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S'
@B-@z#&J\ P6Q&P##footnote reference##XP\ P6QxXP##&a\ P6G;&P#APPENDIX B
S'N METHODOLOGY FOR ESTIMATING OUTSIDE PLANT COSTS
S8'cI.Introduction
S'1.` ` Section II in this appendix explains in specific detail the regression equations and the
adjustments to these equations for estimating the input values adopted in this Order for structure and
cable costs. These regression equations and these adjustments are set forth in this appendix on the
following tables: Table I., labeled "Regression Equations Derived From RUS Data For Estimating
SH 'Cable And Structure Costs;" Table II., labeled "Adjustments To Regression Equations Derived From
RUS Data For Estimating Cable And Structure Costs;" and Table III., labeled "Regression Equations
S
'Derived From NonRural LEC Data For Estimating Cable Costs."
S'2.` ` Section III illustrates use of the Huber methodology to derive reasonable estimates for
S
'24gauge aerial copper cable costs.
N
yO'#X\ P6G;vP#э We used Stata Statistical Software: Release 5 (Stata) to perform the calculations needed to estimate the
regression equations adopted in this Order for cable and structure costs. Stata has a robust regression
methodology that uses formulas developed by P. J. Huber, R. D. Cook, A. E. Beaton and J. W. Tukey. We used
this methodology to estimate the regression equations for cable and structure costs. We refer to this regression
{O'methodology as the Huber methodology. See StataCorp., Stata Reference Manual, Release 5, vol. 3, PZ, 168173 (College Station, TX: Stata Press, 1997). This illustration uses the diagram in this appendix labeled
"Scatter Diagram Of 24Gauge Aerial Copper Cable Cost And Size With The Huber Regression Line."
This diagram shows RUS cable cost observations for 24gauge aerial copper cable and the regression
line fit to these observations by using the Huber methodology. It also uses the frequency distribution
in this appendix set forth on Table IV., labeled "Frequency Distribution Of Huber Weights For 24gauge Aerial Copper Cable Cost." This frequency distribution shows the number of aerial copper
cable observations to which the Huber methodology assigns particular weights.
S@'3.` ` Section IV demonstrates that the Huber methodology generally does not have a
statistically significant impact on the level of the material costs reflected in the cable cost estimates
adopted in this Order. This finding provides support for the large LEC buying power adjustment
reflected in these estimates. This finding is supported by the statistical information set forth in this
appendix on Table V., labeled "Analysis Of Coefficient For Cable Size Variable In The Huber
Regression Equations."
S('II.Regression Equations For Estimating Outside Plant Structure Costs
S'A.` ` Regression Equations Derived From RUS Data For Estimating Cable
S'` ` And Structure Costs
S'
S`'4.` ` Table I, labeled "Regression Equations Derived From RUS Data For Estimating Cable
And Structure Costs," sets forth the regression equations adopted in this Order for estimating the cost
of: (1) 24gauge aerial copper cable; (2) 24gauge underground copper cable; (3) 24gauge buried
copper cable and structure; (4) aerial fiber cable; (5) underground fiber cable; (6) buried fiber cable" B0*(( "and structure; (7) poles; and (8) underground structure. These regression equations, other than the
equations for poles and underground structure, are developed by revising the regression equations for
S'cable and structure costs developed by Gabel and Kennedy in the NRRI Study.YN
yO'#X\ P6G;vP##X\ P6G;vP#э There is no regression equation for underground structure in the NRRI Study. The regression equation for
underground structure adopted in this Order was developed after the NRRI Study was published.Y The regression
equations adopted in this Order, other than the equation for poles, are estimated by using the Huber
S`'methodology with RUS data. The regression equations in the NRRI Study* ` N
yO '#X\ P6G;vP##X\ P6G;vP#э These regression equations are set forth in the NRRI Study at 58, Table 216 (24gauge aerial copper cable
cost); 60, Table 219 (24gauge underground copper cable cost); 41, Table 27 (24gauge buried copper cable
and structure cost); 59, Table 218 (aerial fiber cable cost); 61, Table 220 (underground fiber cable cost); 49,
Table 210 (buried fiber cable and structure cost); 52, Table 212 (pole cost).* are developed by using
S8'ordinary least squares (OLS) with RUS data.@8N
yO'#X\ P6G;vP##X\ P6G;vP#э None of the regression equations adopted in this Order has a variable that indicates the presence of a
second cable at the same location. The regression equations in the NRRI Study, other than the equation for
poles, have a variable that indicates the presence of a second cable at the same location. The regression
equations adopted in this Order for poles, underground structure, buried copper cable and structure, and buried
fiber cable and structure have a variable that indicates the presence of a high water table. The regression
equation in the NRRI Study for poles and buried fiber cable and structure have a variable that indicates the
presence of a high water table. The regression equation in the NRRI Study for buried copper cable and structure
does not have this variable. The regression equation for poles adopted in this Order
is the regression equation for poles in the NRRI Study. The regression equation adopted in this Order
for poles is not estimated by using the Huber methodology because the Huber regression for poles is
not statistically significant at the five percent level.
