*Pages 1--49 from  C:\Pdf2Text\Ready4Text_in\pdf\31391.pdf*
 Federal  Communications  Commission  Office  of  Strategic  Planning  and  Policy  Analysis 
 445  12th  Street,  SW  Washington,  DC  20554 


 OSP  Working  Paper  Series 
 40  Dynamic  Pricing  and  Investment  from  Static  Proxy  Models 


 September  2003 
 David  M.  Mandy  William  W.  Sharkey 
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 The  FCC  Office  of  Strategic  Planning  and  Policy  Analysis  Working  Paper  Series  presents  staff  analysis  and  research  in  various  states.  These  papers  are  intended  to  stimulate 
 discussion  and  critical  comment  within  the  FCC,  as  well  as  outside  the  agency,  on  issues  in  telecommunications  policy.  Titles  may  include  preliminary  work  and  progress  reports,  as 
 well  as  completed  research.  The  analyses  and  conclusions  in  the  Working  Paper  Series  are  those  of  the  authors  and  do  not  necessarily  reflect  the  views  of  other  members  of  the  Office 
 of  Strategic  Planning  and  Policy  Analysis,  other  Commission  staff,  or  the  Commission  itself.  Given  the  preliminary  character  of  some  titles,  it  is  advisable  to  check  with  authors 
 before  quoting  or  referencing  these  Working  Papers  in  other  publications.  This  document  is  available  on  the  FCC's  World  Wide  Web  site  at  http://  www.  fcc.  gov/  osp/.  The  inside  back 
 cover  contains  a  partial  list  of  previous  titles. 
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 Dynamic  Pricing  and  Investment  from  Static  Proxy  Models   
 David  M.  Mandy  *  William  W.  Sharkey  ** 
 Abstract 
 This  paper  evaluates  the  use  of  static  cost  proxy  models  in  setting  forward-looking  prices,  such  as  the  prices  set  according  to  the  FCCs  TELRIC  methodology.  First, 
 it  compares  the  time  paths  of  prices  and  depreciation  under  traditional  regulatory  accounting  with  the  prices  and  depreciation  implied  by  various  versions  of  TELRIC. 
 When  TELRIC  prices  are  recomputed  at  intervals  shorter  than  asset  lives,  the  firm  will  generally  not  earn  the  target  rate  of  return.  In  these  cases,  a  correction  factor  must  be 
 applied  to  the  TELRIC  price  path  in  order  for  revenues  to  exactly  recover  investment  cost,  including  the  target  rate  of  return.  Next,  the  paper  considers  a  firms  cost 
 minimizing  investment  decisions  under  two  different  assumptions  about  asset  obsolescence.  In  both  scenarios,  cost  minimizing  investment  paths  and  implied  utilization 
 rates  for  the  firms  assets  are  derived  under  a  variety  of  assumptions  about  the  relevant  input  parameters.  Some  implications  for  TELRIC  pricing  are  then  derived. 


   The  authors  acknowledge  helpful  discussions  with  Jay  Atkinson  during  preparation  of  this  paper.  We  also 
 benefited  from  the  comments  of  Simon  Wilkie  and  Donald  Stockdale  on  an  earlier  draft.  The  views  expressed  in  this  paper,  however,  are  those  of  the  authors  alone  and  do  not  necessarily  reflect  the  views  of 


 the  Federal  Communications  Commission,  any  Commissioners,  or  other  staff.  *  Department  of  Economics,  University  of  Missouri,  118  Professional  Building,  Columbia,  MO  65211; 
 MandyD@  missouri.  edu.  **  Office  of  Strategic  Planning  and  Policy  Analysis,  Federal  Communications  Commission,  Washington, 
 D.  C.  20554;  William.  Sharkey@  fcc.  gov. 
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 Dynamic  Pricing  and  Investment  from  Static  Proxy  Models:  Executive  Summary 
 Since  release  of  the  FCCs  Local  Competition  Order,  1  incumbent  local  exchange  providers  have  strongly  objected  both  to  TELRIC  as  a  methodology  and  to  its  specific 
 implementation  by  state  regulatory  commissions.  These  objections  generally  fall  into  three  categories.  First,  incumbent  carriers  have  questioned  the  theoretical  consistency  of 
 the  TELRIC  methodology  itself.  Specifically,  they  have  argued  that,  when  equipment  prices  are  falling  over  time,  periodic  recalculation  of  TELRIC  prices  prevents  them  from 
 recovering  their  investment  costs.  Second,  incumbents  have  criticized  the  way  in  which  state  commissions  have  implemented  TELRIC.  They  argue  either  that  states  have  adopted 
 unrealistic  input  values  or  that  the  cost  models  that  were  adopted  contained  flawed  model  algorithms.  2  Finally,  some  incumbents  have  argued  that  any  forward-  looking  pricing 
 methodology,  including  TELRIC,  in  which  the  computation  of  cost  is  not  based  on  the  incumbents  actual  network  as  a  starting  point,  is  inconsistent  with  the  meaning  of  the 
 1996  Act. 
 This  paper  addresses  aspects  of  each  of  the  above  criticisms.  Specifically,  section  2  addresses  the  argument  that  periodic  recalculation  of  TELRIC  prices  prevents 
 incumbents  from  recovering  the  cost  of  their  investment.  It  shows  that,  if  investment  costs  are  falling  over  time,  and  the  period  between  TELRIC  price  adjustments  is  shorter 
 than  asset  lives,  then  traditional  TELRIC  pricing  will  not  permit  incumbents  to  recover  the  cost  of  their  investment.  Similarly,  when  investment  costs  are  rising,  TELRIC  pricing 
 will  result  in  an  over-  recovery  of  investment  costs.  Section  3  examines  a  carriers  cost  minimizing  investment  plan  in  a  dynamic  environment  with  lumpy  investment  costs. 
 While  not  intended  to  recommend  specific  input  prices  for  cost  models,  this  section  is  directly  relevant  to  the  selection  of  forward-  looking  fill  factors  for  such  models.  As  such, 
 it  may  partially  address  incumbents  arguments  that  state  commissions  have  set  unrealistically  high  fill  factors.  3 


 Dynamic  Pricing  of  an  Already-  Determined  Investment 
 Section  2  is  concerned  with  comparing  alternative  time  paths  of  prices  that  will  allow  a  firm  to  exactly  recover  the  cost  of  network  investments  when  these  costs  are 
 expected  to  change  over  time.  Incumbent  carriers  are  correct  to  point  out  that,  when  TELRIC  prices  are  recomputed  at  periodic  intervals,  particular  care  must  be  exercised  in 
 order  to  ensure  that  the  resulting  prices  are  consistent  with  the  assumptions  made  about  asset  lives  and  the  allowed  rate  of  return.  Indeed,  when  investment  costs  are  falling  over 


 1  Implementation  of  the  Local  Competition  Provisions  in  the  Telecommunications  Act  of  1996,  First  Report 
 and  Order,  11  FCC  Rcd  15499,  15509  (1996).  2  For  example,  incumbents  argue  that  proxy  models  often  assume  an  unrealistic  level  of  sharing  of  the  cost 


 of  structures  (i.  e.  poles  and  underground  conduit  facilities)  with  other  utilities.  It  is  also  argued  that  cost  minimization  procedures  in  proxy  models  assume  an  unattainable  level  of  efficiency  that  no  real  world  firm 
 could  expect  to  emulate.  The  results  of  this  paper  are  relevant  to  the  setting  of  one  input  factor    the  firms  utilization  rate  of  existing  capacity  (also  called  a  fill  factor). 
 3  The  third  criticism  is  also  partially  addressed  at  the  end  of  Section  3.  3. 


