK
+ z)- B
K
If this expression is zero for z = O, then the sum of state stocks
already equals the national stock, and there is no need to correct the
first-round saturation rates.
Otherwise, we must use the Newton-Raphson
algorithm to find the value of z for which it is zero.
value of z by z,
Denoting this
corrected saturation rates are defined by
CSATK = f(XK + ZO )
Assuming
that the amount of correction
necessary
is small
(z0 is
small), then
CSATK - SATK : f(XK)zO
Since
X
f'(X)
=
=
f(X)(1 - f(X))
(1 + e)
it follows that
CSATK - SATK = f(XK)(1 - f(XK))z
= SATK(1 - SATK)zO.
Thus revisions in the saturation rate are proportional to SAT(1 - SAT) as
long as the revisions
are small.
large, all of the corrected
Even if the necessary
saturation
rates
will
revisions
lie between
Which method generates the better appliance stock data?
are
O and 1.
The method
here basically fits a special type of time trend through the census
saturation rates.
The DRI method basically benchmarks the incomplete MW
saturation data to the census saturation rates.
In both cases, the state
stocks are revised slightly so as to add up to the national stocks year
32
by year, a procedure probably carried out better here than by DRI, but
which is probably not a very important correction in either case
(amounting on average to only a few percent).1
The method
used here has the disadvantage
of relying
census data in generating intercensus saturation rates.
mainly
The method DRI
uses has the disadvantage of relying on the incomplete MW data.
appliance
stocks
run demand
are to be used as right
specifications,
minimizing
hand side variables
errors
on just
Since
in the short
in the data so as to
minimize errors in variables problems in the estimation is an important
goal.
The data generated here should never be too far from the truth,
since appliance stocks presumably won't deviate too far from a smooth
trend curve.
to deviate
The data generated by DRI, on the other hand, can be seen
widely
from the truth
at least
some of the time,
for reasons
discussed earlier having to do with inaccuracies and incompleteness in
the MW data.
My a priori
guess
is that the appliance
stock
data
generated here should be more suitable for use in the short-run modeling
than the DRI data, but that it would
It should
be worthwhile
be noted that the method
stock data for the short-run
analysis
to utilize
used here to generate
would
both.
appliance
not be appropriate
for
generating appliance gross investment data for the long-run analysis,
1
This correction procedure might even have undesirable results some of
the time. If the data for 49 states were perfectly correct, but for one
state were significantly in error, the correction procedure would
introduce a slight amount of error into the data for the first 49 states,
and improve
the data for the last state
only by a small
amount.
33
even if census data existed for gross investment.
reasons.
First, appliance gross investment would not be expected to
remain close to a smooth trend curve.
is not so smooth
used
There are two basic
as the original.)
as a left hand side variable
(The first difference of a series
Second,
since
in the long-run
gross
investment
analysis,
is
an attempt
should be made to retain as much of the richness in its variation as
possible.
34
C.
TECHNIQUES FOR THE DEVELOPMENT OF GROSS INVESTMENT DATA BY STATE
The development of annual appliance gross investment data by state
has been necessary for the long-run analysis of energy demand ([12 and
[8]).
Two possible methods of forming electric appliance gross
investment are examined in the first part of this section.
second method generated acceptable data.
Only the
A similar (but not identical)
method of generating gas appliance gross investment, and an additional
set of electric dryer gross investment, is discussed next.
The
construction of the original gas appliance stock data (alluded to in
section
B) is discussed
at the end of the section.
The first possible method of forming electric appliance gross
investment relies on the formula
Gt = Kt+ 1 - (1 - 6)Kt
(7)
where Gt represents annual gross investment, Kt represents annual
appliance stocks, and 6 is the estimated national appliance depreciation
rate (from section A).
(both discussed
Two possible sets of annual appliance stock data
in section
B) might
be used
in equation
(7).
These
are
examined in turn below.
Suppose the EPRI annual stock data for electric appliances are used
in equation (7).
The trouble here is that even moderate percentage
random errors in the stock data will cause quite serious errors in the
gross investment data, since annual gross investment is generally a small
percentage of the stock.
Given that the EPRI stock data are subject to a
significant degree of random error (see discussion in section B),
unacceptably
large inaccuracies
would
be expected
in at least some of the
35
gross investment data.
In fact, many of the gross investment figures
turn out to be negative, whereas by the very definition of gross
investment they should be positive.
Suppose the alternative annual appliance stock data developed in
section
B are used
in equation
(7).
This would
be inappropriate
since
these stock data were derived from only census data and annual national
stocks (in turn derived from census data and annual national shipments).
Any gross investment data generated from these stocks would thus be
devoid of any richness of variation over time in response to changes in
the right-hand
side variables
at the state
level.
The second method of constructing electric appliance gross
investment relies on the appliance sales data in the EPRI data base,
derived as follows.
As part of the annual Merchandising Week (MW) survey
mentioned in section B, electric utilities are asked to estimate annual
sales within their districts.
listed in MW's
statistical
Each utility responding to the survey is
issue, along with the number
serves and its appliance sales estimates.
and includes
it in the EPRI data
base.
of customers
it
DRI tabulates this information
For each state and year,
it
calculates the total number of customers served by utilities which report
sales for a given appliance,
and the total reported
sales
of the
appliance.
Gross investment is formed here by adjusting reported state sales by
the coverage
rate to obtain
particular,
G
ELC)
cmnsr
* S
*
an estimate
of total
state
sales.
In
36
where
served by all utilities
in the state [4]
ELCR =
customers
CUST =
customers served by utilities reporting sales of the
S =
appliance
[4]
reported
state
[4].
sales of the appliance
The gross investment data thus formed, although probably not terribly
accurate, are judged to be superior to those formed using the first
method.
In using the gross investment
the long-run
demand specifications,
stochastic nature.
data as left-hand
side variables
their
it is useful to examine
Two sources of inaccuracy exist.
companies do not know appliance sales exactly.
in
First, utility
Second, not all utilities
respond to the survey, with coverage varying widely among states and
All observations where coverage is less than 10% were thrown out
years.
of the sample, including some observations where coverage is actually
Among the remaining observations, those having higher coverage
zero.
rates
are presumably
variations
results
on the average
in the accuracy
more
accurate.
of the data is given
A simple
in Appendix
of this model might be used as part of an attempt
model
2.
of
The
to correct
for
heteroscedasticity.
The raw data for gas appliance
and alternate
electric
dryer
gross
investment comes from GAMA [7] for gas ranges and water heaters and from
AHAM [1] for gas and electric dryers.
These organizations report annual
manufacturers' shipments to the various states.
Coverage is not complete
(especially for the GAMA data) since not all manufacturers report their
37
state by state shipments.
In order to form gross investment data, the sum of reported state
shipments
was divided
by national
shipments
national coverage rate for each year.
(from MW) to obtain
a
Reported state shipments were then
divided by national coverage rates to generate the gross investment
data.
Potential errors clearly remain.
ships to a large number of states,
much
among states,
and the errors
Still, if each manufacturer
actual coverage
might
rates might
not be very bad.
not vary
The problem
is
bound to be much less for dryers (where coverage rates are very close to
one) than for ranges and water heaters (where coverage rates vary from
.55 to .80).
The gas appliance gross investment data described above were used to
generate
section
the original
B.
gas appliance
stock
data
The first step of this process
(by state)
(8)
Nt represents
appliance
value,
stocks.
annual net investment
The 1960 stock
and equation
to 1974.
There
to in
uses the formula
Kt+ 1 = Kt + Nt
where
alluded
and Kt represents
(K1 9 6 0)
is set equal
(8) is used recursively
are two possible
methods
to generate
of forming
annual
to the census
stocks
annual
from 1961
net investment.
In the first method,
Nt = Gt * PNt
(9)
where Nt and Gt are annual
PN t is an estimate
net and gross
of the percentage
investment
of national
(by state)
sales
and
of the appliance
which are new purchases rather than replacement purchases (from
Merchandising Week [10] ).
Equation (8) thus becomes
38
Kt+1 = Kt + Gt * PNt
(10)
In the second method,
Nt = Gt -6 Kt
where
6
(11)
is the national appliance depreciation rate calculated in section
A, so that equation
(8) becomes
Kt+1 = (1 - 6)Kt + Gt .
Each method
(12)
has the disadvantage
the national level.
of relying
on a parameter
at
estimated
The first method has the additional disadvantage
that equation (9), and hence equation (10), holds exactly only if all
appliances which deteriorate are actually replaced.
It appears that the
second method would be at least slightly preferable for this reason.
However,
this difficulty
was the one actually
Before
was not thought
of in time,
and the first method
used.
proceeding
to the second
step,
it is interesting
to look at
the ratio of the 1970 stocks generated in the first step to the
corresponding census values.
closely
The extent to which these ratios cluster
to one is a joint test of the accuracy
of the gas appliance
investment data G t and the procedure relied on in the first step.
results are presented in Table 4.
gross
The
It should be noted that the way
national depreciation rates were calculated in section A ensures that the
average of the ratio across states (weighted by 1970 census stocks)
should equal one when the second method is used.
reasonable.
The results seem
There are two possible reasons for deviation of the ratios
from one; inaccuracies in the gross investment data Gt, and
inaccuracies or variation among states in the national parameters PNt
and
.
It turns out that for method
1 there
is a very strong tendency
39
TABLE 4:
RATIOS OF FIRST STEP 1970 GAS APPLIANCE STOCKS
TO 1970 CENSUS GAS APPLIANCE STOCKS
Number of states with ratios between
Appliance
1.00
1.20
1.20
1.50
1.50
2.00
2.00
3
24
20
1
0
5
15
24
1
2
2
5
20
17
8
0
0
0
0
2
7
14
14
10
3
0
0
1
1
20
20
4
1
3
0
1
7
17
21
4
0
0
.0
.50
.50
.67
.67
.83
1
1
0
1
0
0
.83
1.00
gas ranges
method
1
gas water heaters
method
1
gas dryers
method
1
gas ranges
method 2
gas water heaters
method
2
gas dryers
method 2
40
for states with ratios much below (above) one to be those with the
highest (lowest) growth rates for a particular appliance.
presumably
rapidly,
because
a greater
in a state where
fraction
the stock of an appliance
of retail
sales
is for new rather
replacement investment compared to the national average.
the national
figure PNt in equation
This is
(10) should
is growing
than
Hence, use of
lead to an estimated
1970 state stock that is too low.
The first step gas appliance
the 1970 census stocks.
D.)
stock
estimates
are now benchmarked
to
(For a discussion of benchmarking, see section
For stock estimates derived from gross investment figures (as here),
benchmarking should be quite effective in improving the quality of the
data.
The original gas appliance stock data used in the short-run demand
specifications [13] are the benchmarked method 1 first-step estimates
equation (10)).
procedure
adjust
Another (significantly less important) correction
which might
have been
the annual state by state
carried
out (but wasn't)
would
be to
stocks to make them add up to the annual
national gas appliance stocks calculated in section A, using one of the
methods discussed in section B.
41
D.
BENCHMARKING TECHNIQUES
A short discussion of the benchmarking techniques utilized in
sections
B and C is given here.
of benchmarking
The basic purpose
data
source by the use of census
data.
is the improvement
For example,
of a yearly
raw
let K 0 through
K14 represent appliance stocks (or saturation rates) for a state from
1960 to 1974, calculated from a raw data source and assumed to be
imprecise due to inaccuracies or incompleteness in the raw data source.
C0 and C1 0 are the 1960 and 1970 census
assumed to be reasonably accurate.
stocks
of the appliance,
The object is to obtain corrected
stocks KC0 through KC14 which correspond to the census stocks CO
and C 1 0
in the census years.
A graphical
illustration
of how benchmarking
works
is given
in
Figure 4.
Two possible benchmarking techniques are presented algebraically
below.
The first method defines corrected stocks as
KCt = (et)Kt.
a and
, defined so that corrected stocks equal census stocks in the
census years,
are equal to
CO
0
B = In ln(-/
)
10
o
The second method defines corrected stocks as
KCt = (
+
t)Kt.
Again, a and y are defined so that the corrected stocks equal census
42
Kt,
KCt
10
0
Figure 4:
A Graphical Illustration of Benchmarking
* original stock estimates Kt
x census
stocks
C
and C 1 0
o corrected stock estimates KCt
t
43
stocks
in the census years;
here they
are equal to
CO
Y
_
1 ( C10
10
CO
o
o0
Benchmarking in sections B and C was always carried out using the first
method.
In constructing the EPRI data base, DRI used both methods at
various times [3].
not too different
Note that if the ratios Co/Ko and C 10 /K1 0 are
from 1.0 (which will be the case if the Kt series has
any accuracy whatsoever) then the benchmarked stocks KCt will be
extremely
similar
(for all t) using
the two different
methods.
Thus
it
makes very little difference which benchmarking method is used.
It should be noted that benchmarking a series of stocks or
saturation rates may or may not significantly improve the accuracy of the
series, depending on how systematic the existing inaccuracies in the
series are over time.
Suppose
the original
stocks
This is illustrated algebraically as follows.
stock estimates
Kt are related
to the actual
C t by the formula
K t = (1 + a + bt + nt)Ct
where a, b, and nt are assumed small to simplify the algebraic
development.
the original
KtC
Ct
t
Rewriting the last equation, the percentage inaccuracy in
stock estimates
= a + bt + n
is given
by
44
The systematic portion is represented by a + bt, and the random portion
by the error term nt.
The second benchmarking scheme outlined earlier
defines corrected stocks KCt by
KCt = ( + yt)Kt.
To evaluate a
and Y, note that
Kt
(1 - a - bt - nt)Kt
1 + a + bt + nt
t
where second order terms have been ignored by assumption that a, b, and
Tt are small.
and
c
Y
are thus given
by
Co
= K0
1-
a-
nO
) -b-10-10
= (K o :Y
1
C10
Co
K10
K0
no
10
It follows that
KCt = (
(1
-
+t)Kt
-no-
10
-
aO]
10
[1
+
where second
t
-
nlO)-
n(
t-
order terms
It)(1 + a + bt + nt)Ct
)]Ct
1010
t
in a, b, and nt have once again
Rewriting the last equation,
KC t C
Ct
t
T-
t -
o(110--
10 - t
o(
10
10
been ignored.
45
Assuming the random error terms nt are independent over time with
expectation zero, the inaccuracy of the benchmarked intercensus stock
estimates is characterized by
KCt - C
) =[1
var(
t
+ ()
2
2
+ (
10
The inaccuracy of the original stock estimates is similarly characterized
by
K
var(
Comparing
- Ct
t
)
2
2 +
(a + bt)
the two variances
above,
2
it is seen that benchmarking
eliminates (more generally reduces) systematic inaccuracies in the
original stock estimates, but actually increases random inaccuracies.
The algebraic development in the above paragraph illustrates the
intuitively reasonable statement that benchmarking is more effective in
improving the quality of a yearly raw data series, the more systematic
are the existing inaccuracies in the series over time.
Consider now
DRI's benchmarking of the Merchandising Week appliance saturation rates
(discussed in section B).
Suppose that in state A one particular utility
always responds to the survey, but none of the others does.
Benchmarking
will probably be reasonably helpful for such a state, since the major
reason for inaccuracy in the state saturation rate estimates might be
that saturation rates in the part of the state serviced by the reporting
utility are always high or low compared to other parts of the state.
Suppose that in state B each of three utilities reports some of the time,
and that they all have significantly different saturation rates for a
46
particular appliance.
Then inaccuracies in the state saturation rate
will be random over time (depending on which utilities report in a given
year) and a simple benchmarking scheme might not improve the data very
much.
47
Conclusions
In section A, national depreciation rates are estimated for the
various electric and gas appliances.
interest for two reasons.
Appliance depreciation rates are of
First, appliance stocks Kt are related to
appliance gross investment It through the formula
Kt+1 = It + (1 -6 )Kt.
Second,
the depreciation
(1)
rate of an appliance
is closely
related
to its
average lifetime, which in turn affects the annualized capital cost of
owning the appliance.
Appliance depreciation rates are calculated by
solving the equation
9
K1 0 =
:
It(1
6)9-t
+ (1 -6
10
K0
(2)
t=O
for
, where K
national
and K 1 0 are census
shipments
for the years
stocks,
and It represents
in between.
A careful
theoretical
discussion follows the empricial results, concerning the relationship
between calculated depreciation rates and average appliance lifetimes.
It is shown that the reciprocal
should equal the average
of the calculated
appliance
lifetime,
depreciation
if either
rate
the actual
depreciation pattern is exponential (geometric decay), or in the steady
state situation
that the gross
constant over time.
investment
and stock
of the appliance
are
For an appliance with a realistic depreciation
pattern, and whose numbers are increasing over time, the reciprocal of
the calculated depreciation rate will exceed the actual average appliance
lifetime.
National depreciation rates calculated from equation (2) are
thus of questionable value in computing average appliance lifetimes.
48
On the other hand, they are quite appropriate for use in equation (1) to
convert between stocks and gross investment, and are used for this
purpose in sections B and C.
(1) is used to calculate
Finally, at the end of section A, equation
accurate
annual national
appliance
stocks.
In section B, annual appliance stock data by state are discussed and
DRI [3] generates data for the electric appliances by
developed.
benchmarking the Merchandising Week saturation rate survey data to census
of gas appliance
appliance
One set
Two sets of data are generated in this study.
saturation rates.
stock data, discussed
gross investment
of data for both electric
in section
data by use of equation
and gas appliances
C, is derived
from gas
An alternate
(1).
is generated
set
a
by fitting
special type of time trend through census saturation rates.
Correction
procedures to ensure state stocks sum to national stocks are employed in
both the DRI data and the alternate data here.
The correction procedure
here is better (although more complicated) that that used by DRI, but in
neither
case is it judged
to be of primary
importance.
All three
sets of
stock data are judged suitable for use, but differ widely in their
undesirable aspects.
The DRI data have the advantage of being formed in
a direct manner, but the accompanying disadvantage of containing some
relatively large random errors due to incompleteness in the raw data
source.
The alternate set of data here should be devoid of large random
errors at the expense of being formed indirectly through a type of
trending procedure.
data to the other.
There is no definite reason to prefer one set of
However, since appliance stocks are to be used as
right-hand side variables in the short-run demand specifications,
49
minimizing erros in variables problems in the estimation might favor the
latter set of data.
In section C, annual appliance gross investment data by state are
discussed and developed.
The first method considered, which does not
generate acceptable data, forms gross investment from stock data by use
of equation (1).
The trouble is that even moderate percentage random
errors in the stock data will cause quite serious errors in the gross
investment data.
procedure
Also, if the stock data are derived by a trending
so as not to have significant
random error,
the gross
investment data will be devoid of the richness of variation that would be
expected and ought to be retained for their use as left-hand side
variables.
As a general
data directly.
rule,
it is better
to generate
gross
investment
Data for the electric appliances are derived from
Merchandising Week sales survey data tabulated by DRI [3].
Data for gas
appliances and an additional set for electric dryers are derived from
manufacturers' shipments data compiled by AHAM [1] and GAMA [7].
sets of data are judged
primarily
acceptable
by the coverage
Section
D gives
rates
a brief
for use, their
of the raw data
description
utilized in sections B and C.
accuracy
These
limited
sources.
of the benchmarking
techniques
An algebraic argument illustrates the
proposition that benchmarking is more effective in improving the quality
of a raw data series,
the more
in the series over time.
systematic
are the existing
inaccuracies
The probable effectiveness of DRI's
benchmarking the Merchandising Week appliance saturation rates is then
discussed.