Sp'5.` ` Column A identifies, by type of cost, the regression equations adopted in this Order.
Set forth in columns B, D, F, H, J, L, and N are the intercepts and the slope coefficients reflected in
these regression equations. The coefficients set forth in these columns for these regression equations
S
'are for the variables that indicate the size of a cable,]
N
yO'#X\ P6G;vP#э#X\ P6G;vP# The cable size variable is used in the regression equations for estimating the cost of 24gauge aerial copper
cable, 24gauge underground copper cable, 24gauge buried copper cable and structure, aerial fiber cable,
underground fiber cable, and buried fiber cable and structure. It has values that equal the number of copper
cable pairs in the 24gauge copper cable regression equations and the number of fiber cable strands in the fiber
cable regression equations.] density zone,X
N
yOX'#X\ P6G;vP#э#X\ P6G;vP# The density zone variable is used in the regression equations for 24gauge buried copper cable and structure
cost and buried fiber cable and structure cost. It has a value of 1 if a buried cable is installed in density zone 2;
yO '0 if a buried cable is installed in density zone 1.#x6X@`7X@# soil surface texture,Z
N
yOx"'#X\ P6G;vP##X\ P6G;vP#э The variable that indicates soil surface texture is used in the regression equation for pole cost. It has
{O@#'values that range from 0 for normal soil, to 1 for soft soil, to 3 for hard soil. See NRRI Study at 16 and 46,
Table 28. bedrock"
0*((
"
S'type,ZN
yOh'#X\ P6G;vP##X\ P6G;vP#э The variable that indicates bedrock type is used in the regression equation for pole cost. It has values that
range from 0 for normal rock, to 1 for soft rock, to 2 for hard rock. These bedrock types are at a depth of 48
{O'inches. See NRRI Study at 16 and 44, Table 28. combined
S'bedrock and soil type, N
yOb'#X\ P6G;vP#э The combined bedrock and soil type variable is used in the regression equations for 24gauge buried
copper cable and structure cost, buried fiber cable and structure cost, and underground structure cost. It is the
{O'sum of separate variables for surface soil texture and bedrock type at a depth of 36 inches. See NRRI Study at
45, Table 28. The value of the variable that indicates surface soil texture ranges from 0 for normal soil, to 1
{O 'for soft soil, to 3 for hard soil. See NRRI Study at 16 and 46, Table 28. The value of the variable that
indicates bedrock type ranges from 0 for normal rock, to 1 for soft rock, to 2 for hard rock at a depth of 36
{O'inches. See NRRI Study at 16 and 44, Table 28. Accordingly, the value of the variable for the combined
bedrock and soil type indicator ranges from 0 where there are normal surface soil texture and normal bedrock at
a depth of 36 inches to 5 where there are hard surface soil texture and hard bedrock at a depth of 36 inches. and the presence of a high water table.
N
yO8'#X\ P6G;vP##X\ P6G;vP#э The variable that indicates the presence of a high water table is used in the regression equations for 24gauge buried copper cable and structure cost, buried fiber cable and structure cost, pole cost, and underground
structure cost. It has values that range from 0 for the absence of a high water table, to 1 for the presence of a
{O'high water table. This variable assumes that a high water table has a depth of five feet or fewer. See NRRI
Study at 12, 16 and 46, Table 28. Columns C, E, G, I, K, M, and O
display the tstatistics used to measure the statistical significance of these intercepts and coefficients.
Column P displays the Fstatistics used to measure the statistical significance of these regression
equations. Column O displays the number of observations in the data used to estimate these equations.
