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                                                           APPENDIX D
                                
   DESCRIPTION OF PROPOSED METHODOLOGY FOR ESTIMATING OUTSIDE
                          PLANT COSTS

     I.   Cost of Copper Cable

     A.   24-Gauge Aerial Copper Cable

     1.   We propose to modify by using the Huber methodology the regression equation
for estimating the cost of 24-gauge aerial copper cable developed by Gabel and Kennedy in the
NRRI Study by using ordinary least squares (OLS).  The modified equation for estimating the
cost of 24-gauge aerial copper cable is as follows: 

          Y =  1.022443 + .009691X1 + .065833X2 

t-statistics:       18.878    57.382    .400      
F-statistic:        1668.33
# of observations:  255

where:

          Y  = cost per foot for 24-gauge aerial copper cable;
          X1  =     number of copper cable pairs for 24-gauge aerial copper cable;
          X2 = 1 if two or more cables are placed at the same location, 0 otherwise.

     2.   We propose three adjustments to the modified equation for estimating the cost
of 24-gauge aerial copper cable.  First, we propose to adjust downward by 15.2 percent the
regression coefficient for the number of copper pairs to reflect the superior bargaining power
of the non-rural LECs in comparison to the companies in the RUS data.  Second, we propose
to add a loading of 10 percent to the material and labor cost of the cable (net of LEC
engineering and splicing costs) to approximate the cost of LEC engineering.  Finally, we
propose to add a loading of 9.4 percent for splicing costs. 
     
     3.   After making these adjustments, we obtain the following equation for the cost of
24-gauge aerial copper cable, YAdj:

     YAdj =    (1.022443 + .009691(1   buy power discount %)X1 + .065833X2)(1 
               + splicing % + LEC engineering %)

           =   (1.022443 + .009691(1   .152)X1 + .065833X2)(1 + .094 + .10)     
     
           =   (1.022443 + .009691(.848)X1 + .065833X2)(1.194)
               
           =        (1.022443 + .008218X1 + .065833X2)(1.194).   

     4.   We use this equation to estimate the proposed input values for the cost of 24-
gauge aerial copper cable.  We do this for each cable pair size by substituting into this
equation the number of cable pairs, X1.   At the same time, we substitute into this equation a
value of 0 for X2 to estimate the cost for one cable when only one cable is placed.  We use a
value of 0 for X2 because the value of the coefficient for this variable, .065833, is not
statistically significant.  In addition, the synthesis model does not use a different cable cost if
the feeder or distribution portion of network it builds requires more than one cable.  For
example, we estimate the cable costs for a 25-pair 24-gauge aerial copper cable as follows:

          YAdj =    (1.022443 + (.008218)(25) + (.065833)(0))(1.194)  

                =   $1.47 per foot.

     B.   24-Gauge Underground Copper Cable
     
     5.   We propose to modify by using the Huber methodology the regression equation
for estimating the cost of 24-gauge underground copper cable developed by Gabel and
Kennedy in the NRRI Study by using OLS.  The modified equation for estimating the cost of
24-gauge underground copper cable is as follows: 

          Y =  1.732609 + .015938X1   .000004X12

t-statistics:       5.002          15.578     6.893         
F-statistic:        504.21
# of observations:  80

where:

          Y    =    cost per foot for 24-gauge underground copper cable;
          X1   =    number of copper cable pairs for 24-gauge underground copper 
                    cable;
          X12  =    the mathematical square of the number of copper cable pairs 
                    for 24-gauge underground copper cable.

     6.   We propose to use the same three adjustments proposed for the cost of 24-gauge
aerial copper cable, with one exception.  We propose to reduce by 16.3 percent the value of
the coefficient for the number of copper cable pairs to reflect the superior buying power that
non-rural LECs may have in comparison to the RUS LECs, based on the analysis in the NRRI
Study.  We also include in the equation loadings for splicing and LEC engineering costs of 9.4
percent and 10 percent, respectively, because the RUS data do not include these costs.  After
making these adjustments, we obtain the following equation for the cost of 24-gauge
underground copper cable, YAdj:

     YAdj =    (1.732609 + .015938(1   buy power discount %)X1   .000004X12)(1 
               + splicing % + LEC engineering %)
     
           =   (1.732609 + .015938(1   .163)X1   .000004X12)(1 + .094 + .10)    
   
           =   (1.732609 + .015938(.837)X1   .000004X12)(1.194)

           =   (1.732609 + .013340X1   .000004X12)(1.194).       

     7.   We use this equation to estimate the proposed input values for the cost of 24-
gauge underground copper cable.  We do this for each cable pair size by substituting into this
equation the number of cable pairs, X1, and the mathematical square of the number of cable
pairs, X12.  For example, we estimate the cable costs for a 50-pair 24-gauge underground
copper cable as follows:

          YAdj =    (1.732609 + (.013340)(50)   (.000004)(502))(1.194)     

                =   $2.85 per foot.