50
REFERENCES
1.
Association of Home Appliance Manufacturers, "Home Laundry
Appliance Sales by Distributors - States," annual mimeo, 1960 to
1975.
2.
Ralph Braid [1978], forthcoming MIT Energy Laboratory Report.
3.
Data Resources, Inc. [1977], The Residential Demand for Energy
Using Capital, Electric Power Research Institute Report #EA-235,
January.
4.
Data Resources,
5.
Thomas A. Domencich and Daniel McFadden [1975], Urban Travel
Demand: A Behavioral Analysis. Amsterdam: North Holland
Publishing Company.
6.
Franklin M. Fisher and Carl Kaysen [1962], A Study in
Econometrics: The Demand for Electricity in the U.S. Amsterdam:
North Holland Publishing Company.
7.
Gas Appliance Manufacturers' Association, "Gas Appliance and
Equipment Shipments by State and Export," annual statistical
release, 1960 to 1975.
8.
Raymond S. Hartman [1978], A Critical Review of Single Fuel and
Interfuel Substitution Residential Energy Demand Models, MIT
Energy Laboratory Report #MIT-EL 78-003, March.
9.
Jerry A. Hausman [1978], Consumer Choice of Durables and Energy
Demand, MIT Energy Laboratory Working Paper No. MIT-EL 78-003WP.
Inc. [1977],
the data base for [3], computer
tape.
10.
Billboard Publications, Inc. Merchandising Week, now called
Merchandising, annual Statistical & Marketing Report issue,
February or March.
11.
Billboard Publications, Inc. Merchandising Week, November 10,
1975.
12.
U.S. Department of Commerce, Bureau of the Census, 1960 Census of
Housing and 1970 Census of Housing.
13.
Alix Werth [1978], forthcoming MIT Energy Laboratory Report.
51
APPENDIX
1
No acceptable set of gross investment data for household heating
equipment has yet been developed.
The main reason is that the data
collection efforts were concluded before we had a clear idea of exactly
what raw data should be obtained.
The following discussion outlines some
of the problems encountered in trying to construct gross investment data
for household heating equipment, and some of the possible solutions.
Many parallels should be noticed with the earlier discussion of appliance
data (Sections A through C).
The calculation of national depreciation rates for household heating
equipment has not yet proved possible.
To construct a national
depreciation rate, it is necessary to have census stock data for 1960 and
1970, and national shipments data for the years in between.
but the categories do not necessarily correspond.
Both exist,
The Census of Housing
[12] breaks down household heating equipment in two ways, by heating fuel
and by method of heat distribution (steam or hot water, warm air furnace,
etc.).
The Hydronics Institute and Current Industrial Reports1 list
annual national shipments for some finely divided sub-categories (for
example, oil-fired forced air furnaces).
Not all sub-categories are
covered, however, and it is not obvious that they may be aggregated to
obtain the categories in the census.
Annual stocks (by state) of household heating equipment by heating
fuel are estimated
1
by DRI [ 3] and included
in the EPRI data
base [ 4
Bureau of the Census, "Selected Heating and Cooking Equipment,"
Current Industrial Reports, Series MA-34N.
1
52
Electrically-heated houses and gas-heated houses are estimated directly,
while oil-heated houses and houses heated with other fuels are generated
from the residual (total minus electricity minus gas).
The data for
electrically-heated houses and gas-heated houses seem much superior to
the EPRI appliance stock data discussed in Section B.
The data for
oil-heated houses and houses heated with other fuels are probably
somewhat weaker, since they are estimated from a residual.
One way to generate gross investment data by state for household
heating equipment might be to follow the first procedure discussed in
Section
C.
Namely,
let
Gt = Kt+ 1 - (1 - 6)Kt
where Gt represents annual gross investment, Kt represents annual
stocks, and 6 is the depreciation rate.
would ideally be estimated
using equation (2) of Section A, but (as just mentioned) this has not yet
been possible.
results
should
Alternatively, a depreciation rate might be assumed.
not be as bad here as in Section
C, since
The
the EPRI
household heating equipment stocks have less random error than the EPRI
appliance stocks.
Still, even a moderate degree of random error in the
stock data would be expected to manifest itself seriously in the gross
investment
data.
In fact,
if a depreciation
each fuel 1 , the gross investment
figures
rate of 4% is assumed
for
turn out to be virtually
all positive for total houses, electrically-heated houses, and gas-
1Four percent seems somewhat high for a steady state depreciation rate
for household
heating
equipment
(I think).
However,
for a fuel such
oil, whose share is declining over time, the actual depreciation rate
might very well be above 4%
(see discussion
in Section
A).
as
53
heated houses, but many turn out to be negative for oil-heated houses.
The presence of negative gross investment figures in addition to the use
of an arbitrary depreciation rate make this set of data unacceptable.
The ideal way to generate gross investment data for household
heating equipment would be to do it directly, using one of the methods in
Section C which generated the appliance gross investment data in Tables
25-34.
This would mean using estimated annual sales or manufacturers'
shipments data by state.
Manufacturers' shipments data by state are
available for gas-fired household heating equipment from GAMA [7].
Sales
or shipments data for electric and oil household heating equipment, which
I am currently unaware of at the state level, might very well also exist.
54
APPENDIX
2
The following model examines the stochastic nature of the
electric1 appliance gross investment data generated in section C.
In order to compare the accuracy of different observations
characterized by different reporting rates, it is necessary to make a
number of simplifying assumptions, which although somewhat unrealistic
hopefully capture some of the essence of the problem.
Suppose all
utilities are of the same size, which is assumed sufficiently small that
there are many in each state.
Appliance sales for utility i in a given
state have a true value of p + ni, where
the utility reports a value p +
i +
n i is a random
.i,where
variable,
but
i is a random error
term indicating the utility does not know sales in its region with
certainty.
possible
Suppose M utilities report to the MW survey out of a total
N.
Total reported
sales will
M
S
be
M
)=i
E']
: (+
M
+
i=l
i=l
i
i=l
Dividing reported sales (S) by the coverage rate (M/N) yields estimated
state gross investment
(G)
M
G = Np +
M
ni +
i=l
Actual
1
gross
investment
Unfortunately,
E
i
i=l
is given by
gas appliance
data are not as easily
characterized.
55
N
Go
N
ni) = Np+
(P+
=
ni
The difference is
M
M
G - G=
C-
)n+
i=1
N
E
1
-
i=1
i
i=M+1
Assuming independence of all random terms, the variance of this is
Go)
E[G
N -1)
=N
M( - 1)2a + M)
2 +N
2 + (N - M)
r2
and rearranging terms slightly shows that
2
= N[(1
+
~~n
a2
2-
I
(13)
n
Some assumption must be made about a2, a(2.
suppose the ratio is one.
For example,
Then equation (13) becomes
2
a 2
[C
-
n
where CR = M/N is the coverage ratio.
The N outside the brackets has the
obvious significance that gross investment estimates have higher variance
for larger states (coverage rates equal).1
1
If expressed
in terms of gross
investment
replaced by 1/N, since
var
(G - G)/N
= -var(G - GO)
N
The term inside the
per capita,
the N would
be
56
brackets shows how the variance depends on the coverage rate.
coverage
rate of 1/4,
rate of 3/4.
it is about four times
For a
as large as for a coverage
57
APPENDIX 3: THE DATA BASE
This section provides printouts of those series discussed or
developed in sections B and C that were considered appropriate for
utilization in the short-run analysis of energy demand ([13] and [8]), or
the long-run analysis of energy demand ( [ 2 ] and [8]).
These printouts
are designed to be easily readable; hence in many cases the figures in
the actual data base were rounded off.
In each table, states are
numbered in alphabetical order, a listing of which is provided in Table
5.
The data are presented
here in the same order
as discussed
in the
text, as follows:
Tables 6 to 13 - annual electric appliance stock data from EPRI [41
Table 14 - housing stock data from EPRI [4]
Tables 15 to 24 - alternate annual stock data for both electric and
gas appliances, derived from census [12]
Tables
25 to 30 - annual electric
appliance
gross
investment
and
coverage rates, derived from EPRI [4]
Tables 31 to 34 - annual gas appliance and alternate electric dryer
gross investment, derived from GAMA [7] and AHAM [1]
Tables 35 to 37 - original annual gas appliance stock data, derived
from GAMA [7] and AHAM [1].
Each group of series and the data sources used to derive it are outlined
in more detail immediately before the series are listed.
For the most
complete discussion of the series, however, refer back to sections B and
C.
58
TABLE 5:
AN ALPHABETICAL LISTING OF THE STATES
1
Alabama
2
3
Alaska
Arizona
4
Arkansas
5
6
7
California
Colorado
Connecticut
8
Delaware
9
10
11
12
13
14
15
16
Florida
Georgia
Hawaii
Idaho
Illinois
-Indiana
Iowa
Kansas
17
18
Kentucky
Louisiana
19
20
21
22
Maine
Maryland and the District
Massachusetts
Michigan
23
Minnesota
24
Mississippi
25
26
27
28
29
30
31
32
33
34
35
36
Missouri
Montana
Nebraska
Nevada
New Hampshire
NeW Jersey
New Mexico
New York
North Carolina
North Dakota
Ohio
Oklahoma
37
Oregon
38
39
40
41
42
43
44
45
46
47
48
49
50
Pennsylvania
Rhode Island
South Carolina
South Dakota
Tennessee
Texas
Utah
Vermont
Virginia
Washington
West Virginia
Wisconsin
Wyoming
of Columbia
5g
TABLES 6-13:
EPRI ANNUAL STOCK DATA FOR THE ELECTRIC APPLIANCES
These series come directly from the EPRI data base [4].
basic sources
of raw data used
in their
construction
The two
are Merchandising
Week [10] and the U.S. Census of Housing [12].
See section B for further discussion.
TABLE 14:
EPRI ANNUAL HOUSING STOCK DATA
This series comes directly from the EPRI data base[ 4].
It is used
throughout the paper to convert between appliance stocks and appliance
saturation rates.
60
6
TABLE
STOCK
OF RFFPTGERATORS
(THOUSANDS)
STATE
YEA4
60
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
P0
61
1059 1060
62
59
3A7 410 427
540
665
597
5238 5371 5474
583 606
551
918
59
774
793
312? 3213 3283
1430 1507 1506
932
913
861
767 765
695
907 953
879
954 952
929
299 299
29)
22
23
2331
1016
24
25
26
27
28
29
30
31
32
13
34
35
36
37
38
39
40
41
42
583
1410
203
446
95
186
1849
262
5371
43
?939
44
45
46
251
114
117
1113 1156
49
50
1244
178
2945
767
581
3437
267
628
199
1035
63
64
65
66
67
68
69
70
71
1060 1053 1048 1060 1070 1078 1097 1074 1078
59
85
74
83
78
69
68
70
70
448 462 470 483 504 518 542 566 613
693 698 702 639 65r
716 713 670 698
5739 qg9 5155 6432 6539 6636 6707 6797 6940
634 638 644 652 650 677 690 713 748
909 931 952 969
827 840 860 876
151
165 166 169 173
145 147 151
158
1852 1917 1984 2043 2120 2199 2284 2395 2526
1193 1214 1269 1266 .13-1 1394 1419 1422 1450
163 174 180 185 189 194 202 209 215
211
213 215 21R 220 226 235
191
211
3350 3393 3428 3492 3519 3550 3594 3621 3624
1548 1561 1581 1610 1620 1649 1653 1664 1682
933 931 921 913 912 922 916 923 928
772 774 769 762 751 757 753 750 754
1023 9R9 1009 1035 1051 1069 1079 1021 1079
987 1019 918 1053 1055 1087 1095 1103 1129
299 291 299 303 304 305 305 312 318
1271 1333 1374 1388 1410 1432 1468 1481 1515
1680 1682 1698 1712 1737 1776 1788 1804 1823
1243
1531
2367 2380 2419
1059 1069 1076
607
615 613
1534 1530 1528
187
210 186
475 494 477
103
138
113
188
208
190
1848 1922 1965
273 ?82
303
5439 5456 5343
1417 1428 1438
189
192 189
3084 3106 3153
781
775 789
604 6?5
570
3481 3494 3512
268
263 271
657 660 687
209
205 211
1057 1076 1106
3142 3221
259 268 276
1153 1217
1581 1621
48
R02
134
138
139
1659 1718 1790
1109 1136 11.38
161
157
165
206 207
201
?1
47
62
2461
105
640
2521 2575 2609 2655
1082 1111 1128 1151
654
15~1 1576
226
185
481
476
148
148
2n8 210
2033 2084
310 309
56P6 5729
1473 1488
197
198
31R7 3232
819 833
653 672 632
1585 1583 1592
226 222 223
490 483 476
148 152 156
225
214 21
2135 2174 2228
302 297 299
5788 58;6 5937
1513 1528 1563
165 193
197
3756 3281 3320
837 849 883
72
1093
87
667
73
74
1137 1139
96
94
7?3 756
713 721
7122 7?74
851
802
985 1004
181
176
2662 2857
1468 1513
224 232
244 254
3684 3740
1693 1717
923 923
753 757
721
7435
884
1017
183
2974
1532
241
262
3772
1643
923
752
1145 1164
1175 1185
339 329
1562 1603 1654
1854 1 S87 1905
2696 2731 2782 2836 2892 2931
1154 1181 1197 1203 1216 1245
715 745 799 814
634 661
1587 1588 1603 1612 1624 1527
217 226 23? 237 243 249
;57
478 491 502 483 507
166 173 183 196 200
160
228 232 244 250 256 263
2222 2257 2341 2387 2448 2483
305 315 328 345 352
300
5995 6026 6008 6095 6169 6144
154? 1559 1601 1613 1656 1673
188 194 198 201 204
193
3351 3379 3409 3467 3511 3548
849 896 92? 937 9R6 1001
R23
698 714 747 771 A04
3770 3786 3837 3877 3930 3976
651
638
659 6b5 683
3534 3612 3677 3716 3735
283
292 297 300
286 258
280
711
6?8
729 732 747 751 766
207 207 207 206 206 206 207
11 4 1138 1167 1191 1214 1233 1256
3313 3429 3457 3511 3554 3553 3625
279 284 289 290 293 296 304
128
131
120
136
122
124
133
117
118
11 96 1230 1262 1292 1318 1347 1376 1409 1432
1 n 10 1033 1013 1046 1062 10~4 1113 1139 1161
.53 548 544 542 537 559 562 561 565
1111
1152
325
1305 1332
3720 3791
313 326
311
803 813
215 205
1378 1424
3932 3955
343 355
137
139
1490 1533
143
144
158
1631
1 ?23
303
307
788
211
785
210
309
1163 1183 122
568 582 590 593
1176 1308 1310 1318 ]-43. 1349 1354 1346 1361 1348 1357 1346 1419 1435 1445
109 105 103 108 111 112 111 121
103
111
120
111
112
112
110
942
540
986
568
61.
TABLE
STOCK OF HOmE FREEZERS (THOUSANDS)
7
YEAR
STATE
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
1
2
3
4
177
15
69
116
212
17
83
143
P30
22
101
170
242
28
101
206
239
27
107
230
243
25
107
183
273
26
115
176
302
26
106
219
329
27
114
228
323
28
122
236
428
34
130
245
498
40
144
25
414
36
145
186
469
47
144
?20
502
56
169
233
5
839
926
g94
1103 1130 1209 1270 1310 1506 1424 1481 1504 1965
1607
6
7
8
9
10
11
]2
13
136
101
27
210
222
29
78
533
150
114
33
228
230
29
84
739
193
117
32
210
233
29
87
791
216
131
37
226
364
30
95
444
202
141
58
248
396
36
102
308
188
174
55
212
474
35
90
601
214
1R7
57
260
668
39
95
704
255
191
48
27b
603
42
97
791
257
168
61
268
645
37
104
824
240
188
49
295
699
41
114
953
243
296
203
22?
50n
47
508
478
500
748
43
5n
118
125
991 1051
14
345
360
368
437
411
416
464
475
508
546
550
541
605
629
665
15
16
17
18
19
20
263
161
150
2?4
46
78
289
159
205
272
46
95
?94
177
181
P89
48
109
327
158
192
338
48
146
375
166
200
378
39
189
367
206
203
382
71
215
370
214
213
406
81
243
374
214
232
435
80
277
354
236
239
449
81
293
386
251
345
416
75
427
393
275
314
439
78
363
405
280
287
456
86
379
421
286
310
481
86
403
451
301
385
5?2
97
417
453
302
489
512
97
460
21
115
109
123
128
146
160
175
189
197
211
237
253
317
3q7
419
22
23
448 482
3?22 341
511
362
493
379
532
510
639
505
686
504
709
549
718
531
786
521
797
513
862
518
894
473
934 1036
485
564
24
25
145
284
i49
316
136
133
135
417
176
369
162
372
200
393
193
410
349
448
302
465
305
519
330
506
352
527
382
548
389
567
26
27
-78
136
89
151
89
166
90
168
90
174
110
183
111
193
112
198
113
201
113
209
114
218
128
228
133
245
136
263
157
305
28
20
26
33
42
49
34
49
47
49
45
44
45
48
51
29
30
31
32
33
?5
216
61
514
272
28
264
71
566
346
32
289
69
669
394
42
43
46
41
310 436
406
388
59
73
75
92
969 1123 1176 1368
5S6
601
491
511
50
368
96
911
541
51
402
104
978
590
70
478
109
995
623
1006
42
45
309
312
65
65
686 1404
475
416
329
390
428
383
239
378
h6
74
50
642
549
592
755
831 1667
52
55
55
130
135
140
948 1000 1048
51459
109
953
667
54,
57
86
468
492
130
133
1610 1694
650
718
148
150
1033 1073
1089
137
34
81
103
115
110
94
125
100
146
110
118
35
547
652
667
737
779
780
847
879
935
973
977
1011
36
142
142
163
'190
213
234
227
221
276
267
277
286
292
459
466
37
38
39
40
189
527
14
130
218
565
20
143
?25
611
20
145
273
656
10
166
334
673
11
166
368
751
12
183
370
737
12
204
414
792
20
215
272
838
27
239
297
865
31
255
331
893
33
271
35n
909
34
287
480
914
38
295
545
810
53
329
598
817
60
362
96
101
98
106
112
101
195
184
98 .106
41
74
84
91
93
106
116
108
42
43
44
45
46
217
639
65
24
202
228
72
76
22
217
230
767
76
40
218
249
270
818 1130
88
83
48
36
220
280
280
910
94
42
281
315
967
100
60
292
512
516
590
408
443
468
509
351
999 1147 1145 1149 1204 1333 1380 1289
175
199
190
102
116
115
119
168
116
124
125
73
41
47
13
92
396
358
370
485
292
328 422
419
47
249
293
301
315
317
338
365
401
426
480
483
53I
515
550
48
86
121
108
112
113
129
139
153
157
152
158
169
17?