S'6.` ` The coefficients for the variable that indicates the size of the cable in the regression
equations for 24gauge copper cable cost and fiber cable cost do not reflect the adjustments adopted in
this Order for large LEC buying power. The intercepts and the coefficients in these equations do not
reflect splicing and LEC engineering costs because these costs are not reflected in the RUS data from
which these equations are derived. The intercepts and the coefficients for the water, soil, and bedrock
indicator variables in the regression equations for structure costs do not reflect LEC engineering costs
because these costs are not reflected in the RUS data from which these equations are derived. The
intercept and the coefficients for the water, soil, and bedrock indicator variables in the regression
equation for pole costs do not reflect costs for anchors, guys, and other polerelated items because
these costs are not reflected in the RUS data from which this equation is derived.
S0'B.` ` Adjustments To Regression Equations Derived From RUS Data For
S'` ` Estimating Cable And Structure Costs
S'
S'7.` ` Table II, labeled "Adjustments To Regression Equations Derived From RUS Data For
Estimating Cable And Structure Costs," sets forth adjustments to the regression equations adopted in
this Order for estimating costs for 24gauge copper cable, fiber cable, and structure. The equations
S@'that reflect these adjustments, i.e., the adjusted equations, are used for estimating the cost of: (1) 24gauge aerial copper cable; (2) 24gauge underground copper cable; (3) 24gauge buried copper cable;
(4) aerial fiber cable; (5) underground fiber cable; (6) buried fiber cable; (7) aerial structure; (8)
underground structure; and (9) buried structure. "r
0*(($"Ԍ
S'ԙ8.` ` Column A identifies, by type of cost, the adjusted equations used to derive the cable
and structure costs adopted as input values in this Order.
S'9.` ` Column B displays the intercepts in the adjusted equations. In the adjusted equations
for the cost of aerial and underground 24gauge copper cable, fiber cable, and structure, the intercepts
are those in the regression equations for these costs. The intercepts in the adjusted equations for 24gauge buried copper cable and buried fiber cable represent the fixed cost of buried copper cable and
the fixed cost of buried fiber cable, respectively. The intercepts in the regression equations for 24gauge buried copper cable and structure and buried fiber cable and structure represent the fixed cost of
buried copper cable and structure and the fixed cost of buried fiber cable and structure, respectively, in
density zone 1. The fixed cost of 24gauge buried copper cable used as the intercept in the adjusted
equation for 24gauge buried copper cable, approximately $.46 per foot, is derived by subtracting from
the intercept in the regression equation for 24gauge buried copper cable and structure, approximately
$1.16 per foot, the value of the fixed cost for buried structure in density zone 1 adopted in this Order,
$.70 per foot. The fixed cost of fiber cable used as the intercept in the adjusted equation for fiber
cable, approximately $.47 per foot, is derived by subtracting from the intercept in the regression
equation for buried fiber cable and structure, approximately $1.17 per foot, the $.70 per foot fixed cost
adopted for buried structure in density zone 1. The intercept in the adjusted equation for buried
structure represents the fixed cost of buried structure in density zone 1. The fixed cost of buried
structure in density zone 1 used as the intercept in the adjusted equation for buried structure is the
$.70 per foot fixed cost adopted for buried structure in density zone 1.
S' 10.` ` Column C displays the coefficients for the cable size variable in the adjusted 24gauge
copper and fiber cable equations. In the adjusted equations for the cost of aerial and underground 24gauge copper cable and fiber cable, the coefficients for the cable size variable are those for this
variable in the regression equations for these costs. In the adjusted 24gauge copper cable equation,
the coefficient for the cable size variable is the coefficient for this variable in the 24gauge buried
cable and structure regression equation. In the adjusted 24gauge fiber cable equation, the coefficient
for the cable size variable is the coefficient for this variable in the buried fiber cable and structure
regression equation.
S('
11.` ` Column D displays the large LEC buying power adjustment factors. These factors are
applied to the coefficients for the cable size variable in the adjusted copper and fiber cable equations.
Column E displays the values of the coefficients for these cable size variables in these equations, as
adjusted to reflect large LEC buying power.
S`'12.` ` Columns F, G, and H display the coefficients for the density zone, bedrock indicator,
and combined soil and bedrock indicator variables in the adjusted structure equations. In the adjusted
equations for the cost of aerial and underground structure, these coefficients are those for these
variables in the regression equations for these costs. In the adjusted buried structure equation, these
coefficients are those for these variables in the 24gauge buried copper cable and structure regression
equation. The coefficients for the water and soil indicator variables in the structure regression
equations are not reflected in the adjusted equations because the value for these variables is set equal
to zero to estimate structure costs used as input values.