     C.   24-Gauge Buried Copper Cable

     8.   We propose to modify by using the Huber methodology the regression equation
for estimating the cost of 24-gauge buried copper cable and structure developed by Gabel and
Kennedy in the NRRI Study by using OLS.  The modified equation for estimating the cost of
24-gauge buried copper cable and structure is as follows: 

     Y =  1.500999 + .010652X1   .503644X2  + .733031X3 + .570136X4 
     
t-statistics:  5.012          80.735     4.777    3.175     1.911
F-statistic:   1660.57
Observations:  1,131     

where:

          Y  = cost per foot for 24-gauge buried copper cable and buried copper cable 
               structure;     
          X1 = number of copper cable pairs for 24-gauge buried copper cable;
          X2 = 1 if two or more cables are placed at the same location, 0 otherwise;
          X3 = combined bedrock and soil type indicator;
          X4 = 1 if buried cable is installed in density zone 2; 0 if such cable is 
               installed in density zone 1.

     9.   We propose to modify this equation to estimate the cost of 24-gauge buried
copper cable.  The dependent variable in this equation, Y, represents the per foot labor and
material cost for both cable and outside plant structure.  To estimate the labor and material
cost for the cable only, we derive a new equation that explains the variation in labor and
material costs for a copper cable alone.  We derive this new equation by using the value of
only the fixed cost of buried copper cable reflected in the intercept or constant term in the
modified buried cable and structure equation and only the variable and coefficient in this
equation that primarily explain the variation in cable costs.
     
     10.  We use as the intercept in the new buried cable equation the value of only the
fixed cost of buried copper cable reflected in the intercept in the modified buried cable and
structure equation.  The value of the intercept in the modified buried cable and structure
equation, 1.500999, represents the fixed cost for both buried copper cable and buried copper
cable structure in density zone 1.  Of this amount, we assume that $.80 represents the fixed
cost for one sheath of buried copper cable.  This value roughly approximates the preliminary
value that the Commission staff developed for the smallest buried copper cable size for the
workshop on cable costs and the value that HAI uses as a default for the smallest buried copper
cable size.  

     11.  We use as the independent variable in the new buried cable equation the
independent variable that indicates the number of copper cable pairs in the modified buried
cable and structure equation, X1.  We also use as the coefficient of X1 in the new buried cable
equation the coefficient of X1 in the modified buried cable and structure equation, .010652. 
We include this variable and this coefficient in the new buried cable equation because they
primarily explain the variation in cable costs.  We do not use as independent variables in the
new buried cable equation those in the modified buried cable and structure equation that
indicate whether two or more cables are placed at the same location, soil and rock type, and
whether a buried cable is installed in density zone 2, i.e., variables X2, X3, and X4.  We do
not include these variables in the new buried cable equation because these variables and their
coefficients primarily explain the variation in structure costs. 
     
     12.  By using the estimate of the fixed cost for a sheath of copper cable $.80, the
variable that indicates the number of copper cable pairs, X1, and the coefficient of this
variable, .010652, and assuming that buried copper cable cost is a linear function of X1, we
obtain the following equation for the labor and material cost of buried copper cable, YC:

          YC = .800000 + .010652X1.

     13.  We propose to make the same three adjustments to this equation that we made
above to the equation for 24-gauge aerial cable.  That is, we adjust downward by 15.2
percent the value of the coefficient for the number of copper pairs to reflect the superior
buying power that non-rural LECs may have in comparison to the RUS LECs.  We also
include in the equation loadings for splicing and LEC engineering costs of 9.4 percent and 10
percent, respectively, because the RUS cable costs do not include these costs.  After making
these adjustments, we obtain the following equation for the cost of 24-gauge buried copper
cable, YC Adj:

     YC Adj =  (.80000 + .010652(1   buy power discount %)X1)(1 +          
               splicing % + LEC engineering %)
            
            =  (.800000 + .010652(1   .152)X1)(1 + .094 + .10)   
   
            =  (.800000 + .010652(.848)X1)(1.194)

            =  (.800000 + .009033X1)(1.194).      

     14.  We use this equation to estimate the proposed input values for the cost of 24-
gauge buried copper cable.  We do this for each cable pair size by substituting into this
equation the number of cable pairs, X1.   For example, we estimate the cable costs for a 300-
pair 24-gauge buried copper cable as follows:

          YC Adj =  (.800000 + (.009033)(300))(1.194)  

                  = $4.19 per foot.

