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                                                           Before the
               Federal Communications Commission
                    Washington, D.C.  20554
                                
In the Matter of                        )
                              )
Price Cap Performance Review            )         CC Docket No. 94-1
for Local Exchange Carriers             )
                              )
Access Charge Reform                    )         CC Docket No. 96-262
                              )


             FURTHER NOTICE OF PROPOSED RULEMAKING

Adopted:  November 12, 1999                    Released:  November 15, 1999

Comment Date:  December 30, 1999
Reply Comment Date:  January 14, 2000

By the Commission:

                        I.  INTRODUCTION

1.     In 1997, the Commission represcribed the amount by which it annually adjusts price caps for
incumbent local exchange carriers subject to the price cap rules ("price cap LECs").  The revised price cap
adjustment required price cap LECs to reduce inflation-adjusted prices for interstate access services by an
"X-factor" of 6.5 percent annually.  Pursuant to petitions for review of the Commission's order, the United
States Court of Appeals for the District of Columbia Circuit reversed and remanded the Commission's
decision.  The court has stayed issuance of its mandate until April 1, 2000, to allow time for us to conduct
this proceeding.
2.     In this Notice we seek comment on how we should represcribe an X-factor.  More specifically,
we seek comment on prescribing two separate X-factors to address retroactively the period affected by the
court remand (July 1, 1997 to June 30, 2000), and prospectively the period from July 1, 2000 forward, or a
single X-factor to cover the combined period.  Further, we seek comment on resetting, on a forward-looking
basis, price cap LEC prices to a level that is consistent with any X-factor prescription in order to rebalance
the sharing of benefits of price caps between LECs and their customers.  This Notice is limited to issues
surrounding the setting of the X-factor, and does not include any broader changes to our method of price
cap regulation.   
3.     We seek comment on represcribing the current X-factor from the reasonable range determined
in the 1997 Price Cap Review Order.  In the alternative, we also seek comment on represcribing the X-
factor based on the results of a staff study of the rate of growth in total factor productivity ("TFP") for
price cap LECs.  A third alternative is to prescribe an X-factor based on the results of another staff study
which directly determines, from aggregate interstate expenses and revenues, the X-factor that would have
produced a competitive level of capital compensation in the interstate jurisdiction during the period between
performance reviews.  We seek comment on these alternative methods for represcribing the X-factor.  We
also seek comment on whether we should rely on one of these alternatives to prescribe an X-factor on a
going-forward basis, and, if so, whether we should use data from the same time period as for the period
affected by the court's remand.  In addition, we seek comment on studies submitted in the record that
propose to quantify the consumer productivity dividend ("CPD") necessary to offset the elimination of
sharing requirements from the price cap rules.
4.     In a separate but related proceeding, the Commission is seeking comment on a proposal
submitted by the Coalition for Affordable Local and Long Distance Services ("CALLS").  The CALLS
proposal would purportedly eliminate the necessity of retrospectively adjusting the X-factor in response to
the court's remand.  Instead, it would keep the X-factor at 6.5 percent, but would target X-factor
reductions to the traffic-sensitive price cap basket.  Once local switching rates reached a certain level, all
price cap indices would be frozen.  Adoption of the CALLS proposal would also eliminate the need to
prescribe an X-factor on a going-forward basis.  We seek comment in this proceeding on the prescription
of the X-factor because, in the event that the CALLS proposal is not adopted, or not all price cap LECs
become signatories to the proposal, the Commission must be prepared to prescribe a new X-factor before
April 1, 2000. 
                        II.  BACKGROUND

A.   Prior Commission Decisions

5.     The Commission has determined that competition should be the model for setting just and
reasonable LEC rates because:
          Effective competition encourages firms to improve their productivity and introduce
     improved products and services, in order to increase their profits.  With prices set by
     marketplace forces, the more efficient firms will earn above-average profits, while less
     efficient firms will earn lower profits, or cease operating.  Over time, the benefits of
     competition flow to customers and to society, in the form of prices that reflect costs,
     maximize social welfare, and efficiently allocate resources.

In 1990, the Commission determined that an incentive-based price cap system would more closely represent
the results of a competitive market than did the prior regulatory method of rate-of-return regulation.  
Specifically, the price cap plan was "designed to mirror the efficiency incentives found in competitive
markets . . . by encouraging LECs to move prices for interstate access services to economically efficient
levels, to reduce costs, to invest efficiently in new plant and facilities, and to develop and deploy innovative
service offerings."  In order to promote consumer welfare and economic efficiency, ceilings were set on
prices that were intended to allow carriers to cover their costs and earn a normal, competitive rate of return. 
If prices were set too high, consumers would fail to reap the benefits of the carriers' efficiency; if prices
were set too low, the return on capital would be insufficient to attract investment into the industry.

6.     Regulatory structures that base a firm's allowed rates directly on the reported costs of the
individual firm create perverse incentives, because reimbursing the firm's costs removes the incentive to
reduce costs and improve productive efficiency.  The Commission's price cap plan for LECs avoids this
problem in part by divorcing the annual rate adjustments from the performance of each individual LEC,
and in part by adjusting the cap for experience only with a considerable lag.  Individual companies retain
an incentive to cut costs and to produce efficiently, because in the short run their behavior has no effect on
the prices they are permitted to charge, and they will be able to keep any additional profits resulting from
reduced costs.  The introduction of LEC price cap regulation was expected to stimulate cost reduction and
accelerate technological innovation because the regulated firms would be able to benefit from such behavior
as they could not do under rate-of-return regulation.      
7.     To achieve these goals, the Commission's LEC price cap scheme allows prices to increase by a
measure of inflation minus a productivity offset, or X-factor.  The X-factor represents the amount by which
LECs can be expected to outperform economy-wide productivity gains.  The Commission has periodically
adjusted the LEC price cap plan to ensure that it continues to provide strong incentives to incumbent LECs
to provide a substantial benefit to customers, while not basing permitted prices explicitly on individual
firms' costs.
8.     The X-factor adopted in the LEC Price Cap Order initiating price cap regulation for the
largest LECs included an additional 0.5 percent consumer productivity dividend ("CPD") to ensure "direct
benefits to ratepayers."  The CPD was included to account for an expectation that, because of the more
efficient regulatory scheme being adopted, future productivity growth would be faster than measured past
productivity growth.   
9.     Initially, price cap LECs were required to share a portion of their earnings in excess of
specified rates of return with their access customers by temporarily reducing the price cap ceiling in a
subsequent period.  In 1990, the Commission prescribed two X-factors; a minimum 3.3 percent X-factor,
or an optional 4.3 percent X-factor.  Price cap LECs that opted to use the higher X-factor were allowed to
retain larger shares of their earnings.  The LEC Price Cap Order required that the Commission periodically
review the performance of the price cap regime.  The order in the first performance review was released in
1995, at which time the Commission increased the minimum X-factor from 3.3 percent to 4.0 percent, and
provided two optional X-factors at 4.7 and 5.3 percent.  The 1990 and 1995 prescriptions were derived
from two 1990 staff studies that examined LECs' historical unit cost changes.  These studies did not utilize
a total factor productivity ("TFP") methodology.
10.    In the next performance review order, released in 1997, the Commission further revised the
price cap plan by eliminating all sharing requirements and prescribing a new X-factor of 6.5 percent.  This
X-factor prescription relied primarily on a staff study of the historical rate of growth in LEC TFP ("1997
staff TFP study").
11.    TFP measurement is a methodology commonly used to measure productivity and productivity
growth in the economy as a whole.  Productivity is measured as the ratio of an index of the outputs of a
firm (or industry, or nation) to an index of its inputs.  Productivity growth is measured by changes in this
ratio over time.  Beyond showing changes in the amount of input required per unit of output, TFP analysis
generally does not shed light on the mechanisms by which productivity growth occurs. 
12.    In TFP models, output can be measured either in terms of physical units of the service
produced, such as minutes or calls, or by dividing revenues by an index of output prices.  Output indices
are created to measure changes in the level of outputs over time.  Indices for particular categories of output
are weighted to create a single output index.  
13.    Inputs are usually classified into three categories: labor, materials, and capital services. 
Again, indices reflecting changes in the quantities of labor, materials, and capital services are weighted and
aggregated into a single input index.  The growth rate of the aggregate input index depends on the growth
rates of the individual input indices and their relative weights.  Capital services are assumed to be a fixed
proportion of the capital stock (i.e., plant and equipment), so that changes in capital services can be
measured through measurement of changes in the capital stock.       
14.    In a regulatory setting, if the TFP calculation sets the X-factor too low, and, consequently, sets
prices too high, end users will purchase less of the services produced, and the quantity of output will be
lower than if prices were set at a competitive level.  The productivity of which the plant is capable will not
be revealed.  Since the marginal cost of additional output is believed to be very low in telecommunications,
the effect on measured productivity may be large.
15.    The 1997 staff TFP study calculated the historical difference in productivity growth between
LECs and the economy nationwide for the period 1986 through 1995.  Specifically, it calculated the
difference between LEC TFP change and economy-wide TFP change.  The study then calculated an input
price differential reflecting the difference in the rate of the change of LEC input prices as compared with
the economy as a whole.  These two factors were then added together for each year.  Several averages were
created using these numbers, with the first average being for the entire period, the next average dropping
the oldest year (1986), and each subsequent average dropping another year, with the final average including
only the years 1991 to 1995.  These averages created a "zone of reasonableness" of 5.2 percent to 6.1
percent.  Placing some reliance on slightly higher X-factor estimates calculated by AT&T, the Commission
increased the upper bound of the zone of reasonableness to 6.3 percent.  The Commission prescribed an X-
factor near the upper end of the zone of reasonableness, at 6.0 percent. 
16.    In addition to the 6.0 percent historical portion of the X-factor, the Commission retained a 0.5
percent CPD "to ensure that price cap LECs flow-through a reasonable portion of the benefits of
productivity growth to ratepayers."  The Commission stated that inclusion of a CPD was especially critical
in achieving this goal because the sharing requirements were being eliminated from the price cap plan. 
B.   Court Decision

17.    Several entities filed petitions for review of the 1997 Price Cap Review Order.  In its decision,
the U.S. Court of Appeals for the D.C. Circuit generally denied the petitioners' challenges to the
Commission's decision, but reversed and remanded for further explanation of several aspects of the analysis
supporting the Commission's prescription of a 6.5 percent X-factor.
18.    The court questioned the Commission's stated rationales for selecting 6.0 percent, from the
high end of the 5.2-6.3 percent zone of reasonableness, as the historical component of the X-factor. 
Specifically, the court found that the Commission had not supported its conclusion that the two lowest TFP
year averages, from 1986-1995 and 1991-1995, should be accorded less weight in the selection of the X-
factor.  The court also questioned the Commission's reliance on an upward trend in the X-factor from 1993,
noting that the trend could be part of a larger cyclical pattern, in which case a downward turn in the X-
factor could be expected.  In addition, the court noted that there was no discernible trend in either of the
two X-factor components, i.e., the differences between LEC and U.S. changes in TFP, and the differences
between LEC and U.S. changes in input prices.  Finally, the court rejected the Commission's reliance on
AT&T's higher X-factor results, noting that the Commission had incorporated the portions of AT&T's
study deemed reasonable in its staff study, and therefore should not have given any independent weight to
the results of AT&T's study, or adjusted the range of reasonableness upward from 6.1 percent.
19.    The court also sought an explanation of the inclusion of a 0.5 percent CPD in the X-factor. 
Although the petitioners did not dispute "that it is defensible to include a CPD corresponding to whatever
productivity increase may be expected from the elimination of sharing", the court found that retention of the
prior CPD amount of 0.5 percent required a comparison of the productivity effects of sharing elimination
with the initial rationale for adopting a 0.5 percent CPD. 
                  III.  REPRESCRIPTION OPTIONS

20.    We seek comment on three alternative bases for prescribing the historical component of the X-
factor.  First, we could prescribe an X-factor based on the reasonable range determined by the 1997 staff
TFP study.  In relying on this basis for represcription, we would address only those issues remanded by the
court.  We discuss this approach in Section III.A.
21.    Second, we could rely on a new staff study revising the 1997 staff TFP study ("1999 staff TFP
study"). The 1999 staff TFP study substitutes an independent measure of capital price changes for the
endogenously-determined capital price change used in the 1997 staff TFP study and recalculates the change
in the compensation of the capital input.  The revised study also makes adjustments to the 1997 staff TFP
study to update information and to adjust for possible biases.  We discuss this approach in more detail in
Section III.B.  The 1999 staff TFP study appears as Appendix B.
22.    Third, we could take advantage of our accumulated experience with price cap regulation and
directly determine, from aggregate interstate expenses and revenues, the X-factor that, if it had been
prescribed from the inception of price caps, would leave capital compensation at the competitive level at the
end of the study period.  We discuss this methodology in detail in Section III.C.  A staff study that applies
this methodology appears as Appendix C ("staff Imputed X study").
23.    We also seek comment on other alternatives that would serve as a basis for prescribing the
historical component of the X-factor for the remand period.
A.   Option 1:  The 1997 Staff TFP Study

24.    We seek comment on whether we should use only the results from the 1997 staff TFP study in
setting the historical component of the X-factor for the remand period.  We seek comment on whether, in
addressing the court's remand, we are precluded from revising the X-factor using any other methodology, or
from supplementing the data in the 1997 staff TFP study.
25.    The court did not find fault with the 1997 staff TFP study, and did not ask us to revisit it. 
Instead, the court limited its critique of TFP to our selection of a value at the upper end of the
reasonableness range, and with the upward adjustment to the reasonable range.  
26.    In their responses to a 1998 request to refresh the record in our Access Charge Reform
proceeding, both USTA and AT&T used the methodology in the 1997 staff TFP study to extend the
calculation of the X-factor through 1997.  USTA has also calculated an X-factor for 1998.  We seek
comment on the legal and logical arguments supporting consideration of data that have become available
after the close of the record for the remanded prescription.  We note that USTA and AT&T did not agree
with each other on the value of the historical component for 1996 and 1997.  We seek comment on USTA's
and AT&T's updates of the 1997 staff TFP study, and on their recommendations for prescribing an X-
factor. 
27.    If we set the X-factor by using the 1997 staff TFP study, the court's remand requires that we
justify our selection from within the reasonable range.  Within the reasonable range, should we use some
measure of central tendency, e.g., the mean or median, as the best estimator of productivity?  Could and
should we consider prescribing above the mean?  If the reasonable range includes a statistically meaningful
trend, should this inform our choice?  What other justifications could be made for selecting above or below
some measure of central tendency?  Should these justifications affect our selection from the reasonable
range, or are they more relevant to the selection of a CPD?
B.   Option 2:  The 1999 Staff TFP Study

               1.   Methodology

28.    In comments filed with the Commission late last year, several parties identified what they
believe is a problem in the way in which the 1997 staff TFP study employed the TFP methodology
commonly used in economic analysis to set an X-factor.  The 1999 staff TFP study takes this potential
problem as a point of departure and attempts to correct it.  We seek comment on the 1999 staff TFP study,
and on its premise that the 1997 staff TFP study methodology may fail to calculate an X-factor that is
consistent with the objectives of our price cap plan.
29.    The 1997 staff TFP study subtracts the cost of the labor and material inputs from revenues,
and the residual revenue is assumed to be the cost of the capital input.  The 1999 staff TFP study attempts
to capture the gains in productivity that would have been revealed in a competitive marketplace by varying
total capital compensation according to a measure of the competitive capital compensation rate.  
30.    We seek comment on the following method for adjusting the capital compensation in the 1997
staff TFP study.  The first step is to identify a competitive price index series to use as a surrogate for the
annual change for the cost of capital in a competitive market.  The second step is to assume LEC capital
compensation in 1991, the first full year of LEC price cap, was at a competitive level.  The third step is to
combine the competitive price index and the 1991 LEC capital compensation rate to create a competitive
LEC capital compensation rate for the historical period.  The fourth step is to increase or decrease LEC
capital compensation based on this competitive LEC capital compensation rate.  The fifth step is to adjust
LEC revenues, making appropriate allowance for taxes, for the change in capital compensation.  The final
step is to recalculate LEC historical TFP using these revised capital compensation and revenue data. 
31.    In addition to updating the data for the period 1996-1998, the 1999 staff TFP study makes
three other modifications to the 1997 staff TFP study.  First, the 1999 staff TFP study uses the recently
revised Bureau of Labor Statistics ("BLS") series on multifactor productivity in place of the antecedent
series.  Second, the 1999 staff TFP study uses the number of dial equipment minutes, rather than the
number of calls, in calculating the local service output index.  Third, the 1999 staff TFP study recalculates
the labor input to adjust for the fact that all the costs, but only a fraction of the benefits, of the 1992-95
employee buyouts have been recognized on the accounting books.  We seek comment on these
modifications to the 1997 staff TFP study.
32.    Several additional aspects of the 1997 staff TFP study may warrant highlighting and
comment.  The 1999 staff TFP study does not make these adjustments because they either are not easily
quantified, or do not make a significant impact on the level of the X-factor.  We seek comment on the
decision of the 1999 staff TFP study to not make any of these adjustments.  We also seek comment on
whether there are any additional issues, not noted here or in Appendix A, that necessitate adjusting the X-
factor, how any such adjustments would affect the X-factor, and how they should be made.
               2.   Selecting the Appropriate X-Factor

33.    The court's remand requires that we justify our selection from within a reasonable range.  We
seek comment on how we should determine the reasonable range and how we should select from within this
range.  In our determination of the reasonable range in the 1997 Price Cap Review Order, we gave recent
years more weight than more distant years.  Should we continue to discount more distant years?  Should
the period under price cap regulation be given more weight than the period under rate-of-return regulation? 
Given that price cap regulation may have been anticipated by price cap LECs for some years before its
introduction, what years should be included in the price cap period?
34.    We also seek comment on whether additional years of data should be considered in the remand,
or whether the X-factor we select should rely on the same years of data as used in the 1997 Price Cap
Review Order.  We seek comment on the legal and logical arguments supporting consideration of data that
have become available after the close of the record for the remanded prescription.  Would it be more
responsive to the court's remand to prescribe an X-factor based on data available in 1997 or to consider the
additional data that has become available in the interim in setting the X-factor on a going-forward basis?
C.   Option 3:  The Staff Imputed X Study

