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 Federal  Communications  Commission  FCC  01-  49 
 Before  the  Federal  Communications  Commission 
 Washington,  D.  C.  20554 
 In  the  Matter  of 
 Implementation  of  Section  3  of  the  Cable 
 Television  Consumer  Protection  and  Competition 
 Act  of  1992 


 Statistical  Report  on  Average  Rates  for  Basic 
 Service,  Cable  Programming  Services,  and 
 Equipment 


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 )  ) 
 )  ) 
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 MM  Docket  No.  92-  266 


 REPORT  ON  CABLE  INDUSTRY  PRICES 
 Adopted:  February  8,  2001  Released:  February  14,  2001 
 By  the  Commission: 


 I.  INTRODUCTION 
 1.  Section  623(  k)  of  the  Communications  Act  of  1934  (  Communications  Act),  1  as 
 amended  by  the  Cable  Television  Consumer  Protection  and  Competition  Act  of  1992  (  1992  Cable  Act, 
 47  U.  S.  C.    521  et  seq),  requires  the  Commission  to  publish  annually  a  statistical  report  that  compares 
 prices  charged  by  cable  operators  facing  effective  competition  2  with  those  of  operators  not  facing 
 effective  competition  for  the  delivery  of  basic  service,  other  cable  programming  services,  and  equipment.  3 
 This  2000  Report  is  issued  in  compliance  with  that  statutory  obligation.  4 


 1  47  U.  S.  C.    543  et  seq. 
 2  Under  the  1992  Cable  Act,  effective  competition  is  defined  to  exist:  (1)  where  the  franchise  area  is  served  by  at 
 least  two  unaffiliated  multichannel  video  programming  distributors  (  MVPDs),  each  of  which  offers  comparable 
 video  programming  to  at  least  50%  of  households,  and  at  least  15%  of  households  subscribing  to  programming 
 services  offered  by  an  MVPD  subscribe  to  services  other  than  those  offered  by  the  largest  MVPD  (referred  to  herein 
 as  head-  to-  head  competition  or  the  overbuild  test);  (2)  where  fewer  than  30%  of  the  households  in  the  franchise 
 area  subscribe  to  the  cable  service  of  a  cable  system  (the  low  penetration  test);  or  (3)  where  a  municipal  cable 
 system  offers  service  to  at  least  50%  of  the  households  in  the  franchise  area  (the  municipal  test).  Communications 
 Act    623(  l)(  1)(  A)(  B)(  C),  47  U.  S.  C.    543(  l)(  1)(  A)(  B)(  C).  The  Telecommunications  Act  of  1996  added  a  fourth 
 prong,  finding  that  effective  competition  exists  where  a  local  exchange  carrier  (  LEC)  or  its  affiliate  (or  any 
 MVPD  using  the  facilities  of  such  carrier  or  its  affiliates)  offers  video  programming  services  (other  than  direct-  to-home 
 satellite  services)  in  the  franchise  area  of  an  unaffiliated  cable  operator,  but  only  if  the  services  so  offered  are 
 comparable  to  the  services  provided  by  the  cable  operator  (the  LEC  test).  Communications  Act,    623(  l)(  1)(  D), 
 47  U.  S.  C.    543(  l)(  1)(  D). 


 3  Pub.  L.  No.  102-  385,  106  Stat.  1460  (1992),    623(  k),  47  U.  S.  C.  534(  k)  (1992).  The  1992  Cable  Act  amends  Title 


 VI  of  the  Communications  Act  of  1934.  The  1992  Cable  Act  defines  the  term  basic  cable  service  as  any  service 
 tier  which  includes  the  retransmission  of  local  television  broadcast  signals.  Cable  programming  service  is  defined 
 as  any  video  programming  provided  over  a  cable  system  regardless  of  service  tier  other  than  (A)  video 
 programming  carried  on  the  basic  service  tier,  and  (B)  video  programming  offered  on  a  per  channel  or  per  program 
 basis.  See  47  U.  S.  C.    522(  3)  and  47  U.  S.  C.    543(  l)(  2). 


 4  For  the  results  of  previous  surveys,  see  Implementation  of  Section  3  of  the  Cable  Television  Consumer  Protection 


 and  Competition  Act  of  1992  (Statistical  Report  on  Average  Prices  for  Basic  Service,  Cable  Programming  Services, 
 (continued.) 
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 Federal  Communications  Commission  FCC  01-  49 
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 2.  The  information  and  analysis  provided  in  this  Report  are  based  upon  the  Commissions 
 2000  survey  of  cable  industry  prices  (  Survey).  On  July  3,  2000,  the  Commission  released  an  Order 
 directing  cable  operators  5  selected  as  part  of  a  random  sample  representative  of  the  industry  to  respond  to 
 Commission  data  requests,  pursuant  to  Section  623(  k)  of  the  Communications  Act,  no  later  than  August 
 15,  2000.  6  The  Survey  requested  data  from  selected  cable  operators  as  of  July  1,  1999  and  July  1,  2000. 
 Limited  amounts  of  data  were  requested  as  of  July  1,  1998.  The  Survey  collected  information  about  each 
 operators  regulatory  status,  monthly  charges  for  the  basic  service  tier  (  BST)  and  cable  programming 
 service  tiers  (  CPSTs),  monthly  charges  for  equipment,  installation  fees,  reconnect  fees,  and  fees  for  tier 
 changes. 


 3.  The  Survey  also  sought  information  needed  to  determine  average  rates  per  channel  and 
 to  explain  changes  in  rates  between  the  Survey  dates.  The  Survey  enables  the  Commission  to  compare 
 the  prices  charged  by  two  groups  of  cable  operators:  (1)  cable  operators  that  face  effective  competition  as 
 defined  by  the  Communications  Act,  referred  to  as  the  competitive  group;  and  (2)  cable  operators  that 
 do  not  face  effective  competition,  referred  to  as  the  noncompetitive  group.  Within  the  noncompetitive 
 group,  information  was  collected  from  both  operators  that  were  regulated  and  unregulated.  7  We  also 
 sought  to  gather  information  about  the  price  and  availability  of  services  such  as  digital  tiers,  Internet 
 access,  and  telephony  offered  by  cable  operators.  In  addition,  we  sought  to  gather  information  and 
 analyze  the  effect  of  clustering  (the  practice  of  operating  commonly  owned  cable  systems  in  close 
 proximity  on  an  integrated  basis  through  the  use  of  shared  personnel  and/  or  facilities).  Finally,  we  sought 
 information  on  the  number  of  Direct  Broadcast  Satellite  (  DBS)  subscribers  in  each  cable  operators 
 franchise  area  in  order  to  determine  if  DBS  penetration  has  had  an  effect  on  the  demand  for  cable  as  well 
 as  on  the  monthly  charges  for  cable  service.  The  major  findings  of  the  Survey  are  summarized  below. 


 II.  SUMMARY  OF  FINDINGS 
 4.  Competitive  operators  increased  average  monthly  rates  for  BST,  CPST,  and  equipment 
 by  5.8%  during  the  12-  month  period  ending  July  1,  2000;  noncompetitive  operators  also  increased  rates 
 by  5.8%,  over  the  same  period.  These  increases  compared  with  increases  of  4.5%  and  5.2%  for  the 
 competitive  and  noncompetitive  groups,  respectively,  for  the  year  ending  in  July  1,  1999. 


 (continued  from  previous  page) 
 and  Equipment),  Report  on  Cable  Industry  Prices,  15  FCC  Rcd  10927  (2000)  ("  1999  Report");  14  FCC  Rcd  8331 
 (1999)  (  1998  Report);  12  FCC  Rcd  22756  (1997)  (  1997  Report);  12  FCC  Rcd  3239  (1997)  (  1996  Report); 
 Report  on  the  Cable  Services  Bureaus  Survey  on  the  Rate  Impact  of  the  Federal  Communications  Commissions 
 Revised  Rate  Regulations,  9  FCC  Rcd  5484  (1994);  FCC,  Cable  Services  Bureau,  Report  and  Summary  (released 
 Feb.  22,  1994);  Report  and  Order  and  Further  Notice  of  Proposed  Rulemaking,  8  FCC  Rcd  5801  (1993);  Second 
 Order  on  Reconsideration,  Fourth  Report  and  Order,  and  Fifth  Notice  of  Proposed  Rulemaking,  8  FCC  Rcd  5361 
 (1993)  (  Benchmark  Order). 


 5  For  purposes  of  this  report,  a  cable  company  is  considered  to  be  an  operator  for  each  Community  Unit 


 Identification  Number  (  CUID)  it  serves.  Thus,  if  a  company  serves  50  CUIDs  that  are  included  in  the  Survey,  that 
 company  will  be  referred  to  herein  as  50  operators.  A  CUID  is  a  unique  identification  code  assigned  by  the 
 Commission  to  a  single  operator  within  a  community  unless  the  operator  also  serves  a  separate  area  within  the  same 
 community.  In  that  case,  there  would  be  two  separate  CUIDs,  one  for  each  area  served. 


 6  Implementation  of  Section  3  of  the  Cable  Television  Consumer  Protection  and  Competition  Act  of  1992,  MM 


 Docket  No.  92-  266,  Order,  15  FCC  Rcd  11473  (2000). 
 7  CPST  regulation  ended  on  March  31,  1999.  The  Commission  no  longer  has  authority  to  receive  or  act  upon 


 complaints  regarding  rate  increases  that  occurred  after  March  31,  1999.  Local  communities,  however,  continue  to 
 have  the  authority  to  regulate  the  rates  of  the  basic  service  tier  and  equipment.  See  47  U.  S.  C.    543(  c)(  4),  as 
 amended,  by  Telecommunications  Act  of  1996,  Pub.  L.  No.  104-  104    301(  a)(  1),  110  Stat.  115  (1996). 
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 Federal  Communications  Commission  FCC  01-  49 
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 5.  For  the  12  months  ending  July  1,  2000,  competitive  and  noncompetitive  operators 
 attributed  44.1%  and  41.4%,  respectively,  of  their  rate  increases  to  higher  programming  costs.  In  order  of 
 importance,  other  specific  factors  that  reportedly  led  to  price  increases  were  system  upgrades,  equipment 
 cost  increases,  inflation,  and  increased  costs  for  programming  associated  with  newly  added  channels.  The 
 competitive  group  attributed  21.5%,  and  the  noncompetitive  group  7.5%,  of  their  rate  increases  to 
 unspecified  costs.  Competitive  and  noncompetitive  operators  also  explain  that  9.  6%  and  13.  4%, 
 respectively,  of  their  rate  increases  were  not  identified  with  specific  cost  changes. 


 6.  Since  their  percent  price  increases  were  equal,  the  difference  in  average  monthly  rates 
 for  BST,  CPST,  and  equipment  (typically  a  converter  and  remote)  between  competitive  and 
 noncompetitive  operators  (the  competitive  differential)  also  stayed  the  same  at  5.3%.  On  July  1,  1999, 
 competitive  and  noncompetitive  cable  operators  charged  $30.63  and  $32.25,  respectively,  a  5.  3% 
 differential  between  the  two  groups.  By  July  1,  2000,  cable  operators  facing  competition  were  charging, 
 on  average,  $32.40  while  operators  not  facing  competition  were  charging  $34.11,  also  a  5.  3% 
 differential.  8 


 7.  Within  the  overall  average  monthly  rate,  the  rates  of  increase  for  BST  and  CPST  services 
 were  similar  for  the  competitive  group,  as  BST  rates  rose  6.1%  and  CPST  rates  rose  5.9%.  For  the 
 noncompetitive  group,  CPST  rates  rose  faster  than  BST  rates.  The  average  rate  for  BST  service  increased 
 by  2.3%  between  July  1,  1999  and  July  1,  2000,  while  the  average  rate  for  CPST  service  increased  by 
 8.3%. 