174
177
49
3?6
373
415
437
451
404
453
430
556
476
541
559
590
593
623
50
36
53
39
70
66
67
82
55
58
57
53
52
82
46
80
564
62
TABLE
(THOUSANDS)
STOCK OF ROOM AIR CONDITIONES
8
YEAR
STATE
61
60
52
63
74
73
72
71
70
69
68
67
66
65
64
171
208
?18
277
268
296
303
354
405
314
513
587
511
539
552
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
51
P4
449
26
57
25
336
150
2
12
472
128
194
218
84
58
101
522
20
70
31
384
173
1
16
517
149
113
256
79
65
132
;82
75
55
33
472
173
2
18
502
161
124
286
80
79
75
187
155
923 IOn8
06
79
P9
69
43
40
682
483
187 239
2
2
17
15
838
632
218
236
1R7
148
294
264
161
110
18
1
2
103
117
128
108
96
93
88
7
78
88
282
277
249
299
280
175 198
118 218
121
977 1424 1556 1656 1061 1331 160n 1460 1553 1593
194
264
147
108
92
68
141
94
82
71
620
612
367
331
310
160 258
154
138
113
102
96
102
90
86
81
64
52
53
45
814 981 1011 1287 1385 1479 1534 1719
836
722
973
878
640
617
550
868
617 708
533
397
38
34
34
32
29
24
21
9
7
5
52
48
49
3?
27
24
19
16
13
11
915 1060 1321 1265 1379 1561 1667 1660 1792 1905
548
585
550
533
473
394 433
251
266
247
329
329
352
343
297
292
243 257
227
171
336
386
397
395
383
359
337 344
323
307
417
403
371
360
343
253
260
P22 244
172
682
267
320
433
408
500
507
559
614
676
622
673
705
732
790
19
3
5
6
5
5
15
15
13
11
11
9
8
9
12
14
20
91
89
133
149
151
176
201
232
359
258
429
460
489
520
568
21
22
23
24
95
123
61
111
98
145
84
92
116
147
92
100
140
138
87
102
122
172
75
171
127
223
156
192
168
287
166
260
194
318
23/
25H
258
395
314
259
342
432
322
301
402
514
331
339
444
52'
356
460
491
498
423
506
559
533
431
578
601
617
447
619
25
264
332
351
403
335
354
412
457
522
558
627
679
714
735
720
26
27
P8
29
30
31
32
7
98
6
6
348
17
682
6
117
6
6
355
23
770
7
134
6
7
389
65
877
18
134
18
7
465
R3
675
23
147
18
7
606
93
9S4
30
32
169
118
23
18
23
10
761
603
89
92
898 1014
33
118
160
185
205
249
247
284
?86
488
56?
34
35
36
37
38
3
216
267
21
393
7
237
280
41
458
7
266
287
52
531
7
337
367
68
557
7
398
341
85
487
20
419
336
89
466
22
490
328
88
628
20
22
27
21
791
751
608
453
488
318 468
441
61
53
55
80
757 1022 1166 1308
4
847
534
65
1384
39
40
13
83
24
96
18
119
19
132
20
140
24
157
27
180
27
207
50
305
51
302
24
17
19
21
25
215
201
192
193
159
73
26
25
24
22
52
25
20
19
21
906 1210 1305 1378
856
59
66
4R
40
78
862 1277 1725 2343 2683
349
34
274
477
47
287
41
14
20
32
33
43
45
51
41
48
47
52
5q
42
256
317
344
435
472
561
513
452
554
678
705
758
43
44
1055 1215 1338 1305 1147
29
25
27
16
17
37
33
243
241
90
R8
73
69
925
9?8
74
73
62
19q2 1271 1127
32
229
83
54
868
600
596
39
39
972
952
415
544
128
70
1265 1394
50
939
421
148
1430
74
307
82
318
608
55
305
65
52
842
920
76
993
2058
1380 1413 145r 1585 1818 2051 2087 2047 21?2
75
69
59
50
52
55
39
36
44
47
45
2
3
4
3
3
2
2
7
6
8
6
8
7
8
8
46
47
48
49
140
30
34
62
166
27
93
74
182
32
32
69
227
50
45
77
230
33
149
q4
232
33
151
116
233
40
89
146
264
51
102
154
339
60
89
180
535
75
97
271
535
79
105
283
597
89
121
307
520
84
123
397
538
108
125
346
553
108
126
376
50
4
5
5
6
5
5
5
3
4
4
9
5
10
10
10
63
rARqL
9
STOCK
OF ELECTRIC
RANGES
;TATE
(TH3USANDS)
YEAR
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
1
441
513
551
590
545
586
601
599
629
626
614
625
628
659
671
2
3
4
30
73
72
33
77
79
35
104
88
42
114
107
41
125
101
42
133
121
42
143
109
43
177
144
47
184
129
45
195
131
48
209
139
54
241
160
55
282
151
67
2q99
177
68
327
186
5
937 1131 1133 1252 1477 1495 1685 1821 1874 1963 2078 2789 2?22 2491 2591
6
179
194
223
243
265
294
318
321
342
355
7
324
372
348
413
346
367
462
303
442
462
553
458
565
479
504
528
541
553
649
658
8
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616
5be
507
472
414
413
388
366
361
?3
24
562
188
528
202
462
190
357
57
365
156
301
86
241
58
359
72
34?
174
224
149
304
86
189
8A
143
67
25
97
48
98
49
634
666
609
556
507
419
391
347
308
268
267
26
27
?8
17010162
16
78
216
13
79
208
24
163
163
54
211
38
86
192
34
209
209
9
136
14
29
172
27
27
151
20
24
170
2
25
126
2
22
92
3
27
82
3
17
15
22
12
11
22
16
90
19
17
14
20
?9
69
69
69
69
57
45
45
34
23
17
17
14
15
12
13
30
31
32
500
71
931
429
46
417
337
28
439
314
19
694
221
28
729
282
35
763
246
29
797
192
31
382
33
232
24
391
479
153
22
325
560
124
33
300
575
591
588
602
254
205
107
31
282
172
111
34
339
176
144
33
335
180
86
34
394
183
185
211
280
115
126
99
122
116
138
132
133
1279 1180 1154 1216 1177 951
853
809
204
128
107
78
103 235
168
148
151
138
100
121
110
105
86
82
1572 1591 1l8O 1555 1570 1221 1126 1051
68
48
41
57
50
44
38
19
176
122
121
100
62
63
64
54
121
176
167
187
144
110
134
46
131
718
129
62
869
20
64
51
124
690
81
60
887
19
64
56
56
582
65
49
735
19
65
61
37
631
67
47
531
1
66
63
88
604
23
707
16
66
74
90
645
11
12
751
13
68
65
97
650
12
12
681
11
68
123
34
35
36
37
38
39
40
41
42
448
438
342
333
325
316
43
603
604
513
373
3m7
215 300
44
45
79
54
70
56
59
42
54
43
46
47
48
49
50
47
36
45
37
295
37
31
248
5
370
194
186
138
117
121
258 250
125
213
232
197
158
154
159
26
17
26
17
16
14
18
14
23
13
24
11
31
32
28
30
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
233
323
670
36
166
328
722
16
142
308
683
42
176
297
594
18
157
136
535
23
128
251
478
21
118
231
448
27
98
21
42!
24
83
197
410
27
73
174
377
17
65
174
354
12
69
155
352
12
37
157
241
26
44
159
334
?2
42
161
319
18
67
TABLE
13
STOCK OF ELECTRIC DRYEPS (THOUSANDS)
STATE
YEA ;
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
98
33
1?3
32
139
28
199
23
200
24
244
21
290
32
310
40
35q
35
383
19
415
43
447
45
26
38
32
52
34
45
46
51
62
65
76
79
94
87
107
152
124
158
1R1
123
676
108
149
823
122
170
152
110
?24
135
1
52
69
79
2
13
16
21
3
4
5
6
15
20
511
62
20
21
611
85
23
35
688
96
7
106
127
128
8
22
24
26
30
41
43
45
55
61
66
9
71
109
76
123
158
171
2P5
250
287
526 413
496
586
75
75
778
977 1089
10
61
645
11
11
12
14
12
13
58
301
64
385
69
401
14
280
319
200
15
137
336
?41
16
17
18
19
91
75
53
31
104
95
60
41
122
99
79
40
94
16
73
270
273
300
140
120
107
122
?0
79
3P8
297
304
174
138
131
144
23
87
386
331
285
193
151
138
225
25
93
434
382
314
209
160
153
482
61
124
87P
610
319
281
261
270
85 98
319 294
499
62
115
69?
654
338
297
269
296
104
480
727
70
120
724
544
405
320
346
316
141
78
274
420
56
122
728
576
322
260
274
246
119
72
241
356
48
114
664
539
308
264
252
220
101
47
212
294
40
107
573
506
325
236
206
211
?0
40
187
140
32
]01
531
44b
310
226
173
174
107
380
10R 115
406 467
127 -108
500 556
933 1059 1231 1341 1495 1719 183n 1797 1921 2013
135 156 15/ 200 231 262 29o 333 418 461
192 ?23 257 273 315 361 384 4n08 512 519
51
74
79
743
67
124
762
548
409
303
365
271
?1
140
174
199
22
428
573
611
237
574
281
619
317
749
362
778
424
855
405
881
440
831
485
850
511
874
560
936
559
584
982 1020
23
158
185
213
223
29
238
263
354
397
390
413
357
20
25
125
132
140
26
27
55
77
55
87
78
104
85
211
108
155
465
19
36
58
168 189
R8 105
123 133
348
21
24
158
77
112
429
?4
78
233
112
173
68
270
119
182
21?
377
140
229
10
31
11
31
56
54
54
352
410
169
373
9
21
17
268
3q2
145
278
?8
29
41
155
386
117
217
334
409
149
292
28
95
306
117
203
50
50
33
35
38
40
33
33
38
48
60
73
73
86
95
114
132
123
159
22
451
50
182
22
501
64
212
19
553
78
243
324
292
361
336
422
532
488
531
589
64?
34
676
118
23
38
685
130
74
44
49
64
70
82
85
96
747 1121 1154 1180 1198 1081 1006
188
200 257 299
367
415
553
108
104 113
88
100
8R
120
104
953
523
1'2
106
852
643
110
30
31
32
33
511
34
52
66
73
31
597
81
66
35
665
739
R03
796
36
43
52
68
855 945 1041 1177 1244 1348 1393 1456 1481 1459 1497
37
38
39
40
41
215
496
21
24
43
248
565
24
26
52
276
625
32
27
53
94
286
683
24
29
58
128
299
731
31
31
78
146
329
823
3B
40
78
160
154
327
357
895 1014
45
47
55
7
87
85
186 192 245
267
251
?16
219
394 411
440 _480
505
538
591
985 1151 1224 1303 1309 1?38 1247
62
78
84
92
101
110
117
144 149 170
185
181
P00 205
86
93
94
102
104
123
150
42
110
125
140
131
144
160
?04
304
386
468
501
538
551
173
252
284
360
43
583
308
3r3
427
475
536
645
782
1116
973
44
45
45
13
52
16
56
18
78
75
990
1023
69
893
93
99
114
112
121
135 158
170
142
46
47
48
49
95
343
94
233
137
420
152
282
156
433
125
317
20
182
465
145
25
189
472
161
27
222
500
162
29
264
538
170
3b
286
585
207
4?
315
620
198
46
391
664
224
53
418
724
228
57
487
710
240
54
524
753
249
57
636
773
301
57
692
780
320
333
358
359
409
434
478
48R
537
544
633
651
684
50
19
35
34
48
34
35
43
29
39
45
49
51
52
47
49
TABLE 14
ST3CK
OF HOUSFS
(THOUSANDS)
STATE
YEAR
61
60
1
2
3
4
5
6
.7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
P5
26
?7
918 1053
59
59
62
63
64
65
1047 1054 1052 1056
62
68
71
70
397 409
426 444 457
540 664 667 674 664
5238 5428 5594 5796 6015
584
606
551
630 635
774 791 798 8?2
839
137
134
138
144
148
1659 1717 1779 1843 19n5
1109 1141 1148 1181 1212
164 174
157
161
165
?07 208 209
206
201
3182 3258 3296 3334 3378
1430 1529 1526 1551 1566
909 929 9?5
861
930
470
b62
6187
641
859
152
1976
1245
179
212
3422
1582
918
695 774 768 773 771 765
879 923 950 981 970 976
929 947 954 982 10n06 1025
290 298 296 295 295 294
1153 1234 1262 1296 1329 1364
1581 1615 1629 1639 1662 1676
2331 2362 2380 2407 2451 2503
1016 1057 1066 1043 1107 1118
583
598
506
1562
204 205
466 498
115
105
1410 1566
203
446
622 619 623
1559 1567 1576
209 210 213
480 480 485
32
145
139
198 200 203
1934 1971 2017 2064
288 295 297
278
262
271
5371 5439 5507 5590 5672 5731
33
34
1244 1393 1412
182
178
180
35
36
2945
767
37
38
39
581
3437
267
40
628
?8
29
30
31
41
42
43
44
45
46
47
48
49
50
95
186
1849
190
1891
131
1 93
1432 1448 1465
186
186
1R5
3058 3082 3128 3160 3209
782 789 808 819 833
606 6?3 637 651
588
3474 3493 3520 3554 3592
272 274 ?78 281
270
658 563 690 696 711
?04 210 208 207
207
66
67
68
69
70
71
72
73
74
1065 1059 1069 107? 1074 1079 1083 1116 1118
71
70
83
97
76
85
77
96
87
483 497 516 539 566 613 660 709 741
651
656
651
642 639 648 648 656 655
6315 6450 6574 6680 6797 6945 7128 7303 7457
649 657 675 689 713 747 794 841 874
877 891 90q 930 952 969 985 1004 1017
150
157
164
169
173
181
166
176
182
2037 2113 2197 2289 2395 2525 2677 2868 2983
1296 1329 1368 1399 1422 1450 1468 1513 1548
189
1R5
195 202 209 215
224 232
241
212 214 218 220
226 235 244 254 262
3464 3500 3538 3586 3621 3660 3715 3771 3804
1607 1620 1643 1651 1664 1682 1693 1717 1730
912 918 914 923 927 923
914
924 925
759 757 754 750 750 75? 751 755 751
981 991 1003 1006 1021 1019 1046 1073 1085
1042 105b 1081 1092 1103 1124 1147 1170 1184
297 301 304 305- 312 318 325 339 330
1393 1415 1437 1458 1481 1511 1545 1581 1616
1700 1725 1750 1777 1804 1823 1854 1885 1904
2555 2594 2645 2691 2731 278? 2837 2894 2933
1128 1138 1155 1162 1181 1197 1203 1229 1244
626 634 640 638 661
677 684 734 748
1585 1583 1592 1587 1588 1603 1612 1624 1627
215 219 223 223 226 232 237 243 249
489 488 485 477 491 502 507 518 529
152 158
142 147
166 173 183 196 200
226 232 241 250 258 ?63
209 215 221
2111 2151 2187 2221 2257 2294 2340 2383 2417
292 289 293 298 305 315 325 339 346
5796'5871 5925 5977 6026 6056 6100 6176 6212
1484 1503 1530 1539 1559 1585 1603 1645 1656
187
186 188 190
186
185
193 196 198
3242 3260 3306 3345 3379 3415 3464 3515 3544
837 849 865 877 896 92? 937 967 982
681 698 714 747 774 800 819
660
6S3
3635 3654 3703 3752 3786 3825 3865 3q19 3958
288 293 297 300 303 307 309 311
285
730
734
744
207
207
208
766
784 802 812
213 216 218
1134 1159 1183 1210 1231 1256 1305 1325 1372 1418
3389 3429 3493 3578 3552 3625 3707 3770 3872 3935
282 286 287 292 296 304 312 325 341 350
137
120
130 13?
124
121
136
139 143 144
1285 1313 134e 1374 1407 1432 1475 1518 1572 1614
1039 1n50
1076 1110 1139 1161 1164 1181 1210 1:22
554 554 5 5 b 557 558 565 573 582 590 598
199
1035 1053
749
206
207
787
21?
1090 1112
2939 3147 3206 3284 3310
251 259 265 273 276
116 116 118
114 117
1112 1157 1186 1221 1254
942 977 994 1018 102??
59 555 555
562
540
1176 1306 1310 1316 13?9 1338 1341 1331 1347 1353 1357 1368 1381 1398 1405
107 106 108
111
103 108 108 106 105 10b
113 116 121
112
103
____
1
1_11
__·_____·_^_··
· __I_^· Ilr__l_·___·___··_
69
TABLES 15 TO 24:
ALTERNATE ANNUAL STOCK DATA FOR ELECTRIC AND GAS
APPLIANCES
These series were derived using the U.S. Census of Housing [12] as
the principal raw data source.
both here and in the data base.
They are expressed as saturation rates
Conversion
to appliance
stocks requires
only multiplication by the series of annual housing stocks (Table 14).
See section B for further discussion.
70
TABLE
SATURATION
15
RATE
F HOME FREEZERS
(THOUSANDTHS)
YEAR
STATE
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
1
2
3
4
5
186
244
170
209
152
199
255
172
220
154
220
272
181
237
162
239
218
186
254
169
259
304
1Q3
272
175
279
320
198
288
181
302
337
204
306
186
323
352
209
323
190
342
365
212
337
195
363
380
216
353
19q
384
393
218
369
203
406
408
223
386
207
429
424
228
404
212
452
439
232
421
216
491
470
248
455
232
6
237
242
?55
265
277
287
297
307
314
322
330
338
348
356
380
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
126
200
119
194
181
372
162
234
299
223
166
231
156
142
70
185
132
204
123
204
181
382
161
240
307
234
174
242
161
148
74
190
142
214
132
220
186
400
176
251
322
?49
189
259
172
158
244
105
151
222
139
234
190
415
185
260
335
263
202
274
181
169
86
214
160
231
147
250
194
431
104
272
348
278
216
291
191
179
93
225
167
237
154
265
197
446
202
281
361
292
230
307
200
190
98
236
177
246
162
282
200
461
211
291
374
306
245
324
211
200
105
246
186
253
171
296
202
474
218
299
385
319
258
339
220
211
111
257
193
258
176
310
202
48 5
225
306
394
330
269
352
228
218
116
265
202
264
184
324
203
497
232
313
404
343
283
367
236
228
121
274
209
269
190
338
?03
508
237
320
413
355
297
380
244
-237
128
283
21
274
198
353
204
520
245
328
424
367
311
396
253
249
134
293
P28R
282
207
370
205
532
254
336
435
382
325
412
263
260
142
304
236
288
214
386
205
543
260
344
445
395
341
427
272
269
148
314
258
308
234
417
218
571
281
367
471
424
371
458
295
295
165
338
23
24
310
242
318
257
240
473
347
299
360
3?1
373
342
386
365
397
385
406
404
416
424
425
444
436
464
447
486
457
506
483
543
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
194
386
296
200
132
114
223
93
212
448
180
176
311
148
53
198
361
203
204
250
205
175
251
153
269
337
202
393
306
204
137
117
231
97
223
456
186
185
322
154
56
208
371
214
212
259
212
183
260
161
279
348
199
199
339
165
61
P23
80
203
334
279
216
408
323
213
147
125
389
232
223
276
?23
195
279
175
294
366
228
419
337
221
154
132
255
111
256
487
209
211
353
172
65
239
404
246
234
290
234
207
294
186
307
381
242
431
3q2
228
165
139
265
119
273
501
221
2?3
370
183
72
254
419
264
245
305
245
218
310
19
321
307
255
442
367
235
172
146
277
125
288
514
232
236
385
190
78
269
434
281
256
319
255
231
325
211
334
412
268
454
382
242
183
153
288
133
306
528
244
249
400
200
83
285
449
299
265
334
265
242
342
225
348
428
279
463
394
248
190
158
297
139
322
538
254
260
414
209
88
299
461
315
276
347
274
254
357
237
360
441
290
470
404
251
198
163
306
146
336
547
262
271
425
216
95
311
472
329
283
359
282
263
369
246
369
452
30?