     1.   Methodology

35.    As an alternative to either of the TFP methodologies, the Bureau staff also has performed a
study, the staff Imputed X study, designed to calculate the X factor that yields the aggregate revenues that
would have been generated in a competitive market.  While price caps provide incentives for cost reduction
similar to those of competition, they do not guarantee that revenues will follow a similar path.  In a
competitive market, revenues on average will be equal to costs, including compensation of capital at a
competitive market level.  This method is intended to replicate the effects of a competitive market in
apportioning the gains from successful operation between carriers and consumers.  The approach used here
differs from the TFP approach, inter alia, in that it measures productivity growth by looking at aggregate
expense and revenue data rather than by weighting and aggregating categories of physical inputs and
outputs.  In contrast to both of the TFP approaches, this method appears to have modest data requirements
and to be computationally simple and easily understandable.  Nevertheless, this method should have the
same incentive effects as the TFP approach or any other method of calculating an X-factor.
36.    The staff Imputed X study calculates the change in 1998 revenue and operating income for
each price cap LEC that would result from imposing a hypothetical X-factor from the inception of price
caps in 1991 through 1998.  The results for all price cap LECs are aggregated, and the X factor required to
produce revenues equal to costs, including a competitive level of capital compensation in the aggregate for
all LECs, is calculated.  The calculation was also performed for 1991 through 1995 for comparison with
the original TFP study.  The calculation takes account of the increase in the demand for service that would
have resulted from the lower price.  Changes in the competitive cost of capital were accounted for by
adjusting the capital compensation found reasonable by the Commission at the inception of price caps by
an index of bond rates over the period.  The index is the same one used for the 1999 staff TFP study to
measure the price of capital.  
37.    The data used for these estimates differ from those used for the TFP calculations in that they
are purely interstate in nature.  The TFP calculations used total company data because of the difficulty of
separating interstate and intrastate costs for the TFP calculations, despite interstate data being conceptually
more appropriate for representing the services regulated by the Commission under price caps.  The data
for the staff Imputed X study also include all price cap carriers, whereas the TFP studies use data for the
regional Bell operating companies ("RBOCs") only.  The calculations assume that a decrease in price
would result in an increase in the quantity of service purchased, while the TFP calculations necessarily
reflect only experience under the prices that were actually in effect.  Finally, the staff Imputed X study does
not make an adjustment in expense data comparable to the adjustment made in the 1999 staff TFP study to
compensate for the accounting treatment of employee buyouts.  To provide a check on the revised TFP
calculations, the X-factor calculations using the staff Imputed X study were repeated using data only for
the RBOCs and assuming no demand growth in response to lower prices.  These calculations were
performed for both 1995 and 1998. 
     2.   Previous Study

38.    We note that the approach described here is similar to the Direct Model proposed by AT&T,
which the Commission has referred to as the Historical Revenue Approach.  The staff Imputed X study
differs from the approach proposed by AT&T primarily in that the staff calculation includes an adjustment
to take account of likely demand stimulation resulting from a lower price cap, and the calculation takes
account of changes over time in competitive return to capital.  Data sources and calculations also differ
somewhat.  In the 1995 Price Cap Review Order, the Commission noted that the Historical Revenue
Approach has the advantage that it reflects performance in providing the interstate services that are subject
to price caps, and includes input cost changes.  In comments to the Price Cap Fourth Further Notice,
GSA supported the Historical Revenue Approach and noted that it incorporates both TFP growth and the
input price differential.
39.    Most criticisms of AT&T's Historical Revenue Approach dealt with the data and methodology
used by AT&T in its calculations.  Commenters responding to AT&T's proposal pointed out that data
reported under Commission accounting, separations, and other rules may not accurately track economic
costs.  NYNEX in its comments to the Price Cap Fourth Further Notice criticized use of the Historical
Revenue Approach on the grounds that accounting-based rules are a poor measure of a firm's economic
performance.  We note that the Commission declined to adopt the Historical Revenue Approach in the
1997 Price Cap Review Order due to administrative concerns and incentive effects.
       3. Request for Comment

4.     We seek comment on the validity of the staff Imputed X study for estimating the appropriate
level of the X-factor.  Does the X-factor estimated using these data and assumptions accurately represent
the productivity growth achievable by the price cap LECs over the period examined?  We request comment
on the theoretical appropriateness of this methodology.  We also seek comment on the following questions: 
Is an interstate-only calculation conceptually proper, and do the data allow an accurate measure of
interstate revenues, expenses, and investment?  Calculations reported in Appendix C show that X-factors
calculated on an annual basis appear to increase over time.  Are there explanations for the trend we see
other than increasing efficiency?  Does this apparent trend suggest that an additional adjustment, such as
the CPD, is necessary in addition to revising the calculation of the X-factor?  Alternatively, is the CPD no
longer necessary because the approach described here sufficiently passes the benefits of increased
efficiency to ratepayers?  What is the appropriate method for determining the competitive cost of capital? 
Is applying an index of bond rates to the rate of return used by the Commission to initialize rates at the
inception of price caps a reasonable approach?  Would taking account of the mix of debt and equity held by
the LECs yield a more accurate estimate of the trend in the cost of capital?  
5.     We request comment on the data and calculations used in the staff Imputed X study.  Are more
appropriate data sources available, and can adjustments be made that would improve the accuracy of the
calculations reported here?  AT&T in its Historical Revenue Approach in 1994 used Price Cap Indices
("PCIs") from the Commission's Tariff Review Plan data to measure actual changes in allowed rates.  This
approach includes all changes that occurred in the price caps, including exogenous changes not related to
the operation of the X factor.  Is such an approach conceptually appropriate?  Would use of PCIs rather
than the X factor in effect more accurately reflect price performance for purposes of these calculations?
6.     We also seek comment on whether, in responding to the remand, it is appropriate to use data
for the period that was available to us at the time of the 1997 Price Cap Review Order, or whether we
should make use of the best information available to us now, including data for subsequent years that have
become available in the meantime.  We seek comment on the legal and logical arguments supporting
consideration of data that have become available after the close of the record for the remanded prescription. 
Would it be more responsive to the court's remand to prescribe an X-factor based on data contemporaneous
with the prescription and to consider the additional data in setting the X-factor on a going-forward basis? 
In addition, the court's remand requires that we justify our selection from within a reasonable range.  How
should we determine a reasonable range for setting the X-factor using the staff Imputed X study, and how
we should select from within that range?
              IV.  CONSUMER PRODUCTIVITY DIVIDEND

7.     In the LEC Price Cap Order, the Commission included a CPD of 0.5 percent in the X-factor
offset to ensure that access customers received the first benefits of price caps in the form of reduced rates. 
This CPD was also included in the X-factor in subsequent price cap review orders, including the 1997
Price Cap Review Order, in which it was intended to offset the elimination of sharing requirements.  These
requirements had compelled price cap LECs to share a portion of their earnings above set percentages with
access customers.  The sharing requirements were intended to protect consumers against the possibility of
an error in the establishment of the X-factor.  Pursuant to the court's remand, the Commission seeks
comment on whether to retain the CPD.  
8.     In remanding this issue to the Commission, the court specifically questioned the quantification
of the CPD.  When the Commission made its decision to include a CPD in the 1997 X-factor, the record
included a study by Strategic Policy Research ("SPR") that addressed the effects of eliminating the sharing
requirements.  The SPR study found that the LEC price cap plan with sharing requirements produced less
than 35 percent of the efficiency incentives of unregulated competition.  Those incentives decreased to 18
percent for price cap LECs whose earnings were in the 50-50 sharing category for each year of the four-
year review cycle.  The results of the SPR study were challenged by the Ad Hoc Telecommunications
Users Committee ("Ad Hoc"), but Ad Hoc's own results indicated that sharing substantially reduced
efficiency incentives.  Ad Hoc's more conservative calculations indicated that elimination of sharing would
increase efficiency incentives by at least 17 percent for all LECs, and by 41 percent for LECs in the 50-50
sharing category.  We seek comment on the CPD amount justified on the basis of these studies to ensure
that the benefits of sharing elimination would be apportioned between LECs and ratepayers.  We also seek
comment on additional methods for quantifying a CPD designed to ensure that consumers get a reasonable
portion of the benefits from the elimination of sharing.    
9.     We also seek comment on whether a CPD should be included to reduce rates and correct for
prior years when the X-factor may have been set too low.  As noted above in Section III, the calculations
used to set prior year X-factors may have underestimated LEC productivity.  This underestimation may
have caused rates to be set at too high a level.  A mistake in the X-factor may not be self-correcting, but
instead may cause increasingly erroneous prices over time.  To obtain efficient prices in the future, it may
be necessary both to adjust the value of the X-factor and to reset prices. Therefore, we seek comment on
whether we should include in the X-factor a CPD designed to reduce rates, either by a one-time adjustment,
or over a multi-year period, if we conclude that the X-factor historically has been set too low.  If the
reduction occurs over a multi-year period, should we account for the time value of money, and, if so, how
should we calculate the reduction?  The following table sets forth what CPD might be appropriate to
correct for productivity underestimations in prior year X-factors depending on the X-factor that we
prescribe.

                           RATE REDUCTION IN 1998 
                   IMPLIED BY NEW X-FACTOR PRESCRIPTION
     
     ______________________________________________________________________________

                         Overstatement       Annual Consumer
                 X-Factor          of Price Indices    Benefits Lost
                     (%)            (%)           ($ billion)
______________________________________________________________________________

               5.0         0.14 -  0.44        0.24
               5.5         3.19 -  4.36        1.16
               6.0         7.10 -  8.14        2.06
               6.5       10.70 - 11.79         2.95
               7.0       14.26 - 15.31         3.80
               7.5       17.69 - 18.71         4.64
               8.0       21.00 - 21.98         5.45
               8.5       24.20 - 25.15         6.23
______________________________________________________________________________


            V.  PRESCRIBING THE X-FACTOR ON A GOING-FORWARD BASIS

10.    We seek comment on whether we should prescribe an X-factor that would apply as of July 1,
2000 that is different from the retrospective X-factor applicable to the period affected by the court's
remand, or whether the X-factor that we prescribe for the period beginning July 1, 1997 should continue in
place until the next price cap performance review.  We also seek comment on whether to include a
prospective CPD adjustment in future X-factors to correct for any significant divergences between historic
LEC productivity and prior X-factors, and on whether any such adjustment should be made at once or be
phased in over several years.
11.    In this Notice we seek comment on prescribing a future X-factor based on the results of the
1999 staff TFP study.  In the alternative, we could prescribe an X-factor based on the results of the staff
Imputed X study.  Finally, we invite parties to comment on other alternatives that could serve as a basis
for a future X-factor.
12.    We also seek comment on how the prescription of the X-factor would affect smaller price cap
LECs differently from other price cap LECs, and whether there should be a separate X-factor calculated
for smaller price cap LECs.
13.    In addition, we seek comment on how the Commission's proposed adjustments to the price cap
rate structure should affect the annual reductions required by our price cap rules.   We proposed in our
recent Pricing Flexibility Order to add a "q" factor to the formulae used to adjust annually the price cap
indices ("PCIs") for the baskets that contain the charges for local switching and tandem switching.  The q
factor would reduce switching charges based on growth in demand.  As proposed, the affected baskets
would be reduced annually by both the X-factor and the q factor.  The staff studies attached herein,
however, may capture in their X-factor estimates some or all of the effect intended to be captured by the q
factor.  We seek comment on whether a q factor is necessary if an X-factor is adopted that captures its
effect, and on how to remove any double counting that might result from the application of both factors. 
For example, if the X-factor reduction was $10, and the q factor reduction was $4, then we could directly
apply $4 to the baskets containing local and tandem switching, and allocate the remaining $6 amongst all
the baskets according to our price cap rules.  
14.    We also proposed to adjust on a prospective basis for the past absence of a q factor in the
formulae that annually adjust the PCIs of the baskets containing charges for local and tandem switching. 
We seek comment on how any such adjustment should affect any proposed adjustment to the PCIs for all
price cap baskets to offset the cumulative effect of past X-factors that may have been set below the rate of
cost reduction actually achieved by LECs.   Should we apply the logic suggested in the example of the
previous paragraph?  If so, should the shift of switching ports to common line increase the common line
basket's share of any adjustment based on the past absence of a q factor?
15.    In addition to proposing a q factor, we proposed to increase the "g" factor that applies to
certain revenues in the common line basket from g/2 to a full g.  We seek comment on whether any
prospective adjustment to our X-factor prescription would be appropriate to account for this.
16.    Finally, we proposed to replace the existing per-minute rate structure for local switching and
tandem switching with capacity charges.  We seek comment on whether replacing per-minute charges with
capacity charges affects future growth in LEC productivity.  We seek comment on whether any prospective
adjustment to our X-factor is required and on how we would quantify this adjustment.
                     VI.  PROCEDURAL ISSUES

A.   Ex Parte Presentations

17.    This proceeding shall be treated as a "permit-but-disclose" proceeding in accordance with
Section 1.1206(b) of the Commission's rules, 47 C.F.R.  1.1206(b).  Ex parte presentations are
permissible if disclosed in accordance with Commission Rules, except during the Sunshine Agenda period
when presentations, ex parte or otherwise, are generally prohibited.   Persons making oral ex parte
presentations are reminded that memoranda summarizing the presentations must contain summaries of the
substance of the presentations and not merely a listing of the subjects discussed.  More than a one or two
sentence description of the views and arguments presented generally is required.  See 47 C.F.R. 
1.1206(b)(2).  Additional rules pertaining to oral and written presentations are set forth in Section
1.1206(b).
B.   Initial Regulatory Flexibility Act Analysis

18.    As required by the Regulatory Flexibility Act ("RFA"), the Commission has prepared this
Initial Regulatory Flexibility Analysis ("IRFA") of the possible significant economic impact on small
entities by the policies and rules proposed in this Notice.  Written public comments are requested on this
IRFA.  Comments must be identified as responses to the IRFA and must be filed by the deadlines for
comments on the Notice provided below in Section VI.C.  The Office of Public Affairs will send a copy of
the Notice, including this IRFA, to the Chief Counsel for Advocacy of the Small Business Administration. 
In addition, the Notice and IRFA (or summaries thereof) will be published in the Federal Register.
19.    Need for and Objectives of the Proposed Rules.  As stated in Section II.B above, the court has
remanded to the Commission the selection of a 6.5 percent productivity offset, or X-factor, in the LEC
price cap formula.  In this Notice we seek comment on how we should represcribe an X-factor.  In Section
III we seek comment on prescribing one or more X-factors to address retroactively the period affected by
the court remand (July 1, 1997 to June 30, 2000), and in Section V we seek comment on represcribing one
or more X-factors from July 1, 2000 forward.  Further, we seek comment on resetting, on a forward-
looking basis, price cap LEC prices to a level that is consistent with any X-factor prescription in order to
rebalance the sharing of benefits of price caps between LECs and their customers.  
20.    Legal Basis.  The proposed action is supported by Sections 1, 4(i), 4(j), 201-205, and 303(r)
of the Communications Act of 1934, as amended, 47 U.S.C.  151, 154(i), (j), 201-205, and 303(r).
21.    Description and Estimate of the Number of Small Entities to Which the Proposed Rules Will
Apply.  The RFA directs agencies to provide a description of and, where feasible, an estimate of the
number of small entities that may be affected by the proposed rules, if adopted.  The RFA generally
defines the term "small entity" as having the same meaning as the terms "small business," "small
organization," and "small governmental jurisdiction."  In addition, the term "small business" has the same
meaning as the term "small business concern" under the Small Business Act.  A small business concern is
one which:  (1) is independently owned and operated; (2) is not dominant in its field of operation; and (3)
satisfies any additional criteria established by the Small Business Administration ("SBA").  The SBA has
defined a small business for Standard Industrial Classification ("SIC") category 4813 (Telephone
Communications, Except Radiotelephone) to be an entity that has no more than 1,500 employees.  
22.    We have included small incumbent LECs in this RFA analysis.  As noted above, a "small
business" under the RFA is one that, inter alia, meets the pertinent small business size standard (e.g., a
telephone communications business having 1,500 or fewer employees), and "is not dominant in its field of
operation."  The SBA's Office of Advocacy contends that, for RFA purposes, small incumbent LECs are
not dominant in their field of operation because any such dominance is not "national" in scope.  We have
therefore included small incumbent LECs in this RFA analysis, although we emphasize that this RFA
action has no effect on Commission analyses and determinations in other, non-RFA contexts.
23.    The proposals in the Notice apply only to price cap LECs.  At the current time, there are 13
price cap LECs.  Of these companies, 11 are listed in the Commission's most recent Statistics of
Communications Common Carriers ("SOCC") report as having more than 1,500 employees. 
Consequently, we estimate that 2 or fewer providers of local exchange service are small price cap LECs
that may be affected by these proposals.
24.    Description of Projected Reporting, Recordkeeping and Other Compliance Requirements.  We
expect that, on balance, the proposals in this Notice will not change price cap LECs' administrative burdens
or cause price cap LECs to incur any additional costs associated with proposed reporting and
recordkeeping requirements.  The studies discussed in Section III would establish new X-factors that price
cap LECs would need to utilize in their price cap calculations, but otherwise should not affect their
administrative burdens or costs.
25.    Steps Taken to Minimize Significant Economic Impact on Small Entities, and Significant
Alternatives Considered.  The RFA requires agencies to describe any significant alternatives that it has
considered in reaching its proposed approach, which may include the following four alternatives:  (1) the
establishment of differing compliance or reporting requirements or timetables that take into account the
resources available to small entities; (2) the clarification, consolidation, or simplification of compliance or
reporting requirements under the rule for small entities; (3) the use of performance rather than design
standards; and (4) an exemption from coverage of the rule, or any part thereof, for small entities.  In the
instant proceeding we are seeking comment on the prescription of the productivity offset, or X-factor,
portion of the price cap formula.  Therefore, only the first and last possible alternatives listed in section
603(c) of the RFA would be applicable.  In Section V of the Notice, we seek comment on how the
prescription of the X-factor would affect smaller price cap LECs differently from other price cap LECs,
and whether there should be a separate X-factor calculated for smaller price cap LECs.  We also do not
believe it would be appropriate to exempt small price cap LECs from the application of an X-factor.  We
seek comment on these issues and urge commenting parties to support their comments with specific
evidence and analysis.
26.    Federal Rules that May Duplicate, Overlap, or Conflict With the Proposed Rules.  None.
C.   Filing of Comments and Reply Comments

27.    Pursuant to Sections 1.415 and 1.419 of the Commission's rules, 47 C.F.R.  1.415, 1.419,
interested parties may file comments on or before December 30, 1999 and reply comments on or before
January 14, 2000.  Comments may be filed using the Commission's Electronic Comment Filing System
("ECFS") or by filing paper copies.
28.    Comments filed through the ECFS can be sent as an electronic file via the Internet to
<http://www.fcc.gov/e-file/ecfs.html>.  In completing the transmittal screen, commenters should include
their full name, Postal Service mailing address, and the applicable docket or rulemaking number.  Parties
may also submit an electronic comment by Internet e-mail.  To get filing instructions for e-mail comments,
commenters should send an e-mail to ecfs@fcc.gov, and should include the following words in the body of
the message, "get form <your e-mail address>."  A sample form and directions will be sent in reply.  Only
one copy of electronically-filed comments must be submitted.
29.    Parties who choose to file by paper must file an original and four copies of each filing.  All
filings must be sent to the Commission's Secretary, Magalie Roman Salas, Office of the Secretary, Federal
Communications Commission, 445 12th Street, S.W., Room TW-B204, Washington, D.C. 20554.  
30.    Parties who choose to file by paper should also submit their comments on diskette.  The
diskette should be submitted to:  Wanda Harris, Federal Communications Commission, Common Carrier
Bureau, Competitive Pricing Division, 445 12th Street, S.W., Fifth Floor, Washington, D.C. 20554.  The
submission should be on a 3.5 inch diskette formatted in an IBM compatible format using WordPerfect 5.1
for Windows or compatible software.  The diskette should be accompanied by a cover letter and should be
submitted in "read only" mode.  The diskette should be clearly labeled with the commenter's name,
proceeding (including the docket number in this case), type of pleading (comments or reply comments), date
of submission, and the name of the electronic file on the diskette.  The label should also include the
following phrase:  "Disk Copy - Not an Original."  Each diskette should contain only one party's pleadings,
preferably in a single electronic file.  In addition, commenters must send diskette copies to the
Commission's copy contractor, International Transcription Service, Inc., 1231 20th Street, N.W.,
Washington, D.C. 20036.  Comments and reply comments will be available for public inspection during
regular business hours in the FCC Reference Center, 445 12th Street, S.W., Room CY-A257, Washington,
D.C. 20554.
                    .VII.  ORDERING CLAUSES

31.    Accordingly, IT IS ORDERED that, pursuant to the authority contained in Sections 1, 4(i),
4(j), 201-205, and 303(r) of the Communications Act of 1934, as amended, 47 U.S.C.  151, 154(i), (j),
201-205, and 303(r), NOTICE IS HEREBY GIVEN of the rulemaking described above and that
COMMENT IS SOUGHT on those issues.
32.    IT IS FURTHER ORDERED that the Commission's Office of Public Affairs, Reference
Operations Division, SHALL SEND a copy of this Further Notice of Proposed Rulemaking, including the
Initial Regulatory Flexibility Analysis, to the Chief Counsel for Advocacy of the Small Business
Administration.