 8.  Both  competitive  and  noncompetitive  groups  increased  the  average  number  of  channels 
 offered  on  BST  and  CPST  service  during  the  12  months  ending  July  1,  2000.  The  competitive  group 
 averaged  59.9  channels  and  the  noncompetitive  group  averaged  54.8  channels  as  of  July  1,  2000, 
 increases  in  channel  offerings  of  4.0%  and  5.4%,  respectively.  9  Despite  an  increased  average  number  of 
 channels,  the  per  channel  rate  for  the  competitive  group  was  unchanged  at  $0.57  over  the  12  months 
 ending  July  1,  2000,  and  increased  for  the  noncompetitive  group  from  $0.65  to  $0.66  per  channel  over 
 that  period. 


 9.  Many  cable  operators  offered  digital  and  non-  video  services  in  2000.  As  of  July  1,  2000, 
 the  percentage  of  surveyed  cable  operators  that  offered  a  digital  programming  tier  doubled  from  27%  a 
 year  earlier  to  54%.  Further,  47%  offered  Internet  services  and  7%  offered  telephone  service.  Clustering 
 did  not  lead  to  increases  in  the  availability  of  Internet  or  telephony  services  or  a  reduction  in  the  average 
 monthly  rate  charged  for  cable  services  when  compared  with  non-  clustered  operators. 


 10.  Revenue  from  non-  video  sources  increased  as  a  percent  of  total  revenue  from  1.5%  to 
 3.5%  between  1999  and  2000.  This  may  be  attributed  to  the  growing  importance  of  these  services  and  the 


 8  Ideally,  when  calculating  price  changes,  we  would  like  to  take  into  account  changes  in  the  quantity  and  quality  of 
 service  provided.  In  the  case  of  cable  rates,  however,  that  is  difficult  to  do  because  both  the  quantity  and  quality  of 
 services  provided  have  changed  significantly  in  recent  years  as  cable  operators  have  upgraded  their  systems 
 capacity.  Increased  system  capacity,  typically,  results  in  additional  channels  of  service  and  may  also  result  in 
 improved  signal  quality,  improved  system  reliability  and  the  provision  of  new  services.  Therefore,  we  report 
 average  monthly  rates  on  a  per  channel  basis  as  a  proxy  for  quality  adjusted  price  changes.  See    8,  infra. 


 9  These  figures  only  include  channels  devoted  to  BST  and  the  most  highly  subscribed  CPST  service,  and  do  not 


 include  channels  devoted  to  premium  or  pay-  per-  view  services  (i.  e.,  services  offered  on  a  per  channel  or  per 
 program  basis),  digital  services,  or  non-  video  services.  Taking  into  account  these  additional  channels  and  unused 
 capacity,  the  average  channel  capacity  reported  by  the  competitive  group  rose  from  96.  8  channels  to  100.  5  channels, 
 an  increase  of  3.  8%.  Similarly,  average  channel  capacity  for  the  noncompetitive  group  rose  from  85.  2  channels  to 
 90.  3  channels,  an  increase  of  6.  0%.  Of  the  operators  in  our  Survey,  9.  1%  of  competitive  and  11.  4%  of 
 noncompetitive  operators  reportedly  increased  capacity  during  the  last  12  months. 
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 Federal  Communications  Commission  FCC  01-  49 
 4 
 increasing  number  of  operators  offering  Internet  and  telephony  services.  Of  the  cable  operators  surveyed, 
 52%  received  revenue  from  non-  video  subscriber  services  during  the  12-  month  period  ending  July  2000, 
 an  increase  from  the  32%  who  reported  receiving  such  revenue  during  the  12-  month  period  ending  July 
 1999. 


 11.  Operators  also  reported  that  DBS  service  has  captured,  on  average,  an  estimated  14.  7% 
 share  of  television  households  in  their  service  areas.  In  addition,  we  found  that  the  demand  for  cable 
 service  is  somewhat  sensitive  to  changes  in  monthly  cable  rates. 


 III.  SURVEY  METHODOLOGY 
 A.  Sample 
 12.  To  compare  the  average  prices  of  the  competitive  and  non-  competitive  CUIDs,  we 
 selected  a  sample  from  each  group  independently.  The  competitive  CUIDs  in  our  sampling  universe 
 consisted  of  575  cable  operators,  including  those  found  by  the  Commission  to  face  effective  competition 
 and  the  cable  operators  that  are  their  competitors.  To  gain  more  precise  estimates,  we  used  a  stratified 
 sampling  methodology.  The  575  competitive  CUIDs  were  divided  into  five  subgroups  (or  strata) 
 according  to  the  test  by  which  effective  competition  was  determined.  The  five  strata  were  (1)  local 
 exchange  carrier  (  LEC);  (2)  wireline  overbuild;  (3)  DBS  overbuild  (i.  e.,  where  the  competitor  is  a  DBS 
 operator);  (4)  low  penetration;  and  (5)  municipal.  10 


 13.  We  selected  a  total  of  352  CUIDs  among  these  five  subgroups  to  receive  our 
 questionnaire.  11  Selections  included  all  15  of  the  CUIDs  in  the  municipal  subgroup  in  order  to  have 
 enough  observations  within  that  subgroup  for  adequate  statistical  precision.  The  proportion  of  subscribers 
 nationwide  within  each  subgroup  determined  the  division  of  these  selections  among  the  remaining  four 
 subgroups.  High  proportions  of  subscribers  resulted  in  100%  sampling  of  the  193  CUIDs  in  the  LEC 
 subgroup  and  the  61  CUIDs  in  the  wireline  overbuild  subgroup.  The  remaining  selections  were  divided 
 among  the  low  penetration  and  DBS  overbuild  subgroups.  Sixty-  seven  out  of  176  CUIDs  from  the  low 
 penetration  subgroup,  and  16  out  of  130  CUIDs  in  the  DBS  overbuild  subgroup,  were  randomly  chosen. 


 14.  The  noncompetitive  group  in  our  sampling  universe  included  31,006  CUIDs.  12  We 
 divided  these  CUIDs  into  five  strata  by  cable  system  size.  13  A  sample  of  CUIDs  not  stratified  by  system 


 10  The  overbuild  subcategory  is  disaggregated  into  wireline  overbuild  and  DBS  overbuild  subcategories  because  the 
 characteristics  of  each  subgroup  are  somewhat  different.  While  there  are  twice  as  many  CUIDs  where  the  competitor 
 is  a  DBS  provider  than  a  wireline  overbuilder,  these  operators  tend  to  have  fewer  subscribers  than  wireline  overbuild 
 operators.  Had  we  not  sampled  the  DBS  and  wireline  overbuilds  separately,  a  disproportionate  weight  would  have 
 been  given  to  the  DBS  overbuild  component  relative  to  the  number  of  customers  served. 


 11  This  number  was  derived  from  a  standard  formula  used  to  determine  sample  size.  See  Mandel,  B.  J.,  Statistics 
 For  Management,  1984  at  258  (  Mandel). 
 12  Source:  FCC  Form  325.  It  should  be  noted  that  a  cable  system  might  contain  more  than  one  CUID.  Because  we 


 stratified  by  system  size,  it  was  necessary  to  have  a  system  subscriber  count  for  each  CUID  in  our  universe  from 
 which  we  selected  our  sample.  Thus,  we  eliminated  1,340  CUIDs  for  which  we  did  not  have  system  subscriber 
 counts  from  a  group  of  32,346  noncompetitive  CUIDs,  leaving  31,  006  CUIDs  from  which  to  select  our  sample  of 
 noncompetitive  CUIDs. 


 13  These  size  strata  thresholds  do  not  reflect  the  statutory  definition  of  a  small  cable  system,  company  or  operator. 
 The  Code  of  Federal  Regulations  defines  a  small  system  as  a  cable  television  system  that  serves  15,  000  or  fewer 
 subscribers.  A  small  cable  company  is  defined  as  a  cable  television  operator  that  serves  a  total  of  400,000  or 
 fewer  subscribers  over  one  or  more  cable  systems.  A  small  cable  operator  is  defined  as  an  operator  that,  directly 
 or  through  an  affiliate,  serves  in  the  aggregate  fewer  than  one  percent  of  all  subscribers  in  the  United  States  and  is 
 (continued.) 
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 Federal  Communications  Commission  FCC  01-  49 
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 size  would  have  placed  a  disproportionately  greater  emphasis  on  smaller  systems  relative  to  the  number 
 of  subscribers  the  smaller  systems  serve.  14  CUIDs  with  50,000  or  more  subscribers  comprised  the  very-large 
 stratum.  CUIDs  with  less  than  50,000  subscribers  belonging  to  systems  exceeding  50,000 
 subscribers  comprised  the  large  stratum.  The  medium-  sized  stratum  consisted  of  CUIDs  in  systems 
 ranging  from  10,000  through  49,999  subscribers.  CUIDs  in  systems  with  at  least  1,  000  subscribers  and 
 less  than  10,000  subscribers  were  placed  in  the  small  group.  The  very-  small  stratum  was  comprised  of 
 CUIDs  in  systems  with  less  than  1,000  subscribers. 


 15.  We  selected  a  total  of  460  noncompetitive  CUIDs  to  receive  our  questionnaire.  15 
 Selections  included  all  109  CUIDs  in  the  very-  large  stratum  because  of  the  large  number  of  subscribers 
 these  CUIDs  serve.  The  proportion  of  subscribers  nationwide  primarily  determined  the  selections  among 
 the  remaining  four  stratum.  We  increased  the  number  of  selections  in  the  very-  small  stratum,  however, 
 from  17  CUIDs  (on  the  basis  of  proportion  of  subscribers)  to  35  CUIDs.  This  was  necessary  for 
 statistical  precision  given  the  historically  high  variance  in  rates  among  CUIDs  in  this  stratum.  The 
 remaining  CUIDs  were  divided  and  randomly  selected  from  the  small,  medium,  and  large  subgroups. 
 Sixty-  seven  small  CUIDs,  137  medium  CUIDs,  and  112  large  CUIDs  were  selected. 


 16.  Of  the  812  survey  questionnaires  mailed  to  cable  operators  from  both  groups, 
 respondents  returned  762  completed  questionnaires  to  the  Commission  in  time  to  be  included  in  the 
 analysis.  Of  these,  721  met  minimum  necessary  data  requirements.  16  The  remaining  41  lacked  sufficient 
 information  to  be  included  in  the  analysis.  As  of  July  1,  2000,  operators  serving  the  721  CUIDs  included 
 in  the  analysis  served  a  total  of  13.9  million  subscribers,  or  20.5%  of  the  67.7  million-  cable  subscribers 
 nationwide.  17 


 17.  Competitive  cable  operators  submitted  318  usable  questionnaires.  These  318  respondents 
 served  approximately  2.6  million  subscribers,  or  3.8%  of  all  cable  subscribers.  Of  these,  248  respondents 
 report  facing  direct  competition  in  their  geographic  area,  with  67  meeting  the  overbuild  test  (including 
 both  DBS  and  wireline  overbuilds)  and  181  meeting  the  LEC  test.  Of  the  remaining  respondents  in  the 
 competitive  group,  57  served  fewer  than  30%  of  the  households  in  their  service  area  (thereby  meeting  the 
 low  penetration  test)  and  13  CUIDs  are  served  by  the  municipality  in  their  service  area  (thereby  meeting 
 the  municipal  test). 