478
417
257
205
170
315
153
352
557
272
283
437
223
101
325
484
345
29?
371
290
274
384
260
380
465
313
485
429
260
213
175
323
158
367
565
281
294
449
231
107
339
494
361
300
383
297
283
397
P71
390
477
325
493
441
265
22?
181
33?
167
383
575
29?
306
461
239
11?
355
506
377
309
396
307
296
411
283
402
48n
338
502
454
272
231
188
343
174
400
585
302
319
475
248
121
370
519
395
319
410
316
308
427
297
414
502
350
509
466
277
240
194
352
181
416
594
313
330
487
256
128
385
530
412
328
423
325
319
441
311
425
514
378
533
494
295
260
211
377
200
449
619
338
359
515
278
144
416
557
445
352
452
348
345
472
339
452
543
71
SATURATION
TABLE 16
PATE 3F ROOM AIR CONDITIONERS
YEA;
STATE
60
61
180
189
8
6
125
149
82
46
72
186
189
130
120
160
83
48
79
197
202
139
15
18
58
59
144
87
119
153
93
124
302
306
93
276
100
288
11
11
144
151
52
51
57
55
59
186
181
35
65
197
186
35
214
217
64
65
35
36
184
200
64
124
68
133
92
98
21
70
333
22
74
334
36
111
48
128
70
36
119
51
137
75
240
339
251
342
44
45
66
69
21
21
46
129
137
47
30
30
4
62
51
65
56
41
41
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
3
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
49
50
(THOIISAN)THS)
6?
63
64
65
66
67
?00
6
211
6
2?8
4
260
4
?92
4
32'
116
170
86
50
111
1O
88
51
111
195
93
55
119
227
105
63
125
256
116
72
88
211
68
69
70
71
72
73
74
370
4
406
4
460
4
511
4
544
4
552
4
575
4
130
142
28b
332
130 .48
BO
93
147
367
162
105
162
422
189
125
176
473
216
146
180
508
232
158
97 111
223 242
134 160 189 228
279 314 352 400
170
517
230
160
264
439
167
541
?40
169
319
497
375
550
417
585
436
595
470
620
?16
148
2?8
156
250
170
288
195
324
222
354
251
413
290
453
3??
513
373
566
421
21
59
163
60?
454
24
60
174
30
62
1QO
613
462
638
486
38
69
220
49
75
250
52
83
283
80
93
325
98
102
102
362
105
115 134
230
139
514
264
144
540
147
167
232
208
143
504
135
207
172
134
469
130
153 176
134
119
417
244
309 310
109 116
301 313
189
320
130
334
347
153
373
371 396 429
176 204 242
408 446 493
269
13
160
62
13
15
169
68
183
75
209
92
59
63
69
73
82
79
92
242
111
277
205
37
11
209
190
222
195
36
36
21
68
223
69
38
4
213
17
19
237
107
22
257
126
305
153
95
111
132
133
158
193
311
350
230
251
397
42
277 310
46
232 256
74
83
277
93
40
43
50
57
513
57
301 332
105 120
65
77
274
313
316
353
453 495 53]
274 324 374
529 582 629
347
355
377
382
386
404
551
410
658
545
42
663
554
450
583
36
35
24
28
338
177
33
388
217
436
259
468 476
290 302
498
328
151
183
216
225
241
274
248
325
267
366
435
383
493
33
378
418
580
416
545
442
590
614
73
83
355 396
133 156
88
86
431
179
8
454
193
450
191
461
200
62
87
105
123
135
441
138
37
455
147
218
237
263
73
142
307
77
151
351
398
A3
167
97
194
112
222
455
130
253
503
153
294
568
208
382
665
106
174
328
626
112
24
433
267
46
1'94
b5
227
257
82
304
35
383
190
103
228
128
265
148 156
292 297
172
318
571
564
573
102
427
106
451
I5
146
167
26
80
28
84
32
93
39
109
47
125
337
338
347
374
397
37
126
54
346
38
134
40
147
58
154
64
170
74
197
45
171
50
195
86
223
681
273
479
393
709
291
505
418
144
69
169
422
455
477
64
258
518
553
70
288
83
338
100 119
25
295
96 1?
385
418
135
329
163
382
193
432
214 ?20
467 476
37
502
36
222
80
87
Q6
112
264
130
274
295
49
177
332
367
404
202
242
28?
451
311
357
410
73
22
494
536
7
22
470
88
26
591
144
153
98
29
572
111
32
628
595
649
43b
70
21
386
622
341
347
591
319
345
488 542
166 191
129
37
217
142
40
191
55
208
58
218
61
31
2
283 314
208
59
31
24)
167
48
36
40
44
473
68
51
70
65
77
73
89
88
42
42
43
48
102 lib
10n2 11
5?
58
363
411
442
450
55
65
74
79
78
135
144
15
167
181
204
65
69
80
5
211
231 234
24? 272
P282
9
7 97
95
595
80
?48
306
97
72
TABLE 1
SATURATION RATE
F ELECTRIC RANGES (THOUSANDTHS)
YEAq
STATF
60
61
62
63
64
65
66
67
68
69
70
71
72
73
1
2
462
488
459
484
467
490
475
496
487
507
499
517
512
528
522
531
527
540
541
552
551
560
558
56A
570
576
R55 605
589 608
3
4
5
180
129
170
186
130
174
200
137
184
214
144
194
232
153
208
251
162
222
271
172
237
291
181
251
307
188
262
330
200
279
351
209
295
371
218
309
395
232
328
423
246
349
457
267
377
6
311
319
337
353
376
398
421
443
459
484
505
524
548
574
605
7
407
408
421
434
451
467
485
500
510
528
543
55q
57?
592
616
8
330
328
336
344
356
367
381
390
397
410
421
42Q
442
458
479
9
10
11
494
448
594
495
444
594
509
451
605
521
458
616
538
469
630
555
480
644
572
492
659
57
502
671
597
506
679
614
518
693
628
527
704
639
534
713
655
545
726
673
559
740
695
579
758
12
13
14
15
16
17
18
806
176
325
279
265
292
72
801
172
321
279
269
294
74
P04
176
325
p88
282
306
79
806
177
330
297
294
316
86
811
184
338
310
310
333
95
816
189
346
322
327
349
102
821
195
355
336
344
366
112
824
199
352
346
360
381
123
824
200
364
355
372
390
13n
829
205
373
370
390
409
142
833
211
380
382
407
425
153
834
214
385
392
421
438
165
839
393
406
440
455
179
844
228
404
423
462
476
195
R53
240
423
446
490
503
217
19
362
367
382
397
417
436
457
475
488
509
528
543
563
585
613
20
21
22
?3
?4
p5
188
292
390
345
200
211
186
292
385
346
204
209
190
302
389
357
217
217
195
311
394
367
228
223
204
325
402
383
245
234
212
339
411
398
262
244
221
353
420
414
279
255
228
367
427
428
296
254
232
375
429
436
308
269
242
390
439
453
328
282
250
404
445
467
346
292
256
414
450
47A
362
30o
265
429
458
494
382
311
277
448
470
513
406
325
294
472
488
538
436
347
26
27
28
29
553 549
347 349
547 539
440 443
556
362
543
457
563
374
546
470
574
390
553
488
585
408
561
506
596
425
569
524
605
441
574
54.1
609
452
575
551
620
470
583
570
629
486
588
586
635
499
591
598
645
517
598
615
658
537
608
635
675
563
624
659
30
31
32
33
34
35
36
37
38
39
156
211
153
598
524
319
117
772
294
293
154
212
152
600
526
318
123
771
292
295
158
P20
156
612
540
327
132
779
299
307
163
228
160
624
554
336
142
786
306
319
171
241
167
639
572
349
154
795
316
314
177
253
174
654
589
362
169
805
328
350
186
265
181
670
606
375
184
814
339
367
193
277
188
683622
387
198
822
349
382
195
285
190
691
632
394
209
826
353
392
204
299
199
706
649
408
228
835
366
410
212
311
205
718
664
420
245
841
376
425
217
32?
211
728
675
429
26n
847
383
43R
226
336
218
741
691
443
279
854
395
455
237
353
230
756
708
460
304
862
410
476
253
377
245
774
730
483
333
873
431
503
40
552
552
563
574
5R9
604
619
632
639
654
666
676
689
704
724
41
408
410
422
434
451
467
485
500
509
527
541
553
570
42
637
637
648
658
672
686
699
711
718 731
742
75n
762
775
791
43
135
139
148
158
170
183
197
209
220
236
251
264
282
302
329
44
592
588
595
601
612
622
632
641
644 65S
663
669
678
690
707
45
373
381
400
419
442
465
489
512
52A
553
574
593
615
640
670
46
407
407
428
443
457
472
486
493
522
53?
547
565
58B
47
799
798
;04
810
818
826
833
840
509
843 851
856
86n
867
874
t84
48
282
279
288
296
307
315
330
341
346
3S9
370
378
390
406
428
49
394
390
399
406
418
429
441
451
456 469
479
486
498
513
533
50
351
351
361
371
385
400
415
428
436
465
475
490
508
532
17
452
?20
74
R89 613
73
TABLE 18
SATURATION RATE OF ELECTRIC WATER HEATERS (THOUSANDTHS)
STATE
YEA4
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
?0
21
22
23
24
263
264
82
47
63
115
175
194
545
300
537
800
120
291
279
70
183
22
283
102
91
228
292
96
260
256
80
47
61
107
171
188
543
294
536
789
112
279
265
68
181
24
274
101
89
218
283
101
?71
258
83
51
62
107
174
190
554
300
547
787
111
281
260
68
189
27
278
103
93
218
283
110
279
260
87
54
64
105
177
193
566
306
559
784
111
282
258
69
195
30
281
107
98
220
286
121
292
265
91
58
65
105
184
197
581
314
573
784
111
283
257
69
204
33
286
111
103
222
290
133
305
269
95
62
68
103
190
202
595
322
587
783
111
287
256
69
214
38
291
114
110
223
294
147
319
274
100
68
70
105
197
207
611
332
603
784
112
292
257
72
226
42
297
119
116
227
300
162
330
279
105
73
73
103
202
211
624
339
616
783
112
294
255
73
236
48
302
123
121
228
304
177
347
286
110
79
75
103
209
218
640
351
633
785
114
299
256
74
248
54
310
129
130
232
310
197
369
297
119
88
80
107
22?
228
662
369
654
790
117
310
262
78
265
63
323
138
140
242
322
221
389
309
128
97
84
110
234
239
681
384
674
795
121
319
265
80
283
72
335
146
152
249
333
246
41n
320
137
107
89
111
246
249
700
40n
693
790
125
328
271
84
301
83
347
154
163
257
348
274
436
335
148
119
97
116
262
263
721
421
714
806
130
341
279
88
323
96
363
167
179
268
359
307
463
499
351
162
133
105
121
279
377
181
153
116
130
305
278
302
742
442
769
474
736
813
763
826
135
356
147
380
288
305
25
121
116
116
117
119
121
124
125
128
134
139
144
152
26
27
28
?9
30
31
32
33
34
35
36
37
38
39
40
41
296
209
494
216
87
100
74
522
411
179
21
756
167
73
480
380
282
199
479
213
83
93
70
523
404
172
22
749
162
73
479
371
278
195
478
218
84
91
70
537
409
172
26
752
163
77
492
375
274
193
477
223
84
89
72
552
415
172
29
756
166
80
506
379
274
191
479
232
87
88
73
570
423
175
34
761
170
87
522
386
273
190
481
240
88
88
74
587
431
177
39
766
174
92
537
393
273
191
485
249
91
88
74
606
441
181
45
773
179
98
555
402
272
190
486
257
93
87
75
622
449
183
51
778
183
103
570
408
273
190
491
268
96
87
78
640
460
188
60
785
189
111
588
418
279
195
502
283
101
88
827
664477
195
70
795
198
123
612
434
283
200
511
299
106
91
84
686
493
203
83
805
207
133
634
448
288
203
520
315
111
9?
88
707
509
209
97
814
217
144
65q
463
296
209
533
334
117
96
93
731
529
221
115
825
228
158
679
481
100
109
754
549
782
579
232
137
836
251
167
851
242
265
176
703
199
734
501
530
42
478
479
493
508
526
543
562
579
598
624
647
669
694
719
750
43
44
45
46
47
48
49
50
35
242
239
300
782
138
358
130
36'
225
246
297
774
138
344
124
39
216
263
306
774
144
342
123
42
208
281
316
775
151
339
121
46
202
302
328
777
160
341
121
50
195
324
339
780
169
341
121
55
190
349
353
784
179
343
123
59
185
371
365
78b
1B8
343
123
65
181
398
381
790
200
346
125
73
180
432
402
798
216
35S
129
82
179
464
422
805
232
362
132
91
177
497
44?
812
250
370
135
102
116
179
181
533
571
467
493
821, 430
271
2Q4
381
393
140
148
135
95
103
347
380
112
134
380
180
407
200
195
220
281
375
301
401
342
161
306
218
547
389
175
323
232
571
356
125
386
138
98
106
188
617
528
844
327
415
160
74
TABLE 19
SATURATION RATE
F AUTOMATIC WASHERS (THOUSANDTHS)
STATE
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
.3
39
40
41
42
43
44
45
46
47
48
49
50
YEAR
60
61
62
63
64
65
66
334
325
420
288
472
4?8
530
487
384
357
502
347
336
423
370
355
422
451
482
400
468
507
322
483
460
551
520
427
487
402
525
533
607
594
452
473
582
553
385
425
396
505
455
301
394
376
450
346
495
527
433
543
465
457
295
330
274
400
232
428
318
369
475
388
272
286
288
411
324
473
408
485
387
390
320
193
375
343
489
371
367
319
212
299
399
474
347
334
499
255
274
397
473
439
535
498
436
392
g24
541
561
485
321
358
311
431
?64
458
359
505
339
378
336
453
285
528
508
466
304
339
288
481
399
285
297
300
421
339
473
422
489
393
390
335
207
386
352
498
381
377
332
223
311
402
486
363
344
507
267
290
.412
507
415
416
401
244
438
333
375
568
510
587
567
433
444
388
370
411
4,2
373
390
498
419
307
316
320
440
365
482
445
542
479
386
407
516
441
330
339
342
461
392
493
361
401
365
479
309
561
629
621
473
503
604
578
411
452
430
534
336
366
503
529
417
427
537
466
357
450
556
484
448
471
559
582
492
386
520
364
392
395
421
509
456
522
491
367
484
423
5n7
470 498
502
517 534
409 426 446
400
411 425
359
386 416
228
251 279
406 427
452
370
390 412
516
536 559
401
423 448
396
417 441
353
376 403
242
264 290
335
359 3.87
415, 429 447
509 532 558
388 415 446
363 383 407
524 543 565
287 309 335
313 338 367
437 464 493
527
553
467
440
448
311
478
437
583
474
466
431
316
417
465
586
479
433
587
363
398
524
418
425
536
539
558
573
490
457
482
346
506
463
608
502
493
462348
449
486
614
513
461
611
393
432
557
67
68
69
70
71
72
73
74
514
540
48J
570
534
561
594
556
575
612
633
656
686
507
543
493
571
590
611
641
593
524
549
588
599
606
615
628
648
573
611
636
656
582
568
603
669
666
669
684
692
698
711
621
704
730
641
730
750
5.10
529
543
560
643
624
459
501
493
585
588
662
646
560
589
650
64?
494
534
626
604
437
479
464
552
706
723
551
563
612
677
664
628
648
685
697
67c
485
527
505
547
51o
526
611
554
631
575
645
499
690
537
578
600
662
561
423 454
479
604
549
513
623
629
583
648
610
644
660
630
562
669
571
597
618
631
450
451
478
4.77
509
506
536
530
455
553
526
555
555
547
510
608
588
582
534
627
615
592
551
640
588
481
584
555
567
613
593
608
640
627
513
474
516
382
53?
486
663
640
553
570
5.02
513
546
534
578 .605
451 483
557
512
396
583
520
495
605
548
490
632
530
520
492
379
481
50.7
641
547
49
634
424
451
4'S 1
414.
535 - 552
617
570
70n
522
677
654
576
682
649
578
568
572
656
659
602
697
657
593
525
648
539
635
587
714
614
631
601
619
610
513
608
573
737
676
592
661
636
595
678
646
579
517
625
509
583
60.3
543
518
407
537
673
579
568
548
439
557
690
600
588
572
467
509
522
540
541
566
555
664
576
688
608
707
634
512
652
538
560
721
653
574
673
689
698
451
482
508
496
530
615
558
526
579
644
668
685
651
553
591
611
686
717
738
58s
48
585
562
711
549
603
705
755
778
577
670
600
699
711
706
732
730
557
587
598
626
681
627
661
708
548
583
695
680
592
696
720
712
618
719
668
696
604
638
592
596
624
628
674
684
612
717
669
609
700
716
631
744
690
634
535
555
673
571
705
611
654
606
682
635
730
651
638
752
679
666
632
664
540
577
613
666
587
610
754
699
613
726
778
730
642
748
575
609
630
665
726
754
75
TABLE 20
SATURATION PATE
F CONVENTIONAL WASHERS (THOUSANDTHS)
STATE
YEAR
60
61
62
63
64
65
66
67
68
69
70
71
1
2
3
4
5
6
7
8
9
10
11
12
13
14
324
235
2?2
385
160
287
232
283
167
260
264
346
385
417
279
200
186
335
130
241
193
236
137
218
214
295
337
366
?51
180
165
302
111
211
167
203
119
190
181
?62
307
332
226
162
2n5
148
186
134
170
123
153
111
138
100
124
91
110
80
97
72
146
274
130
250
116
226
103
207
93
186
82
167
73
151
64
134
56
117
96
l15
146
175
A3
163
128
152
72
144
111
132
63
128
98
115
54
112
87
96
47
97
74
84
40
86
65
72
34
74
57
61
29
102
Q1
74
69
62
54
47
41
166
146
128
114
100
87
75
65
153
130
111
95
80
68
57
47
35
56
39
232
207
184
163
146
128
112
97
8'
543
361
489
311
452
279
256
274
365
2?5
234
249
355
202
214
227
328
181
197
205
301
162
177
161
185
166
274- 249
144
129
144
148
223
114
129
13n
15
16
279
300
416
250
17
18
19
20
21
22
23
24
25
26
27
28
29
30
534
271
4R3
273
218
403
540
315
434
387
472
133
361
264
484
232
421
232
180
353
491
276
382
334
416
105
301
217
450
207
378
208
154
321
457
251
348
297
377
88
?59
186
418
3Q0
363
339
314
288
265
242
216
185
337
186
167
302
169
151
269
152
137
240
138
123
212'
124
110
186
111
98
162
100
88
140
88
77
12n
78
134
292
426
230
316
265
341
116
267
3q8
212
200
237
310
101
242
371
195
265
213
279
88
222
347
181
242
190
255
77
65
202 181
323 297
156 152
221 199
170 149
228 204
57
165
274
139
180
133
183
49
147
251
125
161
116
161
4?