               D.   26-Gauge Aerial Copper Cable

     15.  We propose to calculate the cost of 26-gauge aerial copper cable from the
proposed cost of 24-gauge aerial copper cable by applying a discount factor to the proposed
cost of 24-gauge aerial copper cable.  We propose to use the following OLS regression
equation to estimate the discount factor used to derive the cost of 26-gauge aerial copper cable:
     
               Y =  1.055209 + .000074X1 + .094595X2
     
t-statistics:            65.165    3.651          2.184     
F-statistic:   44.383
Observations:  40
     
where:
     
          Y  = the ratio of 24-gauge aerial copper cable cost per foot to 26-   
                    gauge aerial copper cable cost per foot;
          X1 = number of pairs of aerial copper cable;
          X2 = 1 if the number of aerial copper cable pairs is 900 or           
     greater; 0 otherwise.

     16.  We estimate the proposed cost for 26-gauge aerial copper cable for each cable
pair size by first determining the discount factor for each cable size.  We do this by
substituting into this equation the number of cable pairs, X1, and a value of 1 or 0 into the
dummy variable that indicates whether the cable size is 900 pairs or greater, X2.  The
reciprocal of the number derived from this procedure for each cable pair size is the discount
factor.  We then multiply the discount factor for each cable size by the proposed 24-gauge
aerial copper cable costs for each cable size.  For example, we estimate the cable costs for a
25-pair 26-gauge aerial copper cable by first estimating the discount factor for this cable size
as follows:
          
               Y =  1.055209 + (.000074)(25) + .094595(0) 

                  = 1.06.
     
The discount factor is the reciprocal of 1.06 or .94 (1 divided by 1.06).  We then multiply this
factor, .94, by the proposed cost for 25-pair 24-gauge aerial copper cable, $1.47 per foot. 
The proposed cost for a 25-pair 26-gauge aerial copper cable is $1.38 per foot.   

                         E.   26-Gauge Underground Copper Cable

     17.  We propose to calculate the cost of 26-gauge underground copper cable from
the proposed cost of 24-gauge underground copper cable by applying a discount factor to the
proposed cost of 24-gauge underground copper cable.  We propose to use the following OLS
regression equation to estimate the discount factor used to derive the cost of 26-gauge
underground copper cable:

               Y =  1.067986 + .000030X1 + .147755X2
     
t-statistics:            47.076    1.154          2.700
F-statistic:   19.926
Observations:  39

where:

          Y  = the ratio of 24-gauge underground copper cable cost per foot to       
          26-gauge aerial copper cable cost per foot;
          X1 = the number of pairs of underground copper cable;
          X2 = 1 if the number of underground copper cable pairs is        
     900 or greater; 0 otherwise.

     18.  We estimate the proposed cost for 26-gauge underground copper cable for each
cable pair size by first determining the discount factor for each cable size.  We do this by
substituting into this equation a value of 1 or 0 into the dummy variable that indicates whether
the cable size is 900 pairs or greater, X2.  At the same time, we substitute into this equation a
value of 0 for the number of cable pairs, X1, because the value of the coefficient for this
variable, .000030, is not statistically significant.  The reciprocal of the number derived from
this procedure for each cable pair size is the discount factor.  We then multiply the discount
factor for each cable size by the proposed 24-gauge underground copper cable costs for each
cable size.  For example, we estimate the cable costs for a 50-pair 26-gauge underground
copper cable by first estimating the discount factor for this cable size as follows:
          
               Y =  1.067986 + (.000030)(0) + .147755(0) 

                  = 1.07.
     
The discount factor is the reciprocal of 1.07 or .93 (1 divided by 1.07).  We then multiply this
factor, .93, by the proposed cost for 50-pair 24-gauge underground copper cable, $2.85 per
foot.  The proposed cost for a 50-pair 26-gauge underground copper cable is $2.65 per foot. 
                    F.   26-Gauge Buried Copper Cable

     19.  We propose to calculate the cost of 26-gauge buried copper cable from the
proposed cost of 24-gauge buried copper cable by applying a discount factor to the proposed
cost of 24-gauge buried copper cable.  We propose to use the following OLS regression
equation to estimate the discount factor used to derive the cost of 26-gauge buried copper
cable:
     
               Y =  1.113615 + .000174X1   .00000005X12
     
t-statistics:            45.146    3.927           3.679
F-statistic:   7.711
Observations:  41
     
where:
     
          Y   =     the ratio of 24-gauge buried copper cable cost per foot to 26-   
                    gauge buried copper cable cost per foot;
          X1  =     number of pairs for buried copper cable;
          X12  =    the mathematical square of the number of pairs for buried copper cable.

     20.  We estimate the proposed cost for 26-gauge underground copper cable for each
cable pair size by first determining the discount factor for each cable size.  We do this by
substituting into this equation the number of cable pairs, X1, and the mathematical square of
the number of cable pairs, X12.  The reciprocal of the number derived from this procedure for
each cable pair size is the discount factor.  We then multiply the discount factor for each cable
size by the proposed 24-gauge buried copper cable costs for each cable size.  For example, we
estimate the cable costs for a 300-pair 26-gauge buried copper cable by first estimating the
discount factor for this cable size as follows:
          
               Y =  1.113615 + (.000174)(300)   (.000000047)(3002)
                    
                  = 1.113615 + .052200 + .004230
     
                  = 1.17.
     