 18.  Noncompetitive  cable  operators  submitted  the  remaining  403  usable  responses.  These 
 respondents  provide  service  to  11.3  million  subscribers,  or  approximately  16.7%  of  all  cable  subscribers. 
 See  Attachment  A  for  further  statistical  information  about  the  sample. 


 (continued  from  previous  page) 
 not  affiliated  with  any  entity  or  entities  whose  gross  annual  revenues  in  the  aggregate  exceed  $250,000,000.  See  47 
 CFR    76.  901.  See  also  Implementation  of  Sections  of  the  Cable  Television  Consumer  Protection  and  Competition 
 Act  of  1992:  Rate  Regulation,  Sixth  Report  and  Order  and  Eleventh  Order  on  Reconsideration,  10  FCC  Rcd  7393 
 (1995)  ("  Small  System  Order"). 


 14  See  Footnote  23  for  the  rationale  of  using  system  versus  CUID  size. 


 15  See  Footnote  11,  supra. 
 16  In  order  to  be  included  in  the  statistical  analysis,  respondents  must  have  provided  the  average  monthly  charge  and 
 number  of  channels  offered  as  of  July  1998,  1999,  and  2000.  See  Attachment  A1  for  specific  response  rates  and 
 observations. 


 17  Total  cable  subscribers  are  as  of  June  30,  2000.  See  Paul  Kagan  Associates,  Inc.,  Cable  Industry  10-  Year 


 Projections,  Cable  TV  Investors,  June  19,  2000. 
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 B.  Variables 
 19.  We  focused  our  analysis  on  six  variables,  and  calculated  an  average  for  each  variable  by 
 competitive  status  as  well  as  size.  The  variables  are:  (1)  average  monthly  rate  for  BST  and  CPST 
 programming  services;  (2)  average  monthly  charge  for  equipment;  (3)  average  monthly  rate  for 
 programming  services  and  equipment;  (4)  average  number  of  channels;  (5)  average  monthly  rate  per 
 channel;  and  (6)  average  monthly  rate  per  satellite  channel.  We  describe  each  variable  below. 


 Average  Monthly  Rate  for  Programming  Services  (BST  and  CPST).  This  variable  is  the  monthly 
 rate  paid  by  subscribers  for  the  BST  18  and  the  most  highly  subscribed  CPST.  19  It  excludes 
 premium,  a  la  carte,  and  pay-  per-  view  services,  and  digital  tiers.  Additional  CPSTs  beyond  the 
 most  highly  subscribed  are  also  excluded. 


 Average  Monthly  Charge  for  Equipment.  This  variable  is  the  average  monthly  charge  paid  by 
 subscribers  for  a  converter  (either  addressable  or  non-  addressable)  and  remote  control  unit.  It 
 equals  the  monthly  charge  for  a  remote  plus  the  monthly  rate  for  the  type  of  converter  purchased 
 by  the  largest  number  of  subscribers.  20 


 Average  Monthly  Rate  (for  BST,  CPST,  and  Equipment).  This  variable  equals  the  sum  of  the 
 monthly  programming  service  and  equipment  charges.  It  represents  the  rate  that  a  typical 
 subscriber  pays  for  BST,  CPST  service,  and  equipment. 


 Average  Number  of  Channels  (BST  and  CPST).  This  variable  is  the  average  number  of  channels 
 a  typical  subscriber  receives  on  the  BST  and  most  highly  subscribed  CPST.  As  with  the  monthly 
 rate,  this  variable  excludes  channels  devoted  to  premium,  a  la  carte,  and  pay-  per-  view  services, 
 digital  tiers,  and  additional  CPSTs.  We  also  report  the  average  number  of  satellite  channels, 
 which  is  a  subset  of  all  channels  and  does  not  include  local  broadcast,  PEG,  or  other  local 
 origination  channels  or  services. 


 Average  Monthly  Rate  Per  Channel  (BST  and  CPST).  This  variable  is  the  programming  services 
 rate  divided  by  the  average  number  of  channels  offered.  21 


 18  The  BST  in  our  Survey  is  defined  as  the  package  of  channels  (or  tier)  that  includes  signals  from  local  television 
 broadcast  stations  (such  as  affiliates  of  the  major  networks,  independent  stations,  and  noncommercial  stations), 
 public,  educational,  and  governmental  (  PEG)  channels,  and  some  satellite  channels. 


 19  The  CPST  is  defined  as  any  package  or  tier  of  channels  other  than  BST  or  programming  offered  separately  as  pay-per- 


 channel  programming  or  pay-  per-  program  services.  Some  operators  offer  more  than  one  CPST  and  in  such 
 cases  we  use  only  data  from  the  CPST  with  the  greatest  number  of  subscribers.  Thus,  we  refer  to  the  CPST  in  our 
 analysis  as  most  highly  subscribed  CPST.  See  note  3. 


 20  We  do  not  report  separate  figures  for  a  converter  and  a  remote  since  a  large  proportion  of  cable  operators  do  not 
 distinguish  customers  by  their  rental  of  a  particular  type  of  converter  or  remote. 
 21  The  value  of  cable  services  can  be  measured  in  various  ways.  Some  analysts  have  suggested  that  the  average 


 number  of  channels  (or  satellite  channels)  received  by  subscribers,  along  with  their  respective  per  channel  rates,  are 
 an  appropriate  measure  of  value.  Alternatively,  it  has  been  suggested  that  an  increase  in  the  number  of  channels 
 (satellite  or  otherwise)  may  not  be  similarly  valued  by  all  subscribers,  or  that  as  more  channels  are  added,  the 
 additional  channels  have  a  declining  marginal  value.  Because  of  the  difficulty  of  obtaining  consumer  valuation  data, 
 our  survey  did  not  specifically  seek  information  on  how  consumers  value  individual  channels  within  the  BST  and 
 CPST  packages  they  receive,  or  how  they  would  value  these  packages  if  given  the  option  of  receiving  fewer 
 channels  or  different  channels  than  those  offered.  We  report  on  the  average  monthly  rate  per  channel  as  well  as  the 
 average  monthly  rate  per  satellite  channel  in  order  to  facilitate  rate  comparisons  across  all  categories  of  operators 
 and  over  time. 
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 Average  Monthly  Rate  Per  Satellite  Channel  (BST  and  CPST).  This  variable  is  the  programming 
 services  rate  divided  by  the  average  number  of  BST  and  CPST  satellite  channels. 


 20.  In  addition  to  these  variables,  we  sought  information  on  the  availability  of  digital  tiers 
 and  non-  video  services  such  as  Internet  access  and  telephony.  We  also  sought  information  on  charges  for 
 installation,  reconnection,  and  tier  changes,  as  well  as  on  the  distribution  of  channels  among  the  major 
 categories  of  programming  (e.  g.,  news,  sports). 


 C.  Calculation  of  Price  Averages 
 21.  As  discussed  above,  we  used  a  stratified  sampling  methodology  to  gain  more  precise 
 estimates  of  average  prices.  22  The  competitive  group  was  stratified  according  to  the  test  by  which 
 effective  competition  was  determined,  and  the  noncompetitive  group  was  stratified  according  to  the 
 number  of  subscribers  in  the  system  to  which  the  CUID  belonged.  23  Price  averages  were  calculated  using 
 the  following  three  steps. 


 22.  First,  we  divided  the  Surveys  from  competitive  CUIDs  into  five  strata  by  type  of 
 competition  including  LEC,  wireline  overbuild,  DBS  overbuild,  low  penetration,  and  municipal.  Surveys 
 from  noncompetitive  CUIDs  were  divided  into  five  strata  by  system  size.  The  first  size  strata  (very  large) 
 includes  CUIDs  serving  50,000  or  more  subscribers.  The  second  strata  includes  CUIDs  serving  less  than 
 50,000  belonging  to  systems  that  serve  more  than  50,000  subscribers  (large).  The  remaining  three  strata 
 include  CUIDs  belonging  to  systems  serving  at  least  10,000  but  less  than  50,000  subscribers  (medium-sized), 
 at  least  1,000  but  less  than  10,000  subscribers  (small),  and  less  than  1,000  subscribers  (very 
 small).  Second,  we  calculated  a  price  average  for  each  of  the  six  primary  variables  in  each  stratum. 


 22  For  a  general  explanation  of  stratified  sampling  methodology,  see  William  G.  Cochran,  Sampling  Techniques, 
 Third  Edition,  at  87-  113.  The  use  of  statistics  as  an  analytical  tool  is  a  way  of  estimating  the  unknown  characteristics 
 of  a  population  by  examining  a  random  sample  selected  from  the  population.  Nevertheless,  the  average  monthly 
 rate  for  our  sample  probably  will  not  exactly  match  the  average  monthly  rate  for  the  entire  population,  even  though 
 our  sample  is  representative  of  the  entire  population  of  cable  CUIDs.  Rather,  the  average  monthly  rate  for  the 
 population  of  over  30,  000  CUIDs  will  fall  within  a  range  of  values  calculated  from  the  sample.  According  to 
 statistical  theory,  the  average  monthly  rate  for  the  population  of  30,  000  CUIDs  is  bounded  by  the  sample's  reported 
 average  plus  or  minus  1.  96  multiplied  by  the  standard  error  of  the  mean  (average).  This  will  give  us  a  95.  5% 
 confidence  level.  (A  95.  5%  confidence  level  means  that  if  multiple  samples  are  drawn  from  the  population,  the 
 estimated  statistic  [e.  g.,  a  mean  or  average]  will  lie  within  the  interval  for  95.  5%  of  the  samples,  and  outside  the 
 interval  for  4.  5%  of  the  samples.)  Using  this  method,  we  can  estimate  the  average  monthly  rate  for  the  population  of 
 30,000  CUIDs.  If,  for  example,  our  samples  reported  average  monthly  rate  is  $25.00  and  the  standard  error  is 
 $0.  50,  we  estimate  that  the  average  monthly  rate  lies  between  $24.  02  and  $25.  98  with  a  95.  5%  confidence  level. 
 We  arrive  at  the  low  end  of  the  range,  $24.02,  by  subtracting  1.  96  times  $0.  50  (the  standard  error)  from  $25.  00,  and 
 we  arrive  at  $25.  98,  the  high  end  of  the  range,  by  adding  1.96  times  $0.  50  to  $25.  00.  In  this  report,  the  standard 
 error  for  each  estimated  average  is  reported  in  Attachment  B.  See  also,  Kmenta,  J.,  Elements  of  Econometrics,  at 
 pages  70-  153  (  Kmenta)  and  Mandel  at  pages  238-  267,  for  a  further  explanation  of  sampling  methodology. 
 23  We  use  system  size  rather  than  CUID  size  to  determine  the  size  strata  because  system  size  provides  a  more 