202
69
105
69
36
130
117
106
96
228
209
191
112
142
1On
140
103
95
115
78
176
87
103
69
26
31
102
87
74.. 64
125
114
22
73
54
103
51
43
204
125
37
121
88
135
61
225
142
44
143
102
148
15
259
169
52
165
119
158
18
31
32
62
193
138
172
111
13
98
73
223
160
186
33
79
34
33
34
35
36
37
38
39
40
373
633
421
254
265
446
246
269
321
581
372
214
223
398
205
228
287
543
341
188
194
366
179
203
39
87
38
86
37
28
73
30
66
193
112
41
594
544
42
43
44
64
48
52
19c
98
72
R8
79
59
50
44
54
39
107
25
56
95
86
22
19
43
32
33
22
37
22
57
96
93
148
69
169
56
79
56
27
42
44
31
49
33
74
116
116
181
88
129
88
125
110
97
88
79
59
62
55
49
255
228
204
184
153
144
128
111
506
473
440
410
379
347
318
288
311
166
170
288
147
148
264
130
130
244
116
116
223
102
102
204
91
88
186
79
77
167
69
65
338
313
288
269
249
228
209
190
157
138
121
107
93
82
70
62
180
162
144
1.30
116
103
92
80
510
477
448
419
393
367
339
313
287
260
419
367
194
163
3056 259
332
144
?28
299
272
246
223
202
181
162
143
129
116
105
95
84,
75
68
61
125
53
45
462
401
357
46
47
48
374
235
577
328
194
530
299
167
499
200
316
272
144
179
2R2
250
125
158
250
228
110
140
222
211
96
125
195
193
83
110
170
175
72
96
148
156
63
83
128
144
54
45
39
395
323
299
274
505
417
346
556
443
371
49
469
471 438
409
381
356
33u
304
279
256
50
342
295
264
214
191
174
157
139
125
110
231
97
256
213
237
72
126
74
65
45
93
43
97
258
149
60
57
171
53
70
107
73
236
49
37
38
27
42
28
65
106
103
162
78
184
62
91
63
31
74
212
137
53
5n
157
124
47
46
63
40
241
112
48
63
93
116
67
43
143
56
220
lnO
43
55
80
106
34
236
194
77
70
11
41
38
130
35
50
203
89
39
49
70
96
30
220
177
69
76
TABLE 21 SATURATION PATE OF ELECTRIC DRYERS (THOUSANDTHS)
STATE
YEA;N
60
61
62
63
64
65
66
1
2
3
4
5
6
7
8
9
10
11
12
55
213
38
37
93
109
134
160
62
53
69
279
64
227
44
43
100
121
146
172
69
62
78
295
74
245
51
52
110
135
162
186
79
74
88
314
88
264
59
63
120
153
179
203
88
87
101
334
103
286
69
74
132
174
199
2?2
102
103
115
357
13
14
92
190
123
310
80
91
146
195
221
242
116
123
132
381
97
198
144
336
95
110
162
222
246
265
134
147
152
407
102
207
110
218
119
231
128
244
139
260
15
16
17
18
19
20
21
22
23
24
25
26
27
29.
30
31
32
33
34
35
36
156
126
83
56
106
34
86
176
152
36
86
273
169
93
111
83
82
82
39
283
218
54
166
138
91
63
117
93
95
183
162
42
93
287
184
103
124
91
91
88
46
299
228
63
177
151
101
70
132
102
105
190
175
51
102
304
202
116
139
97
101
95
55
316
242
73
190
166
112
80
147
114
116
200
189
61
111
322
221
129
157
107
112
102
65
335
256
84
2n7
184
126
93
166
126
130
211
204
74
1?4
342
242
144
177
116
126
111
78
356
272
100
223
203
143
106
186
140
146
222
223
88
137
363
268
162
200
129
142
121
93
378
288
116
37
242
225
161
121
209
158
165
236
242
107
152
388
295
183
226
142
160
133
111
402
308
138
356
372
390
412
435
458
485
38
39
40
140
77
37
149
86
43
41
162
97
52
209
174
110
61
223
189
125
73
239
204
142
87
257
223
162
105
277
299
42
103
116
132
43
149
56
170
63
73
83
97
44
45
46
47
48
175
117
83
345
167
186
130
92
362
180
202
148
103
382
195
49
218
166
116
404
213
193 .204
218
50
185
?18
28
200
67
68
69
70
71
72
73
74
278
459
180
228
245
356
372
380
234
285
260
525
194
335
339
336
259
213
334
249
262
316
486
360
517
409
549
464
204
236
271
265
310
359
265
290
316
39n
428
469
402
406
436
437
473
469
516
516
508
26n
293
329
324
291
549
373
371
325
577
421
365
606
479
207
351
36n
223
370
386
242
392
414
265
363
285
239
365
395
315
269
401
429
348
302
440
469
389
273
287
300
316
330
350
302
316
333
352
369
390
377
342
226
232
497
427
292
361
213
257
195
228
513
401
260
596
316
273
213
437
361
232
390
380
283
595
392
387
441
365
392
421
457
263
253
519
457
307
278
545
492
356
306
572
528
413
339
319
352
387
395
433
474
23n
282
209
264
251
311
2?8
306
274
345
249
353
535
562
589
420
295
444
336
469
381
434
617
642
668
697
337
30?
246
46?
363
337
286
490
390
375
330
521
425
421
396
437
480
262
416
415
297
445
454
336
476
496
313
347
385
617
643
669
172
204
240
356
396
429
111
134
13?
161
154
194
130
200
22
251
274
293
156
175
1.75
285
305
321
179
20B
200
320
339
351
205
245
231
437
466
497
151
278
255
250
183
140
237
17V
186
251
265
165
296
288
277
205
162
268
200
209
268
290
180
316
314
307
232
186
301
225
236
286
316
130
170
158
190
190
211
415
325
207
251
158
181
442
359
23?
288
175
204
470
394
262
325
194
230
147
162
177
134
162
194
430
330
457
353
486
378
163
513
191
541
225
570
245
1B6
268
213
292
242
323
125
351
151
379
181
409
193
220
251
29Z
323
111
130
237
188
133
4?27
232
257
212
151
452
253
176
334
204
363
232
279
240
172
479
277
151
30b
249
268
288
27
19:
50
30j4
311
-306 343
223 253
5 3q 567
332 362
335 363
237
260
283
311
34
2
374
408
586
314
417
351
411
640
419
448
345
485
605
569
430
521
305
385
276
408
621
501
384
557
529
382
514
544
430
700
418
448
481
409
434
462
519
496
470
503
538
578
77
SATURATION RATE OF GAS RANGES (THOUSANDTHS)
TABLE 22
STATE
YEA
60
61
62
63
64
65
06
67
68
69
70
71
72
73
74
1
283
269
267
265
265
265
269
269
269
272
276
2
277
16
279
18
22
?79
27
282
33
41
51
75
3
4
52
93
115
624
471
599
457
139
587
458
576
459
167
200
239
567
463
559
468
554
476
54o
481
537
484
532
492
527
501
519
506
513
513
506
518
499
524
5
717
696
687
677
670
664
661
655
647
643
640
631
6
629
623
497'
471
458
446
617
437
429
424
416
407
402
398
390
384
7
377
397
370
376 367
361
356 353
352
349
344
343
343
33
338
8
9
335
369
140
333
356
133
355
130
355
130
357
129
361
130
367
130
371
132
373
130
379
133
386
134
3-90
134
395
137
10
316
400
137
302
404
138
300
297
297
300
304
305
305
309
314
315
318
320
322
11
12
232
22
214
22
207
25
200
27
195
30
190
33
188
37
184
41
177
45
176
50
13
14
15
646
426
32
636
414
370
174
56
17n
6
167
69
638
416
373
160
83
641
418
375
647
423
30O
163
75
654
429
386
663
438
395
669
445
402
674
449
406
683
458
415
692
468
425
698
474
43?
76
482
440
712
489
447
719
496
455
16
551
527
518
508
01
496
493
488
17
18
481
478
390
710
374
694
476
371
690
471
367
637
467
462
458
367
686
369
686
373
688
374
688
373
686
377 381
689 - 692
38?
69
385
693
386
694
388
595
19
144
133
128
124
120
117
116
114
110
109
107
10q
623
536
452
102
608
517
436
101
20
21
22
07
512
435
605
507
434
98
607
504
435
610
504
439
615
506
444
617
50O
441
618
502
448
623
504
454
629
507
461
632
506
463
63
507
468
639
507
472
643
507
476
?3
24
382
392
366
372
363
366
361
360
360
37
362
355
365
356
357
353
366
350
370
351
375
352
375
35
378
350
380
348
382
347
25
494
477
475
472
473
475
479
481
481
486
491
493
497
499
502
26
27
296
440
276
417
269
409
262
401
257
395
253
390
251
390
248
386
24?
380
241
379
240
378
236
374
234
371
231
367
28
228
365
169
166
172
177
16
195
205
216
223
237
250
260
274
P86
299
?9
153
147
147
147
148
151
154
158
30
31
32
715
499
712
15
701
481
697
162
170
699
477
693
698
472
690
698
471
688
167
172
176
179
700
472
689
704
474
691
706
475
691
706
473
689
710
476
692
715
479
695
716
479
694
33
34
719
41
696
59
144
722
482
696
724
483
697
57
135
59
135
61
134
64
135
66
137
70
139
74
140
77
142
82
144
87
148
91
14
96
151
101
153
35
106
154
550
528
521
513
508
505
504
50
495
494
494
491
489
486
649
83
483
36
37
627
78
17
75
608
74
601
74
596
74
593
74
588
74
580
74
577
74
575
75
569
75
566
75
561
75
38
39
556
75
539
500
520
479
516
473
511
509
464
510
462
512
463
512
451
509
457
512
458
515
460
514
458
516
4R
516
40
41
42
43
79
83
193
191
175
172
621 S15
91
1l1
167
604
96
194
167
601
102
197
167
601
109
19
161
59
114
200
165
594
121
203
166
594
130
207
167
594
137
20
167
591
146
212
167
590
44
457
153
214
167
5R8
517
456
79
204
186
642
47
86
190
169
608
279
265
?63
260
20
262
265
251
265
269
274
274
277
279
21
45
46
47
48
49
50
110
267
5
514
346
418
102
257
54
495
334
398
102
258
54
491
335
392
101
259
54
487
336
386
100
2A2
54
486
39
383
101
267
55
487
345
382
102
274
56
490
352
382
102
?79
51
491
357
381
02
282
57
489
360
377
103
288
58
492
367
378
105
297
60
496
377
379
10
301
6n
496
38
377
107
308
61
498
388
377
107
313
62
499
394
376
107
319
63
501
400
375
162
217
167
586
78
TABLE 23
SATURATION RATE 3F GAS WATER HEATEPS (THOUSANnTHS)
STATE
1
2
3
4
5
6
7
8
9
10
11
12
1]3
14
15
16
17
18
19
20
71
?2
3
24
25
26
?7
28
'9
30
31
32
33
34
35
36
37
YEA4
60
61
325
324
3
4
708
706
443
449
826
694
828
689
279
319
112
344
228
62
276
323
111
63
64
65
66
67
68
69
70
71
72
73
74
336
348
6
11
742
573
R45
781
293
431
134
427
741
291
288
288
58
617
487
457
135
443
176
148
405
485
508
502
116
724
449
135
438
lR1
138
467
51
376
147
741
563
845
775
294
422
133
422
197
106
712
386
493
744
601
944
797
222
369
9B
737
549
842
765
292
410
130
412
200
95
695
384
387
744
592
844
792
222
357
56
73(
541
84J
760
295
403
130
408
207
88
663
379
209
710
283
341
116
361
363
44
734
528
842
752
294
390
128
400
211
79
667
389
725
490
838
725
290
358
121
376
358
29
731
515
840
743
292
380
125
392
214
72
651
37C
716
470
350
18
726
500
837
732
288
366
1?3
381
216
64
631
519
516
530
530
536
540
556
566
748
571
759
578
739
449
672
;8
544
348
548
555
748
460
685
56
555
358
754
468
695
55
564
365
75U
475
704
53
573
372
5S8
763
479
710
50
577
375
598
770
488
721
49
588
384
781
784'
503
507
513
741
43
747
41
755
39
606
469
616
480
625
488
633
496
637
500
647
509
773
493
728
47
594
389
652
610
788
376
581
566
607
291
116
461
639
334
70
241
693
706
Q3
524
263
P8
2P7
203
7n4
679
381
593
574
617
265
121
476
650
350
75
251
699
711
97
530
273
95
296205
711
694
605
398
663
525
392
610
402
667
530
392
617
407
674
536
646
651
659
597
660
346
147
547
598
663
356
149
555
601
832
41
346
220
45
555
567
446
451
593
469
423
708
413
625
64
502
316
566
431
358
538
541
569
204
430
452
474
710
414
723
430
735
444
630
548
665
61
60
522
330
585
60
538
344
600
448
464
355
541
539
571
211
102
366
'59
375
575
101
409
596
279
53
204
670
690
82
504
504
316
568
432
552
587
564
602
227
242
107
115
414
434
452
600
617
632
267
305
324
56
61
?22
66
235
681
691
82
697
87
706
92
501
513
523
257
84
209
669
687
385 388
387
603
612
617
579
554
584
625 633
636
278 290
299
126
130
133
488
499
507
659
666
672
363
376
386
AO
37
91
260 269
274
704 707
708
714
717
716
100 102
103
534 537
536
281
288
294
101
101
111
302
310
313
207 209
207
717 722, 723
706
716
727
390
627
591
645
313
138
520
682
401
97
286
713
719
107
541
302
120
321
209
730
739
191
515
392
634
593
650
324
140
529
688
412
102
293
715
720
109
38
39
40
41
228
231
68
257
70
?45
77
258
42
195
271
283
43
44
676
620
191
677
198
689
204
701
45
628
82
649
668
79
80
83
46
241
PO
242
82
80
256
80
269
79
79
77
274
64
sno
283
69
572
445
299
82
552
302
87
537
311
95
528
316
409
291
75
562
685
672
47
46
48
54
60
48
614
49
568
SO
735
598
536
717
596
*18
710
593
498
702
420
394
658
642
365
622
541
309
125
325
208
733
748
101
342
515
316
608
589
28f
581
843
785
29n
438
134
431
18S
125
735
562
575
776
496
733
45
598
390
656
518
390
638
593
653
333
143
536
69?
42?
107
29o
71s
719
110
54n
314
13n
32q
700
704
435
114
445
119
308
314
718
719
721
720
803
137
450
171
162
771
587
393
669
369
153
565
711
458
125
323
722
722
114
116
542
544
322
139
335
327
144
339
335
152
344
205
744
783
72
339
130
462
'25
207
?05
738
766
74
329
740
774
73
333
11
488
121
474
268
550
245
530
568
844
112
734
756
74
321
107
29n
746
61 1
542
205
50o
601
511
79
T4;LE
SATURATION
24
PRATE F GAS DRYERS
STATE
(THOUSANDTHS)
YEA60
62
61
63
64
65
1
2
3
4
6
9
13
18
6
10
15
21
5
51
57
6
21
24
7
8
13
22
13
24
8
11
18
25
65
27
16
28
9
10
4
9
4
10
4
6
6
11
13
16
11
4
4
12
4
4
6
6
6
6
6
6
]3
14
15
121
92
95
130
97
102
142
103
111
75
31
75
11
40
29
158
117
152
110
119
82
34
84
13
45
34
169
126
162
115
1?9
88
37
96
13
50
40
180
137
9
13
21
29
73
30
18
31
10
16
25
34
82
33
p1
35
66
11
19
30
41
92
38
24
40
67
16
26
43
68
69
70
71
72
73
74
21
35
59
77
146
60
40
65
24
40
69
88
160
65
45
72
26
45
78
98
17P
72
49
79
29
50
88
110
1RS
75
53
84
32
55
97
123
197
82
58
91
35
61
110
135
209
87
62
97
13
22
36
48
103
43
27
45
116
46
31
51
18
30
50
65
130
54
35
58
8
9
11
13
15
17
1O
21
22
26
19
22
26
30
35
40
45
51
56
62
8
8
9
9
10
10
11
11
13
13
13
13
18
15
17
16
18
17
19
18
176
125
139
97
42
107
15
57
47
194
148
190
133
152
106
46
121
17
65
55
208
162
204
142
153
114
51
135
19
74
54
223
174
218
149
176
124
57
151
21
83
74
237
188
232
158
189
133
63
167
22
93
87
251
200
246
166
200
142
-68
184
24
103
98
265
213
256
17n
20Q
148
73
198
25
112
111
274
22?
263
172
216
153
77
211
27
121
123
282
P?8
271
176
?23
158
80
223
28
130
135
288
237
278
179
230
163
84
237
29
139
149
296
244
56
16
65
69
17
18
25
60
28
68
19
20
21
10
31
21
11
35
25
22
137
146
23
101
109
24
6
8
9
10
11
13
13
16
18
25
P6
?7
28
62
19
64
6
68
19
68
6
74
21
73
8
82
22
78
9
89
22
83
10
100
24
88
11
111
26
96
13
121
28
102
1
133
29
109
19
20
22
24
26
27
29
146
31
116
22
157
32
121
25
167
33
129
28
175
33
129
31
183
34
132
34
191
34
134
38
29
8
9
10
11
13
16
18
21
24
28
32
36
39
43
47
30
31
32
33
34
35
36
61
19
31
2
24
98
40
68
22
34
2
26
102
44
77
25
39
84
29
43
95
34
48
107
40
55
121
46
62
134
53
69
149
62
77
166
70
86
181
80
95
195
89
102
207
97
109
220
107
116
232
119
124
17
4
6
38
78
83
11
2
3
4
4
4
6
8
9
11
13
15
17
20
28
109
49
6
88
13
30
114
55
6
96
18
33
119
60
8
102
?2
36
125
66
8
111
27
39
133
74
9
120
33
42
139
83
10
128
41
45
146
92
11
137
50
49
153
101
13
147
60
52
158
110
13
154
72
55
160
116
15
161
84
56
161
123
15
165
97
58
162
130
16
170
114
60
162
137
17
174
130
39
10
40
1
2
2
2
3
4
4
.4
6
8
9
11
11
13
16
41
46
48
51
3
32
37
13
9
54
4
37
43
13
10
86
4
42
49
15
11
60
4
48
57
16
13
64
4
55
66
18
16
68
6
62
78
19
18
70
6
69
89
21
21
74
8
79
102
2
24
78
9
88
116
24
28
79
10
97
130
25
31
80
10
1ng
143
25
34
82
11
114
157
26
37
82
11
123
171
27
41
42
3
3
43
44
45
25
27
11
28
31
11
46
6
8
47
4
4
48
41
44
49
0o
74
33
79
35
4
6
6
6
8
9
10
11
11
13
13
15
16
47
88
38
50
97
41
54
106
45
58
116
49
63
128
53
68
139
58
73
152
62
78
166
66
82
177
70
86
186
74
88
195
77
89
204
79
92
213
82
80
TABLES 25 TO 30:
ANNUAL ELECTRIC APPLIANCE GROSS INVESTMENT AND
COVERAGE RATES
These series were derived from the EPRI data base [41, which in turn
used Merchandising Week [10] as its principal raw data source.