                                             FEDERAL COMMUNICATIONS COMMISSION



                         Magalie Roman Salas      
                                             Secretary
                                 Appendix A 

           Sources of Potential Errors in the 1997 Staff TFP Study

                                 Noel D. Uri

     A review of the 1997 Staff TFP Study, upon which the Commission relied in its 1997 Price Cap
Review Order, has identified a number of potential errors that appear to affect significantly the results of
the study.  Below we discuss a possible conceptual error and a method of correcting the problem.  We then
discuss three sources of potential bias that are attributable to the study's sources of data and how these
potential biases can be corrected.  Finally, we discuss a number of other sources of possible bias.  These
possible biases either are not easily quantified, or do not have a significant impact on the level of the X-
factor. 

I.  Competitively Determined Historical Cost of Capital

     The 1997 Staff TFP Study used actual imputed cost of capital when measuring the productivity of
regulated companies. Several parties allege that this creates a problem, because of the use of the residual
value approach for determining the cost of the capital input.  With this approach, the Commission in the
1997 Price Cap Review Order first directly determined the price and quantity of every input except capital,
i.e., labor and materials.  That is, it directly calculated the realized return to every non-capital input.  Next,
based on an estimate of the capital stock, the assumption that all revenue is distributed to the inputs, and
given the returns to labor and materials based on historical data, a cost of capital is imputed.

     Conceptually, the difference (residual) between revenue and the required returns to all non-capital
inputs (which is just the nominal amount used to impute a cost of capital) consists of two parts.  The first
part is the required return to capital.  The second part is the excess profit earned by the firm.  Instead of
attempting to separate this difference into two parts, the Commission in the 1997 Price Cap Review Order
assumed that all of this residual was the required return to capital, i.e., that no excess profit was earned. 
This is a reasonable assumption for a competitive market, and even for non-competitive markets, as long as
the goal of the study is simply to measure the productivity gains revealed by market forces.  In a
regulatory setting, however, the productivity gains are "revealed" by the application of the X-factor, not by
market forces.

     By attributing all of the residual to the capital inputs, the residual value method tends
automatically to define whatever profits or losses the LECs realized during the historical period as
increases or decreases in the cost of capital inputs.  Critics contend that if, for example, the Commission
chose too low an X-factor during the historical period being considered, causing the LECs' profits to
increase, the residual value method would indicate that the historical cost of LEC capital inputs rose more
rapidly during this period than it actually did.  The Commission then would predict an equally large growth
in LEC capital cost in the future, and thus calculate an X-factor that was still too low.  Consequently,
critics contend that LECs' profits would continue to increase despite no increase in LEC productivity.  On
the other hand, suppose that the Commission chose too high an X-factor during the historical period,
causing LECs' profits to decrease.  Critics contend that the residual value method would indicate that the
historical cost of LEC capital inputs fell more rapidly during this period than it actually did.  The
Commission then would predict an equally large price reduction for capital in the future, and thus calculate
an X-factor that was still too high.  Consequently, LECs' profits would continue to decrease despite no
decrease in LEC productivity.  In either scenario, critics claim, the LECs' productivity remains constant;
only their rate of return is affected by the incorrect X-factor.  Thus, they assert that the residual value
method produces an X-factor that is biased in the same direction as whatever bias existed in the historical
period.

     Accordingly, the critics' theory posits that, to avoid this problem, any TFP study of a regulated
industry should augment or reduce the actual amounts of capital compensation in such a way as to
duplicate the forces of a competitive market.  USTA proposed an index similar to the one we are using. 
What USTA did not do is reduce the revenue as capital compensation went down.  To capture the gains in
productivity that would have been revealed in a competitive marketplace, total capital compensation must
vary with the competitive capital compensation rate.  

     In order to correct the alleged miscalculation of the LECs' cost of capital in the 1997 Staff TFP
study, it is necessary to replace the TFP study's cost of capital with a competitive cost for the inputs during
the historical years.  Next, it is necessary to adopt a surrogate to emulate a competitive cost of capital for
LECs because LECs have never operated in a competitive market.  This study employs an independent
price series to compute the annual change in the cost of capital for a competitive market.  Specifically,
Moody's Baa corporate bond rate reported in the 1999 Economic Report of the President (Table B-73) is
used to calculate the adjustment.  Combining the base year imputed cost of capital from the 1997 staff
TFP study with the change in the competitive cost of capital gives an independent competitive cost of
capital for LECs in each year of the historical period.  This competitive cost of LECs' capital input is used
in conjunction with an adjusted cost of labor (see below) and materials inputs from the 1997 staff TFP
study, as well as the percent change in the U.S. nonfarm business sector input price growth, to compute the
corrected input price differential portion of the historical X-factor.

     Recalculating the LECs' historical cost of capital changes the level of the LECs' revenues, taxes,
and operating expenses for the historical years.  If we take the difference between our estimate of the
competitive cost of LECs' capital inputs and the imputed cost from the 1997 staff TFP study, we obtain an
estimate of the excess profits realized by LECs for each year of the historical period.  Reducing the LECs'
total revenue by this amount results in a revenue stream that emulates what LECs would have realized in a
competitive market.  A reduction in revenue implies a reduction in taxes, which in turn reduces operating
expenses.

     Reducing LEC revenues to what would have been realized in a competitive market also changes the
LECs' TFP portion of the X-factor.  The new revenue level changes the LECs' input growth rate by altering
the relative share of revenue accounted for by each input: labor, materials, and capital.  In other words,
the LECs' input growth rate changes in response to the changes in the relative weight of each input factor. 
Combining the output growth rate from the 1997 staff TFP study with the revised LECs' input growth rate
yields the corrected TFP growth rate for the LECs.

II.  Other Modifications to the 1997 Staff TFP Study

     In addition to updating the data for the period 1996-1998, the study concludes that a number of
adjustments to the study reasonably could be performed to improve the 1997 Staff TFP Study's accuracy. 
First, we could substitute the recently revised BLS series on multifactor productivity for the series
previously employed.  In addition, our recalculation of the X-factor could adjust for potential biases in the
local service output index and the price of labor.  These adjustments are easily quantified and are likely to
have a significant impact on the level of the recalculated X-factor.

     The potential bias in the LECs' local output index would affect the LEC's TFP.  The local service
output index from the 1997 staff TFP study was based on the number of local calls.  Because the length of
calls can vary significantly, however, basing the LECs' local output index on the number of dial equipment
minutes (DEMs) more accurately measures the use of the LECs' local equipment.  For much of the period
beginning in 1985, the average length of a local call measured by the number of local DEMs divided by the
number of local calls was approximately constant.  Beginning in 1992, however, there is a pronounced
upward trend in local call length.  This trend is attributable in large part to the increase in the use of the
Internet by local subscribers.  This increase has important implications for measuring local output and, in
turn, LECs' TFP.  Using the number of local calls as the output measure, output increased between 1992
and 1997 at a 3.5 percent annual rate.  On the other hand, using the number of DEMs as the local output
measure, output increased at a 6.5 percent annual rate.  

     Because the data are not yet available, it is necessary to forecast two 1998 values used in
computing the X-factor - the number of local dial equipment minutes and the multifactor productivity. 
Local dial equipment minutes for 1998 are forecast using an extrapolation of the average rate of growth in
dial equipment minutes beginning in 1992.  The multifactor productivity value for 1998 was forecast using
a structural model relating the natural logarithm of the multifactor productivity to the natural logarithm of
the output of all persons employed.  This second series is reported by the Bureau of Labor Statistics, and
its value for 1998 is available.  The parameter estimates of the structural model in conjunction with the
1998 value for output per hour of all persons employed gives the forecast of 1998 multifactor productivity.

     Another adjustment we could make concerns the price of labor.  This problem has further
implications because labor's share of total factor payments will be inflated relative to the other factors of
production.  Between 1985 and 1998, the price of labor, defined as the average compensation per
employee, increased in real terms at a 3.6 percent annual rate.  In terms of total compensation, the amount
paid for labor was approximately the same in 1985 as it was in 1998 even though the number of workers in
the aggregate had been reduced by over 30 percent.  The reason for this, at least in part, is that, coincident
with the adoption of price cap plans, labor force reductions were accomplished by offering employees
monetary incentives to leave the company (i.e., buyouts).  There is some variability in the applicable
accounting rules, but these payments were generally accrued as one-time charges against current earnings. 
This will tend to inflate costs in the early years after the implementation of price caps and, in turn, bias the
measure of TFPLEC growth downward for these periods.

     The resulting recalculation of the X-factor, in which we use a competitively determined cost of
capital, update the multifactor productivity series, substitute a better measure than the number of calls for
local output, and adjust the price of labor to reduce the effects of buyouts, is presented in Table B-12 in
Appendix B.

     While we have identified other potential sources of bias from the 1997 Price Cap Order in our
proposed recalculation of the X-factor, the 1999 staff TFP study does not adjust for them because they
either are not easily quantified, or do not have a significant impact on the level of the X-factor.  These other
possible sources of bias are discussed below.

III.  Other Possible Sources of Bias

     The productivity offset or X-factor is given as

     X(H) = (%_ TFPLEC(H) - %_ TFPUS(H)) + (%_ IPUS(H) - %_ IPLEC(H))

where X(H) denotes the historical X-factor, %_ TFPLEC(H) denotes the percent change in the historical total
factor productivity of local exchange carriers between period t-1 and t, %_ TFPUS(H) denotes the percent
change in the historical total factor productivity for the entire U.S. economy between period t-1 and t, %_
IPUS denotes the percent change in the historical input prices of all goods and services used to produce
output of goods and services in the United States between period t-1 and t, and %_ IPLEC denotes the
percent change in the historical input prices of local exchange carriers used to produce local service,
intrastate toll/access service, and interstate service between period t-1 and t.

     It is important to note that there is no debate about whether there is appropriately an X-factor in
the price cap equation nor is there a question about whether an input price differential should properly be
included in the specification.  The issue at hand is whether the components of the X-factor are accurately
measured based on the data actually used in the computation.  An assessment of this is the focus of what
follows.

A.  Biases in the Measurement of TFPLEC

     There are a number of biases inherent in the measurement of TFPLEC.  There are general biases and
data-specific biases which will tend to overestimate or underestimate the true value of TFPLEC.

     i.  General Biases

     First, TFPLEC will be biased since it is not compatible with incentives to be economically efficient
because the disaggregated input and output data are under the control of the regulated LECs and, thus, are
subject to manipulation.  It has been noted that price cap regulation has the potential to introduce pure
waste, inefficient factor utilization, excessive research and development expenses, and over-investment in
demand increasing expenditures.  This will bias the measurement of TFPLEC downward.  The extent of this
downward bias will be a function of the quantitative magnitude of any excessive expenditures and
inefficient factor utilization.

     Another general bias introduced in the measurement of TFPLEC is associated with the use of LEC
performance data immediately post-divestiture.  This will give a downward bias to the measure.  It is
generally conceded that under rate-of-return (ROR) regulation, regulated firms employed too much capital
and too much labor.  Transition from the regulated environment is not instantaneous.  The optimal level of
factors of production will be in disequilibrium for some period of time following the demise of ROR
regulation.  Hence, the measured TFPLEC as reported in the 1997 Price Cap Review Order will contain
some disequilibrium periods.  That is, the measurement of the productivity of LECs is necessarily
calculated, at least partially, in a ROR environment which will bias downward the TFP measure for at least
a portion of the period.

     A final general bias introduced in the measurement of TFPLEC is associated with the demand for
interstate access to local LECs' local loops.  Interstate access service is the focus of price cap regulation.  It
has grown much more rapidly on average than demand for local service and intrastate access service.  The
data on this are clear.  Thus, in the presence of economies of density, this leads to the conclusion that
TFPLEC in interstate services has grown faster than company-wide (regulated) TFPLEC.  More specifically,
the price cap index (PCI) being considered here applies to interstate access service but TFPLEC is computed
based on all LEC services.  There is every reason to expect that productivity enhancements experienced
historically in the interstate access market would be substantially greater than the overall rate of
productivity growth experienced by LECs in supplying all services.  First, most of the productivity growth
experienced in the telecommunications industry is related to reductions in switching costs and to savings in
transmissions costs which occur as a result of using electronics to expand the carrying capacity of
transmissions facilities.  In contrast productivity growth in supplying loop services has been relatively
lower.  As a result of this, the average measure of TFPLEC used in setting X and which should properly
reflect productivity growth in the interstate access market is biased downward.

     ii.  Data-Specific Biases

          a.  Output Biases

     We turn now to specific issues involving the measurement of TFPLEC.  It is generally recognized
that output growth is a key determinant of the rate of growth of TFP.  Thus, it is especially important to
measure it as precisely as possible.

     Characterizing output is not a trivial undertaking.  Output of telephone service includes both access
and use.  Access and use, however, are complicated by access and use externalities.  The presence of these
externalities means that, contrary to what is typically presumed, preferences are interdependent across
subscribers.  That is, as more users gain access to telephone, the utility of customers in the aggregate rises. 
These externalities are exceedingly difficult to quantify and are not measured here.  This will bias
downward the TFPLEC measure.  Additionally, output comes in a variety of forms including type (station,
person, collect, etc.), time-of-day, day of week, distance, and duration.

     In the specification used, total company output consists of three identifiable components:  local
service, intrastate toll/access service, and interstate service.  Revenue shares are used to weight each
component's contribution to total output.

     Each of the components in total company output is measured differently.  This was dictated by the
available data.  It introduces a potential source of bias.  The nature and extent of this bias, however, is
indeterminate.  That is, it is not clear whether there will be a positive or negative bias. This is an empirical
issue.  Since comparable measures are not available for each of the output components, it is not possible to
measure it empirically.

     The local service output measure is based on the number of local calls.  Intrastate service output
index is based just on the number of dial equipment minutes (DEMs) while the interstate service output
index is a function the number of access lines, the number of switched access minutes, and the number of
special access lines.  No measure of special access minutes is used.  It is interesting to note that the
interstate output index endeavors to capture both the access and use components of interstate output. 
Output measures for local service and intrastate service do not endeavor to do so.

     The component of the output measure that is probably the most questionable in the 1997 Price Cap
Review Order is the local service output index.  This, however, has been corrected in the updated study.

          b.  Input Biases

     We next consider the input (factors of production) side of measuring TFPLEC.  Before doing so,
however, it is important to note that the cost of inputs (i.e., the prices paid for inputs) in the TFPLEC
measurement also appear in the measurement of %_ IPLEC.  Hence, observations made concerning
measurement errors and their impact on the computed value of TFPLEC are equally applicable to the
measurement of the percentage change in input prices of LECs.  Furthermore, the nature of the relationship
given by equation (1) means that most measurement errors associated with the prices of the inputs will tend
to cancel out so that the impact on the productivity offset will, in general, be minimal.

     The most problematic input measure is that for the quantity of labor. Measurement of each input in
a total factor productivity study typically requires subaggregation of various types of the factor.  In the
case of labor this would include several different occupational groups and skill levels and would be
calibrated as the number of hours worked with appropriate adjustments for overtime and part-time workers. 
The labor quantity measure used in the 1997 Price Cap Review Order consists solely of the total number
of full-time employees of RBOCs.  Thus, inherent productivity differentials between employees based on
such things as skill levels is not reflected.  If the LECs were in equilibrium such that the relative proportion
of employees in the different occupational groups with defined skill levels characteristic of LECs remained
unchanged as did the average number of hours each employee worked, then there would be little concern
over how the labor variable is measured.  This is not the case, however.  Between 1985 and 1998, there
was been a significant change in the number of employees.  The LECs labor force declined by 2.4 percent
annually over this period.  Moreover, the reduction has taken place so that the number of managers has
been reduced disproportionately more than the number of technical employees.  Thus, there is a disparity
between the change in observed labor versus effective labor.  The latter is what should be included in the
measurement of TFPLEC while the former is what has been included.  Correct measurement of the labor
variable would reduce aggregate labor expenses and hence increase TFPLEC.  Hence, as constructed, TFPLEC
is biased downward due to the incorrect measurement of the number of units of labor.