 representative  classification  methodology.  For  instance,  a  system  with  more  than  50,  000  subscribers  in  total  may  be 
 made  up  of  several  CUIDs,  including  individual  community  units  with  very  few  subscribers.  In  that  case,  the  CUID 
 would  behave  like  a  large  system  because  its  monthly  rate,  number  of  channels  offered,  channel  capacity,  etc., 
 would  be  dictated  by  the  system,  not  the  community  unit  level.  Therefore,  it  is  more  appropriate  to  group  such  a 
 CUID  in  the  large  system  stratum  rather  than  the  small  system  stratum. 
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 23.  Third,  an  overall  average  for  each  primary  variable  was  calculated  individually  for  the 
 competitive  and  noncompetitive  groups.  For  each  group  and  primary  variable,  the  average  equaled  the 
 sum  of  the  weighted  averages  of  the  strata.  The  weight  given  to  the  average  of  each  stratum  was  the 
 proportion  of  subscribers  in  that  stratum  relative  to  the  group,  displayed  in  Attachment  1.  24  Of  the 
 subscribers  in  the  universe  of  competitive  CUIDs,  we  estimate  that  58.  5%  were  served  by  the  LEC 
 subgroup,  22.1%  by  the  wireline  overbuild  subgroup,  4.6%  by  the  DBS  overbuild  subgroup,  13.8%  by  the 
 low-  penetration  subgroup,  and  1.1%  by  operators  in  the  municipal  subgroup.  For  the  noncompetitive 
 group,  we  estimated  that  17.8%  of  subscribers  in  our  universe  were  served  by  the  very-  large  subgroup, 
 27.8%  by  the  large  subgroup,  34.3%  by  the  medium-  sized  subgroup,  16.6%  by  the  small  subgroup,  and 
 3.5%  were  served  by  the  very-  small  subgroup.  These  percentages  became  the  weights  used  to  calculate 
 the  overall  averages  for  the  competitive  and  noncompetitive  groups.  25 


 IV.  SURVEY  RESULTS 
 A.  Comparison  of  Competitive  and  Noncompetitive  Groups 
 24.  Table  1  shows  the  average  monthly  rates  for  the  competitive  and  noncompetitive  groups, 
 and  the  differential  between  these  two  groups,  as  of  July  1,  1998,  1999,  and  2000.  26  Over  the  three  years 
 shown,  average  monthly  rates  (the  rate  charged  for  BST,  the  most  highly  subscribed  CPST,  a  remote,  and 
 a  converter)  have  increased  for  both  groups  and  the  differential  between  them  widened  between  1998  and 
 1999  and  remained  constant  between  1999  and  2000.  The  difference  in  monthly  rates  between 
 competitive  and  noncompetitive  operators  was  4.  5%  in  July  1998,  widened  to  5.3%  in  July  1999,  and 
 remained  at  5.3%  in  July  2000.  These  differentials  are  statistically  significant,  as  denoted  by  the  asterisks 
 in  Table  1.  27  See  Attachments  B-  1,  B-  2,  B-  3  and  B-  5  for  more  detailed  information  on  the  differentials 
 between  the  competitive  and  noncompetitive  groups. 


 24  The  subscriber  counts  used  to  stratify  the  noncompetitive  CUIDs  and  to  compute  the  weights  are  for  1994,  which 
 is  the  latest  year  that  system  and  subscriber  counts  are  available  for  every  CUID  in  the  universe.  Since  it  is  likely 
 that  the  percentage  growth  in  subscribers  has  been  fairly  evenly  distributed  across  all  communities,  the  1994  weights 
 serve  as  a  reasonable  approximation  of  year  2000  weights. 


 25  There  are  several  methods  available  for  calculating  subscriber  weighted  averages.  In  addition  to  the  method  we 


 have  adopted,  there  is  also  a  ratio  method.  The  ratio  method  uses  a  double  weighting  process.  First,  results  are 
 weighted  by  the  number  of  subscribers  in  each  CUID,  and  next  weighted  by  the  proportion  of  subscribers  selected  in 
 each  stratum  to  the  universe  of  subscribers  for  that  stratum.  We  compared  averages  calculated  using  the  ratio 
 method  with  the  method  we  ultimately  adopted  and  found  that  the  results  were  similar  for  both  methods.  For  further 
 information  on  various  methods  of  calculating  subscriber  weighted  averages,  see  William  E.  Deming,  Some  Theory 
 of  Sampling,  at  135-  211. 
 26  The  prices  reported  in  this  document  have  not  been  adjusted  for  inflation  and  therefore  are  in  nominal  dollars. 


 27  For  this  and  all  subsequent  tables  we  measure  statistical  significance  at  the  95.  5%  level  using  a  z  test.  We  apply 
 the  z  test  to  determine  whether  a  change  over  time,  or  the  difference  between  the  estimated  means  for  two  groups,  is 
 significant.  See  Kmenta,  at  136-  137,  for  an  explanation  of  the  z  test.  See  Attachments  B-  1,  C-  1,  and  D-  1,  D-  2  for 
 standard  errors  for  the  averages. 
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 Table  1.  Comparison  of  Average  Monthly  Rates,  Competitive  and  Noncompetitive  Groups 
 Date  Competitive  Noncompetitive  Difference  %  Difference  7/  1/  00  $32.40  $34.11  $1.71  5.3%* 
 7/  1/  99  $30.63  $32.25  $1.62  5.3%* 
 7/  1/  98  $29.32  $30.65  $1.33  4.5%* 


 *An  asterisk  denotes  a  statistically  significant  difference  between  the  competitive  and  noncompetitive  groups  at  a 
 95.  5%  level  of  confidence. 


 25.  Operators  in  the  competitive  group  belong  to  one  of  five  subcategories  --  wireline 
 overbuild,  DBS  overbuild,  low  penetration,  municipal  or  LEC  --  under  the  Commissions  effective 
 competition  standard.  Table  2  reports  the  average  rate  for  each  competitive  subcategory  compared  with 
 the  average  for  the  noncompetitive  group.  Attachment  B-  5  provides  a  more  detailed  comparison  of  these 
 competitive  subcategories  as  well  as  the  differentials  in  average  monthly  rates  between  each  competitive 
 subcategory  and  the  noncompetitive  group  along  with  number  of  channels  and  per  channel  rates  over 
 time. 


 Table  2.  Comparison  of  Averages  for  Competitive  Subcategories  with  Noncompetitive  Group 
 Date  Wireline  Overbuild  DBS  Overbuild  LEC  Low  Penetration  Municipal  Noncompetitive 


 Average  Monthly  Charges  7/  1/  00  $33.74  $33.23  $32.21  $31.56  $22.56  $34.11 
 7/  1/  99  $31.49  $32.90  $30.40  $30.17  $21.54  $32.25 
 7/  1/  98  $29.76  $31.40  $29.96  $28.88  $20.58  $30.65 


 Number  of  Channels  7/  1/  00  56.5  38.6  66.3  45.9  50.3  54.8 
 7/  1/  99  53.2  35.1  64.5  43.5  48.9  52.0 
 7/  1/  98  51.0  31.9  62.9  42.5  46.8  49.8 


 Charge  Per  Channel  7/  1/  00  $0.62  $0.96  $0.49  $0.74  $0.46  $0.66 
 7/  1/  99  $0.62  $1.02  $0.48  $0.74  $0.46  $0.65 
 7/  1/  98  $0.61  $1.07  $0.48  $0.73  $0.47  $0.65 
 See  Attachment  B-  5  for  averages,  standard  errors,  the  percentage  differentials,  and  the  test  for  statistical  significance. 
 Although  both  wireline  and  DBS  overbuilds  are  a  part  of  the  overbuild  subcategory,  for  comparison  purposes  we 
 calculated  their  averages  separately. 


 26.  Table  2  shows  that  average  monthly  rates  vary  significantly  among  the  competitive 
 subcategories,  from  $22.56  to  $33.74  as  of  July  1,  2000.  The  average  monthly  charge  for  every 
 subcategory  of  the  competitive  group,  however,  is  lower  than  the  average  monthly  rate  of  $34.11  for  the 
 noncompetitive  group.  The  Table  also  provides  the  average  number  of  channels  and  the  average  monthly 
 charge  per  channel  for  each  subcategory  of  the  competitive  group  and  for  the  noncompetitive  group. 


 27.  We  recognize  that  rates  charged  by  individual  cable  operators  are  affected  by  a  number  of 
 factors  in  addition  to  competitive  status.  28  Size  is  one  such  factor.  In  order  to  determine  the  extent  to 


 28  The  Commission,  in  its  Benchmark  Order,  identified  a  number  of  variables  as  factors  influencing  subscriber  rates. 
 These  included  competitive  status,  system  size,  average  household  income  in  the  area  served  and  whether  or  not  the 
 (continued.) 
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 which  size  influences  rates,  we  calculated  the  average  monthly  rate  by  system  size  in  both  the  competitive 
 and  noncompetitive  groups.  Tables  3  and  4  present  the  results  of  these  calculations. 


 28.  The  tables  show  that  rates  increased  across  the  size  categories  from  small,  to  medium,  to 
 large  for  both  the  competitive  and  noncompetitive  groups.  When  compared  with  the  noncompetitive 
 group,  the  competitive  group  has  consistently  lower  rates  in  all  categories.  Attachment  B-  2  contains 
 additional  information  on  competitive  and  noncompetitive  differentials  by  size.  Attachment  B-  3  also 
 provides  detailed  information  on  the  number  of  channels  and  per  channel  rates  by  size  category. 


 Table  3.  Average  Monthly  Rates,  Competitive  Group  by  Size  Category 
 Size  Category  7/  1/  98  7/  1/  99  %  Change  7/  l/  00  %  Change  (a)  (b)  (a  to  b)  (c)  (b  to  c) 
 Large  $30.01  $31.46  4.8%*  $33.47  6.  4%* 
 Medium  $30.21  $31.44  4.1%*  $33.31  5.  9%* 
 Small  $26.31  $27.30  3.8%  $28.35  3.8% 


 The  large  category  includes  the  large  and  very  large  subgroups  as  described  in  Section  III,  including  CUIDs  with 
 50,000  or  more  subscribers  (very  large),  and  with  less  than  50,  000  but  belonging  to  systems  with  50,000  or  more 
 subscribers  (large).  The  medium  category  includes  CUIDs  in  systems  with  at  least  10,000  but  less  than  50,  000 
 system  subscribers.  The  small  category  includes  CUIDs  belonging  to  systems  with  at  least  1,  000  but  less  than 
 10,  000  system  subscribers  (small)  and  those  with  less  than  1,  000  system  subscribers  (very  small). 
 *An  asterisk  denotes  a  statistically  significant  change  over  time  at  a  95.  5%  level  of  confidence. 


 Table  4.  Average  Monthly  Rates,  Noncompetitive  Group  by  Size  Category 
 Size  Category  7/  1/  98  7/  1/  99  %  Change  7/  1/  00  %  Change  (a)  (b)  (a  to  b)  (c)  (b  to  c) 
 Large  $31.61  $33.30  5.3%*  $35.16  5.  6%* 
 Medium  $30.67  $32.40  5.6%*  $34.48  6.  4%* 
 Small  $28.43  $29.60  4.1%*  $31.10  5.  1%* 
 *An  asterisk  denotes  a  statistically  significant  change  over  time  at  a  95.  5%  level  of  confidence. 