Coverage
COV
rates and gross
investment
are defined
by
CUST
=
ELC
() * S
G :
where
4]
ELCR =
customers served by all utilities in the state
CUST =
customers served by utilities reporting sales of the
[4]
appliance
S
reported
=
state sales
of the appliance
[4]
For all observations having coverage rates below 0.10, both the coverage
rate and gross
presumably
investment
due to errors
are set to zero.
in the data.
See section C for further discussion.
Coverage
rates over
1.00 are
81
YEAR
STATE
1
69
70
71
72
73
74
0
0
704
630
612
610
61?
618
607
609
380
580
?21
583
274
250
63
64
65
742
630
629
566
621
511
0
0
0
0
0
0
925
556
947
492
924
583
907
825
705
953
620
730
589
948
872
709
955
618
7?7
641
814
877
693
704
604
675
640
1261
935
538
613
615
715
618
730
742
61b
678
572
573
562
911
569
458
857
568
360
554
243
934
931
4
735
569
563
5
6
956
811
956
756
941
768
7
2476
924
948
8
9
10
11
12
631
641
736
735
627
638
924 4856
566
592
536
733
640
926
572
13
14
237
654
232
379
?32
337
15
16
17
1480
601
3n7
465
562
348
472
559
573
382
629
377
690
683
691
1125 1071 1076
879
894
933
879
871
880
866
844
A39
452
456 1142
729
689
796
685
673
657
27
505
250
467
28
29
387
597
383
716
430
714
298
?98
30
68
62
5652
19
20
21
22
3
24
5
26
67
61
3
18
66
60
0 7520
2
(THOUSANDTHS)
RANGES
ELECTRIC
FOR
RATE
COVERAGE
TABLE 25
.297
31
32
33
460
462
775
456
438
817
447
465
A13
34
0
0
0
35
36
37
785
736
1041
38
937
39
40
41
42
43
290
278
311
455
860
44
963
45
46
499
429
47
607
48
49
=0
475
7Q0
273
305
362
376
416
706
717
721
714
0
0
0
611
93A
942
945
0
0
0
558
0 1166
584
938
0
20?
1093
1087 1093 108
603
59?
611
618
0
247
693
688
957
611
693
0
0
765
.696
0
280
636
0
586
734
0
0
0
568
572
0
0
930
555
940
578
957
c38
578
580
0
0
0
939
564
90t' 839
561
553
940
566
941
557
855
338
461
770
769
771
772
707
722? 668
669
338
350
191
341
191
342
189
330
193
324
194
321
195
221
194
0
219
214
576
545
580
542
584
58~
607
612' 599
596
604
357
768
965
199
853
966
507
919
868
847
168
685
867
869
494
697
866
764
627
687
5q1
199
904
968
820
853
72
868
756
343
926
961
827
858
199
883
653
655
353
619
743 1018
956
966
8Rb
771
875
876
821
347
924
956
821
863
606
455
451
762
968
327
621
787
46A
840
875
613
459
422
757
958
650
622
720
968
886
875
734
849
736
840
712
717
703
707
718
0
0
0
0
0
0
0
0
0
576
407
657
655
665
467
536
748
473
449
737
472
0
739
647
564
645
560
299
443
463
199
438
495
305
493
471
802
805
0
0
RR8
8R8
759
761
308
731
736
729
0
0
1042 10n26
746
748
964
945
2R7
289
295
290
289 293
272
270
311
312
364
356
446 447
445
453
838
677
940
822
949 950 952 939
0
487
495
491
410
402 1056
415
617 698 692 837
445 442 442
441
690
'96
691
698
161
209
249
174
0
0
709
837
504
21b
664
657
469
6B4
646
428
651
638
422
654
654
523
614
659
518
607
643
512
607
645
531
450
452
459
464
473
477
0
0
731
0
0
0
704
0
0
131
134
309
315
321
326
334
334
339
366
0
416
453
458
453
463
469
471
470
472
487
809
490
802
826
825
730
804
531
810
0
809
488
805
281
809
0
0
0
0
0
0
0
0
0
893
895
867
895
802
701
557
496
302
0
323
333
305
487
451
333
0
0
0
321
0
0
0
410
890
321
0
0
0
815
0
0
0
0
0
625
295
556
754
754
745
755
751
441
412
280
315
351
280
320
356
279
287
299
136
283
303
569
282
305
579
282
310
574
284
282
283
224
619
837
489
374
397
446
691
186
701
828
479
376
435
446
693
180
608
847
478
374
240
441
693
175
485
823
487
373
193
0
695
154
314
293
294
310
368
431
269
264
835
939
0
388
808
724
887
477
384
764
387
552
196
59Z
890
471
376
762
446
5D5
2B9
624
891
478
375
726
445
318
155
295
447
552
191
804
0
297
309
308
308
203
198
542
912
446
853
0
0
373
373
235
200-
0
0
328
324
157
0
82
TABLE 26
COVERAGE RATE FOR ELECTRIC WATER HEATERS (THOUSANTHS)
rT&TE
60
1
742
2
3
4
5
61
S2
630
%29
566
6?1
511
0
0
0
0
0
0
925
487
263
947
492
872
924
583
877
907
584
601
0 7520
63
64
65
66
67
68
69
70
71
72
73
74
0
630
612
610
612
618
6n7
609
u
305
362
376
416
380
221
704
706
0 1166
538
541
717
558
540
721
0
877
714
0
873
580
0
746
271
0
363
274
250
0
0
5692
735
956
934
569
956
:31
563
911
6
811
688
768
705
0
0
0
0
202
0
7
8
0
2476
641
924
631
948
636
691
620
955
618
704
604
715
618
72
616
9
735
736
733
957 1087 1093 10R
611
618
611
592
676
1093
603
673
280
586
675
677
678
693
688
638
627
640
584
0
0
0
0
0
939
905
564
563
770
75v
338
191
350
347
584
5bb
655
238
619
61
743 1018
966
966
771
8R!
876
875
837
709
839
561
771
191
342
607
650
622
720
968
805
875
712
940
566
772
189
330
612
327
621
787
466
840
875
717
941
557
707
193
324
599
731
347
924
956
821
863
703
930
559
72?
194
321
596
33n
343
926
961
827
858
707
0
0
0
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
p8
29
30
31
32
33
34
35
36
37
38
79
40
q24 4856
926
592
566
572
237
232
P32
399
379
337
1430 465
472
601
562
559
387
348
573
202
454
201
691
683
R37
1125 1071 1076
933
894
920
8PO 871
979
839
844
q66
456 1142
52
796
689
729
0 673
665
505
250
467
387
383
430
597
716
714
297
298
'98
460
456
a47
462
325
350
775
817
813
948
572
175
379
458
496
243
250
757
958
925
849
776
168
685
657
467
536
709
196
443
347
802
0
814 1261
562
573
857 855
338
568
461
360
576
580
545
542
451
357
768
762
968
965
909
919
867 866
869
764
494
627
6R7
687
665
655
473
472
449
0
737
739
305
199
493
438
455
953
805
805
0
0
0
940
957
938
578
668
578
669
580
105
221
194
219
604
613
606
328
199
326
199
234
199
904
461
872
459
853
820
734
853
849
736
847
0
718
0
0
0
0
0
407
0
0
214
0
504
216
664
684
651
654
586
607
579
576
0
0
0
0
0
0
0
0
469
0
0
428
450
422
452
523
459
518
464
512
473
531
564
560
731
0
0
0
704
0
477
0
0
131
309
416
281
809
315
453
487
809
321
458
490
802
326
453
358
825
334
463
268
804
334
469
0
810
134
339
366
0
471
470
472
0
0
0
0
809
815
804
0
0
0
0
0
0
0
0
682
888
0
806
333
834
305
741
487
0
640
451
637
308
834
0
496
731
893
0
0
736
729
736
1041 1042 1026
937
945
964
290
290
P95
890
321
443
333
321
0
0
0
0
0
0
0
0
n
746
287
556
754
555
0
946
289
625
0
547
555
751
0
0
441
412
410
2Q3
295
295
314
368
835
939
293
294
310
431
724
R87
281
299
136b
25
530
890
283
303
569
252
366
891
282
305
579
284
519
837
282
310
574
282
701
828
280
315
351
283
608
847
280
320
356
279
297
308
2?4
485
823
0
221
542
912
311
356
364
142
455
311
42
453
445 446
447
826
822
840
677
a38
963 949
499 491
q50
495
348
4P7
939
0
429
607
475
790
273
410
698'
s45
696
161
402 i056
8?6
837
442
442
691
690
0 209
50
572
¢98
41
49
734
0
0
289
48
568
0
580
?72
47
247
0
270
46
693
0
0
597
278
43
44
45
0
0
364
415
363
'441
698
249
0
309
308
198
446
853
477
471
478
489
388 384
479
478
378
487
375
374
0
0
376
374
373
373
235
373
200
808
764
76g
726, 397
435
447
240
387
44H
445
193
446
446
441
0
0
0
552
191
q52
196
55o
32e
318
150
322
186
693
180
324
175
649
154
280
157
275
0
83
T4 FE
27
COVERAGE RATE FO
ELECTRIC DRYERS (THOIJSAN)THS)
STATF
YE A
60
1
61
62
630
629
566
621
511
0
0
0
0
0
934
569
922
931
563
617
768
947
492
872
709
955
618
924
583
877
693
704
604
907
811 756
925
556
819
705
953
620
0
730
7P7 615
64 1 640
814 1261
573 562
742
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
0 7520
63
5652
735
940
2476
924
948
641
631
636
735 736
638 627
924 4793
733
640
926
572
237
232
399
?32
379
1490
601
m37
465
562
569
472
;59
568
360
338
461
554
387
382
348
629
573
377
691
683
690
576
545
451
762
968
909
867
869
580
542
357
768
965
919
866
764
168
494
685
657
467
493
748
299
443
463
802
522
655
473
1125 1071 1076
911
458
243
422
757
958
?20 925
R79
868
847
R66
894
25
26
871
844
448
689
673
169
729
L65
34
66
566
880O
839
456
796
657
23
589
948
572
65
592
933
22
64
q87
855
68
69
70
71
72
73
74
0
630
612
610
0
305
612
36?
618
376
416
607
609
221
704
380
706
717
721
714
580
583
274
250
67
584
0
1166
55R
947
938
0
n
0
0
942
945
93R
0
0
0
0
202
683
765
692
696
636
935
538
613
615
715
618
742
61b
575
618
693
6R8
693
0
0
0
0
0
957 1087 1093 108Q 1093
611 618 611 592 603
247
568
0
0
0
0
0
905 839
5653 561
94n0 41
566 557
770
338
894
191
771
191
77?
189
707
193
72?
194
668
195
350
347
342
330
324
321
940
578
584 595
655 653
619 618
743 1018
966 966
607
650
622
720
968
612
327
621
787
466
771
599
821
347
924
956
596
756
343
926
961
856
876
837
875
709
886
84n0
?21
604
551
199
904
968
875
712
827
q63
703
820
627
875
717
21
850
707
853
718
504
687
665
472
216
664
657
469
0
0
684
646
42d
450
0
651
638
422
452
0
654
654
523
459
n
0
614
659
518
464
607
643
512
473
607
645
531
477
707
0
0
0
n
0
315
0
734
572
939
564
93n
555
2RO
586
957
578
669
194
219
613
459
938
5 80
0
0
214
606
455
199
199
872
966
734
853
507
841
736
840
0
0
0
0
576
647
564
407
645
560
0
131
134
27
505
250
467
28
29
30
41
32
33
34
387
3B3
0
297
430
716
298
714
298
449
446
437
438 438
465
775
813
0
0
0
0
0
0
761
0
0
731
895
305
0
430
867
333
0
423
P95
323
0
422
R93
0
0
36
37
38
39
40
890
321
0
759
708
308
0
7R5
888
0
35
302
0
5S7
333
0
701
451
496
0
902
487
0
321
0
0
0
0
0
0
0
0
0
412
279
410
297
308
309
308
203
542
912
198
817
1041 1042 1026
650 945 964
449
0
0
73 7
739
1Q9
305
309
438
455
805
493
471
05
45 3
321
416
326
334
458
334
453
339
463
366
469
0
481
809
490
802
826
825
730
904
531
810
521
809
470
488
815
472
281
809
471
704
0
804
290
278
616
746
290
270
625
295
556
28R7
754
2Q9
295
754
745
755
751 441
356
364
289
293
295
41
311
?72
311
442
165
318
960
727
426
314
42
43
44
45
499
282
305
579
284
282
310
574
2R2?
28n
31s
351
283
624
280
320
356
224
619
701
949
608
485
499
950
491
891
837
Q28
847
823
4 R7
0
495
j68
835
939
287
299
136
269
653
890
283
303
569
264
963
647
952
447
838
939
293
294
310
431
724
Ra7
415
617
0
0
410
698
477
471
402
478
1 056
388
608
489
479
47R
487
0
0
442
447
375
726
445
374
397
446
374
24n
441
200
552
55
373
193
0
226
552
376
435
446
373
445
3 76
752
44d
373
441
384
764
387
318
0
0
693
69n
191
695
196
324
322
155
180
175
154
328
157
46
47
312
R?6
83
48
6O0
475
49
790
C0
698
696
273
691
249
690
161
174
209
442
.691
186
0
446
853
0
84
GRDSS TNVESTMFNT
28
TA8L
F ELFCTPIC RANGES (HUNDPEDS)
STATE
1
2
3
4
5
6
7
8
9
10
1
12
13
14
?5
16
17
18
19
60
61
340
388
0
21
0
147
171
121
67
1586
262
82
30
966
343
78
32
33
34
35
36
37
38
49
40
41
281
0
633
0
2n03
?23
222
119
133
169
0
0
68
177
217
0
U
22v
0
69
70
71
545
716
514
82.
5
14
14
221
83
264
278
163
0
25
180
0
158
181
107
462
523
72
73
74
14
PO6
558
47
321
45
7744
0
43
591
0
1959 2377 2419 2007 1533 1576 182q 300? 1635 1916 2078 2089) 2n480o
328 317 304 305 188 197
72
0
0
0
0
0 ) 591
?1 0
227
24 7 278
286 296 1 035
350
346
324
355
0
263
19
20
24
21
24
21
32
56
65
54
66
61
42
841
877
933 1114 1191 1197 1204 1323 1 328 1384 1582
0
0
0
323 522 857 872 878
0
0
0
0
0 1672 1658
0
1 655
377
209
221
75
115
520
641
65
212
515
481
'4 6
507
439
503
816
196
215
190
469
497
21
225
394
61
0
91
274
76
167
56
30
31
543
0
138
25
26
?9
412
A6
77
146
112
28
b5
72
1 46
34
?7
64
144
23
32
105
63
1 35
]44
54
225
376
496
403
20
p1
62
14
199
195
P29
2?5
445
180
298
215
228
542
2?4
74
7n
A5
82
244
294
405
706
262
440
6?8
478
267
783
220
458
234
93
363
470
744
111
1?0
537
926
246
?23
343
288
103
122
13?
151
93
96,
93
86
4b1
67 487
383
1115 1183 1284 1259
251
262
277
278
242 273 260 243
343 360n 629 369
234 289 263 247
B3
135
173
130
471
451
647
431
90b 586 615 655
875 994 962 934
53b 656 689 561
577
375
46
262
360
176
298
382
77
384
208
255
303
342
75
93
85
328
44
170
1?3
275
202
399
84
237
229
236
72
55
444
72
250
o
0
29
277
310
755
0
0
157
146
348
182
386
171
41
103
591
442
415
963
1138
232
369
93
201
0
0
506
547
81
71
260
226
14
0
14
0
13
0
0
0
0
o9
125
940
20
1268 1158
289 295
269 325
442 629
340 591
117 137
392 411
631
454
192
109
0
0
345
316
661
168
702
721
932
350
374
216
624
585
0
0
o
o
570
123
244
745
624
733
801
774
0
0
590
622
91
113
220
276
655
123
270
16
16
0
0
0
0
516
85.
217
104
0
173
107
537
1209
335
311
721
o
40
44
81
60
0
91
46
0
0
11
12
473
381
408 433 430 492 475 554 522 643 544 562 523 493
o
247
108
114
141
143
75
70
118
68
71
66
73
94
1
91
1022 1091 1133 1251 1364 1409 1567 1451 1609
968
829 564
0
802
o
571
562
667
747 703 880 946 1050 1264 1096 1080
1359 1415 1101
112o
0
0
0o
0
0
0
0
0
0
0
0
0
0
0
790
786
780
897 1 044 10655 1052 1017 1126 1208 1203 1404 1346 1095 1718o
173
182
208 222 240 214
0
202 143 254 242 246 242 280
0
51
335
706
78
376
68
541
837
139
56
42
43
44
45
46
604
&,7
540
48
49
244
0
32
I 17
726
83
0
859
o
936
76
44
47
406
421
70
352
51 0
54
491
59
499
49
573
493
803
c(1
1 0 86
104.3
167
h9
177
60
165
60
690
547
425
752
449
784
3?6
627
147
129
1 06
286
?73
45
39
95
o
14b
268
292
25
70
0
0
978 1111 1080 1115 1221 1056 1175
1212 1357 1160
1 OBO
51
58
57
77
85
84
94
109
116
0
456 390 436 433 424 438 447 495 582 592
87
64
43
26
23
27
35
48
52
46
562 605 72b 786 798 737 766 871 922 816
*47 Q75 991 991 1205 1486 1193 2nn5 1872 2067
179
169
157
157
178
217 247
194
138
162
64
73
0
38
26
42
27
21
0
o
667 674
802
747 825 832 1035 1204 1150
S74 614 b43 656 519 529
521
522 550 508
345
42
327
25
121
601
30
143
127
556
o
o
0
56?
606
675
570
43
45
5
24
0
85
TABLE 2
GROSS INVESTMFNT OF ELECTRIC WATER HEATERS (HUNDREDS)
STATE
YEA?
6n
61
64
63
2
66
65
67
68
69
70
71
72
73
74
262
1
208
190
224
201
413
346
0
0
190
253
237
277
291
279
2
0
0
0
0
0
0
0
0
11
21
20
36
78
67
65
3
4
3
17
29
17
41
29
72
36
72
36
35
52
34
72
4+
0
46
26
54
53
66
0
80
0
144
0
312
0
416
0
5
3?8
333
418 1234
670
457
377
296
318 1071
365
557
318
496
439
6
31
34
44
43
0
0
0
0
0
0
0
0
0
0
7
30
87
93
98
104
132
150
131
146
157
165
16R
115
24
0
8
?8
11
11
12
11
13
16
12
14
17
16
18
19
19
16
9
1188
1289 1139
1??0
0
0
10
138
175
187
205
11
12
13
84
94
138
14
78
16
125
153
85
130
187
98
132
174
247
204
15
16
17
?1
23
149
60
24
125
56
24
115
57
25
228
18
19
25
37
25
45
39
34
20
79
84
310
163
32
34
86
86
150
143
5
67
91
123
486
137
51
300
?1
22
23
24
?5
26
234
1397 1443 1456
1297 1451
17
1434 1594 165P
0
0
0
0
0
0
0
127
130
117
167
95
115
111
307
130
122
130
371
149
111
8'1
448
153
98
116
500
159
91
117
570
163
91
79
108
22
118
108
26
116
133
25
41
140
30
231
167
40
97
175
43
284
40
43
24
45
30
45
38
40
66
0
76
45
103
168
290
145
50
59
185
199
319
169
93
73
127
215
328
188
212
82
135
173
330
728
186
82
126
211
356
204
76
70
110
204
286
377
0
91
0
387
384
0
561
164
118
150
476
186
112
149
0
522
177
114
149
591
180
115
0
178
55
126
18P
55
281
229
79
283
292
85
306
272
115
256
100
59
144
54
87
63
177
77
133
85
95
76
122
240
307
372
0
92
88
267
276
224
0
101
83
268
263
334
0
67
122
252
274
260
0
76
145
204
268
0
0
84
0
16?