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 time  and  TELRIC  price  reviews  are  conducted  at  intervals  shorter  than  expected  asset  lives,  the  firm  will  earn  less  than  its  target  rate  of  return  under  traditional 
 implementations  of  TELRIC.  Specifically,  a  TELRIC  price  is  traditionally  computed  as  a  constant  (or  levelized)  price  that,  over  the  life  of  the  asset,  will  earn  sufficient  revenue  to 
 recover  the  full  cost  of  investment  including  the  target  rate  of  return.  When  TELRIC  prices  are  recomputed  at  intervals  shorter  than  these  asset  lifetimes,  and  investment  costs 
 fall  between  price  reviews,  actual  revenues  will  not  fully  compensate  the  firm.  The  paper  shows,  however,  that  it  is  possible  to  compute  a  correction  factor  based  on  estimates  of 
 the  rate  of  change  of  investment  cost  and  the  expected  time  between  TELRIC  reviews.  Corrected  TELRIC  prices  rise  or  fall  at  the  same  rate  over  time  as  underlying  investment 
 cost,  and  allow  the  firm  to  earn  its  target  rate  of  return  no  matter  how  frequently  price  reviews  are  conducted.  Moreover,  no  ad  hoc  adjustments  of  assumed  asset  lifetimes  or 
 depreciation  schedules  are  needed  to  implement  the  suggested  correction. 
 These  points  may  be  illustrated  in  the  following  diagrams  which  represent  different  price  paths  for  a  hypothetical  investment  of  $100  in  an  asset  that  is  assumed  to 
 have  an  economic  lifetime  of  12  years.  Figure  ES1  compares  price  paths  based  on  traditional  regulatory  accounting  and  levelized  TELRIC  pricing.  Both  paths  assume  an 
 allowed  rate  of  return  of  11.25%,  and  the  traditional  price  path  (adjusted  annually)  assumes  straight  line  depreciation  over  the  12  year  life.  Traditional  prices  fall  even  under 
 straight  line  depreciation  because  price  in  each  period  reflects  operating  expense  +  depreciation  expense  +  capital  cost.  The  first  two  terms  are  constant  by  assumption,  and 
 the  capital  cost  term  declines  over  time  at  the  same  rate  as  the  undepreciated  balance.  The  levelized  TELRIC  price  is  by  definition  constant  over  the  life  of  the  asset  and  is  set  at  a 
 level  such  that  the  present  value  of  revenues  equals  the  investment  cost  of  $100.  4 


 1  2  3  4  5  7  8  9  10  11  12 
 12 
 14 
 16 
 18 
 20 
 22 


 6 
 Figure  ES1.  Traditional  Prices  versus  a  Levelized  TELRIC  Price 


 4  Note  that,  due  to  levelization,  a  depreciation  schedule  does  not  enter  in  any  way  into  the  TELRIC 
 computation  in  the  absence  of  tax  effects.  If  tax  consequences  are  accounted  for,  then  the  TELRIC  price  is  set  at  a  level  such  that  the  present  value  of  after-  tax  revenues  is  equal  to  the  present  value  of  after-  tax 


 investment  costs,  where  the  latter  accounts  for  the  deductibility  of  depreciation  expense  and  an  appropriate  weighted  average  cost  of  capital  is  used.  As  a  result,  more  accelerated  tax  depreciation  schedules  lower  the 
 levelized  TELRIC  price. 


 2 
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 Figure  ES1  was  constructed  without  any  reference  to  the  rate  of  change  of  investment  costs,  since  neither  the  levelized  TELRIC  price  nor  the  traditional  price 
 depends  on  future  changes  in  these  costs.  Suppose,  however,  that  investment  costs  are  expected  to  fall  at  a  rate  of  10%  per  year.  In  a  competitive  market,  prices  would  also  be 
 expected  to  fall  at  a  rate  of  approximately  10%  per  year,  since  the  price  at  any  given  time  would  reflect  the  cost  of  newly  incurred  investments  made  at  that  time.  In  order  to 
 recover  their  investment  costs,  potential  entrants  therefore  anticipate  setting  prices  according  to  a  declining  price  schedule,  so  that  prices  in  early  years  recover  more  of  the 
 investment  cost  than  prices  in  later  years. 
 If  TELRIC  price  reviews  are  conducted  periodically,  using  the  current  investment  cost  at  the  time  of  the  review,  then  TELRIC  prices  will  also  decline  over  time  at  a  rate  of 
 approximately  10%.  However,  since  TELRIC  prices  were  defined  to  allow  the  firm  to  break  even  assuming  a  levelized  price  schedule  for  the  entire  life  of  the  asset,  when  there 
 are  periodic  reviews  and  declining  investment  costs,  the  TELRIC  prices  will  no  longer  recover  the  firms  investment  cost  including  its  target  rate  of  return.  Figure  ES2  compares 
 a  price  schedule  that  allows  competitive  firms  to  earn  exactly  the  target  rate  of  return  (dotted  line)  and  TELRIC  prices  (solid  line),  assuming  TELRIC  reviews  are  conducted 
 every  three  years. 


 1  2  3  4  5  6  7  8  9  10  11  12 
 10 
 15 
 20 
 25 


 Figure  ES2.  Competitive  Prices  versus  TELRIC  Prices  Reviewed  Every  Three  Years 
 It  is  a  simple  matter,  however,  to  define  a  correction  factor  based  on:  (1)  the  assumed  rate  of  change  of  investment  cost,  and  (2)  the  period  between  TELRIC  reviews. 
 In  the  current  example,  TELRIC  prices  must  be  increased  by  35%  in  every  year.  The  corrected  TELRIC  price  path  is  shown  in  Figure  ES3.  By  construction,  corrected 
 TELRIC  prices  recover  the  firms  full  investment  costs,  including  its  required  rate  of  return.  In  addition,  TELRIC  prices  fall  at  approximately  the  same  rate  as  the  breakeven 


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 prices  for  competitive  firms,  with  differences  only  in  the  assumed  timing  of  the  price  changes.  5 
 1  2  3  4  5  7  8  9  10  11  12 
 10 
 12.5 
 15 
 17.5 
 20 
 22.5 
 25 


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 Figure  ES3.  Competitive  Prices  versus  Corrected  TELRIC  Prices 


 Efficient  Investment  over  Time 
 Section  3  of  the  paper  is  concerned  with  deriving  cost  minimizing  investment  plans  in  a  dynamic  environment.  This  section  of  the  paper  seeks  to  address  in  part  the 
 second  and  third  objections  raised  by  incumbents  to  TELRIC  pricing.  First,  by  deriving  an  efficient  forward-  looking  investment  plan,  the  paper  is  simultaneously  solving  for  an 
 efficient  utilization  rate  over  time.  Since  assumed  utilization  rates  are  an  important  input  to  cost  proxy  models  used  to  estimate  TELRIC  prices,  these  results  are  potentially 
 relevant  in  setting  appropriate  utilization  input  rates  in  a  forward-  looking  context.  For  example,  using  a  cost  function  derived  from  outputs  of  the  FCCs  Synthesis  Model  to 
 represent  loop  investment  costs,  the  paper  demonstrates  how  to  compute  an  efficient  investment  plan  for  loop  plant  over  a  60  year  time  horizon.  This  plan  is  illustrated  by  the 
 step  function  in  Figure  ES4. 


 5  Section  2  also  demonstrates  that  when  investment  costs  are  increasing  over  time  (e.  g.  due  to  general  price 
 inflation)  then  periodically  reviewed  TELRIC  prices  will  lead  to  an  over-  recovery  of  investment  cost.  In  this  case  the  correction  factor  will  lead  to  a  reduction  in  TELRIC  prices. 