S%'13.` ` Column I displays the loading factors used to reflect splicing costs in the cable cost
estimates for 24gauge copper cable and fiber cable.
"'
0*((0&"Ԍ
S'
14.` ` Column J displays the loading factor used to reflect LEC engineering costs in the
structure cost estimates.
S'15.` ` Column K displays the flat dollar loading used to reflect LEC engineering costs in the
cable cost estimates for 24gauge copper cable and fiber cable.
S'16.` ` Column L displays the adjusted equations used to estimate costs for aerial,
underground, and buried 24gauge copper and fiber cable, buried and underground structure, and
poles.
Sp'17.` ` Columns MO display adjustments to the adjusted pole equation. These adjustments
add to the cost of poles the costs for anchors, guys, and other polerelated items, including LEC
engineering costs associated with these additional items, and convert per pole costs, inclusive of costs
S
'for anchors, guys, and other polerelated items, i.e., aerial structure costs, to per foot costs. Column
M displays the costs for anchors, guys, and other polerelated items for density zones 1 and 2 ($32.98
S'per pole), density zones 37 ($49.96 per pole), and density zones 8 and 9 ($60.47 per pole).ZN
yO'#X\ P6G;vP##X\ P6G;vP#э These costs for anchors, guys, and other polerelated items are based on the costs for these items in rural,
{O'suburban, and urban areas derived by Gabel and Kennedy in the NRRI Study. See NRRI Study at 51, Table 211.
Column N displays the loading factor used to reflect LEC engineering costs in the costs for anchors,
guys, and other polerelated items. Column O displays the distance between poles used to calculate
aerial structure cost per foot for density zones 1 and 2 (250 feet per pole), density zones 3 and 4 (200
feet per pole), density zones 5 and 6 (175 feet per pole), and density zones 79 (150 feet per pole).
S'18.` ` Column P displays the adjusted equation used to estimate aerial structure cost per foot,
including poles, anchors, guys, and other polerelated items.
SB'19.` ` We illustrate how the adjusted equations are used to develop the input values adopted
in this Order by calculating the cost for a 100pair 24gauge aerial copper cable. Column L sets forth
the adjusted equation used to develop the input values adopted in this Order for 24gauge aerial copper
S'cable. The adjusted equation set forth in column L for 24gauge aerial copper cable is as follows:9N
yOT'#X\ P6G;vP#э Set forth on Table II in specific columns and on specific rows are the values for the intercepts,
coefficients (including the adjusted coefficients for the cable size variable), splicing loadings, and LEC
engineering loadings reflected in the adjusted equations used to estimate structure and cable costs. The specific
column is identified by a letter. The specific row is identified by a number. B1, for example, refers to the value
set forth in column B on row 1.9
` ` A1 = (B1 + (E1)(# of Prs.))(1 + I1) + K1
where:
A1 = 24gauge aerial copper cable cost per foot;
B1 = the intercept for 24gauge aerial copper cable in dollars per foot;
S'E1 = the coefficient, adjusted for buying power, in dollars per pair per foot, for the variable (#(# that represents the number of 24gauge aerial copper cable pairs; "b0*((Z"ԌI1 = the splicing loading for 24gauge aerial copper cable expressed as a percentage;
K1 = the LEC engineering loading for 24gauge aerial copper cable in dollars per foot.
S'20.` ` By substituting into the above equation for 24gauge aerial copper cable the values
from Table II for the intercept, adjusted coefficient for the cable size variable, splicing loading, and
LEC engineering loading, and the number of cable pairs in this example, 100, we obtain the following
estimate for the cost of a 100pair 24gauge aerial copper cable:
` ` A1 = (1.014907 + (.008329)(100))(1 + .094) + .19
` ` = (1.014907 + .8329)(1.094) + .19
` ` = (1.847807)(1.094) + .19
` ` = 2.021501 + .19
` ` = $2.21 per foot.
We adopt this estimate as the input in the model for the cost of a 100pair 24gauge aerial copper
cable.