928
0
0
129
0
0
4
3
5
5
6
0
0
0
0
0
0
0
0
0
?7
45
91
34
41
q7
39
42
39
55
47
42
49
98
99
91
28
36
18
139
18
66
0
0
20
12
73
86
0
0
29
30
31
26
319
10
32
261
8
27
281
9
32
254
10
37
270
7
39
284
9
46
331
7
0
386
7
0
0
319
373
n10
9
14
292
11
14
0
10
32
33
264
5S7
300
495
415
627
484
612
376
6o7
134
831
252 300 274 369 265
0
0
0
0
913 1025 1220 1012 1068 ln 1203 1276 1064
o10 12
0
313
9
0
416
9
70
314
10
34
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
35
36
206
27
175
34
151
43
172
61
198
84
216
82
219
0
173
0
138
100
276
129
284
206
244
170
370
210
398
0
37
25O
252
276
38
39
40
41
42
43
44
346
20
430
46
361
124
39
336
25
479
38
344
131
43
409
24
512
23
368
R184
45
324
701
n
713
23
414
25
647
367
70
0
0
0
0
363
20
524
20
380
152
48
334
22
333
19
304
150
56
361
26
334
41
373
175
55
328
19
342
54
435
169
56
0O
394
21
370
73
613
199
5b
0
0
0
339
22
366
22
695
312
56
337
26
359
17
657
336
55
357
21
402
17
649
260
66
0
0
0
265
24
427
29
687
297
72
460
27
521
31
752
417
55
470
0
536
28
732
358
56
45
36
40
30
49
0
0
20
59
8
6
47
48
2
0
0
46
47
48
348
411
52
351
493
54
228
461
52
228
469
47
196
491
51
295
524
53
349
552
59
363
551
7d
383
667
78
432
546
80
494
578
62
486
529
56
619
445
0
936
4Q7
0
98
317
0
49
116
111
121
99
112
121
124
98
208
214
192
273
370
285
264
50
5
3
0
0
4
2
2
2
3
5
0
2
0
1
5
86
TABLE 30
GROSS INVESTFNT
OF ELECTRIC
STATE
DYERS
(HUNDREDS)
YEAq
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
705
1
142
95
169
218
181
269
0
0
393
574
533
815
824
888
2
0
0
0
0
0
3
0
5
0
33
45
42
0
43
5
9
75
69
95
9
28
114
175
216
26
225
272
58
67
62
80
90
111
215
4
5
6
7
8
9
42
104
164
0
1031 1071 1q77 1604 1702 1796 1463 2053
113
123
129
149
1P3 235
196 209
85
162
183
220
238
241
272
321
46
31
39
45
48
49
48
47
]10
174
196
227
330
352
447
546
10
217
170
?14
281
404
568
11
12
13
14
15
16
17
18
19
21
93
654
743
51
183
177
135
43
2
70
722
772
158
208
47
146
39
16
87
384
414
180
192
263
124
54
37
81
476
351
149
174
205
120
1
40
80
505
664
210
195
240
171
65
0
0
525
0
58
451
0
0
1719 2782 1723 1897 2022 2163 2032
0
0
0
64
585
517
497
40?
376
394
377
365
303
0
49
80
73
8?
82
92
77
669
9?2 1023 1323
0
0
0
0
0
0
0 1408
0
0
55
75
84
95
101
110
95
98
109
79
85
98
87
126
122
131
501
460
541
425
353
481
0 612
802 1183 1303 1428 1420 1355 1330 1296
249
275
180
299
301 283
297
333
212
239
260
308
309 376
387
4?7
207
244
305
582
347 443
579
739
260
305
362
374
395 465
717
340
87
73
117
125
135
147
147
155
163
132
0
0
340
409
704
726
142
1397
20
185
196
P1
10
85
667
426
161
176
138
119
36
251
213
231
269
3?1
289
327
405
337
465
501
367
550
784
478
543
542
654
929
294
618
722
427
565
663
22
193
575
59
356
407
648
707
582
666
426
671
723
23
277
249
257
763
830
265
217
957
367
24
743
44d
56
475
68
502
269
147
138
198
8
141
371
136
118
32?
P5
41
170
205
136
268
143
356
0
465
0
513
0
484 56?
26
7
28
84
52
10n2 263
3
7
56
149
23
74
2?3
30
83
248
20
96
262
0
120
289
0
126
313
66
133
314
56
126
259
71
138
321
63
18
17
19
48
56
0
0
0
56
371
373
475
435
578
634
655
750
50
58
71
89
76
96
118
128
1173 1483 1734 1527 1572 1566 1589 1059
135
155
170 223
234
271
339
363
757
127
950
464
781
164
775
489
779
171
973
929
744
19
1260
989
0
169
0
950
29
30
31
32
33
0
13
356
361
45
41
1037 1150
70
97
0
133
230
77
0
473
651
2131
0
0
0
0
5R4 603
424
186
252
76
15
266
0
164
268
0
7
5
0
0
34
0
0
35
0
749
0
0
715
C93
760
0
0
0
899
983 1171 1295 1480 1525 1437 155s 1519 1528 1624
36
72
0
0
0
0
0
0
0
47
128
158
178
188
0
244
216
290
278
313
217
172
0
37
331
297
133
0
0
0
0
0
0
0
0
38
39
40
0
973
32
197
0
709
29
221
0
759
29
256
0
857
12
43
828
19
73
48
41
48
54
39
52
894 1188 1204 1440 1432 1310 1509 1430
20
30
7
88
115
110
99
103
76
78
96
95 111
143
ISs
162
50
58
58
16
17
14
34
39
1682 1421
128
O
222
234
38
39
42
346
530
427
325
370
419
514
43
44
45
46
47
568
92
?0
0
360
164
611
98
20
401
364
158
1013
109
12
255
454
136
640
108
24
272
385
124
676
122
0
238
396
172
751
134
0
414
399
184
914 1129 1273 1421 1514 1745 2200 2432 2573
146
145
190
222
229 247
230
202
220
41
55
B
36
25
25
18
0
0
431
512
558
657
753 73R
923
963
909
430 43/
447
460
501
78?
531
560
525
188 180
208
238
138 219
0
0
0
"4
9
245
251
249
241
273
291
39
41'
38
38
55
21
678
786
'723 768
809
819
930
854
352
399
495
464
446
482
553
572
13
20
23
483
77
33
35
2
11
0
87
TABLES 31 TO 34:
ANNUAL GAS APPLIANCE AND ALTERNATE ELECTRIC DRYER
GROSS INVESTMENT
Annual state shipments come from GAMA [7] for gas ranges and water
heaters, and from AHAM [1] for gas and electric dryers.
Annual national
shipments come from Merchandising Week [10].
The sum of reported state shipments was divided by national
shipments to obtain a national coverage rate for each year. Reported
state shipments were then divided by national coverage rates to generate
the gross investment
data.
See section C for further discussion.
88
TABLE
INVESTMENT
GROSS
31
RANGES
OF GAS
(HUNOREDS)
YEA4
STATE
60
62
61
64
63
66
65
67
68
69
70
71
72
73
74
181
1
189
170
270
286
297
357
423
427
383
448
409
437
226
273
2
2
1
1
2
5
9
7
b
12
15
16
17
16
12
14-
3
I10
92
109
110
1?8 106
97
101
125
163
171
231
311
238
195
4
5
238 248 310 301 315 336 347 351 375 416 396 345 342 435 296
2825 2656 3nh69 3269 3459 2928 2423 2025 257S 3163 3250 3406 3773 3iR8 2504
166
301
63
110
264
48
516
532
403
561
45
97
916
12
48
466
49
21
88
195
40
90
198
35
104
180
31
108
196
41
112
2n3
41
99
242
50
93
237
59
S7
2:5
s5
105
255
52
112
235
39
105
211
43
141
209
48
172
229
72
9
387
380
350
356
400
400
379
406
561
635
609
687
10
11
12
342
16
14
310
27
17
390
25
14
448
21
27
525
16
?0
538
42
34
584
23
38
594
27
8
681
42
24
778
53
39
708
58
38
738
63
66
6
7
8
13
14
1587 1492 155- 1494 16?4 1812 1763 1751 2013 1943 1988 2343 2092 2618 1489
493 551 728 845 934 1043 989 916 688 747 793 593 779 658 453
15
16
248
85
238
144
?64
109
283
87
278
100
290
327
10'7 149
308
200
291
273
280
318
248
270
279
285
755
422
201
165
182
116
17
18
223
497
177'
468
?22
641
251
522
240
577
214 250
-704 747
278 295
653 '712
307
742
292
711
229
734
337
637
271
557
194
486
39
51
37
42
77
46
49
44
63
45
758 90n 880 828
434 431 428 438
962 1038 1120 1050
685
474
840
450
406
284
303
744
6
93
283
640
11
72
21'9
549
24
89
65
45
27
19
52
40
32
40
50
20
21
22
463
541
671
517
566
655
659
455
756
659
448
779
777
543
905
919 816
612 516
959 1002
23
307 309
312
334
316
315
287
295
308
372
393
42?
?4
75
26
77
180
585
20
119
168
587
16
124
?11
653
19
142
205
693
19
147
196
683
30
134
185
834
17
127
211
763
12
118
242
749
9
121
236
850
11
12.8
290
844
11
148
279
792
11
122
262
848
8
130
27
47
78
24
933
82
16
381
99
644. 690
736
443 489 464
950 1160 1217
28
14
14
20
52
37
27
9
12
79
30
31
21
644
67
23
765
45
17
857
58
17
935
62
?1
922
75
23
905
70
20
845
63
22
934
68
1759 2103
1950
32
33
34
35
36
37
38
39
40
41
42
43
2041 2362
1858 1742
?4.
16
895
73
1875 1633
.
48
32
1R
33
144 1037 1090 1073
127 168 160 119
1760 2037 2518 2066
1993 2081
352
33
352
39
346
33
340
31
300
14
246
8
199
6
996 920 1021 1031 1068 1199 1152 1133 1161 1254 1041 1298 1276 1189
248 221 293 271 234 304 290 265 319 295 292 28a 455 295
835
304
45
73
62
66
42
25
22
152
13
181
9
?02
12
254
19
240
22
287
13
280
19
261
27
14
9
18
18
26
34
36
38
198
153
204
217
198
203
-216
224
1042 1071 1183 1165 1276 1482 1424 1530- 1530 1640 1673 1868 1782 1498 1296
95
69
81
94 126 122 138 132 159 188 160 170
77
95 102
83 100 11-8 1?0 177 178 169 188 199 188 137 138 196 104
75
44
50
40
61
34
37
27
20
22
32
45
30
34
29
18
268
328
261
1319 1397 1614 1552 1630 1597 1541 1546 1814 1890.1809
44
19
45
11
46
47
48
49
~0
160
23
120
300
.9
206
221
235
162
2067 2113 1856 1394
30
29
32
?9
39
36
31
37
76
108
112
108
110
8
6
8
10
11
13
14
13
10
8
9
11
11
6
149
22
112
282
7
194
37
147
317
7
201
65
163
370
7
245
42
175
420
6
224
52
185
432
7
19i
53
1i4
409
5
211
76
183
438
6
264
73
195
424
8
252
64
171
401
7
286
47
197
459
7
344
448
54'
61
227
226
426
369
11
11
279
38
188
359
8
193
35
167
3?8'
6
120
89
TABLE
32
GROSS
INVESTMFNT
OF GAS WATER
STATF
(HUNDREDS)
YEA
60
1
HEATERS
61
62
63
64
65
66
67
68
69
70
71
72
73
74
340
378
316
335
231
203
241
337
345
375
421
451
370
2
350
821
5
5
4
7
12
20
15
13
24
3
4
19
2Q4
307
26
300
367
391
389
28
433
278
25
416
302
358
253
28
226
260
254
2?'
23
316
244
40R
289
468
311
679
384
730
357
413
323
388
215
5
3982 4508 3R33 3846 5035 4628 4444 432U 4126 3788 3645 4362 4531 1010 3558
6
7
8
9
10
11
12
13
342
429
458
492
517
464
454
48b
499
491
515
613
783
135
520
327
260
254
210
233
249
248
224
235
291
279
271
257
336
249
81
96
75
60
65
56
53
45
39
51
47
31
29
106
59
440
398
517
356
376 481
496
407
483
418
395
390
402 4303
461
519
447
467
409
511
606
637
5'6
656
576
680
782
728 1583
623
16
28
24
22
14
37
21
23
35
28
38
41
28
9
23
25
22
39
36
24
31
29
38
43
39
76 113
147
353
73
1652 1666 2?03 1583 1686 1556 2070 1816 1979 1732 1670 1977 2037
732 1776
14
15
709
467
745
463
16
17
18
19
20
21
22
23
24
297
217
610
64
955
688
816
337
316
?5
1035
300
321
300
?64
627
738
50
61
875
q19
60?2
95
818 1?70
394
395
376
292
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
92
316
46
47
1315
163
1634
158
45
1569
449
36
1675
122
79
54
276
2434
162
27
67
340
37
42
1296
149
1495
146
34
1316
471
44
1647
101
70
60
254
2530
190
17
147
?83
65
32
382
237
2544
3n9
33
1560
618
120
1469
75
73
79
?87
2 14
270
21
46
249
226
81
P90
75
261
66
58
97
48
133
145
180
142
1PR
120
49
50
554
45
523
51
537
92
482
42
5?9
100
486
89
47
682
587
959 1040
595
428
702
447
269
278
232
277
502
594
45
53
763
692
669
697
991 1038
356
417
150
222
531
465
652
542
353
766 '762
527 480
834 1048 1016
377 44R 449
277
330
285
389
424
470
576
565
243
250
226
237
228
304
247
231
756
686
644
751 ..714
702
759
797
40
36
30
40
44
43
41
24
591
72
549
533
561
554 639
641
113 748
706
757
757
690
82n
795
978 1243 112
1128 1080 1205 111
1183
407
544
450
493
507
540
549
632
221
259
226
225
249
286
293
307
840 10O5 1011 1065
121
184
269
2R5
48
115
47'
51
921
941
210
296
1336 1453
1,7
211
36
a1
1554 1405
465
608
179
116
1144 122
60
93
67
88
9
50
248
342
1929 2294
292
2P9
45
39
623
470
914 1033
937 1008 1227 1161
152
111
92 106
105
275
333
234
355
330
76
39
31
49
52
44
43
23
30
36
768
901
840
874
477
274
169
139
140
124
1452 1948 1463 1581 1838
226
157
142
181
203
42
51
30
43
46
1397 1726 1434 1576 1446
518
485
391
406
405
114
48
6/
89 133
1154 1416 1241 1247 1333
90
102
71
100
81
136
102
?5
114
77
68
58
td
67
68
358
316
30d 357
377
2297
679 240d 2853 2843
283
P05
208
19? 205
17
22
lb
14
18
346
120
283
127
2J3
2n
3
11
650
356
876
297
142
312
370
294
478
468
175
40
734
454
475
676
714 1103
490
512
402
279
624
901
98
342
61
36
850
135
1472
297
42
1518
513
117
1629
87
120
71
570
2801
208
19
175
42R
90
31
929
154
1637
15?
53
1724
481
125
1306
12R
125
101
423
3169
247
16
143
435
113
25
756
168
1676
174
49
1706
552
155
1342
110
86
121
418
3542
229
21
67
140
211
102
614
47
1055
1680
85
1244
457
777
1707
68
637
85
1431
1729
99
51
385
81
266
69
38
1025
125
1476
311
71
1262
512
59
1524
85
189
81
373
2290
174
14
394
391
951
336
1Z2
155
189
154
123
127
14?
135
183
172
169
165
589
53
51U
4-
613
52
S30
h83
560
32
786
37
829
35
541
11
657
30
113
171
151
94
98
90
TaBLF
33
GR9SS
TNVESTMFNT
OF GAS
DRYERS
STATE
(HUNDREDS)
YEA'
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
1
17
12
13
16
23
23
26
33
31
34
31
27
32
30
21
2
0
0
0
1
1
2
1
4
4
5
3
6
6
7
5
3
4
5
6
7
8
53
439
20
19
15
38
479
19
20
13
30
"50
21
19
14
49
796
24
26
?1
27
33
48
55
61
952 1015 1058
31
37
35
31
34
39
W4
8
5
5
5
6
8
9
11
1J
11
13
12
12
10
11
8
9
10
13
16
8
12
7
23
32
31
15
45
38
66
35
76
37
85
35
109
38
124
36
89
36
85
46
96
53
85
41
57
11
12
1
3
0
1
1
1
4
1
8
1
3
2
1
3
2
3
3
2
3
2
4
3
12
4
9
4
9
4
9
3
13
499
554
5P3
642
715
835
853 1090
964
934
896
14
15
16
17
18
147
98
46
41
137
907 1216 1103
140
94
46
35
148
170
11
45
35
128
88
201
112
48
42
170
206
145
54
49
211
245
169
62
56
271
258
176
69
61
289
275
189
84
85
27B
272
191
82
85
260
235
175
80
89
257
219
161
81
90
272
291
191
102
104
320
206
127
69
56
223
BY
191
'v
59
291
214
82
37
311
55
77
80
89
62
86
70
5
1323 1462 1334 1367
52
54
53
59
54
51
47
39
113
95
60
77
49
59
534 1707 1468
76
67
46
SO
46
35
241
162
92
79
310
19
7
4
4
5
5
9
6
d
6
6
7
8
7
88
84
6
5
20
21
93
115
106
124
116
135
136
193
153
160
159
184
209
254
178
247
178
259
184
234
195
221
238
276
198
236
141
161
?2
417
374
425
467
566
658
674
801
732
795
750
743
935
849
23
129
681
119
153
153
182
197
201
25e
227
217
211
22Q
271
242
195
24
5
12
5
6
14
21
23
28
25
27
27
22
24
25
12
11
163
172
205
207
2?7
261
270
338
296
285
274
276
319
271
206
3
2
4
4
6
9
8
9
lo
9
9
8
6
5
?7
48
34
38
39
48
52
54
56
66
65
63
59
70
49
36
28
P9
1
3
1
2
1
3
2
6
12
4
8
5
7
6
6
10
6
7
6
8
9
8
14
8
24
11
18
7
16
6
30
31
253
9
279
14
?96
11
291
14
329
37
366
26
398
23
530
36
486
29
521
33
457
32
464
32
530
43
459
39
330
30
26
10
32
347
425
412
450
511
554
578
788
708
710
673
627
816
33
4
2
3
5
11
14
28
32
34
40
37
46
34
35
51
34
4
349
20
3
5
330) 340
5
361
11
405
12
417
12
428
16
500
13
463
13
451
14
407
13
402
17
452
9
400
8
331
36
54
78
70
79
84
86
94
113
117
110
115
119
145
116
88
9
1
2
3
3
6
8
8
8
12
13
1?