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 Section  3  also  shows  how  to  compute  efficient  investment  plans  based  on  existing  capacity  levels  of  incumbent  firms.  To  the  extent  the  initial  capacity  levels  can 
 approximate  the  existing  investment  base  of  incumbent  carriers,  these  results  may  reconcile  TELRIC  price  computations  with  actual  cost  computations  favored  by 
 incumbents. 


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 1.  Introduction 
 In  February  1996  the  U.  S.  Congress  passed  the  Telecommunications  Act  of  1996,  which  significantly  amended  the  Communications  Act  of  1934.  The  goals  of  the  1996  Act  were 
 to  establish  a  pro-  competitive,  deregulatory  national  policy  framework  for  local  telephony  competition.  8  Implementation  of  the  1996  Act  by  the  Federal  Communications 
 Commission  (FCC)  included  development  of  a  new  regulatory  pricing  standard  known  as  Total  Element  Long  Run  Incremental  Cost  (TELRIC).  9  TELRIC  has  been  used  to 
 price  unbundled  network  elements  and  interconnection,  10  and  has  been  widely  criticized  both  as  a  conceptual  framework  and  as  actually  applied  by  regulators.  11  An  underlying 
 current  in  many  of  these  criticisms  is  the  static  nature  of  TELRIC  pricing  as  implemented  to  date,  when  actual  telecommunications  industry  costs  are  highly  dynamic. 


 This  paper  considers  how  TELRIC  pricing  can  be  correctly  implemented  in  a  dynamic  environment.  We  do  this  by  exploring  first,  in  Section  2,  how  prices  that  are 
 periodically  reviewed  can  be  calculated  to  recover  the  cost  of  a  given  investment  in  physical  equipment.  Second,  Section  3  studies  how  dynamically  efficient  investment 
 plans  can  be  calculated,  thereby  giving  the  costs  to  be  recovered  via  the  pricing  rules  discussed  in  Section  2.  Together,  Sections  2  and  3  move  beyond  the  criticisms  and 
 substantially  toward  theoretically  sound  TELRIC  pricing  rules  that  can  actually  be  applied  in  practice.  In  contrast,  the  existing  literature  is  long  on  criticisms  of  TELRIC 
 but  short  indeed  on  suggesting  rules  and  calculations  thereof  that  show  how  TELRIC  prices  as  currently  implemented  might  be  modified  to  address  some  of  the  criticisms.  12 
 Our  contribution  is  to  take  this  next  step,  with  particular  emphasis  on  correctly  capturing  the  dynamics  of  the  industry  and  the  sense  in  which  costs  and  prices  should  be  forward-looking. 


 One  way  to  view  TELRIC  is  as  a  new  form  of  incentive  regulation.  Traditional  incentive  regulation  tries  to  induce  socially  efficient  behavior  from  a  franchise 
 monopolist.  The  traditional  approach  was  precluded  by  the  1996  Act,  however,  which  nullified  the  state  and  local  statutes  that  historically  granted  franchise  monopoly  status  to 


 8  See  Joint  Managers  Statement,  S.  Conf.  Rep.  No.  104-  320,  104  th  Cong.,  2d  Sess.  113  (1996)  at  1. 
 9  See  Implementation  of  the  Local  Competition  Provisions  of  the  Telecommunications  Act  of  1996 


 (hereinafter  Local  Competition  Order),  11  FCC  Rcd  15499,  15509,  and  15812-  15922  (1996).  10  The  1996  Act  envisioned  three  alternative  methods  for  competitive  entry:  construction  of  new  network 


 facilities,  resale  of  the  incumbent  firms  retail  services,  and  leasing  of  unbundled  network  elements  from  the  incumbent.  The  1996  Act  also  required  incumbents  to  provide  interconnection.  See  47  U.  S.  C.   
 251(  c)(  4)  and  252(  d)(  3).  11  See,  for  example,  Hausman  (1997);  Kahn  (1998,  2001);  Sidak  and  Spulber  (1998);  Alleman  (1999); 
 Kahn,  Tardiff,  and  Weisman  (1999);  Salinger  (1999);  Weisman  (2000);  Mandy  (2002);  Tardiff  (2002);  Weisman  (2002),  and  Weingarten  and  Stuck  (2003).  Although  these  studies  differ  in  their  points  of 
 emphasis,  all  are  critical  of  at  least  some  aspects  of  TELRIC  in  theory  or  practice.  12  Exceptions  are  Hausman  (1997),  Mandy  (2002),  Tardiff  (2002)  and  Weingarten  and  Stuck  (2003). 
 However,  even  these  papers  do  not  calculate  prices  and  costs  under  the  variety  of  possible  assumptions  considered  herein,  and  only  Mandy  (2002)  presents  evidence  on  dynamic  and  forward-  looking  price  and 
 cost  paths  that  might  form  a  conceptually  sound  basis  for  revisions  to  TELRIC  pricing  as  currently  practiced. 


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 incumbents,  and  charged  the  FCC  and  state  regulators  with  creating  rules  under  which  new  competition  would  operate.  13  Under  the  incentive  regulation  view,  by  adopting 
 TELRIC,  the  FCC  tried  to  create  a  market  structure  in  a  highly  concentrated  industry  that  provides  incentives  for  efficient  investment  decisions  similar  to  those  present  in 
 competitive  industries  with  many  small  suppliers.  Under  this  view,  TELRIC  tries  to  induce  socially  efficient  behavior  from  firms  that  may  have  significant  market  power, 
 thereby  sharing  the  same  goal  as  traditional  incentive  regulation.  But  unlike  traditional  incentive  regulation,  TELRIC  must  pursue  this  goal  outside  of  the  franchise  monopoly 
 market  structure.  TELRIC  therefore  tries  to  induce  efficient  investment  decisions,  including  efficient  entry  and  exit,  in  an  industry  that,  because  of  high  concentration  and 
 substantial  scale  economies,  might  experience  very  little  (efficient)  entry  and  exit  without  such  inducement.  There  is  substantial  disagreement  over  whether  TELRIC  succeeds  in 
 promoting  efficient  investment  by  both  entrants  and  incumbents,  or  whether  it  is  even  possible  for  price  regulation  to  achieve  this  objective.  14  However,  even  those  most 
 critical  of  the  TELRIC  methodology  agree  that  the  1996  Act    asks  regulators  to  create  prices  that  will  induce  appropriate  new  entry.  15  In  other  words,  Congress  charged  the 
 FCC  and  state  regulators  with  incentive  regulating  entry  and  exit,  and  doing  so  via  price  regulation. 


 The  strong  objections  of  some  writers,  as  well  as  incumbent  local  exchange  carriers  (ILECs),  to  TELRIC  as  a  methodology  and  to  its  specific  implementation  by  state 
 regulatory  commissions  fall  into  three  categories.  First,  some  have  questioned  the  theoretical  consistency  of  the  TELRIC  methodology  itself.  Specifically,  ILECs  have 
 argued  that,  when  equipment  prices  are  falling  over  time,  periodic  recalculation  of  TELRIC  prices  prevents  them  from  recovering  their  investment  costs.  Second,  some  have 
 criticized  the  way  state  commissions  have  implemented  TELRIC.  They  argue  either  that  states  have  adopted  unrealistic  input  values  or  that  the  cost  models  adopted  contained 
 flawed  model  algorithms.  16  Finally,  some  have  argued  that  any  forward-  looking  pricing  methodology,  including  TELRIC,  in  which  the  computation  of  cost  is  not  based  on  the 
 incumbents  actual  network  as  a  starting  point,  is  inconsistent  with  the  meaning  of  the  1996  Act. 