The discount factor is the reciprocal of 1.17 or .85 (1 divided by 1.17).  We then multiply this
factor, .85, by the proposed cost for 300-pair 24-gauge buried copper cable, $4.19 per foot. 
The proposed cost for a 300-pair 26-gauge buried copper cable is $3.56 per foot.   
     II.  Cost of Fiber Cable

     A.   Aerial Fiber Cable

     21.  We propose to modify by using the Huber methodology the regression equation
for estimating the cost of aerial fiber cable developed by Gabel and Kennedy in the NRRI
Study by using OLS.  The modified equation for estimating the cost of aerial fiber cable is as
follows: 

          Y =  .959272 + .035058X1 + 1.127687X2 

t-statistics:       27.239    40.608    7.476          
F-statistic:        830.58
# of observations:  168

where:

          Y  = cost per foot for aerial fiber cable;
          X1 = number of strands in aerial fiber cable;
          X2 = 1 if two or more cables are placed at the same location, 0 otherwise.

     22.  We propose three adjustments to the modified equation for estimating the cost
of aerial fiber cable.  First, we propose to adjust downward by 33.8 percent the regression
coefficient for the number of fiber strands, to reflect the superior bargaining power of non-
rural LECs.  Second, we tentatively conclude that we should add a loading of 10 percent to the
material and labor cost of the cable (net of LEC engineering and splicing costs) to approximate
the cost of LEC engineering.  Finally, we tentatively conclude that we should add a loading
for splicing costs of 4.7 percent to the material and labor cost of the cable (net of LEC
engineering and splicing costs).   

     23.  After making these adjustments, we obtain the following equation for the cost of
aerial fiber cable, YAdj:

     YAdj =    (.959272 + .035058(1   buy power discount %)X1  + 1.127687X2)(1
                + splicing % + LEC engineering %)

           =   (.959272 + .035058(1   .338)X1 + 1.127687X2)(1 + .047 + .10)     
   
           =   (.959272 + .035058(.662)X1 + 1.127687X2)(1.147)

           =   (.959272 + .023208X1 + 1.127687X2)(1.147).   

     24.  We use this equation to estimate the proposed input values for the cost of aerial
fiber cable.  We do this for each cable size by substituting into this equation the number of
strands in the fiber cable, X1.  At the same time, we substitute into this equation a value of 0
for X2 to estimate the cost for one cable when only one cable is placed.  We use a value of 0
for X2 because the synthesis model does not use a different cable cost if the feeder or
distribution portion of network it builds requires more than one cable.  For example, we
estimate the cost of a 60-strand aerial fiber cable as follows:

          YAdj  =   (.959272 + (.023208)(60) + ( 1.127687)(0))(1.147) 

                 =  $2.70 per foot.

     B.   Underground Fiber Cable

     25.  We propose to modify by using the Huber methodology the regression equation
for estimating the cost of underground fiber cable developed by Gabel and Kennedy in the
NRRI Study by using OLS.  The modified equation for estimating the cost of underground
fiber cable is as follows: 

          Y =  2.096959 + .030226X1 

t-statistics:       19.683    17.232         
F-statistic:        296.94
# of observations:  128

where:

          Y  = cost per foot for underground fiber cable;
          X1 = number of strands in underground fiber cable.
          
     26.  We propose three adjustments to this equation.  First, we propose to adjust
downward by 27.8 percent the regression coefficient for the number of fiber strands, to reflect
the superior bargaining power of non-rural LECs.  Second, we tentatively conclude that we
should add a loading of 10 percent to the material and labor cost of the cable (net of LEC
engineering and splicing costs) to approximate the cost of LEC engineering.  Finally, we
tentatively conclude that we should add a loading for splicing costs of 4.7 percent to the
material and labor cost of the cable (net of LEC engineering and splicing costs).

     27.  After making these adjustments, we obtain the following equation for the cost of
underground fiber cable, YAdj:

     YAdj =    (2.096959 + .030226(1   buy power discount %)X1)(1
                + splicing % + LEC engineering %)

           =   (2.096959 + .030226(1   .278)X1)(1 + .047 + .10)  
   
           =   (2.096959 + .030226(.722)X1)(1.147)

           =   (2.096959 + .021823X1)(1.147).     

     28.  We use this equation to estimate the proposed input values for the cost of
underground fiber cable.  We do this for each size of fiber cable by substituting into this
equation the number of fiber strands, X1  For example, we estimate the cost of a 72-strand
underground fiber cable as follows:

          YAdj  =   (2.096959 + (.021823)(72))(1.147)  

                 =  $  4.21 per foot.