S'C.` ` Regression Equations Derived From NonRural LEC Data For Estimating (#(#
S'` ` Cable Costs
S@'21.` ` We adopt in this Order a methodology to derive estimates of 26gauge copper cable
costs from 24gauge copper cable costs. We first estimate by using the Huber methodology with RUS
S'data the cost for 24gauge copper cable for each cable size.6
N
yOX'#X\ P6G;vP#э#X\ P6G;vP# More technically, we obtain from these RUS data an estimate of the expected value of the cost for 24
yO 'gauge copper cable for each cable size. 6 We then obtain by using the Huber
methodology with certain nonrural LEC data estimates of the cost for 24gauge copper cable and 26
S'gauge copper cable for each cable size.W N
yO`'#X\ P6G;vP#э#X\ P6G;vP# More technically, we obtain from these nonrural LEC data estimates of the expected value of the cost for
yO('24gauge copper cable and 26gauge copper cable for each cable size.W We next divide the 24gauge copper cable cost estimate
derived from the nonrural LEC data into the estimate for 26gauge copper cable cost derived from
these data for each cable size. The result is a ratio of 26gauge copper cable cost to 24gauge copper
S('cable cost for each cable size.(xN
yO@!'#X\ P6G;vP#Ѝ#X\ P6G;vP# More technically, we obtain from these nonrural LEC data a ratio of an estimate of the expected value
yO"'for 26gauge copper cable cost to an estimate of the expected value for 24gauge cable cost for each cable size. Á Finally, we multiply this ratio by the estimate of the cost for 24gauge copper cable derived from the RUS data to obtain the cost for 26gauge copper cable for each
S'cable size.N
yOH%'#X\ P6G;vP#Ѝ#X\ P6G;vP# More technically, we obtain an estimate of the expected value for 26gauge copper cable cost. We adopt these estimates as inputs for 26gauge copper cable costs in the SM.
S'22.` ` Table III, labeled "Regression Equations Derived From NonRural LEC Data For
Estimating Cable Costs," sets forth regression equations derived from the nonrural LEC data for: (1)"`` 0*(("24gauge aerial copper cable; (2) 24gauge underground copper cable; (3) 24gauge buried copper
cable; (4) 26gauge aerial copper cable; (5) 26gauge underground copper cable; and (6) 26gauge
buried copper cable. We use these regression equations to develop the ratios of 26gauge copper cable
costs to 24gauge copper cable costs used to derive the cost for 26gauge copper cable. Column A
identifies these regression equations by type of copper cable cost. Set forth in columns B and D are
the intercepts and the slope coefficients reflected in these regression equations. Columns C and E
display the tstatistics used to measure the statistical significance of these intercepts and coefficients.
Column F displays the Fstatistics used to measure the statistical significance of these regression
equations. Column G displays the number of observations in the data used to estimate these equations.
Column H shows the regression equations derived from the nonrural LEC data for estimating costs
for 24gauge and 26gauge copper cable.
S
'23.` ` These regression equations are derived from ex parte data on 24gauge and 26gauge
copper cable costs submitted by Sprint and Aliant, data on these cable costs submitted by BellSouth
S'with its comments,:N
{O:'#X\ P6G;vP#Ѝ#X\ P6G;vP# See BellSouth Inputs Further Notice comments, Exhibit 1. BellSouth submitted separate copper cable
costs for nine study areas. We calculate the weighted average of these copper cable costs for each cable size
based on the number of access lines in each study area. We include this weighted average cable cost for
BellSouth for each cable size in the nonrural LEC data from which we derive 24gauge and 26gauge copper
cable costs. By using a weighted average, the regression equations derived from the nonrural LEC data do not
reflect a disproportionate number of observations for BellSouth compared to the number of observations for the
other nonrural LECs for which costs are reflected in these data. The cable costs reflected in the data for these
other LECs are either companywide costs or an average for multiple study areas. In either case, there is a
single observation for each of these companies for a given cable size for 24gauge and 26gauge copper cable
cost. By reflecting the weighted average cost for BellSouth in the data, there is only one observation for
yO'BellSouth for a given cable size for 24gauge and 26gauge copper cable cost.: and the BCPM default values for these cable costs. These regression equations
are developed by using the Huber methodology. Using the Huber methodology with nonrural LEC
data to estimate cable costs for 24 and 26gauge copper cable costs is consistent with use of this
methodology to estimate 24gauge copper cable costs from the RUS data. The regression equations
derived from nonrural LEC data use the number of copper cable pairs as the sole independent
variable. Using the number of copper cable pairs as the sole independent variable in these regression
equations is consistent with using this variable as the sole independent variable in the regression
equations for 24gauge copper cable costs estimated from the RUS data.