 29.  We  further  analyzed  average  monthly  rates  using  a  regression  equation,  the  results  of 


 (continued  from  previous  page) 
 operator  was  affiliated  with  more  than  one  system,  i.  e.,  a  multiple  system  operator  (  MSO).  System  size  was 
 represented  by  two  variables:  total  number  of  channels  and  number  of  system  subscribers.  In  addition,  five  product 
 mix  variables  were  also  identified.  These  were:  (1)  the  proportion  of  channels  that  are  not  local  broadcast 
 channels,  (2)  the  ratio  of  additional  outlets  to  the  number  of  subscribers,  (3)  the  proportion  of  total  system 
 subscribers  to  CPST  subscribers,  (4)  the  ratio  of  tier  subscription  changes  to  the  number  of  subscribers,  and  (5)  the 
 ratio  of  remotes  rented  to  the  number  of  subscribers.  We  applied  all  of  these  factors  (except  the  ratio  of  additional 
 outlets  to  the  number  of  subscribers  factor)  to  2000  Price  Survey  data  to  determine  if  the  factors  have  any  effect  on 
 average  monthly  rates  for  1999  and  2000.  We  used  regression  analysis  to  show  the  effects  of  these  factors  on  rates. 
 The  estimated  regression  coefficients  are  shown  in  Attachment  B-  4.  These  regression  coefficients  show  that  total 
 number  of  channels  and  MSO  affiliation  were  factors  that  had  a  significant  effect  on  monthly  rates  for  both  1999 
 and  2000.  For  example,  holding  all  other  variables  constant,  we  found  that  MSO-  affiliated  operators,  on  average, 
 had  rates  that  were  approximately  15%  higher  than  operators  unaffiliated  with  an  MSO.  We  also  found  that  the 
 product  mix  variables  mentioned  above  --  local  channels,  CPST  subscribers,  tier  changes,  and  remotes  --  had  no 
 significant  influence  on  rates  during  1999  and  2000.  In  addition,  we  found  that  one  of  the  variables  representing 
 system  size,  i.  e.,  number  of  system  subscribers,  had  no  significant  influence  on  rates  during  the  same  time  period. 
 The  full  effect  of  size  was  captured  by  the  variable  measuring  the  reciprocal  of  the  average  number  of  channels. 
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 which  are  shown  in  Attachment  B-  4.  29  We  found  that,  for  2000,  competitive  operators  that  meet  the  LEC 
 test  had  rates  that  were  9.4%  lower  than  the  noncompetitive  group.  For  the  same  year,  the  regression 
 coefficients  for  the  wireline  overbuild  and  the  low  penetration  subcategories  were  not  significantly 
 different  from  zero,  which  indicates  that  that  these  subcategories  charged  rates  that  were  statistically 
 indistinguishable  from  the  rates  charged  by  operators  in  the  noncompetitive  group.  We  also  found 
 systems  owned  by  a  municipality  had  rates  that  were  20.0%  lower  than  rates  charged  by  the 
 noncompetitive  group.  Our  results  also  show  that  cable  operators  facing  effective  competition  from  DBS 
 providers  (the  DBS  overbuild  subgroup)  had  rates  that  were  8.2%  higher  than  the  rates  charged  by  the 
 noncompetitive  group.  The  competitive  response  by  this  subgroup,  which  is  made  up  almost  entirely  of 
 small  operators,  may  not  be  representative  of  the  response  to  DBS  competition  generally.  30  Anecdotal 
 evidence  shows  that  the  response  by  large  cable  operators  to  increased  DBS  competition  often  includes 
 the  offering  of  new  services  such  as  digital  tiers  and  Internet  access  rather  than  by  lowering  monthly 
 charges.  31 


 30.  Table  5  disaggregates  the  average  monthly  rate  for  the  competitive  group  into  three 
 components  --  BST,  CPST,  and  equipment.  It  also  shows  the  average  monthly  rate  per  channel  and  per 
 satellite  channel.  Between  July  1,  1999  and  July  1,  2000,  the  average  rates  for  programming  services  and 
 equipment  rose  by  5.8%.  The  charge  for  basic  service  increased  by  6.1%  while  the  charge  for  CPST 
 service  increased  by  5.  9%.  The  monthly  charge  for  equipment,  which  represents  a  relatively  small 
 portion  of  the  overall  monthly  rate,  rose  by  3.  9%.  The  number  of  BST  and  CPST  channels  offered  by  the 
 competitive  group  increased  overall  by  4.0%  from  57.6  channels  on  July  1,  1999  to  59.9  channels  on 
 July  1,  2000.  The  average  rate  per  channel,  however,  remained  at  $0.57  over  this  time  period.  The 
 average  rate  per  satellite  channel  declined  by  a  small  amount,  1.3%,  during  the  year  ending  July  1,  2000.  32 


 29  The  results  from  the  regression  equation  show  competitive  differences  when  the  average  number  of  channels, 
 MSO  affiliation,  and  consumer  income  are  held  constant.  We  estimated  separate  regression  equations  for  1999  and 
 2000,  the  years  for  which  we  had  complete  sets  of  information. 


 30  A  total  of  15  operators  were  part  of  our  DBS  overbuild  subgroup.  Of  those  15  operators,  14  were  from  state  of 
 Vermont.  Of  those  14  Vermont  operators,  10  belonged  to  small  system  size  category. 
 31  See  Annual  Assessment  of  the  Status  of  Competition  in  Markets  for  the  Delivery  of  Video  Programming,  CS 
 Docket  No.  00-  132,  Seventh  Annual  Report  (  2000  Competition  Report),  FCC  01-  1  (rel.  Jan  8,  2001)  at  92-  93. 
 32  The  average  rate  per  channel  is  calculated  for  each  respondent  and  then  weighted  and  averaged.  Therefore,  a 
 direct  division  between  the  average  number  of  channels  and  the  average  monthly  rate  shown  in  the  tables  will  not 
 yield  the  average  monthly  rate  per  channel  (or  per  satellite  channel)  that  is  shown  in  the  tables. 
11
 Federal  Communications  Commission  FCC  01-  49 
 12 
 Table  5.  Averages  for  Competitive  Group 
 7/  1/  99  7/  1/  00  Change  %  Change  Monthly  Charge 
 Basic  Service  Tier  (BST)  $11.34  $12.03  $0.69  6.1% 
 Cable  Programming  Service  Tier  (CPST)  $16.44  $17.41  $0.97  5.9% 
 Programming  Services  (BST  &  CPST)  $27.78  $29.44  $1.66  6.  0%* 
 Equipment  (Converter  &  Remote)  $  2.  85  $  2.96  $0.11  3.9% 
 Total:  Program  &  Equipment  Charge  $30.63  $32.40  $1.77  5.8%* 
 Number  of  Channels  Channels  (Broadcast  &  Satellite)  57.6  59.9  2.  3  4.  0%* 


 Charge  per  Channel  $0.57  $0.57  $0.0  0.0% 
 Channels  (Satellite  Only)  42.2  44.4  2.  2  5.  2%* 
 Charge  per  Satellite  Channel  $0.80  $0.79  -$  0.01  -1.3% 


 *An  asterisk  denotes  a  statistically  significant  change  over  time  at  a  95.  5%  level  of  confidence.  See  Attachment 
 B-  1  for  standard  errors  for  the  reported  averages. 


 31.  Table  6  reports  similar  information  for  the  noncompetitive  group.  The  average  monthly 
 rate  for  programming  services  and  equipment  increased  by  5.8%  from  July  1,  1999  to  July  1,  2000  (the 
 same  rate  of  increase  as  the  competitive  group).  The  BST  charge  rose  2.3%,  while  the  CPST  rate  rose  by 
 8.3%.  The  average  monthly  charge  for  equipment  rose  by  5.8%.  Subscribers  received  52.0  channels,  on 
 average,  on  July  1,  1999,  and  54.8  channels,  on  average,  as  of  July  1,  2000,  which  represents  an  increase 
 of  5.4%.  Despite  the  growth  in  channels,  the  per  channel  rate  rose  between  1999  and  2000  from  65  to  66 
 cents.  The  average  rate  per  satellite  channel,  however,  declined  slightly  from  92  cents  per  channel  on 
 July  1,  1999  to  91  cents  per  channel  on  July  1,  2000. 


 Table  6.  Averages  for  Noncompetitive  Group 
 Monthly  Charge  7/  1/  99  7/  1/  00  Change  %  Change  Basic  Service  Tier  (BST)  $12.55  $12.84  $0.29  2.3% 
 Cable  Programming  Service  Tier  (CPST)  $16.97  $18.38  $1.41  8.  3%* 
 Programming  Services  (BST  &  CPST)  $29.52  $31.22  $1.70  5.  8%* 
 Equipment  (Converter  &  Remote)  $2.73  $2.89  $0.16  5.9% 
 Total:  Program  &  Equipment  Charge  $32.25  $34.11  $1.86  5.  8%* 
 Number  of  Channels  Channels:  (Broadcast  &  Satellite)  52.0  54.8  2.  8  5.  4%* 


 Charge  per  Channel  $0.65  $0.66  $0.01  1.5% 
 Channels:  (Satellite  Only)  37.9  40.5  2.  6  6.  9%* 
 Charge  per  Satellite  Channel  $0.92  $0.91  -$  0.01  -1.1% 


 *An  asterisk  denotes  a  statistically  significant  change  over  time  at  a  95.  5%  level  of  confidence.  See  Attachment  B-1 
 for  standard  errors  for  the  reported  averages. 
12
 Federal  Communications  Commission  FCC  01-  49 
 13 
 32.  The  Bureau  of  Labor  Statistics  (  BLS)  publishes  a  Consumer  Price  Index  (  CPI)  for 
 cable  services  (the  cable  CPI).  The  cable  CPI  increased  by  4.7%  over  the  12  months  ending  in  July 
 2000.  The  cable  CPI,  however,  measures  the  prices  charged  for  a  slightly  different  mix  of  services  than 
 the  Survey  and  makes  adjustments  for  channels  added.  33 


 B.  Charges  for  Other  Services 
 33.  Table  7  provides  a  comparison  of  average  charges  for  other  cable  services  that  are  not 
 included  in  the  average  monthly  rate  for  the  competitive  and  noncompetitive  groups.  These  services 
 include  installation,  reconnection,  and  tier  changes.  For  the  most  part,  prices  increased  although  at  a 
 slower  pace  than  monthly  charges  for  programming  and  equipment.  These  charges  are  difficult  to 
 interpret,  however,  since  they  are  subject  to  frequent  promotions,  which  may  result  in  deep  discounts  at 
 certain  times  and  steep  increases  at  other  times. 


 Table  7.  Charges  for  Other  Services   
 Competitive  Group  Noncompetitive  Group 
 7/  1/  99  7/  1/  00  Change  7/  1/  99  7/  1/  00  Change  Installation  $26.44  $27.65  4.  6%  $37.16  $37.76  1.6% 
 Reconnection  $21.16  $21.76  2.  8%  $23.39  $24.01  2.7% 
 Tier  Change  $6.  13  $6.  40  4.  4%  $8.  49  $8.  76  3.  2% 


 The  average  of  operators  that  reported  having  a  non-  zero  charge.  See  Attachment  B-  6  for  standard  errors  of 
 the  reported  averages. 