     Materials quantity and materials expense are computed as residuals.  Materials quantity is equal to
materials expense divided by materials price.  Materials expense is defined to equal total adjusted operating
expense minus the sum of labor compensation, depreciation, and amortization expense.  The increase in
materials expense account for the major portion of the increase in total factor payment over the period 1985
to 1998.  It is unclear whether there is a superior approach for measuring materials quantities and materials
expense.  The nature of any TFPLEC measurement bias is uncertain.

     The measurement of capital stock and the cost of capital was of greatest concern in the 1997 Price
Cap Review Order.  Accurate measurement of capital stock is exceedingly difficult.  Different types of
capital with different vintages and technology comprise the stock in any given period.  This stock,
moreover, is subject to different utilization rates.  With these difficulties come two significant problems in
the development of the measures of capital and the cost of capital that potentially serve to bias downward
the reported measure of TFPLEC.  The first involves the changing quality of capital over the historical period
that is not adequately reflected in the computations.  The second involves changes in capacity utilization
that are not captured.  

     The quantity of capital is measured for each depreciable asset by the perpetual inventory method
from data on investment.  Many types of capital inputs used by LECs have changed including computer
chips, digital electronics, fiber optics, and digital switching equipment.  This change in the quality of
capital is not effectively reflected in the perpetual inventory approach adopted because the output
associated with one unit of new capital brought on line is not necessarily equivalent to the output of one
unit already in operation.  If they are different, there has been a change in quality.  The typical approach to
reflecting this quality change is to adjust the cost of capital downward to avoid understating the change in
the effective level of real capital stocks.    Additionally, to the extent that succeeding generations of capital
equipment are more productive, an appropriate adjustment to reflect this increases the computed level of
capital stock, increases the flow of capital services, and, holding output constant, decreases the measured
TFPLEC.  Since there was no quality adjustment in the computations reported in the 1997 Price Cap Review
Order, TFPLEC will be biased upward.

     The second significant omission is the failure to adjust for changes in capacity utilization.  Over
time as the existing capital stock is used more intensively, output is higher without a corresponding increase
in capacity.  Consequently, TFPLEC is greater.  There is, however, no adjustment for a change in capacity
utilization in the report.  TFPLEC will, consequently, be biased downward.

B.  Biases in the Measurement of TFPUS

     The measure of TFPUS used is the Bureau of Labor Statistics' estimate of Nonfarm Business Sector
Multifactor Productivity.  There is concern that this measure underestimates the growth in TFPUS.  There
is, however, no basis for determining the magnitude of the underestimation although the consensus is that it
is relatively small.  This being the case, while the productivity offset will be overestimated, its size is small
but indeterminate.

     The major issues related to the BLS measure of productivity that potentially give rise to
overestimation of TFPUS include:

(1)  Mismeasurement of productivity growth in the services portion of the economy.  This portion of the
economy is defined to include communications.  The problem centers on how to define output in the
service-producing industries.  In the case of the services provided by LECs, this can be thought of as
measuring output in terms of access and use.  There is an enormous literature on the mechanics of defining
output in these service-producing industries although there is no consensus on how this should be done. 
Inadequate definitions of output underlie the published data for many service activities.

(2)  Biases in the Consumer Price Index (CPI) on productivity data.  Components of the CPI are used to
construct approximately 57 percent of the business sector output measure used for BLS productivity
statistics.  Thus, any biases in constructing the CPI are directly reflected in TFPUS.  Biases in the CPI are
well documented although their precise magnitude is subject to debate.  These biases include incorrectly
reflecting the substitution bias where consumers' tendencies to substitute among items or categories of
items as relative prices change over time, failure to capture new-outlet bias where consumers respond to
relative price changes by shopping at different retail outlets, and inadequately measuring quality changes
and new products reflecting changes in technology and consumer demand.

(3)  Whether the BLS productivity data fully reflect changes in the quality of goods and services. 
Questions persist as to whether the total factor productivity measure for the United States economy reflect
the extent that succeeding generations of capital equipment are more productive and hence whether an
appropriate adjustment to reflect has been incorporated.  Note that this will increase the computed level of
capital stock and increase the flow of capital services.  

(4)  Whether the best techniques are used to introduce new, advanced products into the data series.

(5)  Whether the BLS methods capture the full impact of new information technology on economic
performance.  It has been suggested, for example, that failure to adequately reflect information technology
understates TFPUS.

     These issues are discussed fully in a series of articles in the February 1998 issue of the Monthly
Labor Review.  

     One other source of bias not previously noted is also present.  This involves composition changes
in inputs.  In the case of labor composition, changes include increased educational attainment over time
which increases TFPUS and an increased share of teenagers and females in the labor force which reduces
TFPUS.  In the case of capital, there has been continuous substitution of equipment for structures and of
short-lived equipment like computers for long-lived equipment like furniture.  Failure to reflect this
substitution underestimates the capital stock component of the TFPUS measure.

C.  Biases in the Measurement of IPUS

     The general input price measure used is the Bureau of Labor Statistics Nonfarm Business Sector
Price Index.  The sources of the data used in constructing this measure are the same as those for the BLS
measure of TFPUS.  Consequently, the major issues related to the BLS measure of TFPUS are applicable to
the measurement of IPUS.  These include the question of how to define output in service-producing
industries, the biases present in constructing the Consumer Price Index, the issue of the introduction of
new, improved factors of production, and the effect of quality changes in goods and services used in
production.

     While there are biases in the measure of IPUS due to biases in its components, considered together
with any bias in the measure of TFPUS attributable to input prices would most likely have an insignificant
net effect on the productivity offset.  For example, an increase in the price of one of the factor inputs will
lower TFPUS but it will increase the input price differential resulting in little net change in X.

D.  Biases in the Measurement of IPLEC

     The measure of IPLEC is a composite index using the labor price index, a materials price index, and
a cost of capital index.  The biases introduced were previously noted in the context of measuring TFPLEC
including changes in the quality of capital and capacity utilization variations.  The effective price of labor
is probably overestimated while the cost of capital even after adjustment to reflect competitive conditions
might or might not be correct.  An adjustment in the cost of capital to reflect changes in quality would
increase the price while an adjustment to reflect changes in capacity utilization would reduce the price.

     As noted previously, there are obvious upward biases in the measure of IPLEC due to biases in its
components.  This, however, considered in conjunction with the bias in the measure of TFPLEC attributable
to these input prices results in a minimal net effect on the productivity offset (X-factor).  That is, increasing
(decreasing) the price of one of the factor inputs will lower (raise) TFPLEC but it will reduce (raise) the
input price differential resulting in little net change in X.

IV.  Conclusion

     Based on the above analysis, the X-factor calculated in the 1997 Staff TFP Study is a significantly
downward biased estimator of the actual rate of cost reductions achieved by the price cap LECs.  The
residual value method employed in this study inappropriately incorporated the steadily rising profits of
LECs into increases in the cost of the capital input.
Correction of the LECs' historical cost of capital plus the change in the local output measure results in a
somewhat larger absolute value of the X-factor than the Commission computed in the 1997 staff TFP
study.  Over the 1986-1995 period, for example, we compute the average X-factor to be 5.82 versus an
average of 5.23 from the 1997 staff TFP study.  Between 1991 and 1995, when price caps were in effect,
our corrected average X-factor is 6.14 versus an average of 5.22 from the 1997 staff TFP study.  Also,
there is somewhat more year-to-year variation in our corrected X-factor than there is in the 1997 staff TFP
study.  Using data covering the period 1986 to 1998, the updated X-factor is 6.02 while for the 1991 to
1998 period, the X-factor is 6.33.
                                Appendix B


                         The 1999 Staff TFP Study


                                 Noel D. Uri


                                 
Introduction

     Under price cap regulation, the weighted average of the prices for the services in a given price cap,
or the actual price index (API), must be less than or equal to the price cap index.  An incumbent LEC's
Price Cap Index (PCI) is adjusted annually in accordance with the PCI relationship defined in the Code of
Federal Regulations.  The PCI relationship consists of a measure of inflation, in this case the Gross
Domestic Product Price Index (GDP-PI), minus the X-factor, plus or minus any permitted exogenous cost
changes.  The X-factor is nominally referred to as the productivity offset.

     The X-factor is defined to equal the sum of the change in LECs' productivity less the change in
productivity of the aggregate economy plus the change in input prices for the aggregate economy less the
change in LECs' input prices.  In the 1997 Price Cap Review Order, a total factor productivity (TFP)
approach was adopted for estimating LECs change in productivity.   

     Considerable thought has gone into and extensive comments were made concerning the selection of
a technique to calibrate the X-factor.  This decision process will not be revisited.  Rather, the immediate
concern is with measuring the X-factor based on the most recent, consistent, and comprehensive data
generally and publicly available.  

Background 

     The methodology used by the FCC's staff to estimate LEC Total Factor Productivity (TFP) and the
input prices, and to calculate the LEC TFP and input price differentials used in the FCC's LEC X-factor
for interstate access is discussed here.  TFP is calculated based on the LECs regulated books of account
excluding miscellaneous services.  Thus, the measure of total factor productivity is based on the
productivity of all LEC activities including local service, intrastate toll/access service, and interstate
service.  The calculations are for the period 1985 through 1998.

     The calculations are based on the Fisher Ideal Index, a standard and economically justifiable
measure.  The TFP estimates embody what is believed to be the best approach available for measuring the
X-factor and emulates the approach used in 1997 Price Cap Review Order.  

     The study is based on data publicly available from the Federal Communications Commission, the
Bureau of Economic Analysis of the U.S. Department of Commerce, and the Bureau of Labor Statistics of
the U.S. Department of Labor.  Consistent with the 1997 Price Cap Review Order, the data are for just the
Regional Bell Operating Companies (RBOCs).  

Methodological Issues

     A productivity index is generally defined as an output index divided by an input index.  An
important question is which functional form for the index number should be used.  Here, known functional
forms for index numbers are related to functional forms for the underlying aggregator function.

     Two important examples of a quantity index are the Laspeyres and Paasche index.  The Laspeyres
quantity index, QL, is defined as

(1) QL (p0, p1, x0, x1) = p0 x1 / p0 x0

where pt > 0 is a vector of prices in period t = 0, 1 and x > 0 is the corresponding vector of quantities.  The
Paasche quantity index, QP, is defined as

(2) QP (p0, p1, x0, x1) = p1 x1 / p1 x0.

     Fisher suggested that the Ideal Index is given as the geometric mean of QL and QP

(3) QF (p0, p1, x0, x1) = ((p0 x1 / p0 x0) (p1 x1 / p1 x0))1/2.

     Let f(x) define an aggregator function and suppose that xt > 0 is the solution to

(4) maxx {f(x): pt x  pt xt }  t=0, 1

where f(x) = (x'Ax)1/2 and A = [aij] is a symmetric matrix of coefficients.  Konus then shows that

(5) f(x1) / f(x0) = QF (p0, p1, x0, x1).

     If a quantity index QF (p0, p1, x0, x1) and a functional form aggregator function f satisfy (5), then
the quantity index QF is said to be exact for the aggregator function.  Konus shows that the Laspeyres
quantity index is exact for a fixed aggregator function while the Paasche quantity index is exact for a linear
aggregator function.  Afriat, Diewert, Pollack, and Samuelson and Swamy provide other examples of
exact index numbers.  Among exact index numbers, however, the Fisher quantity index corresponds to a
functional form for f that can provide a second order approximation to an arbitrary twice-differentiable
linearly homogeneous function.  Thus, the use of the Fisher Ideal Index is economically justified.  

     The input and output quantity indices are constructed using the Fisher Ideal Index.  As noted, this
index is the geometric average of the Laspeyres Index and the Paasche Index.  This index is desirable
because it is calculated using the weights of adjacent years.  During periods of relatively substantial and
significant changes in prices, a significant bias can appear in fixed weight measures, even during periods
close to the base period.

     Expanding beyond just two periods, a chained Fisher Ideal Quantity Index can be constructed
between periods 0 and t.  It is the product of each of the Fisher Ideal Quantity Indexes between periods 0
and t.  All input and output quantity indexes are chained Fisher Ideal Quantity Indexes.  The chained Fisher
Ideal Quantity Index addresses one of the most fundamental problems in measuring output - the choice of
the base period with which all other periods are compared.  Since changes in the Fisher Ideal Quantity
Index are calculated using weights of adjacent years, the chaining of the annual changes allows for the
effect of changes in relative prices.  Thus, the Fisher Ideal Chained Quantity Index calculates an index that
is appropriate for each period and avoids having to update a fixed-weight index.  It also negates the
substitution bias that is inherent in a fixed-weight index.  Finally, the chain-type index provides a more
accurate measure of current period output during periods of significant price changes.

     Indexes of input prices are constructed in a fashion analogous to that for the input and output
quantity indexes.  That is, by calculating a Fisher Ideal Price Index.

     The Laspeyres price index, PL, is defined as

(6) PL (p0, p1, x0, x1) = p1 x0 / p0 x0

where pt > 0 is a vector of prices in period t = 0,1 and x > 0 is the corresponding vector of quantities.  The
Paasche price index, PP, is defined as

(7) PP (p0, p1, x0, x1) = p1 x1 / p0 x1.

     The Fisher Ideal Index for prices is given as the geometric mean of PL and PP

(8) PF (p0, p1, x0, x1) = ((p1 x0 / p0 x0) (p1 x1 / p0 x1))1/2 .

     A chained Fisher Ideal Price Index can be constructed between periods 0 and t.  It is the product of
each of the Fisher Ideal Price Indexes between periods 0 and t.  All input price indexes are chained Fisher
Ideal Price Indexes.  As is the case for output and input indexes, a chained price index is superior to a
fixed-weight index.

     Aggregating across different types of outputs to construct the Fisher Ideal Quantity Index for
output in a given period is accomplished by using the relevant commodity share of total revenue
corresponding the type of output.  Aggregating across the different factors of production to construct the
input quantity and input price indexes in a given period is accomplished by using the relevant shares of
total payments to the corresponding factors.  

Calculation of Output Quantity Indexes

(a) Data Sources 

     The output index is based on actual quantity measures available from the Commission.  Basic local
service revenue, end user revenue, switched access revenue, special access revenue, state access revenue,
and total long distance network revenue are taken from the Commission's Statistics of Communications
Common Carriers for 1985 through 1998.  Also taken from this source are data on the number of special
access lines, the number of business access lines, residential access lines, and public access lines.  Local
access volume is measured by the number of local dial equipment minutes as are state toll and intrastate
access volumes by dial equipment minutes.  These data are taken from the FCC Monitoring Reports.  They
are directly accessible via the FCC web site.  Interstate switched access minutes are from the same
Monitoring Reports.  The component data for interstate revenue are given in are given in Table B-1.  Total
revenue data for each type of service are given in Table B-2.  

(b) Output Category Quantity Indices and Revenue Shares 

     The initial step in the process is to construct an interstate quantity index to measure growth of
interstate services.  This index is constructed using the physical measures of three services including the
number of access lines, the number of interstate switched access minutes, and the number interstate special
access lines.  The number of access lines is measured by the sum of the number of business, public, and
residential access lines.   

     A service's share of total interstate revenue is used to weigh each service in the construction of the
measure of interstate output.  That is, the number of access lines is weighted by the End User Common
Line revenue share of total interstate revenues.  The number of switched access minutes is weighted by the
switched access revenue share, and the number of special access lines is weighted by the special access
revenue share.  A Fisher Ideal Quantity Index is then constructed.  The composite Fisher Ideal Interstate
Quantity (Output) Index is derived by chaining the Fisher Interstate Ideal Output Index.  The resulting
Fisher Ideal Chained Output Index is given in Table B-3.

     A comparable procedure is used to construct revenue shares and quantity indices for total local
service and state toll/access service.  State toll/access revenues are total toll service revenues plus intrastate
access revenues.  The physical units associated with total local service are the number of dial equipment
minutes for local calls while for state toll/access service, the physical units are intrastate dial equipment
minutes.  These data are taken from the FCC Monitoring Reports. 

(c) Total Output Index

     The total LEC output index is computed using the quantity indexes for local service, intrastate
toll/access service, and interstate service and their respective revenue shares.  The interstate share of total
revenue is calculated using the sum of end user revenue, switched access revenue (formerly called "carrier's
carrier facilities revenues"), and interstate special access revenue.  A Fisher Ideal Quantity (Output) Index
is constructed by aggregating these measures for each year.  The composite Fisher Ideal Output Index is
derived by chaining the Fisher Ideal Output Index.  The resulting Fisher Ideal Chained Output Index for
total LEC output is given in Table B-4.  Note that the percentage changes (growth rate) are calculated as
natural logarithmic (loge) changes.

Calculation of Input Quantity Indexes

(a) Labor
     
     The measure of the quantity labor is based on annual accounting data for the number of employees
from the Commission's Statistics of Communications Common Carriers.  These data are reported in Table
B-5.  Since there is no objective way to account for the contribution of part-time versus full-time
employees, just the total number of employees is used as the labor input measure.  This, however, does not
introduce a substantial bias in the labor quantity measure since part-time employees accounted for less that
0.7 percent of the workforce in 1998.

(b) Capital

          (i) Perpetual Inventory Method

     The starting point for construction of a quantity index of capital input is the measurement of the
capital stock.  A perpetual inventory method is employed to estimate the level of capital stock.  In discrete
time, the method is 

(9) Kt = It + (1 - d) Kt-1

where Kt is the end-of-period capital stock, It is the quantity of investment occurring in the period, and d is
the rate of replacement (depreciation).  The data requirements for implementation of this perpetual
inventory method are investment in constant (inflation-adjusted) prices, a capital benchmark, and a rate of
replacement.

     The perpetual inventory method is used to remove embedded inflation that would distort the
measurement of capital.  Consistent with the 1997 Price Cap Review Order, only one asset class is
considered because the record shows that the number of asset classes does not significantly impact the
measured change in TFP.  The application of the perpetual inventory model relies on Commission
depreciation rates.

     The book value of plant is used as the basis for calculating the benchmark (i.e. initial level) capital
stock. In order to calculate constant dollar investment, chained Fisher asset prices from the Bureau of
Economic Analysis of the U.S. Department of Commerce are used deflate capital additions.  