Sj'24.` ` In this Order, we find it reasonable to rely on the nonrural LEC data for calculating
the ratio of the cost for 24gauge copper cable to that for 26gauge copper cable but not for
S'calculating the absolute cost for 24gauge copper cable and 26gauge copper cable.
X*
N
yO '#X\ P6G;vP#э We discuss the rationale for using nonrural LEC data to calculate relative copper cable costs, but not
absolute copper cable costs, in this Order, section V.C.4.b.
As discussed in
this Order, we find that the nonrural LEC data is not a reliable measure of absolute costs.
Notwithstanding this finding, we conclude that it is reasonable to use the nonrural LEC data to
determine the relative value of the cost for 24gauge copper cable to that for 26gauge copper cable.
We find that it is reasonable to conclude that each LEC used the same methodology to develop both
24gauge and 26gauge copper cable costs. Accordingly, any bias in the costs for 24gauge and 26gauge copper cable that results from using a given methodology is likely to be in the same direction"*J
0*((J"and of a similar magnitude. As a consequence, cost estimates for 24gauge and 26gauge copper cable
for each cable size developed from nonrural LEC data by using the Huber methodology are likely to
be biased by approximately the same factor. The ratios of these estimates are not likely to be affected
significantly because the bias in one estimate approximately cancels the bias in the other estimate
when the ratio is calculated.
S'25.` ` We illustrate how we calculate the costs that we adopt in this Order for 26gauge
copper cable by calculating the cost for a 100pair 26gauge aerial copper cable. As explained above,
we derive a ratio of 26gauge copper cable cost to 24gauge copper cable cost from nonrural LEC
data to obtain costs for 26gauge copper cable. To calculate this ratio for a 100pair aerial copper
cable, we estimate separately from nonrural LEC data the cost for a 100pair 24gauge aerial copper
SH 'cable and a 100pair 26gauge aerial copper cable. We first estimate the numerator of this ratio, i.e.,
the cost for a 100pair 24gauge aerial copper cable. Column H shows the regression equation derived
from nonrural LEC data for estimating the cost for 24gauge aerial copper cable. The regression
equation set forth in column H for 24gauge aerial copper cable is as follows:
` ` ,A1 = B1 + (D1)(# of Pairs)
where:
A1 = 24gauge aerial copper cable cost per foot;
B1 = the intercept for 24gauge aerial copper cable in dollars per foot;
S'D1 = the coefficient in dollars per pair per foot for the variable that represents the number of (#(#
24gauge aerial copper cable pairs.
S'26.` ` By substituting into the above equation for 24gauge aerial copper cable the values
from Table III for the intercept and the coefficient for the cable size variable, and the number of cable
pairs in this example, 100, we obtain the following result for the cost of a 100pair 24gauge aerial
copper cable:
` ` ,A1 = 2.1548 + (.012393)(100)
` ` , = 2.1548 + 1.2393
` ` , = $3.39 per foot.
Sb'27.` ` We next estimate the denominator for the ratio of 26gauge aerial copper cable cost to
S:'24gauge aerial copper cable cost for a 100pair aerial copper cable, i.e., the 26gauge aerial copper
cable cost for a 100pair cable. Column H shows the regression equation derived from nonrural LEC
data for estimating the cost for 26gauge aerial copper cable. The regression equation set forth in
column H for 26gauge aerial copper cable is as follows:
` ` ,A4 = B4 + (D4)(# of Pairs)
where:
A4 = 26gauge aerial copper cable cost per foot;
B4 = the intercept for 26gauge aerial copper cable in dollars per foot;
S''D4 = the coefficient in dollars per pair per foot for the variable that represents the number of (#(#"'0*((0&" 26gauge aerial copper cable pairs.
S'28.` ` By substituting into the above equation for 26gauge aerial copper cable the values
from Table III for the intercept and the coefficient for the cable size variable, and the number of cable
pairs in this example, 100, we obtain the following result for the cost of a 100pair 26gauge aerial
copper cable:
` ` ,A4 = 2.385108 + (.008721)(100)
` ` , = 2.385108 + .8721
` ` , = $3.26 per foot.