 C.  Operators  Explanation  for  Changes  in  Rates 
 34.  The  Survey  asked  respondents  to  explain  any  changes  in  their  rates  between  July  1,  1999, 
 and  July  1,  2000,  by  attributing  those  changes  to  increased  costs  or  other  factors.  For  those  respondents 
 who  raised  rates,  Table  8  shows  the  percentage  by  which  each  factor  contributed  to  the  overall  price 
 increase.  Both  the  competitive  and  noncompetitive  groups  attributed  much  of  their  rate  increases  to 
 higher  programming  costs.  For  the  12  months  ending  July  1,  2000,  the  competitive  group  attributed 
 44.1%  and  the  noncompetitive  group  attributed  41.4%  of  their  higher  rates  to  programming  cost 
 increases. 


 35.  For  the  competitive  and  noncompetitive  groups,  system  upgrades  were  the  next  specific 
 cost  factor  cited  as  contributing  most  to  rate  increases  (9.  0%  and  12.4%,  respectively).  For  the 
 competitive  and  noncompetitive  groups,  respectively,  this  was  followed  in  importance  by  increased 
 equipment  costs  (6.  8%  and  10.  8%),  inflation  (5.  6%  and  9.  7%),  and  increased  channel  addition  costs 
 (3.  4%  and  4.8%).  In  addition,  the  competitive  group  attributed  21.5%  of  its  rate  increases  to  unspecified 
 costs,  while  the  noncompetitive  group  attributed  7.5%  to  this  factor.  Finally,  respondents  reported  that 
 9.6%  of  the  rate  changes  made  by  the  competitive  group,  and  13.4%  of  the  rate  changes  made  by  the 
 noncompetitive  group,  were  not  identified  with  specific  cost  changes. 


 33  The  cable  CPI  includes  premium  channels  and  pay-  per-  view  services  as  well  as  installation  charges.  The  Survey 
 averages  do  not  include  those  charges,  which  may  explain  differences  between  the  rates  of  increase  reported  by  the 
 BLS  and  our  Survey. 
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 Federal  Communications  Commission  FCC  01-  49 
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 Table  8.  Explanation  for  Changes  in  Rates 
 Competitive  Group  Noncompetitive  Group  7/  1/  99  7/  1/  00  7/  1/  99  7/  1/  00 
 Programming  Costs  48.9%  44.1%  49.4%  41.4% 
 System  Upgrades  13.7%  9.0%  10.6%  12.4% 
 Equipment  Costs  11.4%  6.8%  6.9%  10.8% 
 Inflation  7.6%  5.6%  9.4%  9.7% 
 Channel  Additions  4.6%  3.4%  4.4%  4.8% 
 Franchise  Fees  0.8%  0.0%  0.6%  0.0% 
 Unspecified  Costs  3.1%  21.5%  5.0%  7.5% 
 Changes  Not  Based  on  Costs  9.  9%  9.  6%  13.7%  13.4% 


 Increases  in  costs  on  existing  programming,  including  copyright  fees.    Includes  upgrades  pursuant  to  a  social 
 contract  or  local  franchise  agreement.  Includes  the  cost  of  programming  for  newly  added  channels.  For  more 
 detailed  information,  see  Attachment  B-  7. 


 V.  OTHER  FINDINGS 
 A.  Distribution  of  Programming  by  Major  Categories 
 36.  Table  9  shows  a  breakdown  of  the  average  number  of  satellite  channels  by  major 
 category  --  childrens,  news,  sports,  and  general  entertainment  --  for  the  competitive  and  noncompetitive 
 groups.  This  table  shows  that  increases  were  relatively  uniform  across  all  programming  categories. 
 Attachment  C-  1  provides  additional  information  on  the  number  of  channels  offered  in  each  category. 


 Table  9.  Average  Number  of  Satellite  Channels  by  Type  of  Programming 
 Competitive  Group  Noncompetitive  Group  7/  1/  99  7/  1/  00  7/  1/  99  7/  1/  00 
 Childrens  3.8  4.1  3.2  3.7 
 News  6.4  6.7  5.9  6.3 
 Sports  4.3  4.8  3.6  4.0 
 General  Entertainment  29.5  31.7  26.9  29.1 
 Total  Satellite  Channels  44.  0  47.  3  39.  6  43.  1 


 Satellite  channels  reported  here  include  all  CPST  channels,  not  just  those  carried  on  the  most  highly-  subscribed 
 CPST,  as  well  as  any  satellite  channels  carried  on  BST.  See  Attachment  C-  1  for  other  results. 


 B.  Annual  System  Revenues 
 37.  The  Survey  sought  information  on  annual  system-  wide  revenues  from  five  major  sources: 
 (a)  programming  (BST,  CPST,  premium  and  pay-  per-  view),  (b)  leases  and  sales  of  equipment 
 (converters,  remote  controls,  etc.),  (c)  non-  video  services  (Internet  and  telephony),  (d)  advertising,  and  (e) 
 other  fees  (commissions,  launch  fees  and  leased  access).  34  All  of  the  operators  reported  receiving  the  bulk 
 of  revenues  from  programming  services.  Table  10  shows,  however,  that  revenue  from  non-  video  sources 
 increased  as  a  percent  of  total  revenue  from  1.5%  to  3.5%  between  1999  and  2000.  This  may  be 


 34  Revenues  were  calculated  by  summing  across  systems.  Of  436  systems,  373  reported  data  suitable  for  the  purpose 
 of  calculating  Table  10. 
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 15 
 attributed  to  the  growing  importance  of  these  services  and  the  increasing  number  of  operators  offering 
 Internet  and  telephony  services.  Of  the  cable  operators  surveyed,  52%  reported  receiving  revenue  from 
 non-  video  subscriber  services  during  the  12-  month  period  ending  July  2000,  an  increase  from  the  32% 
 who  reported  receiving  such  revenue  during  the  12-  month  period  ending  July  1999.  Revenue  from 
 advertising  also  increased  as  a  percent  of  total  revenue  between  July  1,  1999  and  July  1,  2000. 


 Table  10.  Percent  of  Annual  System  Revenues  from  Various  Sources 


 Revenue  Source  7/  1/  99  7/  1/  00  Programming  86.8%  84.2% 
 Equipment  5.  5%  5.  4% 
 Non-  Video  Services  1.5%  3.5% 
 Advertising  5.  6%  6.  3% 
 Other  Fees  0.6%  0.6% 


 C.  System  Capacity  and  Non-  Video  Services 
 38.  As  of  July  1,  2000,  55.5%  of  operators  in  our  sample  reported  a  capacity  of  550  MHz  or 
 more,  the  vast  majority  of  which  report  a  capacity  of  750  MHz.  A  total  of  46.6%  of  operators  reported 
 offering  Internet  access  service,  and  6.5%  offered  cable  telephony  service. 


 Table  11.  System  Capacity  and  Non-  Video  Services 


 Operators  Reporting  a  Capacity  of:  Total  Competitive  Noncompetitive  Up  to  330  MHz  10.7%  9.1%  11.9% 
 Between  331  MHz  and  550  MHz  33.8%  24.5%  41.2% 
 Above  550  MHz  55.5%  66.4%  46.9% 
 Operators  Offering:  Internet  Access  46.  6%  48.  1%  45.  4% 


 Cable  Telephony  6.  5%  7.  9%  5.  5% 


 D.  Clustering 
 39.  We  sought  to  gather  information  on  and  analyze  the  effects  of  clustering.  For  the  past 
 several  years,  cable  operators  have  engaged  in  a  strategy  of  buying  and/  or  swapping  cable  systems  of 
 various  sizes  with  the  objective  of  creating  clusters  of  contiguous,  commonly-  owned  and  operated,  cable 
 systems.  Some  of  these  clusters  may  consist  of  large  regional  groupings  involving  a  million  or  more 
 subscribers  while  others  may  be  made  up  of  a  handful  of  small  operators  serving  a  few  thousand  or  less 
 subscribers.  It  is  believed  that  clustering  can  create  greater  economies  of  scale  and  scope  and  that  it  may 
 enable  operators  to  offer  a  wider  variety  of  services,  including,  for  example,  Internet  access  and  other 
 broadband  services,  at  lower  prices  to  consumers. 


 40.  Analysts  report  that  since  1999,  MSOs  sought  to  create  larger  clusters  to  better  enable 
 cable  operators  to  provide  local  telephone  and  Internet  services.  35  A  total  of  710  operators  provided 
 cluster  information.  The  Survey  found  that,  of  those  710  operators,  493,  or  69%,  are  part  of  clusters.  Of 
 those  493  clustered  operators,  only  35  operators,  or  7%,  offer  cable  telephony,  and  237  operators,  or  48%, 


 35  See  Annual  Assessment  of  the  Status  of  Competition  in  Markets  for  the  Delivery  of  Video  Programming,  CS 
 Docket  No.  99-  230,  Sixth  Annual  Report  (  1999  Competition  Report),  15  FCC  Rcd  978  at    161-  165. 
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 Federal  Communications  Commission  FCC  01-  49 
 16 
 offer  Internet  access  service  to  their  subscribers.  Similarly,  217  operators  of  the  710,  or  31%  do  not 
 belong  to  a  cluster.  Of  those  217  non-  clustered  operators,  93,  or  43%  offer  Internet  access  service  and  12, 
 or  6%  offer  cable  telephony  to  their  subscribers. 


 41.  We  also  sought  to  determine  whether  clustering  had  a  measurable  effect  on  monthly 
 rates.  Table  12  shows  a  comparison  of  rates  charged  by  clustered  and  non-  clustered  operators.  While 
 clustered  operators  charge  more,  on  average,  than  non-  clustered  operators,  they  also  offer  more  channels. 
 On  a  per  channel  basis,  monthly  rates  for  these  two  groups  are  similar. 


 Table  12.  Averages  as  of  July  1,  2000  for  Clustered  and  Non-  clustered  Operators 
 Clustered  Non-  clustered 
 Monthly  Charge  $33.79  $31.73 
 Number  of  Channels  57.8  54.2 
 Monthly  Charge  per  Channel  $0.63  $0.62 


 42.  We  further  analyzed  the  effects  of  clustering  on  monthly  rates  using  a  regression  equation 
 similar  to  the  Benchmark  equation.  We  found  that  operators  that  were  part  of  a  cluster  had,  on  average, 
 higher  monthly  rates  than  operators  that  were  not  part  of  a  cluster.  See  Attachment  D-  1  for  results  of  this 
 analysis. 


 43.  Our  finding  of  a  positive  relationship  between  clustering  and  monthly  rates  shown  in 
 Table  12  and  reflected  in  the  discussion  in  Attachment  D-  1  may  be  due  to  a  variety  of  reasons.  For 
 example,  we  note  that  clustering  could  involve  either  a  series  of  systems  that  are  being  operated,  in  effect, 
 as  a  single  system  or  a  series  of  systems  that  are  not  integrated  but  are  commonly  owned  in  communities 
 that  are  simply  in  close  proximity.  Both  types  of  clusters  meet  our  definition  and  the  data  collected  by 
 our  Survey  did  not  distinguish  between  these  two  categories.  36  This  definitional  dichotomy  may  have 
 influenced  our  findings  since  non-  integrated  systems  should  not  be  expected  to  produce  economic 
 efficiencies.  In  addition,  for  those  systems  that  are  integrated,  it  may  take  several  years  for  the  full 
 benefits  of  clustering  to  be  realized  as  operators  go  through  a  process  of  consolidation  and  rationalization 
 of  disparate  systems.  Also,  higher  costs  may  be  incurred  in  the  early  stages  of  this  process.  Our 
 regression  equation  does  not  take  into  account  the  difference  between  integrated  and  non-  integrated 
 systems,  cost  factors  or  the  timing  of  consolidation  because  that  information  was  not  available  to  us. 
 Therefore,  those  factors  are  not  represented  in  the  equation. 