     The benchmark capital stock is based on the end of year 1985 book value.  Because of the 1988
capital/expense shift, it is necessary to adjust both end of year 1985 total plant in service less accumulated
depreciation and 1985-1987 capital additions.  The capital/expense shift factor used in the 1997 Price Cap
Review Order is employed here to reduce capital additions for 1985 through 1987.  Adjusted capital
additions for 1985, 1986, and 1987 are just the product of the unadjusted capital additions and the
adjustment factor of 0.888.  Unadjusted capital addition data were obtained from FCC Form M.

          (ii) Asset Price

     With just a single asset class, a single composite asset price index is needed.  First, Bureau of
Economic Analysis asset prices were obtained from the National Income and Product Accounts.  These
included prices for three asset categories including Communications Equipment (NIPA Table 7.8:
Chained-Type Price indexes for Private Purchases of Producers' Durable Equipment by Type, Line 7),
Telecommunication Structures (NIPA Table 7.7: Chained-Type Price Indexes for Private Purchases of
Structure by Type, Line 12), and a composite asset price for Producer Durables (NIPA Table 7.1, Line
39).  Capital additions data are then grouped into categories corresponding to the NIPA asset categories,
and each category's share calculated.  (The capital/expense shift adjustment factor noted previously has no
effect on the shares because it is multiplicative and applies equally to all asset categories.)  

     From these data, a Fisher Ideal Price Index is computed and used to form a chained Fisher Ideal
Price Index for the single asset.  This price index is used to deflate adjusted capital additions in the
perpetual inventory model.

          (iii) Benchmark Capital Stock

     The benchmark capital stock is derived using the FCC accounting relationship

(10) TPIS.BOYt + CAt - Retirest = TPIS.EOYt

where TPIS.BOYt denotes beginning of the year total plant-in-service for period t, CAt denotes capital
additions in period t, Retirest denotes plant retirements in period t, and TPIS.EOYt denotes total plant-in-
service at the end of the year for period t.  All of these data are taken from the FCC Form M.

     Adjusted capital additions are incorporated which results in revised values for TPIS.EOYt for
1985, 1986, and 1987.  The benchmark capital stock is then obtained by subtracting accumulated
depreciation from adjusted TPIS.BOY1985. 

     As is standard practice in most TFP studies, land is not included as a capital stock component
when forming the benchmark capital stock.  

          (iv) Depreciation Rate

     A time-invariant depreciation rate for the single asset class is computed as an arithmetic average of
annual depreciation rates.  The depreciation rate for period t is given as

(11) dt = (DEPR.ACRLSt) / ((TPIS.BOYt + TPIS.EOYt)/2).  

where DEPR.ACRLSt denotes depreciation accruals.  The data are taken from FCC Form M.

     The value of d is the average (mean) value of dt over the period 1985-1998.

     A summary of capital adjustments and average depreciation is given in Table B-6.  

          (v) Capital Input Quantity Index

     The capital input quantity index series is computed by dividing current period capital stock by the
base period capital stock. These data are reported in Table B-7.

(c) Materials - Part I

     The materials quantity is computed as materials expense divided by a materials price index. 
Materials expense is a residual.  It is the difference between total operating expense and the sum of labor
compensation and depreciation and amortization expense.

     Until now computation of the various components of the X-factor have been straightforward and
mechanistic.  Things are somewhat more complicated, however, from this point forward.  To explain the
complications and what is necessary to compute materials quantity, a digression is in order.

(d) Digression

     TFP models in general measure productivity as the ratio of an index of outputs of a firm to an
index of its inputs over a given time period (e.g., a year).  The growth in productivity is the amount by
which this ratio changes over time.  In making these calculations, it is critical that real changes in
productivity be separated from the effects of changes in input prices.

     It is typically the case that three inputs are considered in TFP-type studies.  These inputs consist of
labor, capital, and materials.  Sometimes a fourth input energy is considered.  This is not done here. 
When just three inputs are used in the analysis, materials is considered as a residual.  That is, it accounts
for whatever input expenditures are not attributable to labor and capital.

     The growth rate of the index of inputs is determined by the growth rates of the labor, capital, and
materials input indices weighted by their relative contribution to total input cost.  The growth rate of capital
is a complex procedure, requiring a determination of capital stock and the flow of capital services from
capital stock.

     A number of very explicit assumptions underlie TFP analyses.  In particular, the conventional
method of measuring TFP of firms (which is used in the 1997 Price Cap Review Order) is to assume that
there are constant returns to scale and that observed inputs and outputs have been generated by firms in
competitive, long run equilibrium.  With prices of output and inputs fixed, the firm chooses input levels so
as to maximize profit.  The measure of TFP growth obtained by conventional means is not, however,
appropriate whenever firms are not in a long run cost minimizing equilibrium.  A firm is not in long run
equilibrium whenever the firm's input-output bundle is other than corresponding to a point on the long run
unit cost curve.  If the firm is not in long run equilibrium, then profit is not zero.

     Before exploring the implications of this observation for the results reported in the 1997 Price Cap
Review Order, it is necessary to examine what price caps are and to assess the mechanics of estimating an
historical productivity offset.

     (i) Price Caps in Theory

          Overview

     Assume that there are two periods, t= 1,2.  Suppose that in each period the firm produces units of a
single output, qt, using a single input which will be called labor and denoted by Lt.  Let wt denote the price
of labor in period t and pt denote the price of output in period t.  An outcome for the market in period t is
defined to be a vector of these four variables, (pt, qt, wt, Lt).  If the output price of the firm is regulated so
that its revenues equal its costs, then the outcome in each period will satisfy

(12) pt = wt Lt /qt .

     Define the variable zt to be the productivity of the firm in period t measured in units of output per
units of input.  Thus, 

(13) zt = qt /wt .

     Substitution of relationship (13) into relationship (12) yields

(14) pt = wt /zt .

     That is, in a regulated market where the firm is constrained to earn zero economic profit, the output
price will be equal to the input price divided by productivity.

     Use the following notation to denote the percentage change in each variable between periods 1 and
2:

(15) %D p = (p2 - p1)/p1 

(16) %D q = (q2 - q1)/q1 

(17) %D pw = (w2 - w1)/w1 

(18) %D L = (L2 - L1)/L1 

(19) %D z = (z2 - z1)/z1 

     It follows immediately from equation (14) that when outcomes in both periods are regulated so that
the firm earns zero economic profit, then 

(20) %D p = %D w - %D z.

     That is, if the firm is constrained to earn zero economic profit, then the percentage change in
output price will just equal the percentage change in input price minus the percentage change in
productivity.

          Price Caps With an Exogenous Input Price Index

     The well-understood problem with cost-based regulation is that the regulated firm has very little
incentive to be efficient because any efficiency gains are immediately captured by the regulator.  Price caps
are meant to ameliorate this problem.  The basic idea is very simple.  Suppose that period 1 has just ended
and the regulator is considering how to set price in period 2.  The regulator knows that if he or she uses
cost-based regulation to set price in period 2 that the resulting price will satisfy relationship (9).  The
essential idea of price caps is to replace the term %D z with an estimate of %D z made in period 1.  Let E
denote the estimate of productivity change.  At the end of period 1, it is announced that the price in period 2
will be set according to the formula

(21) %D p = %D w - E.

     That is, the regulator will wait until the end of period 1 and observe the actual change in input
prices and allow output prices to increase by this percentage.  Rather than wait to observe actual changes
in productivity, however, the output prices are adjusted by a fixed amount regardless of the firm's realized
productivity change.

     The firm will then earn a normal profit (and zero economic profit) if the regulator is able to
correctly guess the actual (realized) productivity change.  The firm will have a strong incentive, however, to
improve productivity because it will keep any positive or negative profits that result if its actual
productivity improvement is different than the predicted productivity change.

     One could also imagine the regulator replacing %D w with an exogenous, pre-specified estimate. 
Then the regulator would simply tell the regulated firm that its output prices would change by a certain
percent regardless of the level of actual input price inflation in period 2.  This practice is not usually
followed, however, because the regulated firm typically purchases inputs in relatively competitive markets
so that the regulated firm has very little influence over the price it pays for inputs.  Therefore, exogenously
pre-specifying a target percentage change for input prices would have no desirable incentive effects.  It
would increase the risk, however, that the regulated firm is required to incur to the extent that future input
prices vary unpredictably.  Therefore, %D w is not typically replaced by a pre-specified estimate.

          Price Caps With An Exogenous National Output Price Index

     Price cap schemes generally have the form that output price is allowed to increase in a given year
by the amount that some price index actually increases minus some pre-specified amount.  The foregoing
section suggests that a very simple, transparent, and straightforward method for implementing a price cap
system would be to base the price index on INPUT prices for the industry being regulated.  This practice,
however, is not typically followed.  Rather, instead of basing the price index on INPUT prices for the
industry being regulated, regulators generally use a composite price index for OUTPUT prices for the
economy as a whole.  In particular, this is the practice followed by the Federal Communications
Commission (hereafter Commission) to regulate interstate access prices.

     When a national output index is substituted for an industry input index, a correction has to be
made for the fact that input prices in the particular industry being regulated may be systematically growing
at a different rate than output prices in the economy as a whole.  For example, because of rapid
technological advances in telecommunications, input prices for telecommunications firms are not changing
at the same rate as output prices in the economy.  Consequently, the regulator must choose an adjustment
factor to correct for this difference.  Let D denote the regulator's estimate of the rate at which output prices
in the economy as a whole change differently than input prices in the regulated industry.  Let RPI denote
the percentage change in the national output price index.  The price cap formula becomes

(22) %D p = RPI - D - E .

     This can be rewritten as 

(23) %D p = RPI - X

where

(24) X = D + E.

     This is the familiar form of a price cap plan.  That is, the X-factor is composed of two separate
components.  It is the sum of the predicted productivity growth of the regulated firm, E, plus the expected
amount that national output prices grow faster than industry input prices, D.

          Choosing the X-Factor

     The efficiency incentives created by a price cap scheme are not affected by the size of the X-factor
that the regulator chooses.  The simple fact that the X-factor is fixed and independent of the actual costs
incurred creates an incentive for the firm to be efficient.  The regulator is still concerned with the level of
the X-factor, however, because this affects the distribution of the economic surplus between the firm and
consumers.  It can also potentially affect whether or not the regulated firm chooses to exit the industry.  If
the X-factor is chosen too high, the regulated firm may well choose to exit the industry.  On the other hand,
if it is chosen too low, the regulated firm will earn positive economic profit and consumers will pay higher
prices than necessary.  Therefore, the regulator has a considerable interest in choosing an X-factor so that it
will be above but as close as possible to the sum of the expected value of the firm's productivity change and
the difference between the industry's input price change and the economy's output price change.

     One relevant piece of information is the behavior of these variables in the recent past.  Let EH
denote the historical rate of productivity growth for the regulated firm over the recent past.  Let DH denote
the historical difference between the rate of change in output prices for the economy as a whole and the rate
of change of input prices for the regulated industry.  Let XH denote the sum of these two variables.  That is, 

(25) XH = DH + EH.

     The variable XH will be referred to as the historically justified X-factor.  The typical practice of
regulators is to calculate the historically justified X-factor and then to set the X-factor equal to this unless
factors can be identified which will cause the future values to depart systematically from the historical
values.  If so, some attempt must be made to adjust exogenously for such factors. 

     These identifiable factors are customarily most important when price caps are being first
introduced to replace rate-of-return regulation.  In such a circumstance, it is generally argued that the
increased efficiency incentives created by the switch to price caps will result in higher future rates of
productivity growth than were historically observed.  Therefore, it is argued that future productivity growth
is likely to be higher than past productivity growth for some period of time.  Therefore, when price caps
are first introduced, regulators often set the X-factor somewhat higher than the historically justified rate in
anticipation of increased production efficiency.  The Commission followed this practice when it first
introduced price caps for LECs in 1991.  The actual X-factor was set 0.5 percent above the historically
justified level and this difference was nominally referred to as the consumer productivity dividend.  

     Note, however, that increased efficiency incentives created by the switch to price caps will
dissipate when price caps have been in effect for some time and the historical period being evaluated is one
where price caps were in place.  In this case, the historical data are already reflecting the increased
incentives for efficiency created by price caps.

     In theory it is possible to imagine all sorts of reasons why future rates of productivity growth may
diverge from past rates, even if price caps have been in place for some time.  For example, one of the main
sources of measured productivity growth is simply growth in demand, since production technologies of
regulated firms frequently exhibit economies of scale.  Therefore, if the estimated rate of demand growth in
the future is different than the historical rate of demand growth, this would create a basis for predicting a
difference between historical and future rates of productivity growth.

     In practice, however, regulators' information is often much too unreliable to attempt to make such
corrections.  Consequently, in many regulated industries it may be that the only course of action on the part
of the regulator than can withstand a critical challenge is for the regulator to set the future X-factor equal
to the historical rate.

     There is some evidence that the Commission is in fact in this position.  In the 1997 Price Cap
Review Order, the Commission calculated that the historically justified X-factor was approximately 5.2
percent but then attempted to argue that the future X-factor should be set at 6.0 percent.  The U.S. Court of
Appeals for the D.C. Circuit recently remanded this decision to the Commission, stating that the
Commission had not adequately justified the additional amount to the historically justified rate.

     (i) Price Caps in Theory and Practice

     The Commission's description of its methodology for calculating the historically justified X-factor
in the 1997 Price Cap Review Order appears to be different than the procedure for estimating the DH and
EH described above.  This difference, however, is only superficial.  The procedure used by the Commission
to estimate XH is, in fact, precisely as described above.  This is explained in what follows.

     In the description of its procedure in the 1997 Price Cap Review Order, the Commission states
that it calculates the historically justified X-factor according to the following formula:

(26) X(H) = (%D TFPLEC(H) - %D TFPUS(H)) + (%D IPUS(H) - %D IPLEC(H))

where X(H) denotes the historical X-factor, %D TFPLEC(H) denotes the percent change in the historical
total factor productivity of local exchange carriers between period t-1 and t, %D TFPUS(H) denotes the
percent change in the historical total factor productivity for the entire U.S. economy between period t-1 and
t, %D IPUS denotes the percent change in the historical input prices of all goods and services used to
produce output of goods and services in the United States between period t-1 and t, and %D IPLEC denotes
the percent change in the historical input prices of local exchange carriers used to produce local service,
intrastate toll/access service, and interstate service between period t-1 and t.

     On the surface, relationship (26) does not appear to be the same as equation (25) which the
previous analysis suggests is what is used to calculate the historically justified X-factor.  Equation (26) can
be rewritten, however, as

(27) X(H) = {%D TFPLEC(H)} + {- %D TFPUS(H)) + %D IPUS(H) - %D IPLEC(H)} .

     The term in the first set of brackets in equation (27) corresponds to the variable EH in equation
(25).  Therefore, equations (27) and (25) are in fact equivalent if it can be shown that the terms in the
second set of bracket of relationship (27) correspond to DH.  This equivalence is demonstrated in what
follows.  Let RPI(H) denote the rate of change in output prices in the economy as a whole over the
historical period.  Then, it is always true that

(28) RPI(H) = - %D TFPUS(H)) + %D IPUS(H).

     That is, because the economy in aggregate is nearly competitive, the percentage change in output
prices is just equal to the percentage change in input prices minus the percentage change in productivity. 
Substitute relationship (28) into the second bracketed term of relationship (27).  Rearranging terms gives 

(29) RPI(H) - %D IPLEC(H)

     This is the historical difference between the rate of change of prices for aggregate output and
industry input, which is, by definition, DH.

     (iii) The Use the Residual Value Method for Determining Capital Prices

     The above discussion shows that the Commission in the 1997 Price Cap Review Order
implemented price caps and calculated an historically justified X-factor equal to the sum of DH and EH
where the formulas for estimating DH and EH are given by

(30) DH = RPI(H) - %D IPLEC(H)  

(31) EH = %D TFPLEC(H).

     This being the case, it is possible to explain the error that the Commission made in the 1997 Price
Cap Review Order in the calculation of the historically justified X-factor.

     The 1997 Staff TFP Study associated with the 1997 Price Cap Review Order made a conceptual
error in using actual imputed cost of capital when measuring the productivity of regulated companies.  The
problem arises because of the use of the residual value approach for determining the cost of the capital
input.  With this approach, the Commission in the 1997 Price Cap Review Order first directly determined
the price and quantity used of every input (i.e., labor and materials) except capital.  That is, it directly
calculated the realized return to every non-capital input.  Next, based on an estimate of the capital stock,
the assumption that all revenue is distributed to the inputs, and given the returns to labor and materials
based on historical data, a cost of capital is imputed.

     Conceptually, the difference (residual) between revenue and the required returns to all non-capital
inputs (which is just the nominal amount used to impute a cost of capital) consists of two parts.  The first
part is the required return to capital.  The second part is the excess profit earned by the firm.  Instead of
attempting to separate this difference into two parts, however, the Commission in the 1997 Price Cap
Review Order simply assumed that all of this residual was the required return to capital, i.e., that no excess
profit was earned.  This is a reasonable assumption for a competitive market, and even for non-competitive
markets, as long as the goal of the study is simply to measure the productivity gains revealed by market
forces.  In a regulatory setting, however, the productivity gains are "revealed" by the application of the X-
factor, not by market forces.

     By attributing all of the residual to the capital inputs, the residual value method tends
automatically to define whatever profits or losses the LECs realized during the historical period as
increases or decreases in the cost of capital inputs.  Suppose, for example, that the Commission chose too
low an X-factor during the historical period being considered, causing the LECs' profits to increase.  Under
the residual value method, the Commission would conclude that the historical cost of LEC capital inputs
rose more rapidly during this period than it actually did.  The Commission then would predict an equally
large growth in LEC capital cost in the future, and thus calculate an X-factor that was still too low. 
Consequently, LECs' profits would continue to increase despite no increase in LEC productivity.  On the
other hand, suppose that the Commission chose too high an X-factor during the historical period, causing
LECs' profits to decrease.  Under the residual value method, the Commission would conclude that the
historical cost of LEC capital inputs fell more rapidly during this period than it actually did.  The
Commission then would predict an equally large price reduction for capital in the future, and thus calculate
an X-factor that was still too high.  Consequently, LECs' profits would continue to decrease despite no
decrease in LEC productivity.  In either scenario, the LECs' productivity remains constant.  Only their rate
of return is affected by the incorrect X-factor.  Thus, the residual value method produces an X-factor that
is biased in the same direction as whatever bias existed in the historical period.