     C.   Buried Fiber Cable

     29.  We propose to modify by using the Huber methodology the regression equation
for estimating the cost of buried fiber cable and structure developed by Gabel and Kennedy in
the NRRI Study by using OLS.  The modified equation for estimating the cost of buried fiber
cable and structure is as follows:  

Y =  1.141649 + .037893X1 + .128555X2  + .256692X3 + .825424X4 + .024891X5
     
t-statistics:  4.166     25.167    1.046          1.097     3.151          .215      
F-statistic:  138.33
# of observations:  707  

where:

          Y  = cost per foot for buried fiber cable and buried fiber cable structure;
     
          X1 = number of buried fiber cable strands;
          X2 = water value indicator;
          X3 = combined bedrock and soil type indicator;
          X4 = 1 if fiber buried cable is installed in density zone 2; 0 if such cable is 
               installed in density zone 1;
          X5 = 1 if two or more cables are placed at the same location, 0 otherwise.

     30.  We propose to modify this equation to estimate the cost of buried fiber cable. 
The dependent variable in this equation, Y, represents the per foot labor and material cost for
both cable and outside plant structure.  To estimate the labor and material cost for the cable
only, we derive a new equation that explains the variation in labor and material costs for a
fiber cable alone.  We derive this new equation by using the value of only the fixed cost of
buried fiber cable reflected in the intercept or constant term in the modified buried cable and
structure equation and only the variable and coefficient in this equation that primarily explain
the variation in cable costs.
     
     31.  We use as the intercept in the new buried cable equation the value of only the
fixed cost of buried fiber cable reflected in the intercept in the modified buried cable and
structure equation.  The value of the intercept in the modified buried cable and structure
equation, 1.141649, represents the fixed cost for both buried fiber cable and buried fiber cable
structure in density zone 1.  Of this amount, we assume that $.60 represents the fixed cost for
one sheath of fiber cable.  
     
     32.  We use as the independent variable in the new buried cable equation the
independent variable that indicates the number of fiber cable strands in the modified buried
cable and structure equation, X1.  We also use as the coefficient of X1 in the new buried cable
equation the coefficient of X1 in the modified buried cable and structure equation, .037893. 
We include this variable and this coefficient in the new buried cable equation because they
primarily explain the variation in cable costs.  We do not use as independent variables in the
new buried cable equation those in the modified buried cable and structure equation that
indicate the presence of a high water table, soil and rock type, whether a buried fiber cable is
installed in density zone 2, and whether two or more cables are placed at the same location,
i.e., variables X2, X3, X4, and X5.  We do not include these variables in the new buried cable
equation because these variables and their coefficients primarily explain the variation in
structure costs. 

     33.  By using the estimate of the fixed cost for a sheath of fiber cable $.60, the
variable that indicates the number of fiber cable strands, X1, and the coefficient of this
variable, .037893, and assuming that buried fiber cable cost is a linear function of X1, we
obtain the following equation for the labor and material cost of buried fiber cable, YC:
     
          YC = .600000 + .037893X1.
     
     34.  We also propose three adjustments to the proposed equation.  First, we
propose to adjust downward by 27.8 percent the regression coefficient for the number of fiber
strands, to reflect the superior bargaining power of non-rural LECs.  Second, we tentatively
conclude that we should add a loading of 10 percent to the material and labor cost of the cable
(net of LEC engineering and splicing costs) to approximate the cost of LEC engineering. 
Finally, we tentatively conclude that we should add a loading for splicing costs of 4.7 percent
to the material and labor cost of the cable (net of LEC engineering and splicing costs).  

     35.  After making these adjustments, we obtain the following equation for the cost of
buried fiber cable, YC Adj:

     YC Adj =  (.60000 + .037893(1   buy power discount %)X1)(1 +          
               splicing % + LEC engineering %)
            
             = (.600000 + .037893(1   .278)X1)(1 + .047 + .10)   
   
             = (.600000 + .037893(.722)X1)(1.147)

             = (.600000 + .027359X1)(1.147).      

     36.  We use this equation to estimate the proposed input values for the cost of buried
fiber cable.  We do this for various sizes of fiber cable by substituting into this equation the
number of fiber strands, X1.  For example, we estimate the cost of an 18-strand buried fiber
cable as follows:

          YC Adj =  (.600000 + (.027359)(18))(1.147)   

                  = $1.25 per foot.

III. Structure Costs

     A.   Aerial Structure

     37.  In the NRRI Study, Gabel and Kennedy developed the following regression
equation to estimate the cost of 40-foot, class four poles:

          Y =  310.645 + 49.99036X1 + 112.5506X2 + 66.077993

t-statistics:       9.233          .204      2.233          2.101          
F-statistic:   3.51
Observations:  19   

where:

          Y =  cost per pole for a 40-foot, class four pole;     
          X1 = soil surface texture indicator value;
          X2 = water indicator value;
          X3 = bedrock indicator value.  