S
'29.` ` We next calculate the ratio of 26gauge copper cable cost to 24gauge copper cable
cost for a 100pair cable. The ratio of 26gauge copper cable cost to 24gauge copper cable cost for a
100pair cable is .96 ($3.26 per foot divided by $3.39 per foot).
SX'30.` ` Finally, we multiply this ratio by the estimate of the 24gauge copper cable cost for a
100pair cable derived from the RUS data, $2.21 per foot, to obtain the cost for a 100pair 26gauge
copper cable, $2.12 per foot. We adopt this estimate as the input in the SM for the cost of a 100pair
26gauge aerial copper cable.
S'III.Huber Methodology
Sh'
S@'31.` ` We find in this Order that it is reasonable to use the Huber methodology to develop
input values for cable and structure costs. The structure and cable cost inputs used in the SM should
reflect those that are typical for cable and structure for a number of different density and terrain
conditions. Otherwise, the model may substantially overestimate or underestimate the cost of building
a network. The Huber methodology produces estimates of costs that are typical for cable and structure
by assigning zero or less than full weight to cable and structure cost observations that have extremely
high or extremely low values. At the same time, it assigns full or nearly full weight to closely
clustered cable and structure cost observations.
S'32.` ` Use of the Huber methodology to derive reasonable estimates from RUS data is
illustrated for aerial copper cable cost on the diagram labeled "Scatter Diagram Of 24Gauge Aerial
Copper Cable Cost And Size With The Huber Regression Line" and on the frequency distribution set
S`'forth on Table IV, labeled "Frequency Distribution Of Huber Weights For 24Gauge Aerial Copper
Cable Cost." The scatter diagram shows RUS cable cost data points representing combinations of
aerial copper cable costs (measured on the vertical axis in dollars per foot) and cable size (measured
on the horizontal axis by number of pairs). It also shows the regression line that the Huber
methodology fits to these data points. The algebraic expression of this line explains or predicts the
S"'effects on aerial copper cable costs of changes in cable size.q0"N
S%'#X\ P6G;vP##X\ P6G;vP##&a\ P6G;&P#э #X\ P6G;vP#The algebraic expression of the regression line for 24gauge aerial copper cable estimated from RUS data
by using the Huber methodology is as follows:
24gauge aerial copper cable cost per foot = 1.014907 + (.009822)(number of pairs)."h'0*((c'"ԌIn this regression equation, 24gauge aerial copper cable cost is the dependent variable for which a value is
measured along the vertical axis. The number of pairs is the independent variable for which a value is measured
along the horizontal axis. The value 1.014907 is the intercept of the regression line. It is the point at which the
regression line hits the vertical axis. It measures the fixed cost for 24gauge aerial copper cable. The value
.009822 is the slope coefficient of the regression line. It is the slope of the regression line. It measures the
additional cost for one additional pair of 24gauge aerial copper cable.q The observations to which Huber"" @0*((]!"assigns a weight that is less than .47 are identified with an o; those to which it assigns a weight that
is greater than .47 are identified with an *. The frequency distribution shows the number of aerial
copper cable observations to which the Huber methodology assigns particular weights.
S`' 33.` ` The scatter diagram and the frequency distribution demonstrate that the aerial copper
cable estimates derived by using the Huber methodology with RUS data reflect most of the
information contained in nearly all of the observations. As depicted on the scatter diagram, the
majority of the aerial copper cable observations are clustered closely around the regression line. These
are the observations to which Huber assigns the greatest weight when fitting the regression line to the
data. As the frequency distribution shows, approximately 82 percent of the aerial copper cable
observations is assigned a weight of at least .8. This large majority of closely clustered observations
clearly represents typical cable costs. The minority of the aerial copper cable observations lies a
considerable distance from the regression line. These are the observations to which Huber assigns the
least weight when fitting the regression line to the data. As the frequency distribution shows,
approximately 18 percent of the observations is assigned a weight of at less than .8. This small
minority of observations comprises extremely high and extremely low values that do not represent
typical cable costs. The scatter diagram also shows that some of the observations that receive a
relatively small weight lie a substantial distance above the regression line while others that receive
such weight lie a substantial distance below this line. This demonstrates that the Huber methodology
excludes or assigns less than full weight to data outliers without regard to whether these are high or
low cost observations.