     To be useful to regulators, then, any X-factor study of a regulated industry must augment or
reduce the actual amounts of capital compensation in such a way as to duplicate the forces of a competitive
market.  Merely replacing the residual capital value method of determining the capital compensation rate
with an independent price index would not be sufficient.  It would merely cause counterbalancing shifts
between the input price differential and the productivity growth rate differential.  To capture the gains in
productivity that would have been revealed in a competitive market, total capital compensation must vary
with the cost of capital one would observe in a competitive market.  

     In order to correct the miscalculation of the LECs' cost of capital in the 1997 Staff TFP study, it is
necessary to replace the TFP study's cost of capital with a competitive cost for the inputs during the
historical years.  Next, it is necessary to adopt a surrogate to emulate a competitive cost of capital for
LECs because LECs have never operated in a competitive market.  An independent price series is employed
to compute the annual change in the cost of capital for a competitive market.  Specifically, Moody's Baa
corporate bond rate reported in the 1999 Economic Report of the President (Table B-73) is used to
calculate the adjustment.  These data are reproduced in Table B-8.  Combining the base year imputed cost
of capital from the 1997 staff TFP study with the change in the competitive cost of capital gives an
independent competitive cost of capital for LECs in each year of the historical period.  This competitive
cost of LECs' capital input is used in conjunction with an adjusted cost of labor (see below) and materials
inputs from the 1997 staff TFP study, as well as the percent change in the U.S. nonfarm business sector
input price growth, to compute the corrected input price differential portion of the historical X-factor.

     Recalculating the LECs' historical cost of capital changes the level of the LECs' revenues, taxes,
and operating expenses for the historical years.  If the difference between the estimate of the competitive
cost of LECs' capital inputs and the imputed cost from the 1997 staff TFP study is computed, an estimate
of the excess profits realized by LECs for each year of the historical period is obtained.  Reducing the
LECs' total revenue by this amount results in a revenue stream that emulates what LECs would have
realized in a competitive market.  A reduction in revenue implies a reduction in taxes, which in turn
reduces total operating expense.  It is this reduced total operating expense that is used in the computation
of the materials input quantity.

     Reducing LEC revenues to what would have been realized in a competitive market also changes the
LECs' TFP portion of the X-factor.  The new revenue level changes the LECs' input growth rate by altering
the relative share of revenue accounted for by each input - labor, materials, and capital.  In other words,
the LECs' input growth rate changes in response to the changes in the relative weight of each input factor. 
Combining the output growth rate from the 1997 staff TFP study with the revised LECs' input growth rate
yields the corrected TFP growth rate for the LECs.

(e) Materials - Part II

     As noted, an adjustment to the cost of capital changes the effective total operating expense due to a
change in taxes.  The adjusted total operating expense less labor compensation less depreciation and
amortization divided by the materials price index gives materials input quantity.  The materials price index
is the same as that used in the 1997 Price Cap Review Order.  The materials input quantity series is found
in Table B-9.

(f) Total Input Quantity Index

     Having constructed input quantity indexes for each of the factors of production, a composite input
index can be computed.  Using relative shares of payments to each of the factors as weights, an aggregate
input value for each year is calculated.  These values are used to compute a Fisher Ideal Index for input
quantity.

     To compute the relative shares, payments to each of the factors is needed.  The payment to labor is
adjusted total compensation, the payment to materials is adjusted materials expense, and the payment to
capital is adjusted property income with depreciation.  Adjusted property income is capital stock quantity in
period t-1 times the imputed competitive cost of capital for period t.  Adjustments to material payments and
property income (capital compensation) have been previously discussed.  Adjustments to labor
compensation are deferred to a subsequent section.  Payments to the factors of production together with
factor shares are given in Table B-10.

     The composite Fisher Ideal Input Quantity Index is derived by chaining the Fisher Ideal Input
Quantity Index.  The resulting Fisher Ideal Chained Input Quantity Index is given in Table B-11.  Note that
the percentage changes (growth rate) are calculated as natural logarithmic (loge) changes.

Total Factor Productivity for LECs and the TFP Differential

     The percentage change in total factor productivity is the measure for the productivity component of
the X-factor.  This is calculated as the percentage change in total output (Table B-4) less the percentage
change in input quantity (Table B-11).  For both output and input quantity, the Fisher Ideal Chained Index
is used.  The percentage changes (growth rate) are calculated as natural logarithmic (loge) changes.  Annual
changes together with the historical averages for various periods is given in Table B-10.

     The productivity component of the X-factor as specified in relationship (26) consists of the
difference between LECs TFP growth rate and the TFP growth rate of the aggregate economy.  This
differential is presented in Table B-12.  The Bureau of Labor Statistics of the U.S. Department of Labor
estimate of Private Nonfarm Business Sector Multifactor Productivity is used to compute the TFP growth
rate for the aggregate economy.,  The 1998 value of this multifactor productivity series is not currently
available.  It is forecast by estimating a structural relationship between output per hours of all persons
employed and private nonfarm business multifactor productivity using a double logarithmic (loge)
transformation.  Data for output per hour of all persons employed for 1998 is available from the Bureau of
Labor Statistics and is used to generate the forecast.     

     The results indicate that total factor productivity of LECs grew about 4.2 percent faster than
productivity in the nonfarm private business sector of the economy over the 1986 to 1998 period.  

Calculation of Input Price Indexes

     The second component of the X-factor is the input price differential.  This is just the value in the
second set of parentheses in equation (26), %D IPUS(H) - %D IPLEC(H).  Focus for now on the changes in
LEC input prices.  The price of each factor of production will be considered separately.

(a) Labor

     Total labor compensation divided by the number of employees gives a simple way of computing the
average annual price of labor.  The resulting series, however, is not homogeneous over the 1985-1998
period and hence it introduces measurement error into the analysis.  Between 1985 and 1998, the price of
labor, defined as the average compensation per employee, increased in real terms at a 3.6 percent annual
rate.  In terms of total compensation, the amount paid for labor was approximately the same in 1985 as it
was in 1998 even though the number of workers in the aggregate had been reduced by over 30 percent. 
The reason for this, at least in part, is that, coincident with the adoption of price cap plans, labor force
reductions were accomplished by offering employees monetary incentives to leave the company (i.e.,
buyouts).  There is some variability in the applicable accounting rules, but these payments were generally
accrued as one-time charges against current earnings.,

     To have a labor price series meaningful for TFP analysis, it is necessary to adjust for the impact of
the exogenous changes in labor compensation and accounting rules.  This is accomplished by adjusting the
labor compensation series to net out one-time charges for such things as buyouts and accounting rule
changes.  Sufficiently detailed information to allow for such an adjustment to the total compensation series
is not available from Statistics of Communication Common Carriers, the source of the total labor
compensation and number of employees data used in the 1997 Price Cap Review Order.  Alternate data
must be relied upon.  These data are discussed below.

     From the FCCs' ARMIS Report 43-02, total compensation for the year is defined to equal payroll,
including salaries, wages, and payroll related benefits.  Separate items from the same report include
salaries and wages and benefits.  Salaries and wages are defined to equal salaries, wages, commissions,
bonuses, incentive awards, and termination payments.  Benefits include pensions, saving plan contributions,
worker's compensation, life and health insurance, social security and other payroll taxes.  These data series
are reported in Table B-5.  Benefits are equal to approximately 20 percent of the sum of salaries plus
wages plus benefits for the years 1988-1990.  Subsequently, they increase annually, reaching a maximum
of 30 percent in 1994 and then decline to approximately 21 percent in 1998.  The increase in the proportion
of benefits above 20 percent is assumed to be the amount attributed to buyouts, accounting rule changes,
and so on.  This amount is nominally referred to as excess benefits.  This is the amount that must be netted
out to give a labor compensation series that can be used in the TFP analysis.

     Using this rule, excess benefits are computed with the resulting amount subtracted from total
compensation to give the adjusted labor compensation series in Table B-5.  The values in this series
divided by the number of workers gives an adjusted labor price.  The adjusted labor price index is then
computed (Table B-5).

(b) Capital

     As noted previously, in order to correct the miscalculation of the LECs' cost of capital in the 1997
Staff TFP study, it is necessary to replace the TFP study's cost of capital with a competitive cost for the
inputs during the historical years.  Next, it is necessary to adopt a surrogate to emulate a competitive cost
of capital for LECs because LECs have never operated in a competitive market.  An independent price
series is employed to compute the annual change in the cost of capital for a competitive market. 
Specifically, Moody's Baa corporate bond rate reported in the 1999 Economic Report of the President
(Table B-73) is used to calculate the adjustment.  Combining the base year imputed cost of capital from the
1997 staff TFP study with the change in the competitive cost of capital gives an independent competitive
cost of capital for LECs in each year of the historical period.  

(c) Materials

     The materials price index is the same as that used in the 1997 Price Cap Review Order.  The price
index is based on those categories of expenditures from the National Input-Output Tables compiled by the
Bureau of Economic Analysis of the U.S. Department of Commerce that focus on materials purchases by
communications industries.  The materials price index is a Tornquist index.  The materials price index is
given in Table B-9.

(d) Total Input Price Index

     Having constructed input price indexes for each of the factors of production, a composite input
index can be computed.  Using relative shares of payments to each of the factors as weights, an aggregate
input value for each year is calculated.  These values are used to compute a Fisher Ideal Index for input
price.

     To compute the relative shares, payments to each of the factors is needed.  The payment to labor is
adjusted total compensation, the payment to materials is adjusted materials expense, and the payment to
capital is adjusted property income with depreciation. Adjusted property income is capital stock quantity in
period t-1 times the imputed competitive cost of capital for period t.  Adjustments to material payments and
property income (capital compensation) have been previously discussed.  Adjustments to labor
compensation are deferred to a subsequent section.  Payments to the factors of production together with
factor shares are given in Table B-10.

     The composite Fisher Ideal Input Price Index is derived by chaining the Fisher Ideal Input Price
Index.  The resulting Fisher Ideal Chained Input Price Index is given in Table B-13.  Note that the
percentage changes (growth rate) are calculated as natural logarithmic (loge) changes.

Input Price Differential

     The input price differential, the second component of the X-factor, is computed as the percentage
change in input prices for the aggregate economy less the percentage change in LECs' input prices.  The
measure of aggregate input price change used is the Nonfarm Business Sector Input Price Index compiled
by the Bureau of Labor Statistics of the U.S. Department of Labor.

     The input price differential is presented in Table B-12.  The results suggest that input prices in the
nonfarm private business sector of the economy grew about 1.8 percent faster than input prices for LECs'
over the 1986 to 1998 period.

The X-Factor

     The computed X-factor defined by equation (26) and consisting of a productivity component plus
an input price differential component is presented in Table B-12.  Averages for different time period
intervals are presented.  The average is in the range of 5.8 to 6.3 percent.  It is interesting to note that the
averages are approximately equal for these different time periods.
Table B-1.  LEC Interstate Revenue ($) - 1985-1998

______________________________________________________________________________

Year End User       Interstate Switched Special Access Total Interstate
     Revenue        Access         Revenue        Revenue
               Revenue   
______________________________________________________________________________

1985 1499413893     10906203190    1960688644     14366305727

1986 2400475814     10484265170    2574800716     15459541700

1987 3090639929     9611996187     2657677439     15360313555

1988 3604221000     9662529000     2539698000     15806448000

1989 4398692000     9092575000     2253922000     15745189000

1990 4679142000     8595750000     2209064000     15483956000

1991 4828177000     8514130000     2119037000     15461344000

1992 4963262000     8650880000     2153565000     15767707000

1993 5244094000     8999065000     2097997000     16341156000

1994 5589662000     9293783000     2217125000     17100570000

1995 5770285000     9332869000     2529667000     17632821000

1996 5930960000     9409639000     3070598000     18411197000

1997 6268026000     8763815000     3851028000     18882869000

1998 7928205000     7447289000     4894584000     20270078000
______________________________________________________________________________

Source:  Federal Communications Commission, Statistics of Communication Common Carriers 
[various years]
Table B-2.  LEC Revenue ($) by Type of Service1 - 1985-1998
     
______________________________________________________________________________
     
Year Local Service  Intrastate Toll     Interstate          Total
     Revenue        and Intrastate Service        Revenue
               Access         Revenue
               Service
               Revenue
______________________________________________________________________________

1985 26960554164    13047095682    14366305727    54373955573

1986 28626174049    13538946795    15459541700    57624662544

1987 29150842991    14166723124    15360313555    58677879670

1988 29226988000    14994975000    15806448000    60028411000

1989 29973157000    14868219000    15745189000    60586565000

1990 30699085000    15014729000    15483956000    61197770000

1991 32059008000    14522276000    15461344000    62042628000

1992 33359990000    14225181000    15767707000    63352878000

1993 34598957000    14496831000    16341156000    65436944000

1994 35758637000    14355983000    17100570000    67215190000

1995 37684860000    13123225000    17632821000    68440906000

1996 40523387000    12987476000    18411197000    71922060000

1997 42460592000    12308613000    18882869000    73652074000

1998 45643024000    12236469000    20270078000    78149571000
______________________________________________________________________________

1 This excludes miscellaneous services.

Source:  Federal Communications Commission, Statistics of Communication Common Carriers 
[various years]
Table B-3.  Interstate Output Index - 1985-1998

________________________________________________________________________________________________________________________________________________________________________________

Year End User       Interstate          Special   Number of      Number of      Number of Laspeyres      Paasche   Fisher         Fisher
     Revenue        Switched       Access    Access         Switched       Special   Output              Output    Ideal          Ideal
     Share          Access         Revenue   Lines          Access         Access    Index               Index     Output         Chained
               Revenue        Share               Minutes        Lines                    Index          Output
               Share                                                                 Index
________________________________________________________________________________________________________________________________________________________________________________
                                        
1985 0.10437        0.75915        0.13647   92671959       156853820000   1230590   1              1    1                   1

1986 0.15527        0.67817        0.16655   95333884       157302701000   1664101   1.05324             1.05225   1.05275        1.05275

1987 0.20120        0.62576        0.17302   98228585       173154171000   1764445   1.08309             1.07881   1.08095        1.13797

1988 0.22802        0.61130        0.16067   98270787       187663836000   2701817   1.14444             1.11496   1.12960        1.28546

1989 0.27936        0.57748        0.14314   101190050      210406134000   2448090   1.06576             1.05892   1.06233        1.36559

1990 0.30219        0.55513        0.14266   103857988      231960296000   3518005   1.12908             1.11449   1.12176        1.53188

1991 0.31227        0.55067        0.13705   107383807      246710182000   5151699   1.11181             1.09485   1.10330        1.69012

1992 0.31477        0.54864        0.13658   108938065      262187655000   6033139   1.06251             1.06025   1.06138        1.79387

1993 0.32091        0.55069        0.12838   112196681      278173161000   10153615  1.13614             1.10261   1.11925        2.00781   

1994 0.32686        0.54347        0.12965   115264861      298342017323   13824365  1.09511             1.08680   1.09095        2.19042

1995 0.32724        0.52928        0.14346   119887506      334981582000   16107677  1.10126             1.09992   1.10059        2.41077   

1996 0.32213        0.51108        0.16677   125333996      363445050000   20775150  1.10141             1.10070   1.10105        2.65440

1997 0.33194        0.46411        0.20394   131618657      387587696669   28051449  1.10851             1.10823   1.10837        2.94207   

1998 0.39112        0.36740        0.24146   138481147      407903661000   34142101  1.08591             1.08785   1.08688        3.19768   
________________________________________________________________________________________________________________________________________________________________________________

Source:  Federal Communications Commission, Statistics of Communication Common Carriers [various years] and Federal Communications Commission, Monitoring Reports [various years]
Table B-4.     Total LEC Output Index - 1985-1998

______________________________________________________________________________________________________________________________________________________________
___

Year Revenue   Revenue   Revenue   Local          Intrastate          Interstate     Laspeyres           Paasche             Fisher              Fisher         Growth
     Share -   Share -   Share -   DEMs      DEMs      Fisher    Output         Output              Ideal                    Ideal               Rate (%)
     Local     Intrastate     Interstate     (000)          (000)          Ideal     Index               Index               Output              Chained
          Toll                          Chained                       Index          Output
                                        Output                                  Index
                                        Index
______________________________________________________________________________________________________________________________________________________________
___

1985 0.4958    0.2400    0.2642    1380145900     164191177 1    1         1         1              1

1986 0.4968    0.2350    0.2683    1396014000     173173536 1.05275   1.03276        1.03218             1.03247             1.03247             3.19590
     
1987 0.4968    0.2414    0.2618    1404776000     183597411 1.13797   1.03908        1.03778             1.03843             1.07215             3.77145

1988 0.4869    0.2498    0.2633    1469781200     191904837 1.28546   1.06784        1.06673             1.06728             1.14430             6.51202

1989 0.4947    0.2454    0.2599    1496826800     207298177 1.36559   1.04541        1.04429             1.04485             1.19562             4.38736

1990 0.5016    0.2453    0.2530    1514588700     217913904 1.53188   1.05008        1.04755             1.04881             1.25399             4.76646

1991 0.5167    0.2341    0.2492    1512946987     219713721 1.69012   1.02751        1.02531             1.02641             1.28711             2.60724

1992 0.5266    0.2245    0.2489    1558762543     224278538 1.79387   1.03580        1.03567             1.03573             1.33311             3.51158

1993 0.5287    0.2215    0.2497    1640600472     227540869 2.00781   1.06059        1.05960             1.06010             1.41324             5.83650

1994 0.5320    0.2136    0.2544    1719329169     235362364 2.19042   1.05559        1.05559             1.05559             1.49181             5.41052

1995 0.5506    0.1917    0.2576    1802545593     246926539 2.41077   1.06183        1.06161             1.06172             1.58389             5.98968

1996 0.5634    0.1806    0.2560    1955027929     263719641 2.65440   1.08554        1.08570             1.08562             1.71951             8.21567

1997 0.5765    0.1671    0.2564    2179309093     273526580 2.94207   1.09909        1.09937             1.09923             1.89015             9.46127

1998 0.5841    0.1566    0.2594    2275450746     286005821 3.19768   1.05533        1.05512             1.05523             1.99454             5.37567
______________________________________________________________________________________________________________________________________________________________
___

Source:  Federal Communications Commission, Statistics of Communication Common Carriers [various years] and Federal Communications Commission, Monitoring Reports [various years]

Table B-5.  Price of Labor - 1985-1998

____________________________________________________________________________________________________________________________________________________________________________________