 E.  Digital  Services 
 44.  As  of  July  1,  2000,  the  Survey  shows  that  154  (48%)  competitive  operators  provide 
 digital  service,  while  235  (58%)  noncompetitive  operators  offer  such  service.  37  Both  competitive  and 
 noncompetitive  operators  offered  on  average  1.  9  digital  tiers.  Competitive  operators  charged  $7.  46 
 monthly,  at  $0.  28  per  channel,  for  digital  service  while  noncompetitive  operators  charged  $8.42  monthly 
 at  $0.34  per  channel.  These  averages  represent  a  continuation  of  enormous  growth  in  the  number  of 
 operators  offering  digital  services. 


 36  We  defined  cluster  in  the  Survey  as  systems  that  are  situated  in  close  proximity  to  another  commonly  owned  or 
 managed  cable  system(  s). 
 37  Services  on  digital  tiers  are  separate  from  BST  and  CPST.  Digital  tier  information  was  not  included  in  the 
 calculation  of  the  average  monthly  rates  that  serve  as  the  focus  of  this  report. 
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 Federal  Communications  Commission  FCC  01-  49 
 17 
 Table  13.  Digital  Tiers,  Competitive  and  Noncompetitive  Groups 
 Competitive  Noncompetitive  7/  1/  99  7/  1/  00  7/  1/  99  7/  1/  00 
 Number  of  Operators  Offering  Digital  Service  56  154  138  234 
 Percent  of  Sample  17.6%  48.4%  34.2%  58.1% 
 Average  Number  of  Digital  Tiers  1.  6  1.  9  1.  2  1.  9 
 Number  of  Channels  Offered  37.8  39.0  35.9  39.9 
 Average  Monthly  Charge  $8.82  $7.46  $9.05  $8.42 
 Average  Price  Per  Channel  $0.36  $0.28  $0.41  $0.34 


 Results  are  reported  for  the  most  highly  subscribed  digital  tier. 


 F.  Commercial  Leased  Access 
 45.  Of  the  surveyed  cable  operators,  82%  reported  at  least  one  channel  available  for  lease 
 under  the  Commissions  leased  access  rules.  38  Of  those  with  channels  for  lease,  57%  reported  leases  at 
 an  average  of  1.  8  channels  per  operator.  About  one-  half  of  those  channels  were  leased  part-  time  and  the 
 other  half  on  a  full-  time  basis.  In  over  95%  of  the  cases,  purchasers  of  leased  access  paid  less  than  one 
 cent  per  subscriber  per  hour  of  leased  access  programming. 


 G.  Lifeline  Basic  Service 
 46.  The  Survey  asked  operators  if  they  offered  a  tier  of  service  that  excluded  satellite 
 channels  and  carried  only  signals  from  local  television  broadcast  stations  and  PEG  channels.  This  tier  is 
 frequently  called  lifeline  or  limited  basic.  In  our  2000  Survey,  19  (3%)  operators  reported  that  they 
 offered  lifeline  basic  service  at  an  average  monthly  rate  of  $9.29  for  an  average  of  14.4  channels. 


 H.  Elasticity  of  Demand  for  Cable  Services 
 47.  We  also  analyzed  demand  for  cable  services  by  creating  a  demand  equation  model.  A 
 detailed  discussion  of  the  econometrics  used  in  this  analysis  can  be  found  in  Attachment  D-  2.  The 
 equation  presupposes  that  changes  in  demand  for  cable  services  are  a  function  of:  (a)  average  monthly 
 rate  for  programming  services  and  equipment;  (b)  median  household  income;  (c)  number  of  households 
 passed;  (d)  ratio  of  non-  urban  population  to  total  population;  (e)  average  number  of  satellite  channels 
 offered;  and  (f)  competitive  status.  39  Based  on  this  analysis,  we  found  that  demand  for  cable  service  was 
 sensitive  in  varying  degrees  to  changes  in  all  but  one  variable  listed  above.  Competitive  status,  non-  urban 
 population,  and  average  monthly  rate  variables  are  inversely  related  to  the  demand  for  cable  services;  as 
 these  variables  increase,  the  demand  for  cable  service  decreases.  Conversely,  median  household  income 
 and  number  of  households  passed  have  a  direct  relationship  to  demand,  i.  e.,  as  these  variables  increase, 
 the  demand  for  cable  service  increases.  However,  the  number  of  satellite  channels  variable  had  no 
 significant  effect  on  the  demand  for  cable  service  since  the  estimated  coefficient  for  this  variable  was  not 
 significantly  different  from  zero. 


 38  Leased  access  is  a  channel  set  aside  requirement  where  cable  operators  designate  channel  capacity  for  commercial 
 use  by  persons  unaffiliated  with  their  system.  See  47  CFR    76.  970. 
 39  All  variables  except  for  competitive  status  are  in  the  form  of  natural  logs.  The  variables  measuring  household 


 income  and  non-  urban  population  are  from  Census  Bureau  data  for  the  specific  area  served  by  those  cable  operators 
 included  in  this  analysis  and  can  be  found  in  Census  CD,  GeoLytics,  Inc. 
17
 Federal  Communications  Commission  FCC  01-  49 
 18 
 48.  The  demand  equation  also  produced  price  and  income  elasticities  of  demand  for  cable.  40 
 The  estimated  price  elasticity  of  cable  according  to  this  equation  is  1.95,  which  indicates  that  the  demand 
 for  cable  services  is  somewhat  price  elastic.  41  This  means  that  a  one  percent  increase  in  the  price  of  cable 
 services,  for  example,  would  result  in  a  slightly  less  than  two  percent  decrease  in  the  demand  for  those 
 services.  Since  our  measure  of  cable  price  elasticity  is  greater  than  one,  the  equation  also  suggests  that 
 cable  service  has  substitutes.  The  effects  of  one  such  substitute,  DBS,  is  discussed  below.  With  regard  to 
 income  elasticity,  we  found  that  the  estimated  income  elasticity  of  cable  services  was  0.  62.  This  suggests 
 that  the  demand  for  cable  service  is  not  very  sensitive  to  changes  in  household  income.  Results  from  the 
 estimated  demand  equation  are  shown  in  Attachment  D-  2. 


 I.  Effects  of  DBS  on  the  Demand  for  and  Price  of  Cable  Services 
 49.  In  this  years  Survey,  we  again  sought  to  investigate  the  extent  to  which  DBS  penetration 
 may  have  had  an  effect  on  the  demand  for  cable  services.  In  the  2000  Competition  Report,  the 
 Commission  notes  that  DBS  is  cables  largest  competitor  with  approximately  thirteen  million  subscribers 
 as  of  June  2000.  42  In  response  to  Survey  questions,  a  number  of  cable  operators  provided  estimates  of  the 
 number  of  DBS  subscribers  in  their  service  areas. 


 50.  Table  14  shows  the  number  of  cable  and  DBS  subscribers  in  the  cable  operators  service 
 areas  expressed  as  a  percentage  of  TV  households  in  the  same  areas,  as  of  July  1,  2000.  The  data  are 
 shown  by  size  strata  and  for  both  competitive  and  noncompetitive  groups.  On  average,  cable  operators 
 responding  to  our  Survey  reported  that  DBS  has  a  14.7%  share  of  television  households  in  their  franchise 
 areas.  Noncompetitive  operators  report  that  their  share  of  TV  households  is  slightly  over  61%,  on 
 average,  whereas  the  competitive  operators  report  their  share  at  approximately  45%,  as  of  July  1,  2000.  43 
 Competitive  operators  report  a  significantly  lower  level  of  penetration  than  noncompetitive  operators 
 because  the  competitive  group  includes  a  large  number  of  operators  with  relatively  low  penetration,  i.  e., 
 those  meeting  the  low  penetration  test. 


 51.  The  Survey  results  also  indicate  that  DBS  made  relatively  more  progress  in  acquiring 
 new  subscribers  in  rural  areas  than  in  urban  areas.  For  those  operators  who  provided  DBS  subscribership 
 information,  we  found  that  those  serving  areas  having  less  than  25%  urban  population  had  an  average 
 DBS  penetration  (DBS  subscribers  as  a  percent  of  TV  households)  of  approximately  18%.  In  areas  with 


 40  According  to  a  well-  established  economic  theory  related  to  consumer  demand,  substitutability  of  a  product  or 
 service  depends  upon  the  level  of  responsiveness  of  the  quantity  demanded  to  changes  in  price  for  that  good.  The 
 responsiveness  of  the  quantity  demanded  to  changes  in  price  of  the  good  is  known  as  price  elasticity  of  demand. 
 For  example,  the  price  elasticity  of  demand  for  cable  services  would  measure  the  effects  of  changes  in  average 
 monthly  cable  rates  on  the  demand  for  cable  services  assuming  that  all  other  factors,  such  as  the  number  of  satellite 
 channels  offered,  were  held  constant.  Income  elasticity  is  defined  as  the  responsiveness  of  demand  for  a  particular 
 good  or  service  to  changes  in  household  income.  See,  for  example,  C.  E.  Ferguson  and  J.  P.  Gould,  Microeconomic 
 Theory,  Richard  D.  Irwin,  Inc.,  Fourth  Edition,  1975. 


 41  A  price  elasticity  estimate  of  less  than  one  would  be  referred  to  as  inelastic.  Conversely,  an  elasticity  estimate 


 of  more  than  one  is  considered  elastic.  Other  econometric  estimates  of  the  price  elasticity  of  demand  for  cable 
 service  range  from  1.  05  to  3.  38.  See,  for  example,  Annual  Assessment  of  the  Status  of  Competition  in  Markets  for 
 the  Delivery  of  Video  Programming,  First  Report,  9  FCC  Rcd  7442  (1994),  Appendix  H,  at  Table  H-  1. 


 42  Nationwide,  as  of  June  2000,  80.  19%  of  all  MVPD  subscribers  received  their  video  programming  from  a  local 


 franchised  cable  operator  while  DBS  subscribers  represented  15.  38%  of  all  MVPD  subscribers.  See  2000 
 Competition  Report  at  Table  C-  1. 


 43  It  should  be  noted  that  there  are  other  ways  of  measuring  cable  penetration  including  the  more  generally  used 


 measure  of  subscribers  as  a  percent  of  households  passed.  That  measure  is  not  appropriate  for  comparison  with 
 DBS  because  DBS  passes  virtually  all  TV  households. 
18
 Federal  Communications  Commission  FCC  01-  49 
 19 
 more  than  75%  urban  population,  the  average  DBS  penetration  was  approximately  11%.  44 
 TABLE  14.  Average  Share  of  TV  Households  by  Size  Strata,  Cable  and  DBS,  as  of  July  1,  2000 
 Size  Strata  Competitive  Noncompetitive  DBS 


 Large  42.5%  59.9%  11.8% 
 Medium  41.7%  65.0%  17.0% 
 Small  50.9%  60.3%  18.0% 


 Overall  (all  sizes)  Share  44.7%  61.4%  14.7% 
 DBS  penetration  data  was  reported  by  cable  operators  responding  to  the  Survey.  Therefore,  size  stratification  for 
 the  DBS  data  was  based  on  the  size  strata  of  the  reporting  cable  operators  and  does  not  represent  stratification  of 
 DBS  operators. 
   Combined  very  large  and  large  size  strata. 
   Combined  small  and  very  small  size  strata. 