 This  paper  examines  these  claims.  17  Section  2  studies  whether  TELRIC,  as  implemented,  permits  cost  recovery  of  investments  in  physical  equipment.  We  show  that 
 the  claim  of  potential  under-  recovery  is  correct.  When  investment  costs  are  falling  over  time  and  TELRIC  price  reviews  are  conducted  at  intervals  shorter  than  expected  asset 


 13  47  U.  S.  C.    253. 
 14  See  the  references  cited  in  footnote  9. 


 15  Justice  Breyer  (Verizon  v.  FCC,  Dissent:  22),  as  quoted  by  Weisman  (2002). 
 16  For  example,  ILECs  argue  that  proxy  models  often  assume  an  unrealistic  level  of  sharing  of  the  cost  of 


 structures  (i.  e.  poles  and  underground  conduit  facilities)  with  other  utilities.  They  also  argue  that  cost  minimization  procedures  in  proxy  models  assume  an  unattainable  level  of  efficiency  that  no  real  world  firm 


 could  expect  to  emulate.  The  results  of  this  paper  are  relevant  to  the  setting  of  one  input  factor    the  firms  utilization  rate  of  existing  capacity  (also  called  a  fill  factor). 
 17  We  do  not,  however,  evaluate  the  realism  of  proxy  model  algorithms  or  attempt  to  recommend  specific 
 input  values  for  use  in  proxy  model  computations.  In  addition,  we  do  not  specifically  consider  the  conditions  under  which  unbundled  network  elements  should  be  offered  under  TELRIC  prices. 


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 lives,  a  firm  will  earn  less  than  its  target  rate  of  return  under  the  TELRIC  methodology  as  generally  implemented.  A  TELRIC  price  is  usually  computed  as  a  constant  (or  levelized) 
 price  that,  over  the  life  of  the  asset,  will  earn  sufficient  revenue  to  recover  the  full  cost  of  investment  including  the  target  rate  of  return.  This  paper  shows  that,  when  TELRIC 
 prices  are  recomputed  at  intervals  shorter  than  these  asset  lifetimes,  and  investment  costs  fall  between  price  reviews,  actual  revenues  will  not  fully  compensate  the  firm.  The  paper 
 further  shows  that  it  is  possible  to  compute  a  correction  factor  based  on  estimates  of  the  rate  of  change  of  investment  cost  and  the  expected  time  between  TELRIC  reviews. 
 Corrected  TELRIC  prices  rise  or  fall  at  the  same  rate  over  time  as  underlying  investment  cost,  and  allow  the  firm  to  earn  its  target  rate  of  return  no  matter  how  frequently  price 
 reviews  are  conducted.  Moreover,  no  ad  hoc  adjustments  of  assumed  asset  lifetimes  or  depreciation  schedules  are  needed  to  implement  the  suggested  correction. 


 Section  3  of  the  paper  partially  addresses  the  second  and  third  objections  raised  to  TELRIC  pricing.  We  consider  two  stylized  assumptions  about  asset  replacement.  Under 
 one  scenario,  which  we  call  expected  innovation  date  replacement,  we  assume  the  physical  life  of  an  asset  is  effectively  infinite,  in  the  sense  that  technical  advances  make  it 
 obsolete  before  it  suffers  substantial  physical  deterioration,  so  that  assets  are  eventually  replaced  due  to  technological  advances.  In  the  second  scenario,  which  we  call  light  bulb 
 performance,  we  assume  each  asset  has  a  fixed  lifetime.  In  both  scenarios,  we  derive  cost  minimizing  investment  plans  over  assumed  planning  horizons.  These  results  are 
 relevant  to  TELRIC  cost  studies  and  cost  models  generally  in  that  they  provide  a  method  by  which  forward-  looking  capacity  utilization  factors  (an  important  input  in  cost  models) 
 can  be  derived.  Section  3  also  shows  how  to  compute  efficient  investment  plans  starting  from  existing  capacity  levels  of  an  incumbent  firm.  To  the  extent  that  initial  capacity 
 levels  can  approximate  the  existing  investment  base  of  ILECs,  these  results  may  reconcile  TELRIC  price  computations  with  actual  cost  computations  favored  by  ILECs 
 and  some  writers.  Based  on  our  derivation  of  efficient  investment  plans  in  the  light  bulb  performance  scenario,  we  also  compare  TELRIC  pricing  rules,  as  generally  implemented, 
 with  prices  defined  by  an  efficient  contestable  entry  criterion. 
 This  paper  does  not  address  the  criticism,  raised  by  some  observers  and  ILECs,  concerning  the  appropriate  cost  of  capital  to  be  used  in  calculations  like  those  performed 
 herein.  Specifically,  some  18  have  argued  that  a  competitive  environment  exposes  ILECs  to  more  risk  than  the  former  franchise  monopoly  environment.  They  argue  that  higher 
 risk,  including  the  risk  associated  with  foregone  option  value  when  an  investment  is  made,  must  be  compensated  through  higher  input  values  for  the  firms  cost  of  capital. 
 The  analysis  herein  makes  no  judgments  regarding  these  arguments.  Throughout,  we  treat  the  cost  of  capital  as  an  exogenous  input  that  has  been  derived  via  some  other 
 analysis. 
 Both  sections  2  and  3  are  based  on  extensive  computations  using  Mathematica,  and  details  of  the  relevant  programming  code  are  available  from  the  authors  upon  request. 
 Some  of  the  results  of  section  2  have  appeared  elsewhere  in  the  academic  literature,  19 
 18  See  Hausman  (1997). 
 19  See,  for  example,  Biglaiser  and  Riordan  (2000),  Mandy  (2002)  and  Salinger  (1998). 


 9 
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 Figure  4  compares  TELRIC  prices  reviewed  every  three  years  with  traditional  prices  based  on  straight-  line  depreciation.  As  Figure  4  indicates,  TELRIC  prices  subject 
 to  three-  year  reviews  understate  traditional  prices  in  every  year.  Note  that  neither  traditional  prices  nor  TELRIC  prices  computed  at  each  review  period  account  for  the  rate 
 of  decline  of  investment  cost  in  future  years.  While  this  does  not  create  a  problem  in  the  case  of  traditional  pricing,  since  it  is  designed  to  recover  the  historical  cost  of  the  asset 
 over  its  lifetime,  it  creates  a  problem  for  TELRIC  computations  subject  to  a  three-  year  review.  More  specifically,  the  TELRIC  computation  ignores  the  impact  of  future  cost 
 reviews  on  prices  during  the  life  of  the  asset,  instead  incorrectly  assuming  the  initial  levelized  TELRIC  price  will  continue  to  be  received  for  the  entire  life  of  the  asset.  Thus, 
 while  the  TELRIC  price  computed  in  year  0  was  computed  to  fully  compensate  the  firm  for  its  investment  costs  made  in  year  0,  it  does  so  only  if  maintained  throughout  the  life 
 of  the  asset.  If  prices  are  reduced  in  future  years  due  to  the  lower  investment  costs  at  future  TELRIC  cost  reviews,  then  the  resulting  price  schedule  no  longer  fully 
 compensates  the  firm. 