     38.  We propose to use this equation to develop proposed input values for the labor
and material cost for a 40-foot, class four pole.  We develop separate pole cost estimates for
normal bedrock, soft bedrock, and hard bedrock.  By successively substituting values of 0, 1,
and 2 into the bedrock indicator variable in this equation, X3, we obtain cost estimates for
normal bedrock, soft bedrock, and hard bedrock, respectively.  When we develop these cost
estimates, we assume that the soil surface texture is normal and that there is no high water
table in the geographic area where the pole is placed.  We reflect these assumptions in the
calculation of pole costs by substituting values of 0 into the soil surface texture variable, X1,
and the water indicator variable, X2.  For example, for a 40-foot, class four pole placed in
hard bedrock, we estimate the pole cost as follows:

     Y =  310.645 + 49.99036(0) + 112.5506(0) + 66.07799(2)

        = 310.645 + 132.16

        = $442.81 per pole.

     39.  We propose to add to these estimated pole costs estimates for the cost of
anchors, guys, and other materials that support the poles, because the data from which the
regression equation for pole costs is developed do not include these costs.  Gabel and Kennedy
developed separate cost estimates for anchors, guys and other pole-related items for rural,
urban, and suburban areas by:  (1) estimating the probability that a particular asset is used; (2)
calculating the per unit cost of each asset from the RUS data; (3) multiplying the per unit cost
for each asset by the probability that it is used (4); and summing the weighted costs.  They
estimated that the cost for anchors, guys, and other pole-related items is $32.98 in rural areas,
$49.96 in suburban areas, and $60.47 in urban areas.  We propose to add these estimated costs
to the cost estimates we derived above for poles to obtain proposed input values for aerial
structure.  For example, we add $32.98, $49.96, and $60.47 to the estimated cost for a 40-
foot, class four pole placed in hard bedrock, $442.81, to obtain per pole costs (inclusive of
costs for poles, anchors, guys, and other pole-related items) of $475.79, $492.77, $503.28 in
rural, suburban, and urban areas, respectively.
  
     40.  We also tentatively add to these estimated pole costs an estimate for the cost of
LEC engineering, which is not reflected in the data from which Gabel and Kennedy derived
cost estimates for poles and anchors, guys, and pole-related materials.  We tentatively
conclude that we should add a loading of 10 percent to the material and labor cost (net of LEC
engineering costs) for poles, anchors, guys, and other pole-related items to approximate the
cost of LEC engineering.  For example, adding a loading of 10 percent for LEC engineering
costs to the estimated per pole costs for 40-foot, class four poles placed in hard bedrock
(inclusive of costs for poles, anchors, guys, and other pole-related items) of $475.79, $492.77,
and $503.28 in rural, suburban, and urban areas yields per pole costs (inclusive of costs for
poles, anchors, guys, and other pole-related items and LEC engineering) of $523.36, $542.04,
and $553.61 in rural, suburban, and urban areas, respectively.  

     41.  In order to obtain proposed input values that can be used in the model, we must
convert the estimated pole costs into per foot costs for each of the nine density zones.  For
purposes of this computation, we propose to use for density zones 1 and 2 the per pole cost
that we have estimated for rural areas, based on the NRRI Study; for density zones 3 through
7 the per pole cost for suburban areas; and for density zones 8 and 9 the per pole cost for
urban areas.  We then divide the estimated cost of a pole by the estimated distance between
poles.  We propose to use the following values for the distance between poles:  250 feet for
density zones 1 and 2; 200 feet for zones 3 and 4; 175 feet for zones 5 and 6; and 150 feet for
zones 7, 8, and 9.  For example, for a 40-foot, class four pole placed in hard bedrock in
density zone 9, we divide into the estimated per pole cost (inclusive of costs for poles,
anchors, guys, and other pole-related items and LEC engineering), $553.61, the average
distance between poles for density zone 9, 150 feet per pole, to obtain a proposed per foot cost
for aerial structure of $3.69. 

               B.   Underground Structure

     42.  We propose to use the Huber methodology with RUS data to develop a
regression equation for estimating the cost of underground structure.  Based on this
methodology and these data, we obtain the following equation for estimating the cost of
underground structure: 

               Y =  1.560572 + 4.487123X1

t-statistics:            17.104    2.212          
F-statistic:   4.89
Observations:  235  

where:

          Y  = cost per foot for underground cable structure;    
          X1 = combined bedrock and soil type indicator.
          
     43.  We propose to use this equation to develop proposed input values for the labor
and material cost for underground cable structure.  We develop separate underground structure
cost estimates for normal bedrock, soft bedrock, and hard bedrock for density zones 1 and 2. 
By successively substituting values of 0, 1, and 2 into the combined bedrock and soil type
indicator variable in this equation, X1, we obtain cost estimates for normal bedrock, soft
bedrock, and hard bedrock, respectively.  In developing these cost estimates, we assume that
the soil surface texture is normal in the geographic area where the underground structure is
installed.  We reflect this assumption in the calculation of underground structure costs by using
a value of 0 for the soil surface texture in the combined bedrock and soil type indicator
variable, X1.  For example, for underground structure placed in hard bedrock in density zone 1
or 2, we estimate the underground structure cost as follows:

     Y =  1.560572 + 4.487123(2)

        = 1.560572 + 8.974246
     
        = $10.53 per foot.