Year Labor     Number of ARMIS     ARMIS     Ratio     Excess    Adjusted  Labor     Labor          Labor          Labor     Labor          Labor
     Compensa- Employees Salaries+ Benefits       Benefits  Labor     Price     Price     Price     Price          Price -   Price -
     Tion ($)       Wages     ($000)         ($)  Compensa- (original)     (adjusted)     Index     Index          % Change  % Change
               ($000)                   tion ($)  ($)  ($)  (original)     (adjusted)     (original)     (adjusted)

               A    B    B/(A+B)
____________________________________________________________________________________________________________________________________________________________________________________

1985 16991572326    504113                        16991572326    33705.88008    33705.88008         1.00000        1.00000                       

1986 16728435454    482698                        16728435454    34656.11097    34656.11097         1.02819        1.02819   2.78018        2.78018        

1987 16978905847    477714                        16978905847    35541.98924    35541.98924         1.05447        1.05447   2.52407        2.52407             

1988 17030359791    466827    15033849  3636033   0.19475   0    17030359791    36481.09426         36481.09426    1.08234   1.08234        2.60794        2.60794        

1989 16910850694    461149    14977589  3669768   0.19680   0    16910850694    36671.12082         36671.12082    1.08797   1.08797        0.51954        0.51954        

1990 17586868921    443105    15230268  3768099   0.19834   0    17586868921    39690.07102         39690.07102    1.17754   1.17754        7.91115        7.91115        

1991 17186211200    414457    15038534  4537703   0.23180   622455600 16563755600    41466.81369    39964.95559    1.23025   1.18570        4.37924        0.69019

1992 17160988000    411167    14976159  4920448   0.24730   941126600 16219861400    41737.26977    39448.35408    1.23828   1.17037        0.65011        -1.30106       

1993 17956438000    395639    15479969  5918883   0.27660   1639112600     16317325400    45385.91494    41242.96493         1.34653        1.22361        8.38073   4.44882        

1994 17154284000    367196    15085400  6539928   0.30242   2214862400     14939421600    46716.96859    40685.14254         1.38602        1.20706        2.89056   -1.36176       

1995 16203522000    346843    15088974  5677574   0.27340   1524264400     14679257600    46717.16598    42322.48481         1.38602        1.25564        0.00042   3.94555        

1996 18457448000    338040    15337179  5140712   0.25104   1045133800     17412314200    54601.37262    51509.62667         1.61994        1.52821        15.59473  19.64502       

1997 17451673000    338177    15358125  4395933   0.22253   445121400 17006551600    51605.14464    50288.90670    1.53104   1.49199        -5.64377       -2.39842       

1998 18262990000    345317    15302883  4263993   0.21792   350617800 17912372200    52887.60762    51872.25709    1.56909   1.53897        2.45477        3.09996        
____________________________________________________________________________________________________________________________________________________________________________________

Source:  Federal Communications Commission, Statistics of Communication Common Carriers [various years] and ARMIS Reports 43-02, Table 1.B.  
Table B-6.  Capital Stock Adjustments and the Average Rate of Depreciation - 1985-1998
                 (Dollar amounts shown in 000)
______________________________________________________________________________________________________________________________________________________________
___

Year TPIS.BOY       Capital        TPIS.EOY       Capital        Adjustment     Adjusted  Adjusted       Depreciation        Adjusted
               Additions                Retires        Factor         Capital   TPIS.EOY            Accruals                 Depreciation 
                                                       Additions                     Rate

     A         B         C         D=A+B-C        E         F=B*E     G+A+F-D        H              I=H/((A+G)/2)
______________________________________________________________________________________________________________________________________________________________
___

1985 138879365 15001998       149061793 4819570        0.888          13321774  147381569 10241376       7.15527

1986 149061793 14842725       159010189 4894329        0.888          13180340  157347804 11826961       7.71971

1987 159010189 14138370       168505114 4643445        0.888          12554873  166921617 13311655       8.16837

1988 168505114 14284742       175860216 6929640        1         14284742  175860216 13134992            7.62852
     
1989 175860216 13283569       182978381 6165404        1         13283569  182978381 13420810            7.48014

1990 182978381 14476334       187168695 10286020       1         14476334  187168695 13439933            7.26194

1991 187168695 14527049       192034545 9661199        1         14527049  192034545 13200593            6.96228

1992 192034545 14611866       196411915 10234496       1         14611866  196411915 13337581            6.86714

1993 196411915 14860116       203082418 8189613        1         14860116  203082418 14032782            7.02527

1994 203082418 14717999       209325562 8474855        1         14717999  209325562 14863196            7.20801

1995 209325562 15374568       217430207 7269923        1         15374568  217430207 15358553            7.19782

1996 217430207 18026150       227317120 8139237        1         18026150  227317120 16252281            7.30855

1997 227317120 18253199       236896179 8674140        1         18253199  236896179 16667034            7.18077

1998 236896179 18553791       248970288 6479682        1         18553791  248970288 17154619            7.06145

                                                                      avg1(85-98)    7.30180
                                                                      var2(85-98)    0.11142
______________________________________________________________________________________________________________________________________________________________
___

1 avg denotes the arithmetic mean of the series.
2 var denotes the variance of the series.
Source:  FCC Form M
Table B-7.  Quantity of Capital for 1985-1998 and the Imputed Cost of Capital for 1991
                 (Dollar amounts shown in 000)

_____________________________________________________________________________________________________________________

Year Benchmark Adjusted       BEA       Capital        Capital   Property       Imputed
     Capital        Capital        Composite      Stock          Stock     Income         Cost of
     Stock          Additions      Asset Price    Quantity       Quantity  /w Depreciation          Capital
                         Index                    Index     
_____________________________________________________________________________________________________________________
          
1984                               103903095 

1985 109602959 13321774       1         109602959 1    23445593794    

1986           13180340       1.01048        114643584 1.04599   26792578943         

1987           12554873       1.02734        118493306 1.08111   27701751800         

1988           14284742       1.03047        123703569 1.12865   26866209000         

1989           13283569       1.07018        127083465 1.15949   25845853000         

1990           14476334       1.08973        131088425 1.19603   25584541000         

1991           14527049       1.10222        134696416 1.22895   24641357000    0.18798             

1992           14611866       1.10830        138045138 1.2595    26477135000         

1993           14860116       1.11231        141325020 1.28943   26914823000         

1994           14717999       1.11766        144174285 1.31542   26366385000         

1995           15374568       1.11481        147438176 1.3452    27166096000    

1996           18026150       1.11862        152787122 1.39401   30414808000    

1997           18253199       1.11764        157962763 1.44123   30679731000    

1998           18553791       1.11769        163028757 1.48745   33830949286    
_____________________________________________________________________________________________________________________

Source:  Table B-6 and National the Income and Product Accounts compiled by the Bureau of Economic Analysis of the U.S. Department of Commerce
Table B-8.  Cost of Capital - 1985-1998

_____________________________________________________________

Year      Moody's        Imputed        Competitive
          Baa Corporate       Competitive         Cost of
          Bond Rate (%)  Cost of             Capital
                         Capital ($)              Index
______________________________________________________________

1985      12.72               0.21717        1.00000

1986      10.39               0.19387        0.89271

1987      10.58               0.19577        0.90146

1988      10.83               0.19827        0.91297

1989      10.18               0.19177        0.88304

1990      10.36               0.19357        0.89133

1991      9.8            0.18797        0.86554

1992      8.98           0.17977        0.82778

1993      7.93           0.16927        0.77944

1994      8.62           0.17617        0.81121

1995      8.2            0.17197        0.79187

1996      8.05           0.17047        0.78496

1997      7.86           0.16857        0.77621

1998      7.22           0.16217        0.74674
_____________________________________________________________

Source:  Moody's Baa Corporate Bond Rate is from Table B-73 of the 
Economic Report of the President- 1999, U.S. Government Printing 
Office, Washington, DC, 1999.
Table B-9.  Materials Input Quantity - 1985-1998

_________________________________________________________________________________________________________

Year Materials Adjusted  Depreciation   Adjusted  Materials Materials Materials
     Price          Total          and       Employee  Expense   Quantity  Quantity
     Index          Operating Amortization   Compensation   ($)                 Index
               Expense ($)    Expense ($)    ($)  

     A         B         C         D         E=B-C-D   F=E/A          
_________________________________________________________________________________________________________

1985 1.00000        40609705224    10024710656    16991572326    13593422242    13593422242         1

1986 1.03135        40262200069    11592001248    16728435454    11941763367    11578768961         0.85179

1987 1.05353        42242744320    13316999560    16978905847    11946838913    11339818432         0.83421

1988 1.08639        45494083588    13646937000    17030359791    14816786797    13638527159         1.00332

1989 1.12623        47773003404    13860101000    16910850694    17002051710    15096429424         1.11057

1990 1.17203        49160848820    13931515000    17586868921    17642464899    15052912382         1.10737

1991 1.20494        50278593400    13499778000    16563755600    20215059800    16776818597         1.23419

1992 1.23480        48875289820    13822882000    16219861400    18832546420    15251495319         1.12198

1993 1.25535        49744107201    13244514000    16317325400    20182267801    16077004661         1.18270

1994 1.29144        53129310801    15068058000    14939421600    23121831201    17903914391         1.31710

1995 1.32167        54381863101    15556284000    14679257600    24146321501    18269554050         1.34400

1996 1.36140        54780054849    16377242000    17412314200    20990498649    15418318385         1.13425

1997 1.39550        57364316191    16758832000    17006551600    23598932591    16910736361         1.24404

1998 1.43074        58408447446    17646242000    17912372200    22849833246    15970695654         1.17488
________________________________________________________________________________________________________

Source:  Materials price index comes from the Input/Output Tables compiled by the Bureau of Economic Analysis of the 
U.S. Department of Commerce, depreciation and amortization expense data come from the Statistics of Communication 
Common Carriers, and the other values are derived as detailed in the text.
Table B-10.  Factor of Production Shares of Total Payments - 1985-1998

_____________________________________________________________________________________________________________

Year Adjusted       Property       Adjusted       Adjusted       Labor     Capital   Materials
     Labor          Income         Materials      Total          Share     Share     Share
     Compensa- /w Deprecia-   Payment ($)    Factor
     tion ($)       tion ($)                 Payments ($)
_____________________________________________________________________________________________________________

1985 16991572326    22565165047    13593422242    53150159615    0.31969   0.42455   0.25576

1986 16728435454    21249284636    11941763367    49919483458    0.33511   0.42567   0.23922

1987 16978905847    22444359210    11946838913    51370103970    0.33052   0.43691   0.23256

1988 17030359791    23494272047    14816786797    55341418635    0.30773   0.42453   0.26773

1989 16910850694    23723264293    17002051710    57636166697    0.29341   0.41160   0.29499

1990 17586868921    24600194384    17642464899    59829528203    0.29395   0.41117   0.29488

1991 16563755600    24641359753    20215059800    61420175153    0.26968   0.40119   0.32913

1992 16219861400    24215061717    18832546420    59267469536    0.27367   0.40857   0.31776

1993 16317325400    23367604541    20182267801    59867197742    0.27256   0.39032   0.33712

1994 14939421600    24897949618    23121831201    62959202419    0.23729   0.39546   0.36725

1995 14679257600    24794387029    24146321501    63619966130    0.23073   0.38973   0.37954

1996 17412314200    25134537868    20990498649    63537350717    0.27405   0.39559   0.33036

1997 17006551600    25756104311    23598932591    66361588503    0.25627   0.38812   0.35561

1998 17912372200    25617626841    22849833246    66379832287    0.26985   0.38592   0.34423
_____________________________________________________________________________________________________________

Source:  Federal Communications Commission, Statistics of Communication Common Carriers [various years] with adjustments as described in the text.

Table B-11.  Total LEC Input Quantity Index - 1985-1998

__________________________________________________________________________________________________________________________________________________

Year Labor          Capital        Materials           Labor     Capital   Materials      Laspeyres Paasche        Fisher    Fisher         Growth
     Share          Share          Share          Quantity  Quantity  Quantity       Input          Input          Ideal     Ideal          Rate (%)
                                        Index     Index          Quantity  Quantity  Input          Chained
                                                       Index     Index     Quantity  Input
                                                                 Index     Quantity
                                                                      Index     
__________________________________________________________________________________________________________________________________________________

1985 0.31969        0.42455        0.25576        504113    1    1         1    1    1    1         

1986 0.33511        0.42567        0.23922        482698    1.04599   0.85179        0.96804        0.96360        0.96582   0.96582        -3.47804

1987 0.33052        0.43691        0.23256        477714    1.08111   0.83421        1.00590        1.00588        1.00589   0.97150        0.58715

1988 0.30773        0.42453        0.26773        466827    1.12865   1.00332        1.05882        1.05913        1.05898   1.02880        5.73029

1989 0.29341        0.41160        0.29499        461149    1.15949   1.11057        1.03648        1.03715        1.03681   1.06668        3.61531

1990 0.29395        0.41117        0.29488        443105    1.19603   1.10737        1.00064        0.99974        1.00019   1.06688        0.01899

1991 0.26968        0.40119        0.32913        414457    1.22895   1.23419        1.02608        1.02662        1.02635   1.09499        2.60077

1992 0.27367        0.40857        0.31776        411167    1.25950   1.12198        0.97791        0.97651        0.97721   1.07003        -2.30554

1993 0.27256        0.39032        0.33712        395639    1.28943   1.18270        1.01657        1.01592        1.01625   1.08742        1.61153

1994 0.23729        0.39546        0.36725        367196    1.31542   1.31710        1.02658        1.02765        1.02712   1.11690        2.67569

1995 0.23073        0.38973        0.37954        346843    1.34520   1.34400        1.00330        1.00269        1.00300   1.12025        0.29912

1996 0.27405        0.39559        0.33036        338040    1.39401   1.13425        0.94905        0.94842        0.94874   1.06282        -5.26234

1997 0.25627        0.38812        0.35561        338177    1.44123   1.24404        1.04549        1.04625        1.04587   1.11157        4.48479

1998 0.26985        0.38592        0.34423        345317    1.48745   1.17488        0.99809        0.99732        0.99770   1.10902        -0.22988
__________________________________________________________________________________________________________________________________________________

Source:  Table B-10, Federal Communications Commission, Statistics of Communication Common Carriers [various years], Table B-7, and Table B-9.
Table B-12.  Summary of the Components of LECs' Price Cap X-Factor (excluding the Consumer Productivity Dividend) - 1985-1998

______________________________________________________________________________________________________________________________________________________________
___

Year U.S.      LECs'     LECs'          LECs'          TFP       U.S.      LECs'          Input          X-factor            Previous
     Nonfarm   Output    Input          TFP       Differential   Nonfarm        Input               Price                    (%)            X-factor1
     Business  Growth    Growth         Growth         (%)       Business       Price               Differential                  (%)
     Sector    Rate (%)  Rate (%)       Rate (%)                 Sector         Growth              (%)
     TFP                                     Input          Rate (%)
     Growth                                       Price
     Rate (%)                                     Growth
                                             Rate (%)

     A    B    C         D = B-C        E = D-A        F         G         H = F-G        I = E+H        J
______________________________________________________________________________________________________________________________________________________________
___

1986 1.10166   3.19590   -3.47804       6.67394        5.57228        2.80830        -3.15211            5.96041             11.53269            -0.5

1987 -0.39920  3.77146   0.58715        3.18431        3.58351        2.53178        1.92376             0.60802             4.19153             5.0

1988 0.29955   6.51202   5.73029        0.78173        0.48218        3.72958        2.39282             1.33676             1.81894             5.0

1989 0.19920   4.38736   3.61531        0.77206        0.57285        3.03629        -1.52894            4.56522             5.13808             7.9

1990 -0.69895  4.76646   0.01899        4.74748        5.44643        3.30913        3.88344             -0.57432            4.87211             8.8

1991 -1.41274  2.60725   2.60077        0.00647        1.41921        2.05824        -0.13437            2.19261             3.61182             5.8

1992 1.61294   3.51159   -2.30554       5.81713        4.20419        2.88104        -1.36727            4.24830             8.45250             3.4

1993 0.09995   5.83651   1.61153        4.22497        4.12502        3.71664        -0.64768            4.36432             8.48934             4.7

1994 0.39880   5.41052   2.67569        2.73483        2.33603        3.50341        2.22171             1.28171             3.61774             5.4

1995 0.29806   5.98969   0.29912        5.69056        5.39250        1.96268        0.84015             1.12253             6.51503             6.8

1996 1.47713   8.21568   -5.26234       13.47802       12.00089       1.38258        5.65415             -4.27157            7.72932        

1997 0.39024   9.46127   4.48479        4.97648        4.58623        1.89887        -0.22680            2.125670            6.71190        

1998 0.59259   5.37568   -0.22988       5.60556        5.01297        0.71810        0.18976             0.52834             5.54131        

                         avg2(86-98)    4.21033                            1.80677        6.01710   
                         var3(86-98)    8.08404                            6.48203        6.22591

                         avg(91-98)          4.88463                            1.44899             6.33362
                         var(91-98)          8.81863                            6.38164             3.33409        

                         avg(86-95)          3.31342                            2.51056             5.82398                  5.23
                         var(86-95)          3.55698                            4.06310             7.69230                  5.93

                         avg(91-95)          3.49539                            2.64189             6.13729                  5.22
                         var(91-95)          2.03050                            1.98155             4.75223                  1.29
______________________________________________________________________________________________________________________________________________________________
___

1 X-factor reported in the 1997 Price Cap Review Order.

2 avg denotes the arithmetic mean of the series.

3 var denotes the variance of the series.

Source:  Bureau of Labor Statistics' Multifactor Productivity Table 2: Private Nonfarm Business: Productivity and Related Indexes (annual and quarterly tables), Table B-4, Table B-11, and Table B-13.