 1  2  3  4  5  6  7  9  10  11  12  13  14  15  16 
 2.5 
 5 
 7.5 
 10 
 12.5 
 15 


 8 
 Figure  4.  Traditional  and  Triennially  Reviewed  TELRIC  Prices:  Case  of  Decreasing  Investment  Cost 


 Figure  5  compares  TELRIC  economic  depreciation  and  straight-  line  depreciation.  While  in  the  benchmark  analysis,  depreciation  under  TELRIC  pricing  was  increasing 
 over  time  (see  Figure  3),  the  economic  depreciation  identity  (1)  now  reveals  a  secularly  decreasing  depreciation  schedule  under  TELRIC  that  increases  only  within  each  review 
 cycle.  This  is  because  the  periodic  reviews  with  decreasing  investment  cost  produce  TELRIC  prices  that  fall  fast  enough  in  this  example  to  more  than  offset  the  decelerated 
 depreciation  caused  by  levelization. 


 17 
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 2  4  6  8  10  12  14  16  18  20  22  24  26  28  30 
 5 
 10 
 15 
 20 
 25 
 30 


 Figure  6.  Traditional  and  Triennially  Reviewed  TELRIC  Prices:  Case  of  Increasing  Investment  Cost 
 The  economic  depreciation  implied  by  TELRIC,  as  shown  in  Figure  7,  is  now  severely  decelerated,  to  the  point  that  it  is  negative  in  the  early  years  after  the  investment. 
 This  is  because  the  deceleration  caused  by  levelization  is  reinforced  by  the  decelerating  effects  of  rising  prices.  Rising  prices  decelerate  economic  depreciation  for  two  reasons. 
 First,  other  things  constant,  economic  depreciation  is  higher  when  prices  are  higher.  Recall  that  economic  depreciation  is  simply  the  change  in  the  value  of  the  asset  from  one 
 period  to  the  next.  As  equation  (1)  indicates,  however,  the  drop  in  the  value  of  the  asset  is  equal  to  the  revenue  received  in  the  period.  28  Thus,  if  prices  rise,  revenue  will  rise,  which 
 will  increase  depreciation. 
 Second,  as  time  passes  discounting  takes  a  progressively  lighter  toll  on  the  present  value  of  the  as-  yet  unrealized  relatively  high  late-  life  prices.  Even  with  only  3  percent 
 growth  and  triennial  reviews,  prices  are  so  high  at  the  end  of  thirty  years  compared  to  the  initial  prices  (over  twice  as  high)  that  the  value-  enhancing  effect  of  moving  them  one 
 year  closer  in  time  can  be  larger  than  the  revenue  actually  received  in  an  early  year.  Hence  value  can  actually  increase  over  time.  An  increase  in  value  that  occurs  without 
 additional  investment  is  negative  economic  depreciation.  This  second  factor  is  responsible  for  the  negative  economic  depreciation  observed  in  Figure  7. 


 28  Prior  to  time  t,  the  revenue  pt  qt  is  in  the  assets  future  and  therefore  contributes  to  its  value.  After  time  t, 
 however,  the  revenue  pt  qt  is  no  longer  in  the  assets  future,  so  the  asset  must  lose  value  pt  qt  at  time  t. 


 19 
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 incumbent  firm  to  recoup  its  costs  and  earn  the  target  rate  of  return  on  a  forward  looking  basis. 
 Figure  8  illustrates  both  corrected  (solid  line)  and  uncorrected  (dashed  line)  TELRIC  prices  compared  to  traditional  prices  (dotted  line).  The  corrected  TELRIC  prices 
 begin  above  but  quickly  fall  below  traditional  prices,  reflect  the  difference  in  three  year  versus  one-  year  review,  and  have  the  same  pattern  as  the  uncorrected  TELRIC  prices. 


 1  2  3  4  5  6  7  9  10  11  12  13  14  15  16 
 5 
 10 
 15 
 20 


 8 
 Figure  8.  Traditional  versus  Corrected  and  Uncorrected  Triennially  Reviewed  TELRIC  Prices:  Case  of  Decreasing  Investment  Cost 


 By  construction,  the  corrected  TELRIC  prices  also  deliver  the  regulator's  target  cost  of  capital,  equal  to  11.25%  in  the  present  case. 
 2.7.2  Increasing  Initial  Investment  Cost 
 These  same  comparisons  between  traditional  and  TELRIC  prices  can  be  made  when  investment  cost  is  increasing,  using  the  parameter  values  in  section  2.6.  The  TELRIC 
 correction  factor  is  now  0.802743.  That  is,  assuming  the  parameter  values  in  scenario  3  and  a  three  year  review  period,  TELRIC  loop  prices  should  be  reduced  by  approximately 
 20%  in  order  to  allow  the  incumbent  firm  to  recoup  its  cost  and  earn  the  target  rate  of  return  on  a  forward  looking  basis.  The  corrected  TELRIC  prices,  again  shown  as  a  solid 
 line  in  Figure  9,  begin  below  but  rise  above  traditional  prices  after  less  than  one-  third  of  the  life,  again  reflect  the  difference  between  three-  year  versus  one-  year  reviews,  and 
 again  have  the  same  pattern  as  the  uncorrected  TELRIC  prices. 


 21 
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 1  2  3  4  5  6  7  9  10  11  12  13  14  15  16 
 5 
 10 
 15 
 20 


 8 
 Figure  10.  Contestable  versus  Corrected  Triennially  Reviewed  TELRIC  Prices:  Case  of  Decreasing  Investment  Cost 


 2  4  6  8  10  12  14  16  18  20  22  24  26  28  30 
 12.5 


 15 
 17.5 
 20 
 22.5 
 25 
 27.5 


 Figure  11.  Contestable  versus  Corrected  Triennially  Reviewed  TELRIC  Prices:  Case  of  Increasing  Investment  Cost 
 2.8  Variable  Utilization  Rates 
 All  computations  up  to  this  point  have  assumed  a  constant  utilization  rate.  If  demand  is  growing,  a  cost-  minimizing  firm  may  make  investments  in  anticipation  of  future  growth, 
 in  which  case  utilization  rates  will  increase  as  the  asset  ages.  All  of  the  definitions  of  previous  sections  are  valid  under  these  conditions,  although  the  specific  time  paths  of 
 price  and  depreciation  will  change  when  utilization  rates  are  not  constant. 
 However,  when  utilization  rates  are  not  constant,  a  discrepancy  emerges  between  the  TELRIC  pricing  rule  (5)  and  the  TELRIC  prices  actually  calculated  by  cost  proxy 
 models,  such  as  the  FCCs  synthesis  model.  Specifically,  the  Synthesis  Model  uses  average  utilization  to  calculate  the  TELRIC  price,  rather  than  anticipating  that  utilization 
 will  change  over  the  life  of  the  asset.  In  addition,  the  size  of  the  investment  F0  is  assumed 


 24 
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 to  be  sufficient  to  satisfy  current  demand  divided  the  utilization  factor.  These  issues  will  be  explored  further  in  the  following  section.  31 
 In  this  section,  we  assume  increasing  investment  cost  using  the  same  parameter  values  as  in  section  2.6,  except  that  we  assume  a  growing  utilization  rate  given  by  qt  = 
 .40  +  .55  t  /  (L-  1)  for  t  =  0,    ,  L-  1.  This  utilization  path  models  loops  that  are  used  at  40%  of  capacity  when  installed  but  whose  usage  increases  linearly  to  95%  at  the  end  of 
 the  thirty  year  life. 
 Figure  12  below  compares  three  separate  price  paths:  traditional  prices  (solid  line),  contestable  prices  (dotted  line),  and  TELRIC  prices  reviewed  every  three  years 
 (dashed  line).  The  traditional  prices  still  fall,  as  when  the  utilization  rate  is  constant,  but  now  they  begin  much  higher  and  decrease  faster.  This  is  because  the  traditional  rule  only 
 uses  utilization  in  period  t  to  calculate  the  price  in  period  t,  so  the  price  must  drop  to  offset  growing  quantity.  This  effect  reinforces  the  downward  slope  caused  by  straight-line 
 depreciation.  In  contrast,  the  contestable  and  TELRIC  prices  still  increase  over  time  because  they  take  account  of  the  entire  utilization  path  to  calculate  the  price  at  each  time 
 (see  equations  5  and  7).  Hence  their  dynamics  are  driven  entirely  by  the  growth  rate  of  initial  investment  cost.  Both  paths  are  higher  than  under  scenario  3,  where  utilization 
 rates  are  constant,  reflecting  the  fact  that  average  utilization  over  the  life  of  the  asset  is  about  the  same  as  scenario  3  but  revenues  are  delayed  because  utilization  is  initially  low. 