12
37
687
1i
539
7
38
39
40
375
7
1
391
8
1
375
12
1
354
11
1
412
15
2
466
18
4
501
23
5
661
31
6
580
41
8
625
36
9
627
37
9
587
31
11
764
40
12
41
42
9
6
8
3
10
3
10
3
11
6
14
10
14
14
17
15
16
12
16
14
17
12
16
13
21
13
13
12
10
8
43
190
187
172
2n7
261
286
337
414
445
430
422
42'
492
425
357
44
15
2
12
16
1
11
3
22
17
2
14
4
22
25
1
16
6
25
36
1
17
6
?7
43
2
23
42
2
28
55
4
32
51
5
29
51
S
36
48
3
38
58
3
44
61
4
50
46
2
29
33
1
20
8
11
15
15
16
15
13
17
15
14
35
40
51
45
45
50
51
64
46
37
25J
212
220
196
202
263
222
176
4
5
4
6
5
4
3
45
46
47
48
17
27
49
194
128
132
140
170
201
219
t)
r,
2
1
1
1
2
3
4
4
586
29
8
480
21
5
9i1
TARLF 34
GROSS INVESTMFNT OF ELECTRTC
STATE
RYERS (HUNDREDS)
Y
61
62
63
6 67
6
69
70
71
72
73
74
6n
61
62
63
64
65
66
67
68
69
70
71
7?
73
74
1
109
141
31
211
13
258
23
37
311
43( 6
494
15
371
2-
40i?
74:3
81
9:
31
416
1 07
144
570
51
296
5
sO
71
23
176
69(
62
107
2;
601
16
669
6
148
7
8
26
110
24
42
701
107
183
28
169
128
54
291
180
2
3
4
9
10
11
12
200
120
63
321
?.q
13
154
14
11.7
15
16
111
]7
45
170
189
391
156
40
18
19
30
21
;2
23
24
'5
89
163
62
127
245
136
116
99
94
40
177
220
281
144
42
153
48
117
17
17
236
37
?7
29
28
216
39
42
218
50
30
563
31
95
52
40
48
66
q56 1141
1 30
155
190
207
31
39
213
274
167
205
1237 1277
202
181l
229
271
213
?96
67
370
70
291
399
4
348
79
422
?98
177
134
117
1 1 75
48
217
274
336
176
50
170
58
138
27
39
225
50
,524
1 84
140
145
119
52
230
301
356
201
65
193
65
153
48
40
255
52
706
149
52
764
140
280
647
63
558
92
35
608
100
201
581
39
29
44
189
361
58
19
44
21
1 41
45
46
321
135
1g5
376
47
272
48
23
138
319
124
237
20
24
153
271
23
11
10
9
10
20
20
28
38
32
33
34
670
35
209
36
652
37
35
38
39
31
80
40
196
41
42
43
3r01
49
.50
84
122
52
25
132
243
609
53
41
56
?23
399
72
25
137
P56
85
57
44
330
52
66
70
80
82
724
812
683
101
105
10v
70
117
83
127
450
452
530
571
574
625
171
223
138
47
265
179
74
293
364
535
283
272
?26
71
541
283
227
324
24d
86
340
428
109
39~
566
66U
317
341
210
586
279
266
348
283
117
425
561
655
171
335
105
204
396
44
227
227
41
50
.37
92
422
60
70
356
54
57
756
198
69
864
283
62
899
374
77
89
8'3 1010 1166
176
166
221
356 364
314
848 966
717
60
67
71
86
275
440
P6
27
210
79
121
69
164
320
527
395
599
495
788
4n6
88
91
110
31
41
49
248
4?8
300
459
186
374
549
209
331
374
432
29
31
77
103
343
241
251
451
483
112
244
64
114
692
884
94
106
169
129
569
602
287
541
631
340
294
526
112
234
66
664
705
302
356
457
406
15I
564
57?
764
384
339
629
131
271
87
118
508
124
108
109
472 437
75
856
89
91
1059 1101 1156 1097 1269
490
597 694 857 1021
90
94
94
98 112
1239 1332 1425 1306 146n
248
290 317 338 41
375
394 422
380 469
10)96 1118 1227 1225
11401
109
10o
113 106 10I
287 334 358 431
222
54
90
93
90
99
633 615 646 791
93 1153 1198 1297
1 621
155
134
155 147 187
50
64
69
65
70
43? 501 555 611 771
603 604 581 507 560
2821 230
267
?82 33?
471
464 436 485
34
3,8
37
38
40
46
394
580
45C
97
907 1146 1477 1922
302 291
364 391
295 317
133 135
458 -469
653
344
132
182
45
303
505
277
92
304
30.
72
7
544
398
613
194
i8.
71
408
381
541
165
58
350
520
234
401
q1923 2194
40O
482
56.
375 5
380
489
142
335
294
30' S
37(
370
375
190
438
2'8
86
232
80
173
39
4?
266
1493
164
2155 245
1564 1431
31C
325
356
68
523
515
257
374
12F
32
230
313
1709
1043 1154
92
4
204
817
814
356
221
972
957
430
414
451
535
469
175
662
588
529
661
901
441
694
402
419
847
721
161
322
1954
479
382
90
1529
89
130
203
933
875
414
383
511
464
189
1 56
731
672
538
895
494
309
736
139
995
500
156
324
108
137
676
714
145
155
329
126
143
291
115
126
642
142
1605 1699 1431
1172 1302 992
136 134 137
1724 1Q97 1679
480 544 457
513 570 542
1760 1806 1516
112
88
512
544
410
129
127
120
117
924 1053 q36
1934 2196 1906
214 232 193
74
71
54
874 948 757
625 724 693
383 369 301
554 587 530
54
59
60
92
TABLES 35 TO 37:
ORIGINAL ANNUAL GAS APPLIANCE STOCK DATA
These series were derived from the gross investment data in Tables
31 to 33 and the U.S. Census
of Housing
[12].
See section C for further discussion.
93
TABLE 35
STICK
F GAS DANhlES (THOUSAN35)
YEAR
STTF
6n
61
62
63
64
1
2
260
0
260
1
260
1
263
1
267
3
241
247
?51 257
4
254
259
?64
5
37c7 3826 3e86
65
66
67
68
69
70
71
72
73
74
1
270
2
274
3
274
4
281
5
290
7
296
9
29R
12
3n2
15
299
19
297
22
?A3
269
?74
277
282
291
298
30n
316
328
338
272
278
3968 4n02
277
278
312
314
53
55
261
2A9
285
?91
292
300
312
320
325
329
332
338
6
7
8
9
274
307
49
234
275
309
51
244
?75
311
52
?53
10
351
356
360
367
11
36
36
36
36
12
13
135 4187 4184 4212 4291 4350 439R 4453 4510 4560
260
315
56
277
280
317
58
284
27
316
59
264
280
319
61
292
282
325
64
310
283
327
65
323
284
326
66
332
285
326
68
343
287
326
70
348
290
328
72
354
376
387
395
347
409
431
445
45q
465
468
481
35
35
35
3b
35
35
36
37
37
36
36
4
4
5
6
7
7
9
9
10
11
12
13
15
18
20
2056 2101 2141 2186 227 2269 2312 2326.2376 2459 2506 2547 2600- 2640 2700
14
15
16
17
18
19
609
3?8
383
343
660
42
618
334
378
348
668
41
529
340
375
350
674
40
648
347
370
355
689
39
671
3;4
365
3A0
607
38
694
361
361
365
706
38
718
368
356
367
717
37
724
359
351
357
719
35
747
377
350
373
730
35
767
387
355
383
752
34
778
392
357
389
763
33
738
396
357
393
770
3?
792
400
357
395
778
31
799
418
360
399
781
30
20
21
718
847
732
857
748
771
794
RPO
819
885
847
897
859
895
884
899
91.2 932
911 914
951
914
975
915
997 1018
914 914
22
1052
1066
1272
1289
1307
1323
23
398
394
401
407
414
420
424
423
428
436
442
447
453
458
463
24
25
26
2?8
696
60
228
703
59
'28
709
59
230
719
58
230
728
58
230
736
53
229
745
57
226
742
56
228
751
55
231
772
55
233
780
54
233
783
53
233
788
52
233
788
51
232
786
51
?7
196 . 195
194'
194
194
193
191
187
186
186
185
183
181
178
174
28
?9
30
31
32
33
34
968 875
1079 1098
1116 1137 1156
16
17
19
20
24
28
29
30
31
32
13??
1343 1369 1401 1435
131
132
133
134
116
1152 1185
27
30
32
34
33
34
35
36
1466 1494 1506 1540
135
139
139
141
1230-1258
804
419
356
402
783
30
37
41
4A
53
60
66
37
38
39
40
41
44
1583 1513.1619 1617 1646 1677
144
146
148
151
155
159
3826 3873 3932 3969 4018 4055 4082 4079 4116 4162 4186 4212 4255 4278 4301
72
77
82
R7
05
101
107
109
116
128
135
141
146
149
151
25
25
25
25
25
25
25
25
26
27
27
28
28
28
27
35
36
1620 1626 1628 1636 1642 1646 1651 1638 1645 1665 1670 1664 1666 1665 1662
498 499 500 503 506 506 508 505 507 514 515 515 515 519 519
37
38
39
40
41
42
48
48
48
48
48
48
49
4i
5n
52
54
5;
57
57
57
1854 1858 1062 1872 1879 1886 1896 1854 1902 1936 1949 1957 1971 1978 1979
133
133
]33
133
132
133
133
132
133
136
138
13Q
139
136
135
50
53
56
59
64
65
74
77
83
93
99
105
108
112
117
40
40
40
41
42
42
42
42
42
42
43
43
44
44
44
192
195
195
197 2no
201
201
199
201
207
210
21!
210
209
208
43
18A5 1904 1932 1968 19g
2026 2047 2044 2069 2124 2154 2172 2200 2223 2241
44
69
70
71
72'
74
75
76
77
78
80
83
87
91
94
45
12
12
12
12
13
13
13
13
13
14
14
14
14
14
14
46
296
306
316
328
341
353
367
317
390.
408
424
440
457
480
501
47
48
54
277
54
276
.55
275
56
276
;7
275
59
277
60
277
51
275
63
276
67
279
69
280
70
279
71
279
72
279
74
280
49
50
406
43
415
43
423
42
432
42
442
42
452
42
464
42
458
41
481
41
500
41
511
41
512
40
530
40
538
40
545
40
98
94
STOCK F GAS WATER HEATERS (THOUSANDS)
TaBLE 3
YEA?
STATE
68
67
66
65
64
63
62
61
60
69
70
71
7?
73
74
481
1
298
316
131
343
390
356
363
373
392
406
425
439
450
2
0
0
0
1
1
3
4
b
8
12
17
24
34
43
56
370
380
387
402
420
444
478
507
527
3
4
5
6
274
290
307
3?4
339
357
379
432
416
38? 402
366
353
3n2 315 325 33t 341
239 256 ?76 22
4338 4527 4743 4874 492 515S 5279 5406 5477 5616 5740 S880 6049 6181 6203
50b 517 537 556 580 609 637 643
490
475
45
420 439
398
380
7
8
216
42
230
47
p41
52
247
56
2q1
58
256
61
261
64
256
56
267
68
272
70
279
73
287
76
294
78
298
80
307
85
9
10
186
381
207
409
225
433
242
460
251
475
263
496
275
517
2bd
541
293
555
308
583
320
607
334
640
347
678
356
707
507
776
11
12
35
36
9
37
11
37
13
38
14
38
16
38
17
36
19
38
.20
39
23
40
26
41
31
42
38
13
8
1766 1864 1965 2066 213i 2215 22R4 2374
42
46
2431 2532 2623 2724 2941 2940
42
b8
2996
1018 1058 1099
S66 575
553
14
15
639
364
676
386
717
-08
746
428
768
440
797
454
817
467
842
482
859
489
891
507
924
523
966
536
16
492
505
517
527
532
540
546
55J
556
568
580
597
618
613
635
451
721
454
741
474
752
489
778
503
802
523
830
541
860
556
984
578
901
16
15
14
12
13
566
587
608
633
660
255
259
265
271
362
580
377
610
397
540
411
666
423
6R0
438
700
18
19
20
?0
19
19
18
23
437
455
476
493
5n5
522
536
5
24
208
220
235
242
243
245
248
25? 252
p25
758
801
Q40
869
17
18
19
20
21
22
26
27
28
29
30
31
32
33
34
35
36
17
14
13
830 854 879 907 940 966 1 00
578 629 576 713 740 769 790 Rlb
657 679 701 723 751 770 781
;55 577 593 614 630 6 4
498 529
1730 1781 1846 1907 1959 1999
1676
16h5
1595
1555
1510
1470
1414
1366
1318
118
114
112
109
285
279
266
254
28
25
22
19
24
23
21
18
929
905
830
756
177
169
163
156
1503 1611 1715 1844
98
84
75
66
42
41
39
36
1974 2044 2101 2151
529
546
565
960 985 1006
932 924
913
134
132
130
130
128
126
121
319
312
305
304
298
295
2R9
53
49
45
43
41
37
31
32
31
30
30
28
27
25
968 1014 1049 1087 1116 1163 1194
209
207
203
202
198
191
182
1918 d007 2088 2193 2260 2366 2485
105 116 125 133 138 148 159
55
5?
50
49
47
46
44
2190 2231 2264 2309 2326 2374 2416
P5
583 592
60
55
1904 1922
76
74
608
617 627
628
637
645
683
7U5
?75 283
1034 1070 10n921101
144
143
141
136
345
346
338
327
88
73
66
59
39
36
35
34
1247 1305 1346 13b7
?22
222
21213
2601 2729 2P43 2940
285
198
188
177
66
62
60
57
2469 2530 2573 2609
659
672
683
692
120
91
87
82
78
73
70
69
68
65
1948 1964 1989 1994 2020 2049 2095 2127 2149 2189
107
105
101
96
93
90
86
85
82
79
39
47
1733
61
49
1801
67
51
1867
72
40
42
47
52
57
61
66
72
lb
82
90
96
10O
115
1?2
162
Lii
51
53
56
58
59
61
62
b3
64
66
67
69
73
76
78
42
43
201
199
211
2097
44
155
163
172
181
189
199
206
212
215
221
228
235
244
251
10
10
10
11
11
11
11
10
10
10
10
10
10
10
322
59
337
63
359
70
378
77
396
85
410
92
431
103
454
117
484
128
516
144
544
157
605
221
37
38
9
45
247 247 254 261 277 287 292 331
242
226 229 236
220
2210 p29 2334 2399 2452 2457 2485 2572 2656 2753 2863 295q 2998
253
46
47
268
43
286
48
304
54
48
332
329
327
324
320
315
310
3U0 299
294
290
287
285
281
278
49
F6
648
628
601
572
547
520
4)
469
450
429
411
398
382
364
50
75
69
66
64
62
56
53
64
60
57
54
51
73
70.
59
95
TAeBLE
(THOUSANDS)
RYERS
GAS
STOCK-OF
37
STATE
61
60
7
6
15
74
73
72
71
70
69
68
67
66
65
64
63
62
9
10
12
14
17
19
2?
25
28
31
34
37
0
8
0
10
1
13
1
16
1
20
2
24
2
30
3
38
3
48
4
59
5
73
6
86
?4
20
497
417
P0
17
s15 1
28
586
23
21
33
685
27
24
38
790
31
?a
44
824
35
32
2
3
0
5
0
5
0
7
4
5
6
7
9
267
11
9
14
308
13
11
17
355
15
13
8
9
2
6
3
7
3
8
4
9
5
13
6
17
7
21
8
26
9
30
10
35
1?
40
13
46
15
5?
16
59
18
67
10
9
11
12
14
17
21
26
33
3
47
57
65
72
81
88
11
12
0
0
0
1
0
1
1
1
1
1
2
1
2
2
2
2
2
2
2
2
2
3
3
3
3
3
4
4
5
4
13
14
15
16
17
18
3R
131
81
45
22
56
426
142
89
49
25
66
467
53
96
54
28
77
511
165
105
59
31
87
561
181
114
64
35
100
610
195
124
70
40
115
668
212
137
76
45
134
725
229
14
63
50
154
777
243
160
90
55
169
838
260
173
98
62
187
891
275
185
106
69
202
944
289
196
114
76
21
994
301
206
122
83
233
19
2
3
3
4
4
4
5
6
6
7
7
8
8
9
20
35
42
50
60
71
82
95
109
123
138
153
169
185
206
21
33
- 40
50
61
74
87
101
2
23
?4
25
26
27
28
9
30
320
102
4
87
3
351
113
4
381
124
5
676
724
771
815
873
918
167
183
200
216
234
251
268
286
308
326
8
10
11
13
14
16
17
18
19
178
197
213
232
249
26h
281
301
314
7
160
135
157
178
5
5
6
6
6
7
7
8
8
8
40
43
46
49
52
56
60
63
66
69
71
1
3
1
3
2
4
3
4
3
5
3
6
4
7
4
8
5
9
6
10
7
11
156 131 208 235
265
331
369
409
445
481
525
559
12
14
16
19
21
24
27
30
33
37
426
470
523 572
620
664
723
768
8
7
10
8
17
9
21
10
25
11
30
11
34
12
511 533
32
34
0
1
0
1
0
2
112
133
7
35
290
314 338
36
30
8
9
?26 260
299
338
381
3
5
3
5
4
6
6
7
361
387
412
438
2
4
2
4
41
35
47
2
3
4
4
266
294
324
353
0
3
1
9
9
10
10
3
3
121
11
2
627
118
4
192
42
245 26
57
4
165
41
219
539
128
32
139
40
190
492
4
5
.38
144
9
22
112
0
1
2
4
6
5
37
?8
11
1064 1118
329
317
227
218
142
13
98
92
268
252
3
4
37
137
41
78
74
67
62
1605
1444
1361
1224
76
68
59
53
62
57
51
47
99
31
33
4
414
56
49
952 1089
47
41
4?
37
3
1
5
1
3
298
553
571
594
609
81
90
98
106
114
125
133
7
8
9
11
12
14
15
511 549
587
625
659
705
735
33
12
36
14
19
464 485
54
60
67
75
4
5
5
6
13
9
444
479
6
1
7
2
9
2
11
3
14
4
18
5
21
6
25
8
28
10
11
12
13
14
14
15
16
17
17
18
5
7
8
9
10
12
13
14
16
247
27
286
31
322
35
36n
39
397
44
442
49
479
53
31
410
4
5
141
13
163
16
189
20
219
2
1
2
2
2
2
2
3
3
3
3
3
28
33
39
46
54
64
71
20
43
44
73
6
88
8
105
9
45
1
1
1
1
46
7
8
10
12
14
17
20
24
47
3
5
5
6
6
7
8
9
10
13
15
16
18
48
49
22
A6
24
102
26
113
37
189
40
205
43
223
46
241
49
258
53
274
57
297
60
314
10
3
3
3
5
6
7
7
8
9
10
10
-
27
125
4
30
139
4
32
153
4
34
170
5
12