Table B-13.  Total LEC Input Price Index - 1985-1998

__________________________________________________________________________________________________________________________________________________

Year Labor          Capital        Materials           Labor     Capital   Materials      Laspeyres Paasche        Fisher    Fisher         Growth
     Share          Share          Share          Price     Price     Price          Input          Input          Ideal     Ideal          Rate (%)
                                   Index     Index     Index          Price     Price     Input     Chained
                                                       Index     Index     Price     Input
                                                                 Index     Price
                                                                      Index     
__________________________________________________________________________________________________________________________________________________

1985 0.31969        0.42455        0.25576        1    1    1         1    1    1    1    

1986 0.33511        0.42567        0.23922        1.02819   0.89271   1.03135        0.97148        0.96647        0.96897   0.96897        -3.15211

1987 0.33052        0.43691        0.23256        1.05447   0.90146   1.05353        1.01788        1.01768        1.01778   0.98620        1.76258

1988 0.30773        0.42453        0.26773        1.08234   0.91297   1.08639        1.02157        1.02184        1.02170   1.00760        2.14711

1989 0.29341        0.41160        0.29499        1.08797   0.88304   1.12623        0.99750        0.99801        0.99776   1.00534        -0.22468

1990 0.29395        0.41117        0.29488        1.17754   0.89133   1.17203        1.04001        1.03918        1.03960   1.04515        3.88344

1991 0.26968        0.40119        0.32913        1.18570   0.86555   1.20494        0.99842        0.99889        0.99866   1.04375        -0.13437

1992 0.27367        0.40857        0.31776        1.17037   0.82779   1.23480        0.98717        0.98567        0.98642   1.02958        -1.36727

1993 0.27256        0.39032        0.33712        1.22361   0.77944   1.25535        0.99388        0.99321        0.99354   1.02293        -0.64768

1994 0.23729        0.39546        0.36725        1.20706   0.81121   1.29144        1.02192        1.02302        1.02247   1.04591        2.22171

1995 0.23073        0.38973        0.37954        1.25564   0.79187   1.32167        1.00872        1.00816        1.00844   1.05473        0.84015

1996 0.27405        0.39559        0.33036        1.52821   0.78497   1.36140        1.05810        1.05824        1.05817   1.11609        5.65415

1997 0.25627        0.38812        0.35561        1.49199   0.77622   1.39550        0.99737        0.99810        0.99773   1.11356        -0.22680

1998 0.26985        0.38592        0.34423        1.53897   0.74675   1.43074        1.00231        1.00149        1.00190   1.11568        0.18976
__________________________________________________________________________________________________________________________________________________

Source:  Table B-10, Table B-5, Table B-8, and Table B-9.

                                Appendix C

                   The Staff Imputed X Study
                                
                        Florence Setzer
                                
     This study estimates an X-factor for LEC price caps by solving for the past X-factor that would
have allowed price cap LECs on average to achieve the return they would have had if they had been
subject to competitive market forces.  The study is based on the reported interstate operating revenues,
operating expenses, and average net investment of price cap LECs and on an estimate of the elasticity
of demand for interstate telephone services.  The calculations show the effects on the revenues and
operating income of price cap LECs, as well as on the welfare of consumers of telecommunications
services, of setting the X-factor at a level producing a competitive return.  These calculations assume
that the hypothetical X-factor remained in effect from the inception of price caps in 1991 through the
end of the period.  An adjustment is made for the change in the quantity of output sold as a response
to changes in price.  In order to examine trends over time in the rate of productivity growth, the study
also calculates for individual years the X-factor that would have been necessary to prevent the rate of
return from rising above that of the previous year.  For comparison with the 1997 and 1999 TFP
Studies, calculations were also made assuming no demand response and using data for the RBOCs
only, rather than for all price cap LECs.  Calculations were performed for 1995, for comparison with
the 1997 TFP study, and for 1998, to make use of the most recent data available.

     The effects of a hypothetical X-factor are estimated by first calculating the change in price,
output, and revenue that would have occurred in each year if that X-factor had been in effect.  The
calculation of these effects for an X-factor of 6.5 percent, the X-factor (including CPD) chosen in the
1997 Price Cap Review Order, is shown in Table C-1.  Separate calculations are made for some carriers
because not all carriers chose the same X-factor during the period of sharing, so that the effects of moving
to a new X-factor differ among carriers.  The second column of Table C-1 shows the actual X-factor, taken
from Tariff Review Plan ("TRP") data submitted by the carriers.  A minimum X-factor of 4.0 percent is
used because that level was imposed retroactively by the Commission on carriers that chose lower X-
factors.  The difference between the actual and hypothetical X-factors is shown in the third column.  The
fourth column is an index of the cumulative price change over time resulting from the change in the X-
factor.  The fifth column shows the percentage change in price in each year relative to the actual price in
that year resulting from the cumulative effect of the changed X-factor.  If the 6.5 percent X-factor had been
in effect for the entire price cap period, prices would have been between 10.7 percent and 11.79 percent
lower than they actually were in 1998.    

     The last two columns of Table C-1 show the change in output and revenue resulting from a given
X-factor change.  Because X-factors change on July 1, the beginning of the tariff year, an average of the
prices, both actual and hypothetical, in adjacent tariff years is used in the calculation.  The percentage
change in output was calculated by assuming that a 1 percent reduction in price results in an increase in
output purchased of 0.2 percent.  This assumes that all reductions in access prices are passed on to
interstate end-user customers.  The percentage change in revenue is calculated taking account of both the
price change and the output change. 

     The effects of changes in the X-factor are calculated separately for each carrier using data on
operating revenue, operating expense, and average net investment reported by the carriers on FCC Form
492-A.  These data are shown in Table C-2 for 1995 and 1998.  Aggregate results are shown in Table C-3. 
For each carrier, adjusted operating revenue under the hypothetical X-factor is calculated by adjusting
actual revenue for the change in price and level of output, as reflected in the final column of Table C-1. 
Operating expense is adjusted for the change in federal and state taxes, which together are assumed to be
39 percent of revenues.  We have no evidence of the effects of an increase in output on costs, but short-run
marginal costs are generally believed to be very low.  Consequently we assume that costs other than taxes
are unchanged by the increase in output, and make no further adjustments in operating expense.

     Adjusted operating expense is subtracted from adjusted operating revenue to give after-tax profits,
which are reported as adjusted operating income.  Adjusted operating income and average net investment,
which is assumed to be unchanged by the increase in output, are summed for all companies.  An average
adjusted rate of return is calculated for the industry as the ratio of adjusted operating income to average net
investment for all firms in the industry.  As shown in the first line of Table C-3, the average rate of return
in 1998 if the X-factor of 6.5 percent had been in effect since 1991 would have been 11.88 percent.  Thus
an X-factor of 6.5 percent for the entire period of price caps would still have allowed carriers on average to
earn returns above the target rate in 1998.

     The benefits to consumers of the rate reduction resulting from the given X-factor are shown by the
change in consumer surplus (the final column in Table C-3).  The calculation of consumer surplus assumes
that IXCs pass on the entire reduction in access prices to end-user customers.  The change in consumer
surplus consists of two parts: the benefit accruing from the lower price of the amount of output originally
purchased, and the benefit accruing from the additional output purchased because of the reduction in price,
which would have been forgone had the price remained at the original level.  Because of the increase in
output resulting from the reduction in price, the increase in consumer welfare is larger than the reduction in
LECs' revenues.  If the 6.5 percent X-factor had been in effect for the whole period beginning in 1991,
benefits to consumers from lower prices in 1998 would have been $2.95 billion.

     The second and third lines of Table C-3 show the calculation of the X-factor required to produce a
competitive rate of return in 1995 and 1998.  The background calculations of percentage changes in price,
output, and revenue have not been presented because these calculations can easily be replicated.  The
required rate of return for each year was found by adjusting the rate of return approved by the Commission
at the inception of price caps by the basis-point change in bond rates over the period to reflect the action of
competitive capital markets.  The precise level of the X-factor required to reach the target rate of return in
each case was found by trial and error.  The estimated X-factor using data through 1995 was 7.10 percent;
using data through 1998 the required X-factor was 7.71 percent.

     For comparison with the TFP studies, the calculations were repeated assuming no demand
stimulation and using data only for the RBOCs.  The results are shown in the last two lines of Table C-3. 
These calculations show required X-factors of 6.61 percent in 1995 and 6.97 percent in 1998.  Note that
these numbers are lower than those using data for all price cap LECs and including a demand adjustment,
but somewhat higher than those for the same time periods in the 1999 staff TFP study.  The data on which
they are based have not been adjusted for accounting biases in the data as have the TFP data.  On the other
hand, they are based on interstate services only, so they more closely reflect price cap services.  This result
suggests that more accurate data and assumptions would increase the TFP estimates.   

     Table C-4 shows the X-factor required in each year to maintain the average rate of return at the
level of the previous year.  This single-year X-factor was calculated for each year from 1992, the first full
year of price caps, through 1998.  To make this calculation, operating revenues in each year were adjusted
to account for the effects of sharing and low-end adjustments.  This calculation resulted in an estimate of
the revenues that would have resulted from the action of a given X-factor in the absence of sharing and
low-end adjustments.  Operating expenses were correspondingly adjusted for the change in taxes.  In
addition, for years through 1994, the actual X-factor in effect for each carrier at the time, rather than the
retroactive X-factor imposed later, was used.  The X-factor calculation was performed as described above,
except that changes in output and revenue were based on the difference between the actual and hypothetical
X-factors in a given year rather than on the cumulative price level change from the beginning of the period. 
As Table C-4 shows, the X-factor required to maintain the rate of return of the previous year trended
upward, though not monotonically, from a low of 5.50 percent in 1992 to a high of 8.51 percent in 1998. 
This appears to reflect an increase in the rate of productivity growth over the period of price caps, and
suggests that an X-factor based on an average over the period is likely to underestimate the rate of
productivity growth. 
                           Table C-1
                              
  HISTORIC PRICE, OUTPUT, AND REVENUE CHANGES
  RESULTING FROM HYPOTHETICAL X-FACTOR
  
  Hypothetical X-factor         6.50%     
  End user price elasticity     -0.5 
  Access price elasticity* -0.2
  
  
                                                    CALENDA
                                                          R
                                                       YEAR
                                                           
                                                     Actual
                                                 X-Factor**
                                                           
                                                   X-Factor
                                                     Change
                                                 Cumulative
  Price
  Index
  
  Price
  Change
  
  Output
  Change
  
  Revenue
  Change
  
                              
  Ameritech, Bell Atlantic, NYNEX, SBC, GTE, others***
  
  
  1991
  4.00%
  2.50%
  0.975
  -2.50%
  0.25%
  -1.13%
  
  
  1992
  4.00%
  2.50%
  0.951
  -4.94%
  0.74%
  -3.00%
  
  
  1993
  4.00%
  2.50%
  0.927
  -7.31%
  1.23%
  -4.98%
  
  
  1994
  4.00%
  2.50%
  0.904
  -9.63%
  1.69%
  -6.92%
  
  
  1995
  5.30%
  1.20%
  0.893
  -10.72%
  2.03%
  -8.35%
  
  
  1996
  5.30%
  1.20%
  0.882
  -11.79%
  2.25%
  -9.25%
  
  
  1997
  6.50%
  0.00%
  0.882
  -11.79%
  2.36%
  -9.71%
  
  
  1998
  6.50%
  0.00%
  0.882
  -11.79%
  2.36%
  -9.71%
  
  
  BellSouth
  
  
  1991
  4.00%
  2.50%
  0.975
  -2.50%
  0.25%
  -1.13%
  
  
  1992
  4.30%
  2.20%
  0.954
  -4.65%
  0.71%
  -2.88%
  
  
  1993
  4.00%
  2.50%
  0.930
  -7.03%
  1.17%
  -4.74%
  
  
  1994
  4.00%
  2.50%
  0.906
  -9.35%
  1.64%
  -6.69%
  
  
  1995
  5.30%
  1.20%
  0.896
  -10.44%
  1.98%
  -8.11%
  
  
  1996
  5.30%
  1.20%
  0.885
  -11.52%
  2.20%
  -9.02%
  
  
  1997
  6.50%
  0.00%
  0.885
  -11.52%
  2.30%
  -9.48%
  
  
  1998
  6.50%
  0.00%
  0.885
  -11.52%
  2.30%
  -9.48%
  
  
  Pacific Telesis
  
  
  1991
  4.30%
  2.20%
  0.978
  -2.20%
  0.22%
  -0.99%
  
  
  1992
  4.30%
  2.20%
  0.956
  -4.35%
  0.66%
  -2.64%
  
  
  1993
  4.00%
  2.50%
  0.933
  -6.74%
  1.11%
  -4.50%
  
  
  1994
  4.00%
  2.50%
  0.909
  -9.07%
  1.58%
  -6.45%
  
  
  1995
  5.30%
  1.20%
  0.898
  -10.17%
  1.92%
  -7.88%
  
  
  1996
  5.30%
  1.20%
  0.888
  -11.24%
  2.14%
  -8.79%
  
  
  1997
  6.50%
  0.00%
  0.888
  -11.24%
  2.25%
  -9.25%
  
  
  1998
  6.50%
  0.00%
  0.888
  -11.24%
  2.25%
  -9.25%
  
  
  U S West
  
  
  1991
  4.30%
  2.20%
  0.978
  -2.20%
  0.22%
  -0.99%
  
  
  1992
  4.30%
  2.20%
  0.956
  -4.35%
  0.66%
  -2.64%
  
  
  1993
  4.30%
  2.20%
  0.935
  -6.46%
  1.08%
  -4.38%
  
  
  1994
  4.30%
  2.20%
  0.915
  -8.51%
  1.50%
  -6.10%
  
  
  1995
  5.30%
  1.20%
  0.904
  -9.61%
  1.81%
  -7.41%
  
  
  1996
  5.30%
  1.20%
  0.893
  -10.70%
  2.03%
  -8.33%
  
  
  1997
  6.50%
  0.00%
  0.893
  -10.70%
  2.14%
  -8.79%
  
  
  1998
  6.50%
  0.00%
  0.893
  -10.70%
  2.14%
  -8.79%
  
  
  Sprint
  
  
  1991
  4.00%
  2.50%
  0.975
  -2.50%
  0.25%
  -1.13%
  
  
  1992
  4.00%
  2.50%
  0.951
  -4.94%
  0.74%
  -3.00%
  
  
  1993
  4.00%
  2.50%
  0.927
  -7.31%
  1.23%
  -4.98%
  
  
  1994
  4.07%
  2.43%
  0.904
  -9.56%
  1.69%
  -6.89%
  
  
  1995
  5.30%
  1.20%
  0.894
  -10.65%
  2.02%
  -8.29%
  
  
  1996
  5.30%
  1.20%
  0.883
  -11.72%
  2.24%
  -9.20%
  
  
  1997
  6.50%
  0.00%
  0.883
  -11.72%
  2.34%
  -9.65%
  
  
  1998
  6.50%
  0.00%
  0.883
  -11.72%
  2.34%
  -9.65%
  
  
  Source:  See text
  *    Assumes access = 40% of IXC costs, and all price reductions passed on to end user
  customers.
  **   In effect 7/1 of each year
  ***  Assumes "others" chose lowest X-factor 1991-1994
                              
                                                           Table C-2
                                
FINANCIAL DATA
                       FOR PRICE CAP LECS
                                

Price
Cap
Company
Operating
Revenue*
(000)
Operating
Expense
(000)
Average Net
Investment
(000)

                                
1995


Ameritech
$2,314,807
$1,795,638
$3,093,308


Bell Atlantic
$6,177,664
$5,121,678
$8,122,916


BellSouth
$3,341,690
$2,613,050
$4,618,137


Pacific Telesis
$1,742,343
$1,346,448
$2,505,561


SBC
$2,091,805
$1,646,644
$3,327,268


U S West
$2,416,832
$1,954,164
$3,855,836


GTE
$2,729,239
$2,195,426
$4,422,624


Sprint
$1,028,598
$778,826
$1,335,617


Others
$498,379
$403,046
$728,670








All
$22,341,357
$17,854,920
$32,009,937



1998


Ameritech
$2,553,594
$1,918,674
$2,794,765


Bell Atlantic
$6,453,096
$5,378,333
$8,380,851


BellSouth
$3,794,553
$2,842,101
$4,578,390


Pacific Telesis
$2,027,231
$1,639,515
$2,645,273


SBC
$2,359,902
$2,022,258
$3,407,300


U S West
$2,670,048
$2,089,034
$3,513,985


GTE
$3,222,880
$2,354,224
$4,432,509


Sprint
$1,130,092
$857,222
$1,400,433


Others
$939,899
$739,759
$1,241,895








All
$25,151,295
$19,841,120
$32,395,401



Source:  FCC Form 492-A

*  Interstate Revenue

                                        Table C-3
                                            
                   X-FACTOR REQUIRED FOR COMPETITIVE AGGREGATE RETURN
                                            
                                            
                                            
                                            
                                            
                                          Year
                                            
                                        X-Factor
                                          Since
                                          1991
                                                                                  Actual
Operating
Revenue*
(000)
                                                                                Adjusted
Operating
Revenue
(000)
                                                                                  Actual
Operating
Expense
(000)
                                                                                Adjusted
Operating
Expense**
(000)
                                                                                  Actual
Operating
Income
(000)
                                                                                Adjusted
Operating
Income
(000)

                                                                             Average Net
                                                                              Investment
                                                                                   (000)
                                                                                        
                                                                                  Actual
                                                                                 Rate of
                                                                                    Return
                                                                                        
                                                                             Competitive
                                                                                 Rate of
                                                                                  Return
                                                                               Change in
                                                                                Consumer
                                                                              Surplus***
                                                                                   (000)
                                                                                        

All Price Cap LECs, Demand Elasticity = -0.2


1998 with
  1997 X****
6.50%
$25,151,295
$22,753,012
$19,841,120
$18,905,790
$5,310,176
$3,847,222
$32,395,401
16.39%
11.88%
$2,947,187
















1995
7.10%
$22,341,357
$20,051,518
$17,854,920
$16,961,883
$4,486,437
$3,089,635
$32,009,937
14.02%
9.65%
$2,810,519
















1998
7.71%
$25,151,295
$21,053,989
$19,841,120
$18,243,171
$5,310,176
$2,810,819
$32,395,401
16.39%
8.68%
$4,979,309


RBOCs Only, No Demand Response


1995
6.61%
$18,085,141
$16,208,672
$14,477,622
$13,745,799
$3,607,519
$2,462,873
$25,523,026
14.13%
9.65%
$1,876,469
















1998
6.97%
$19,858,424
$16,948,374
$15,889,915
$14,754,996
$3,968,510
$2,193,379
$25,320,564
15.67%
8.66%
$2,910,050


Source:  See text.

*    Interstate revenue.
**   Assumes federal + state tax rate = 39 percent.
***  Assumes all price reductions passed on to end user customers.
**** X-factor chosen in 1997 Price Cap Review Order.
                                                                        Table C-4
                                
                 X-FACTOR REQUIRED TO MAINTAIN 
                    UNCHANGED RATE OF RETURN
                       FROM PREVIOUS YEAR


                    Year      X-Factor
                                  (%)

                    1992              5.50
                    1993              5.94
                    1994              5.51
                    1995              6.83
                    1996              7.90
                    1997              6.57
                    1998              8.51


          Source:  See text.