 2  4  6  8  10  12  14  16  18  20  22  24  26  28  30 
 10 
 20 
 30 
 40 


 Figure  12.  Traditional,  Contestable,  and  Triennially  Reviewed  TELRIC  Prices:  Case  of  Increasing  Investment  Cost  and  Increasing  Utilization 
 As  before,  the  TELRIC  prices  can  be  corrected  so  that  they  yield  the  same  rate  of  return  as  the  traditional  and  contestable  prices.  The  correction  factor  in  this  case  is 
 0.761538,  which  is  not  much  different  from  scenario  3.  The  corrected  TELRIC  prices 


 31  In  the  present  section,  the  function  q  has  served  both  as  a  utilization  rate  and  as  a  proxy  for  potentially 
 varying  demand  conditions.  When  an  efficient  investment  plan  requires  repeated  investments  made  over  a  planning  horizon,  there  is  no  longer  a  simple  relationship  between  utilization  rates  and  aggregate  demand. 


 In  section  3,  these  issues  are  treated  in  a  more  general  framework  in  which  demand  is  the  exogenous  variable  and  utilization  rates  are  determined  through  cost  minimization. 


 25 
28
 (solid  line)  again  track  the  contestable  prices  (dotted  line),  as  shown  in  Figure  13,  and  as  expected,  the  corrected  prices  yield  the  target  rate  of  return  of  11.25%. 
 2  4  6  8  10  12  14  16  18  20  22  24  26  28  30 
 15 


 20 
 25 
 30 


 Figure  13.  Contestable  and  Corrected  Triennially  Reviewed  TELRIC  Prices:  Case  of  Increasing  Investment  Cost  and  Increasing  Utilization 
 We  note  in  conclusion  that  these  results  demonstrate  that  demand  growth  as  well  as  changing  investment  cost  must  be  considered  when  setting  a  time  path  of  prices.  32 
 Generally,  a  firms  utilization  rate  at  any  point  in  time  is  determined  by  a  solution  to  a  cost  minimization  problem.  The  cost  minimum  determines  the  time  and  level  of 
 investments  needed  to  satisfy  demand  at  every  future  point  in  time.  It  may  very  well  involve  intentional  under-  utilization  that  varies  over  time.  We  consider  some  of  these 
 issues  in  the  next  section  in  a  framework  in  which  efficient  investment  decisions  can  be  determined  when  the  rate  of  demand  growth  is  explicitly  modeled,  and  a  more  general 
 investment  cost  function  is  introduced. 
 3.  Efficient  Dynamic  Investment 


 Section  2  was  concerned  with  the  time  path  of  TELRIC  prices  that  could  be  used  to  recover  the  cost  of  an  arbitrary  investment  F0  that  has  an  arbitrary  utilization  path  qt. 
 There,  it  was  assumed  the  investment  cost  and  utilization  path  had  already  been  determined. 


 Actual  investment  cost  and  utilization  of  assets  subject  to  TELRIC  pricing  result  from  decisions  made  by  incumbent  suppliers.  An  efficient  supplier  makes  such  decisions 
 to  minimize  the  cost  of  serving  an  evolving  expected  demand,  given  the  expected  costs  of  raw  inputs,  the  expected  evolution  of  those  costs,  the  expected  performance  of  the  assets 
 over  time,  the  cost  of  capital  and  other  input  prices.  These  are  dynamic  cost-  minimizing  investment  decisions. 


 32  While  the  assets  utilization  rate  has  been  allowed  to  vary  in  the  present  section,  the  aggregate  level  of 
 capacity  has  remained  constant  at  a  normalized  value  of  one  unit. 


 26 
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 1  2  3  4  5  6  7  8  9  10  11  12  13  14  15  16  t 
 20000 


 21000 
 22000 
 23000 
 24000 
 25000 
 26000 
 27000 


 Capacity 


 Figure  15.  Demand  and  Efficient  Capacity,  Benchmark  Case  Switching  Scenario 


 2.5  5  7.5  10  12.5  15  t 
 0.02 
 0.04 
 0.06 
 0.08 
 0.1 
 0.12 
 0.14 


 Percent  Excess  Capacity 


 Figure  16.  Percent  Excess  Capacity,  Benchmark  Case  Switching  Scenario 
 Table  1  summarizes  the  results  for  various  parameterizations.  The  benchmark  parameterization  is  in  row  1.  Subsequent  rows  report  only  those  parameters  that  differ 
 from  the  benchmark.  The  second  row,  which  may  be  interpreted  as  an  incremental  cost  calculation,  shows  the  optimal  investment  plan  if  initial  demand  is  only  80%  of  initial 
 capacity.  This  initial  excess  capacity  is  adequate  to  satisfy  demand  until  year  11.2,  at  which  time  efficient  investment  installs  exactly  enough  capacity  to  satisfy  demand 
 through  the  end  of  the  horizon.  Costs  are  much  lower  than  in  the  benchmark  plan,  because  the  initial  excess  capacity  both  reduces  the  need  for  new  investment  and 
 forestalls  the  time  of  that  investment.  The  third  row  examines  the  effect  of  a  change  in  the  cost  of  capital.  It  shows  that  the  optimal  plan  places  heavier  emphasis  on  delaying 
 investment  costs  rather  than  exploiting  scale  economies  when  the  cost  of  capital  is  higher.  This  delaying  tactic,  along  with  the  pure  discounting  effects  of  a  lower  discount  factor, 
 reduces  the  present  value  of  the  plan  compared  with  the  benchmark  even  though  the  total  cash  outlay  is  higher.  The  fourth  row  shows  how  a  50%  delay  in  the  innovation  date 
 affects  the  optimal  investment  plan.  The  second  investment  is  accelerated  slightly  and  a 


 31 
34
 10  20  30  40  50  60  t 
 0.  05 
 0.1 
 0.  15 
 0.2 
 0.  25 
 0.3  Percent  Excess  Capacity 


 Figure  19.  Percent  Excess  Capacity,  Benchmark  Case  Loop  Scenario 
 Table  2  presents  results  when  some  of  the  benchmark  assumptions  are  modified.  43  As  the  cost  of  capital  rises,  it  becomes  more  expensive  to  have  units  of  unused  capacity 
 and  the  present  value  of  future  investment  costs  is  reduced.  As  a  result,  there  is  a  reduction  in  the  size  of  the  initial  investment  and  a  corresponding  acceleration  in  the  time 
 that  subsequent  investments  are  made.  When  investment  costs  are  assumed  constant,  instead  of  increasing  at  the  benchmark  rate  of  3%  per  year,  the  size  of  the  initial 
 investment  is  again  reduced  modestly.  If  the  life  of  the  asset  is  15  years,  substantially  less  than  in  the  benchmark  case,  it  is  efficient  to  invest  as  infrequently  as  possible  under  the 
 light  bulb  replacement  scenario.  The  cost  minimizing  investment  plan  then  consists  of  investments  made  at  15  year  intervals  with  no  intermediate  investments. 