     44.  We propose to add a loading of 10 percent to these underground structure cost
estimates for the cost of LEC engineering, because LEC engineering costs are not reflected in
the RUS data from which the regression equation for underground cable structure is
developed.  For example, by adding a loading of 10 percent for LEC engineering costs to the
estimated cost for underground cable structure placed in hard bedrock in density zone 1 or 2,
the proposed cost estimate rises from $10.53 to $11.58 per foot. 

     45.   We are able to develop directly from this equation cost estimates for
underground cable structure only for density zones 1 and 2, because the regression equation is
based on RUS data for companies that operate only in these two density zones.  We tentatively
conclude that we should derive cost estimates for density zones 3 through 9 by extrapolating
from the estimates for density zone 2.  We further tentatively conclude that we should perform
this extrapolation based on the growth rate in the BCPM and HAI default values for
underground and buried structure.  This proposed extrapolation methodology is composed of
five steps.

     46.  First, we calculate separately for the BCPM and HAI default values for
underground structure costs and buried structure costs the natural logarithm growth rate from
one density zone to the next highest density zone, e.g., going from density zone 2 to density
zone 3, from density zone 3 to density zone 4, etc.  For example, the BCPM default cost for
buried structure for distribution cable is $1.73 per foot for normal rock in density zone 2 and
$2.48 per foot in density zone 3.  The natural logarithm growth rate between these two density
zones is 35.93 percent.  BCPM has default underground structure costs for distribution cable
of $3.04 per foot for normal rock in density zone 2 and $3.66 per foot in density zone 3.  The
natural logarithm growth rate for these underground cable structure costs going from density
zone 2 to density zone 3 is 18.65 percent.

     47.  Second, starting with density zone 2, we calculate the average of the natural
logarithm growth rates of the BCPM and HAI default values for underground structure costs
and buried structure costs from one density zone to the next highest density zone.  For
example, for BCPM default costs for normal rock, the natural logarithm growth rate for buried
structure going from density zone 2 to density zone 3 is 35.93 percent.  For HAI default costs
for normal rock, the natural logarithm growth rate for buried cable structure going from
density zone 2 to density zone 3 is 0 percent.  Therefore, the average of the natural logarithm
growth rates for BCPM and HAI default values for buried structure in normal rock between
density zones 2 and 3 is 17.96 percent.

     48.  Third, we calculate the average of the average of the natural logarithm growth
rates for the BCPM and HAI default values i.e., the "grand average growth rate," for buried
structure costs and underground structure costs from one density zone to the next highest
density zone, starting with density zone 2.  For example, for normal rock, the average of the
natural logarithm growth rates for the BCPM and HAI default values for buried structure costs
between density zones 2 and 3 is 17.96 percent.  For normal rock, the average of the natural
logarithm growth rates of the BCPM and HAI default values for underground structure costs
between density zone 2 and 3 is 9.33 percent.  Therefore, for normal rock, the average of the
average of the natural logarithm growth rate of the BCPM and HAI default values for buried
cable structure costs and underground cable structure costs going from density zone 2 to
density zone 3 is approximately 13 percent.

     49.  Fourth, we calculate the natural exponential value, i.e., the inverse of the
natural logarithm, for each grand average growth rate calculated in step three of the
methodology.  For example, for normal rock, the average of the average of the natural
logarithm growth rate of the BCPM and HAI default values for buried cable structure costs
and underground cable structure costs from density zone 2 to density zone 3 is approximately
13 percent.  The natural exponential value of this 13 percent growth rate is approximately
1.14.

     50.  Fifth, we multiply the natural exponential value for each grand average growth
rate from one density zone to the next highest density zone by the estimated structure costs for
the lower of these two density zones.  For example, for normal rock in density zone 2, the
underground structure cost that we estimate using the modified results of the Gabel and
Kennedy regression analysis is $1.72, including LEC engineering.  For normal rock, the
natural exponential value for the grand average growth rate associated with going from density
zone 2 to density zone 3 is 1.14.  Thus, for normal rock in density zone 3, the extrapolated
cost estimate for underground structure is $1.72 per foot times 1.14, or $1.96. 

     C.   Buried Structure

     51.  We tentatively conclude that we should use the modified equation proposed for
estimating the cost of 24-gauge buried copper cable and structure to estimate the cost of buried
structure.  This equation has the following form: 

     Y =  1.500999 + .010652X1   .503644X2  + .733031X3 + .570136X4 
     
t-statistics:  5.012          80.735     4.777    3.175     1.911
F-statistic:   1660.57
Observations:  1,131     

where:

          Y  = cost per foot for 24-gauge buried copper cable and buried copper cable 
               structure;     
          X1 = number of copper cable pairs for 24-gauge buried copper cable;
          X2 = 1 if two or more cables are placed at the same location, 0 otherwise;
          X3 = combined bedrock and soil type indicator;
          X4 = 1 if buried cable is installed in density zone 2; 0 if such cable is  
          installed in density zone 1.