S'IV.Analysis Of Coefficient For Cable Size Variable In The Huber Regression (#(#
Sh'Equations
S'!34.` ` In this Order, we derive equations to estimate the nonrural LECs' labor and material
cost for cable. We derive these equations by: (1) deriving regression equations by using the Huber
methodology with RUS cable cost data that reflect labor and material costs; and (2) adjusting
downward the coefficient for the variable that represents cable size in these regression equations to
reflect the buying power of large LECs in comparison to RUS companies. The coefficient for the
variable that represents cable size represents the additional cost for an additional pair of cable and
therefore represents cable material costs. The adjustment to this coefficient is based on the difference
between the average cable material prices that Bell Atlantic and the RUS companies pay for different
cable sizes. The RUS companies' average cable material prices are calculated by using unweighted
RUS data. Conversely, the Huber methodology used to estimate the regression equations assigns zero
or less than full weight to data points that have extremely high or extremely low values. Below we
demonstrate that the Huber methodology generally does not have a statistically significant impact on
the level of material costs reflected in the cable cost estimates. That is, in general, there is not a
statistically significant difference between the value of the coefficient for the cable size variable in the
regression equations estimated by using the Huber methodology and the value of this coefficient in the"
@0*(("regression equations developed in the NRRI Study by using OLS. Accordingly, the buying power
adjustment for material is based on averages of RUS companies' cable material prices calculated by
using unweighted RUS data.
S`'"35.` ` Table V, labeled "Analysis Of Coefficient For Cable Size Variable In The Huber
Regression Equations," displays the values of the coefficient for the cable size variable in the
regression equations estimated from RUS data by using the Huber methodology in this Order and the
95 percent confidence interval surrounding the value of this coefficient in these equations in the NRRI
Study estimated from these data by using OLS. Except for 24gauge buried copper cable, the value of
the this coefficient estimated by using the Huber methodology lies inside the 95 percent confidence
interval surrounding the value of this coefficient in these equations in the NRRI Study estimated from
these data by using OLS. That is, except for 24gauge buried copper cable, the value of the cable size
coefficient estimated by using the Huber methodology lies within an interval that contains with 95
S
'percent certainty the true value of the OLS cable size coefficient.X
N
yO`
'#X\ P6G;vP#э#X\ P6G;vP# Strictly speaking, over a large number of different samples, 95 percent of the confidence intervals
associated with different OLS estimates of the cable size coefficient are expected to contain the true value of the
yO'OLS cable size coefficient. This statistical evidence supports a
finding that the Huber methodology does not have a statistically significant impact on the level of the
S'material costs reflected in the cable cost estimates derived by using this methodology.N
{O0'#X\ P6G;vP#э#X\ P6G;vP# In this Order, we affirm the tentative decision in the Inputs Further Notice to use conservatively the lower
of the buying power adjustments for aerial and underground copper cable material costs as the adjustment for
buried copper cable material costs because the Huber methodology does have a statistically significant impact on
{O'the buried copper cable material costs reflected in the buried copper cable cost estimates. See this Order, section
V.C.4.b. The cable size
coefficient obtained by using the Huber methodology for buried copper cable lies outside the 95
percent confidence interval associated with the cable size coefficient obtained by using OLS for buried
S0'copper cable. This supports a finding that the Huber methodology does have a statistically significant
S'impact on the level of the material costs reflected in the buried copper cable cost estimates.j
N
yOD'#X\ P6G;vP#э#X\ P6G;vP# The specifications for the copper and fiber cable regression equations in the NRRI Study differ slightly
from the copper and fiber cable regression equations adopted in this Order. The difference in the specifications
does not alter the statistical conclusions regarding the impact of the Huber methodology on the level of cable
material costs reflected in the cable cost estimates. We estimated by using OLS copper and fiber cable
regression equations for which the specifications matched identically those for the copper and fiber cable
regression equations estimated by using the Huber methodology. Again, with one exception, the cable size
coefficient in the regression equations estimated by using the Huber methodology lies inside the 95 percent
confidence interval associated with the cable size coefficient in the regression equations with the identical
specifications estimated by using OLS. The one exception is that the value of the cable size coefficient in the
buried copper cable and structure regression equation estimated by using the Huber methodology lies outside the
95 percent confidence interval associated with the cable size coefficient in the buried copper cable and structure
regression equation with the identical specification estimated by using OLS. Again, we conclude that the Huber
methodology does not have a statistically significant impact on the level of the cable material costs reflected in
the cable cost estimates other than the buried cable cost estimates.j
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