 If  there  is  existing  capacity  from  previous  investments  at  time  t  =  0,  then  the  time  of  initial  investment  is  delayed  until  demand  growth  exhausts  the  initial  capacity.  In  this 
 situation,  the  cost  minimizing  investment  plan  of  an  efficient  firm  should  take  account  of  these  initial  investments.  However,  the  timing  of  subsequent  investment  decisions  will 
 not,  in  general,  have  a  simple  relationship  to  the  time  that  existing  investments  were  made.  44  The  last  row  of  Table  2  and  Figure  20  describe  the  efficient  investment  program 
 for  one  possible  set  of  initial  conditions. 


 43  In  this  table  only  we  use  the  notation  F  j  =  F(  Ij  ,  Tj). 
 44  Note  that  the  optimal  investment  plan  illustrated  in  Figure  20  has  existing  assets  retired  at  times  t  =  10, 


 15,  25,  and  even  as  late  as  year  55,  without  any  corresponding  new  investments  at  those  times.  Thus,  initial  capacities  can  have  a  substantial  impact  on  the  firms  capital  stock  even  after  many  years  have  elapsed. 


 36 
39
 10  20  30  40  50  60  t  10000 
 15000 
 20000 
 25000 
 30000 
 35000 


 Capacity 


 Figure  20.  Demand  and  Efficient  Capacity,  Loop  Scenario  With  Initial  Installed  Capacity  at  Time  t  =  0 
 3.4  Implications  for  TELRIC  Pricing 
 Let  us  now  consider  some  implications  of  the  light  bulb  efficient  investment  results  for  TELRIC  pricing.  TELRIC  pricing  rules  have  traditionally  been  defined  in  an 
 environment  in  which  little  or  no  account  is  taken  of  market  dynamics.  In  particular,  current  TELRIC  pricing  rules  are  generally  defined  without  reference  to  either  expected 
 changes  in  future  investment  cost  or  expected  changes  in  future  demand  (or  utilization  rates).  In  section  2.7  we  illustrated  how  a  simple  multiplicative  correction  factor  could  be 
 defined  to  take  proper  account  of  changing  investment  cost.  Under  corrected  TELRIC  pricing,  a  regulated  firm  would  exactly  recover  its  forward  looking  investment  cost,  even 
 if  TELRIC  price  reviews  occur  at  intervals  shorter  than  assumed  asset  lifetimes.  In  section  2.8,  it  was  similarly  demonstrated  that  varying  utilization  rates,  which  could 
 result  from  cost  minimizing  decisions  made  in  the  face  of  growing  demand,  could  be  easily  incorporated  into  the  TELRIC  pricing  rule. 


 Sections  3.2  and  3.3  have  focused  on  another  aspect  of  efficient  investment  planning  in  a  dynamic  environment.  In  these  sections,  a  cost  minimizing  investment 
 program  was  explicitly  calculated  in  a  variety  of  circumstances.  In  order  to  complete  our  analysis,  it  only  remains  to  demonstrate  how  these  cost  minimizing  investment  decisions 
 can  be  used  as  inputs  into  a  fully  efficient  forward  looking  pricing  regime.  In  the  case  of  assets  having  light  bulb  performance  characteristics  this  process  is  relatively 
 straightforward.  The  TELRIC  prices  for  a  sequence  of  investments  made  as  part  of  an  optimal  investment  plan  now  depend  on  the  demand  conditions  at  the  time  at  which  the 
 investment  occurs.  45  With  this  modification,  equation  (5)  of  section  2  is  repeated  using  notation  of  the  current  section  as  equation  (10): 


 45  In  section  2,  utilization  rates,  which  play  the  same  role  as  aggregate  demand  in  section  3,  were  generally 
 assumed  to  be  constant.  In  the  case  of  growing  utilization  rates  discussed  in  section  2.8,  the  utilization  rate  path  was  assumed  to  be  based  on  the  time  of  investment  rather  than  calendar  time. 


 38 
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 under  a  previous  regulatory  compact.  Details  of  possible  additions  for  embedded  costs,  that  preserve  incentives  for  efficient  entry  and  exit,  are  left  for  future  research. 
 4.  Concluding  Comments 
 The  objective  of  this  paper  has  been  to  evaluate  the  use  of  static  cost  proxy  models  in  setting  forward-  looking  prices  such  as  the  prices  set  according  to  TELRIC.  Section  2 
 compared  the  time  paths  of  prices  and  depreciation  under  traditional  regulatory  accounting  with  the  prices  and  depreciation  implied  by  various  versions  of  TELRIC. 
 Under  levelized  TELRIC  pricing,  where  prices  are  assumed  to  remain  constant  for  the  entire  economic  life  of  an  asset,  both  prices  and  implied  depreciation  schedules  follow 
 significantly  different  trajectories  than  under  traditional  regulation.  Under  both  pricing  rules,  however,  the  firm  earns  revenues  that  fully  recover  investment  costs  and  a  target 
 rate  of  return. 
 When  TELRIC  prices  are  recomputed  at  intervals  shorter  than  asset  lives  and  investment  costs  change  over  time,  however,  the  firm  will  generally  not  earn  the  target 
 rate  of  return.  In  these  cases,  a  correction  factor  must  be  applied  to  the  TELRIC  price  path  in  order  for  revenues  to  exactly  recover  investment  cost,  including  the  target  rate  of 
 return.  When  investment  costs  are  falling  by  11%  per  year  (as  is  assumed  for  switching  assets  in  the  FCC  Synthesis  Model),  the  TELRIC  correction  factor  is  approximately  50%. 
 That  is,  switching  prices  should  be  increased  by  50%  from  those  suggested  by  Synthesis  Model  runs.  When  investment  costs  are  rising  at  the  rate  of  inflation,  assumed  to  equal 
 3%  per  year,  the  TELRIC  correction  factor  is  -20%.  In  this  case,  TELRIC  prices  should  be  reduced  by  20%  from  those  suggested  by  model  outputs. 


 Section  3  of  the  paper  considered  a  firms  cost  minimizing  investment  decisions  over  time.  Two  different  assumptions  about  asset  lives  were  analyzed.  Under  one 
 scenario,  characterized  as  light  bulb  performance,  assets  have  a  fixed  and  known  physical  life.  In  a  second  scenario  the  assets  last  forever,  but  due  to  technological  change 
 it  is  assumed  that  they  will  be  replaced  by  a  new  generation  of  assets  regardless  of  the  date  at  which  the  original  assets  were  put  into  service.  In  both  scenarios  the  optimal 
 investment  path  and  the  implied  utilization  rates  were  derived  under  a  variety  of  assumptions  about  the  relevant  input  parameters.  TELRIC  pricing  rules,  as  well  as  a 
 contestable  pricing  rule,  were  considered. 


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46
 References 
 Alleman,  J.,  The  Poverty  of  Cost  Models,  the  Wealth  of  Real  Options,  Chapter  10  (pp.  159-  178)  in  Real  Options:  The  New  Investment  Theory  and  its  Implications  for 
 Telecommunications  Economics  (J.  Alleman  and  E.  Noam,  eds.),  Boston:  Kluwer  Academic  Publishers  (1999). 