     52.  After modifying this equation, we propose to use it to develop proposed input
values for the cost of buried structure.  The dependent variable in this equation, Y, represents
the per foot labor and material cost for both buried cable and buried structure.  To estimate the
labor and material cost for the buried structure only, we derive a new equation that explains
only the variation in labor and material costs for buried structure alone.  We derive this new
equation by using the value of only the fixed cost of buried structure reflected in the intercept
or constant term in the modified buried cable and structure equation and only the variables and
coefficients in this equation that primarily explain the variation in buried structure costs.

     53.  We use as the intercept in the new buried structure equation the value of only
the fixed cost of buried fiber structure reflected in the intercept in the modified buried cable
and structure equation.  The intercept in the modified buried cable and structure equation,
1.500999, measures the fixed labor and material cost for both buried copper cable and buried
copper cable structure in density zone 1.  We tentatively concluded above that the fixed cost
for buried copper cable reflected in the intercept is approximately $.80.  Accordingly, the
fixed labor and material cost for buried cable structure in density zone 1 is $1.500999 minus
$.80 or $.70.  

     54.  We use as the independent variables in the new buried structure equation the
independent variables in the modified buried cable and structure equation that indicate soil and
rock type, and whether a buried cable is installed in density zone 2, i.e., variables X3 and X4. 
We also use as the coefficients of X3 and X4 in the new buried structure equation the
coefficients of X3 and X4 in the modified buried cable and structure equation, .733031 and
.570136, respectively.  We include these variables and these coefficients in the new buried
structure equation because they primarily explain the variation in structure costs.  We do not
use as an independent variable in the new buried structure equation the variable in the modified
buried cable and structure equation that indicates whether two or more cables are placed at the
same location, X2.  This variable and its coefficient also primarily explain the variation in
structure costs.  We do not include this variable in the new buried structure equation, however,
because the synthesis model does not use a different structure cost if the feeder or distribution
portion of the network it builds requires more than one cable.  Nor do we use as an
independent variable in the new buried structure equation the variable that indicates the
number of copper cable pairs in the modified buried cable and structure equation, X1.  We do
not include this variable in the new buried structure equation because this variable and its
coefficient primarily explain the variation in cable costs.
          
     55.  By using the estimate of the fixed cost for buried cable structure in density zone
1, $.70, the variables that indicate soil and rock type, and whether a buried cable is installed in
density zone 2, X3 and X4, and the coefficients of these variables, .733031 and .570136, and
assuming that buried cable structure cost is a linear function of X3 and X4, we obtain the
following equation for the labor and material cost for buried cable structure, YS: 

          YS = .700000 + .733031X3 + .570136X4.
     
     56.  We use this equation to develop proposed input values for the labor and material
cost for buried structure.  By successively substituting values of 0, 1, and 2 into the combined
bedrock and soil type indicator variable in this equation, X3, and a value of 0 into the dummy
variable for density zone, X4, we obtain cost estimates for normal bedrock, soft bedrock, and
hard bedrock, respectively, in density zone 1.  By successively substituting values of 0, 1, and
2 into X3 and a value of 1 into X4, we obtain cost estimates for normal bedrock, soft bedrock,
and hard bedrock, respectively, in density zone 2.  In developing these cost estimates, we
assume that the soil surface texture is normal in the geographic area where the buried structure
is installed.  We reflect this assumption in the calculation of buried structure costs by using a
value of 0 for the soil surface texture in the combined bedrock and soil type indicator variable,
X3.  For example, for buried structure placed in soft bedrock in density zone 1, we estimate
the buried structure cost as follows:

     YS = .700000 + .733031(1) + .570136(0)

         =     $1.43 per foot.

     57.  We tentatively conclude that we should add a loading of ten percent for LEC
engineering costs, because these costs are not reflected in the RUS data from which the
regression equation for buried cable and buried cable structure costs is developed.  For
example, we add a loading of 10 percent for LEC engineering costs to the estimated costs for
buried structure placed in soft bedrock in density zone 1, $1.43 per foot, to obtain a proposed
cost estimate of $1.57.

     58.  We are able to develop directly from the regression equation cost estimates for
buried structure only in density zones 1 and 2, because the RUS data is for companies that
operate only in those density zones.  We tentatively conclude that we should derive cost
estimates for density zones 3 through 9 by extrapolating from the estimates for density zone 2. 
We further tentatively conclude that we should perform such extrapolation based on the same
method proposed for extrapolating the cost of underground structure, as described above.