 Biglaiser,  G.  and  M.  Riordan,  Dynamics  of  Price  Regulation,  Rand  Journal  of  Economics  31:  4  (2000),  744-  67. 
 Federal  Communications  Commission,  Implementation  of  the  Competition  Provisions  of  the  Telecommunications  Act  of  1996,  First  Report  and  Order  (Local  Competition  Order), 
 CC  Docket  No.  96-  988,  11  FCC  Rcd  15499  (1996). 
 Federal  Communications  Commission,  Federal-  State  Joint  Board  on  Universal  Service,  Forward-  Looking  Mechanism  for  High  Cost  Support  for  Non-  Rural  LECs,  Tenth  Report 
 and  Order,  CC  Docket  Nos.  96-  45,  97-  160,  FCC  99-  304  (1999). 
 Hausman,  J.  A.,  Valuing  the  Effect  of  Regulation  on  New  Services  in  Telecommunications,  Brookings  Papers  on  Economic  Activity  (Microeconomics) 
 (1997),  1-  38. 
 Kahn,  A.,  Whom  the  Gods  would  Destroy,  or  How  Not  to  Deregulate,  AEI-  Brookings  Joint  Center  for  Regulatory  Studies  (2001). 


 Kahn,  A.,  Letting  Go:  Deregulating  the  Process  of  Deregulation,  East  Lansing,  MI:  Institute  of  Public  Utilities  and  Network  Industries,  Michigan  State  University  (1998). 
 Kahn,  A.,  T.  J.  Tardiff,  and  D.  L.  Weisman,  The  1996  Telecommunications  Act  at  Three  Years:  An  Economic  Evaluation  of  its  Implementation  by  the  FCC,  Information 
 Economics  and  Policy  11:  4  (1999),  319-  65. 
 Mandy,  D.  M.,  TELRIC  Pricing  with  Vintage  Capital,  Journal  of  Regulatory  Economics  22:  3  (2002),  215-  249. 


 Salinger,  M.  A.,  Lowering  Prices  with  Tougher  Regulation:  Forward-  Looking  Costs,  Depreciation,  and  the  Telecommunications  Act  of  1996,  in  Michael  A.  Crew,  ed,. 
 Regulation  under  Increasing  Competition,  Boston:  Kluwer  (1999). 
 Salinger,  M.  Regulating  Prices  to  Equal  Forward-  Looking  Costs:  Cost-  Based  Prices  or  Price-  Based  Costs,  Journal  of  Regulatory  Economics  14  (1998),  149-  64. 


 Sidak,  J.  G.  and  D.  F.  Spulber,  Deregulatory  Takings  and  the  Regulatory  Contract,  Cambridge:  Cambridge  University  Press  (1998). 


 44 
47
 Stokey,  N.  L.  and  R.  E.  Lucas,  Recursive  Methods  in  Economic  Dynamics,  Cambridge:  Harvard  University  Press  (1989). 
 Tardiff,  T.  J.,  Pricing  Unbundled  Network  Elements  and  the  FCCs  TELRIC  Rule:  Economic  and  Modeling  Issues,  Review  of  Network  Economics  1:  2  (2002),  132-  46. 
 Telecommunications  Act  of  1996,  Pub.  L.  No.  104,  110  Stat.  56  (1996  Act),  47  U.  S.  C. 
 Telcordia  Technologies,  Telcordia  Notes  on  the  Networks,  Special  Report  SR-  2275,  Issue  4,  October  2000. 


 Weingarten,  M.  and  B.  Stuck,  Why  ILECs  Wont  Invest,  Business  Communications  Review  58  (2003),  54-  58. 
 Weisman,  D.  L.,  Did  the  High  Court  Reach  an  Economic  Low  in  Verizon  v.  FCC?,  Review  of  Network  Economics  1:  2  (2002),  90-  105. 
 Weisman,  D.  L.,  The  (In)  Efficiency  of  the  Efficient  Firm  Cost  Standard,  The  Antitrust  Bulletin  XLV:  1  (2000),  195-  211. 


 45 
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 Working  Papers  Series  Office  of  Strategic  Planning  and  Policy  Analysis 
 Federal  Communications  Commission 
 Unlicensed  and  Unshackled:  A  Joint  OSP-  OET  White  Paper  on  Unlicensed  Devices  and  Their  Regulatory  Issues,  by  Kenneth  Carter,  Office  of  Strategic  Planning  and  Policy  Analysis,  Working  Paper  #39,  May 
 2003;  pp.  67 
 A  Proposal  for  a  Rapid  Transition  to  Market  Allocation  of  Spectrum,  by  Evan  Kwerel  and  John  Williams,  Office  of  Plans  and  Policy;  Working  Paper  #38,  November  2002;  pp.  54 


 Broadcast  Television:  Survivor  in  a  Sea  of  Competition,  by  Jonathan  Levy,  Deputy  Chief  Economist  Marcelino  Ford-  Livene,  Office  of  Plans  and  Policy  and  Anne  Levine,  Media  Bureau;  Working  Paper  #37, 
 September  2002;  pp.  139 
 The  Potential  Relevance  to  the  United  States  of  the  Eurpoean  Unions  Newly  Adopted  Regulatory  Framework  for  Telecommunications,  by  J.  Scott  Marcus,  Office  of  Plans  and  Policy;  Working 
 Paper  #36,  July  2002;  pp.  32 
 Horizontal  Concentration  in  the  Cable  Television  Industry:  An  Experimental  Analysis,  by  Mark  M.  Bykowsky,  William  W.  Sharkey;  Office  of  Plans  and  Policy,  and  Anthony  M.  Kwasnica; 
 Pennsylvania  State  University,  Smeal  College  of  Business  Administration;  Working  Paper  #35,  June  2002;  (Revised  July  2002);  pp.  115 


 A  Competitively  Neutral  Approach  to  Network  Interconnection,  by  Jay  M.  Atkinson,  Christopher  C.  Barnekov;  Economists  in  the  Competitive  Pricing  Division,  Common  Carrier  Bureau; 
 Working  Paper  #34,  December  6,  2000;  pp.  36 
 Bill  and  Keep  at  the  Central  Office  As  the  Efficient  Interconnection  Regime,  by  Patrick  DeGraba,  Deputy  Chief  Economist;  Working  Paper  #33,  December  2000.  pp.  43 


 The  Digital  Handshake:  Connecting  Internet  Backbones,  Michael  Kende,  Director  of  Internet  Policy  Analysis;  Working  Paper  #32,  September  2000.  pp.  50 
 The  FCC  and  the  Unregulation  of  the  Internet,  by  Jason  Oxman,  Counsel  for  Advanced  Communications;  Working  Paper  #31,  July  1999.  pp.  29 
 Internet  Over  Cable:  Defining  the  Future  In  Terms  of  the  Past,  by  Barbara  Esbin,  Associate  Bureau  Chief,  Cable  Service  Bureau;  Working  Paper  #30,  August  1998.  pp.  130 
 Digital  Tornado:  The  Internet  and  Telecommunications  Policy,  by  Kevin  Werbach;  Working  Paper  #29,  March  1997.  pp.  98 
 Putting  It  All  Together:  The  Cost  Structure  of  Personal  Communications  Services,  by  David  P.  Reed;  Working  Paper  #28,  November  1992.  NTIS  PB93  114882  pp.  86 
 Changing  Channels:  Voluntary  Reallocation  of  UHF  Television  Spectrum,  by  Evan  R.  Kwerel  and  John  R.  Williams;  Working  Paper  #27,  November  1992.  NTIS  PB93  114874  pp.  146 
 Broadcast  Television  in  a  Multichannel  Marketplace,  by  Florence  Setzer  and  Jonathan  Levy;  Working  Paper  #26,  June  1991.  NTIS  #PB91  201749;  $23.  00;  pp.  180 
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