 52.  The  1999  Competition  Report  noted  that  cost  differences,  notably  installation  and 
 equipment  costs,  between  cable  and  DBS  continue  to  diminish.  45  As  a  result,  some  observers  assert  that 
 many  consumers  now  perceive  DBS  and  cable  to  be  substitutable  services.  46  In  economic  terms,  the  better 
 the  substitute  for  a  particular  good  or  service  the  greater  its  price  elasticity  will  tend  to  be. 


 53.  In  order  to  measure  the  effects  of  DBS  on  the  demand  for  cable  services,  we  modified  our 
 demand  equation  to  include  the  effects  of  DBS.  We  hypothesized  a  negative  coefficient  for  this  variable 
 suggesting  that  as  the  number  of  DBS  subscribers  increases,  the  demand  for  cable  services  would  grow  at 
 a  slower  pace  or  decrease.  As  hypothesized,  the  sign  for  the  DBS  coefficient  is  negative  and  statistically 
 significant.  Our  finding  suggests  that  DBS  is  a  substitute  for  cable  services.  This  result  is  different  from 
 our  earlier  finding  reported  in  the  1999  Price  Survey  Report,  which  showed  DBS  exerting  only  a  modest 
 influence  on  the  demand  for  cable  service.  One  explanation  for  the  increased  importance  of  DBS  as  a 
 competitor  of  cable  is  the  passage  of  the  Satellite  Home  Viewer  Improvement  Act  (SHVIA)  in  November 
 1999,  which  eliminated  the  prohibition  on  DBS  delivery  of  local  network  signals  into  their  local 
 television  markets.  47  The  two  DBS  operators  have  begun  offering  local  signals  in  many  major  television 
 markets  thus  more  closely  matching  services  provided  by  cable  operators.  48  The  results  and  a  fuller 


 44  The  percentage  of  urban  population  in  cable  operators  service  areas  is  from  Census  CD,  GeoLytics,  Inc.  We  used 
 county  names  which  were  included  in  both  Census  and  Survey  data  to  uniquely  match  and  then  merge  these  two 
 data  sets. 


 45  1999  Competition  Report,  15  FCC  Rcd  978  at    73. 


 46  Id.  at    71. 
 47  A  Skytrends  analysis  of  13  designated  market  areas  (  DMAs)  where  DirecTV  and/  or  EchoStar  have  introduced 
 local-  into-  local  service  which  was  cited  by  Satellite  Broadcasting  and  Communications  Association  found  that 
 between  June  and  December  1999,  prior  to  SHVIA,  DBS  operators  added  an  average  of  4,  002  new  subscribers  per 
 month  within  each  DMA.  For  the  post-  SHVIA  period  (January-  June  2000),  DBS  operators  added  an  average  of 
 5,706  new  subscribers  per  month  in  each  of  these  DMAs,  an  increase  of  43%  over  the  pre-  SHVIA  period.  See  2000 
 Competition  Report  at    69. 


 48  As  of  November  2000,  DirecTV  offers  the  local  affiliates  of  ABC,  CBS,  NBC,  and  Fox  in  38  markets.  Similarly, 
 EchoStar  transmits  local  network  packages  to  its  subscribers  in  34  markets.  See  Implementation  of  the  Satellite 
 Home  Viewer  Improvement  Act  of  1999:  Broadcast  Signal  Carriage  Issues,  CS  Docket  No.  00-  96,  Report  and 
 Order,  FCC  00-  417  (rel.  Nov.  30,  2000)  at  Appendices  D  and  E. 
19
 Federal  Communications  Commission  FCC  01-  49 
 20 
 discussion  of  the  analysis  are  shown  in  Attachment  D-  2. 
 VI.  CONCLUSION 
 54.  We  found  that  both  competitive  and  noncompetitive  operators  increased  their  average 
 monthly  rates  by  5.8%  for  BST,  CPST  and  equipment  during  the  time  period  surveyed.  We  also  found 
 that  the  competitive  differential  between  competitive  and  noncompetitive  operators  remained  constant  at 
 5.3%  between  1999  and  2000. 


 55.  Both  competitive  and  noncompetitive  cable  operators  point  to  increased  programming 
 costs  to  explain  a  significant  portion  of  their  rate  increases.  System  upgrades  and  equipment  cost 
 increases  are  also  cited  as  factors  to  explain  higher  rates.  Competitive  and  noncompetitive  operators  have 
 increased  system  capacity  and,  as  a  result,  are  now  able  to  offer  their  subscribers  more  channels  on  BST 
 and  CPST  along  with  new  services  such  as  digital  programming  tiers,  Internet  access,  and  telephony. 


 56.  On  a  per  channel  basis,  the  average  monthly  rate  for  competitive  operators  remained 
 constant  for  the  year  ending  July  1,  2000,  while  for  noncompetitive  operators  the  average  monthly  rate 
 per  channel  increased  by  one  cent  or  1.  5%  over  the  same  period.  The  average  monthly  rates  per  satellite 
 channel,  however,  decreased  by  one  cent  or  about  one  percent  for  both  the  competitive  and 
 noncompetitive  groups  over  the  period  studied. 


 57.  Cable  operators  estimate  that  DBS  service  continues  to  capture  market  share  in  their 
 service  areas  with  greater  inroads  being  felt  by  small  and  rural  cable  operators  than  by  urban  systems. 
 Finally,  we  found  that  demand  for  cable  service  is  somewhat  sensitive  to  changes  in  cable  rates. 


 58.  This  report  fulfills  the  Commissions  annual  statutory  obligation  to  compare  prices 
 charged  by  competitive  cable  operators  with  those  of  cable  operators  not  facing  effective  competition  for 
 the  delivery  of  basic  service,  other  cable  programming  services,  and  equipment. 


 VII.  ADMINISTRATIVE  MATTERS 
 59.  It  is  ORDERED  that  this  Report  be  issued  pursuant  to  authority  contained  in  Section 
 623(  k)  of  the  Communications  Act  of  1934,  as  amended,  47  U.  S.  C.  543(  k). 


 FEDERAL  COMMUNICATIONS  COMMISSION 


 Magalie  Roman  Salas 
 Secretary 
20
 Federal  Communications  Commission  FCC  01-  49 
 21 
 ATTACHMENT  A 
 SURVEY  SAMPLE,  BY  GROUP  AND  STRATA 
 CUIDs  IN  UNIVERSE    PERCENT  OF  SUBSCRIBERS  CUIDs  IN  SAMPLE  CUIDs  RESPONDING  USABLE  RESPONSES 


 COMPETITIVE  GROUP  STRATA 
 Local  Exchange  Carrier  193  58.  48%  193  186  181 
 Wireline  Overbuild  61  22.11%  61  53  52 
 Low  Penetration  176  13.  77%  67  60  57 
 Municipal  15  1.  07%  15  14  13 
 DBS  Overbuild  130  4.  57%  16  15  15 
 Total  575  100%  352  328  318 


 NONCOMPETITIVE  GROUP  STRATA 
 Very  Large  109  17.75%  109  109  107 
 Large  3,  789  27.82%  112  107  100 
 Medium  7,  285  34.33%  137  128  113 
 Small  10,837  16.62%  67  62  57 
 Very  Small  8,  986  3.48%  35  28  26 
 Total  31,006  100%  460  434  403 


 Grand  Total  31,581  -----  812  762  721 


 Source:  FCC  Form  325  filings.  For  the  noncompetitive  group  strata,  CUIDs  serving  50,  000  or  more  subscribers,  in 
 systems  serving  50,  000  or  more  subscribers,  were  placed  in  the  very  large  category.  CUIDs  serving  less  than  50,  000 
 subscribers,  in  systems  serving  50,  000  or  more  subscribers,  were  placed  in  the  large  category.  CUIDs  in  systems 
 serving  10,  000  through  49,  999  subscribers  were  placed  in  the  medium-  sized  category;  those  serving  at  least  1,  000 
 and  fewer  than  10,  000  subscribers  were  placed  in  the  small  category;  and  those  serving  less  than  1,  000  subscribers 
 were  placed  in  the  very  small  category.  We  stratified  the  competitive  group  by  competitive  test,  rather  than  system 
 size.  Had  the  competitive  group  been  stratified  by  system  size,  157  of  the  usable  CUIDs  would  have  belonged  to  the 
 large  or  very  large  category,  72  to  the  medium  category,  and  89  to  the  small  or  very  small  category. 


   These  percentages  are  the  weights  that  were  used  in  this  report  to  compute  the  overall  averages  for  each  group. 
 Each  percentage  equals  the  number  of  subscribers  in  that  category  divided  by  the  total  number  of  subscribers  for  the 
 group.  These  subscriber  counts  are  for  1994,  the  latest  year  that  subscriber  counts  are  available  for  every  CUID  in 
 the  universe.  Since  it  is  likely  that  the  percentage  growth  in  subscribers  has  been  fairly  evenly  distributed  across  all 
 communities,  the  1994  weights  serve  as  a  reasonable  approximation  of  year  2000  weights. 


   Of  the  762  CUIDs  responding,  721  were  usable.  Of  the  41  unusable  responses,  we  eliminated  30  responses  that 
 lacked  the  requisite  3  years  of  price  data  and  11  responses  as  a  result  of  other  incomplete  or  inconsistent  data. 
21
 Federal  Communications  Commission  FCC  01-  49 
 22 
 ATTACHMENT  B-  1 
 COMPARISON  OF  COMPETITIVE  AND  NONCOMPETITIVE  GROUPS 


 COMPETITIVE  NON-  COMPETITIVE  $  DIFFERENCE  IN  MEANS  %  DIFFERENCE  BETWEEN  MEANS 
 2000  BST  $12.03  $12.84  $0.81  6.7% 
 Standard.  Error  0.  45  0.  56  --  --  - 
 CPST  $17.41  $18.38  $0.97  5.6%  Standard.  Error  0.  70  0.  61  --  --  - 


 Equipment  $2.96  $2.89  -$  0.07  -2.  4%  Standard.  Error  0.  15  0.  12  --  --  - 
 BST,  CPST&  Equipment  $32.40  $34.11  $1.71  5.3%* 
 Standard.  Error  0.  51  0.  38  --  --  - 
 Charge  per  Channel  $0.57  $0.66  $0.09  15.8%*  Standard.  Error  0.  02  0.  01  --  --  - 


 Charge  per  Satellite  Channel  $0.79  $0.91  $0.12  15.2%*  Standard.  Error  0.  03  0.  02  --  --  - 
 Number  of  Channels  59.9  54.8  -5.1  -8.5%* 
 Standard.  Error  1.  22  0.  92  --  --  - 
 Number  of  Satellite  Channels  44.4  40.5  -3.9  -16.3%*  Standard.  Error  0.  98  0.  82  ---  --  - 


 1999  BST  $11.34  $12.55  $1.21  10.7% 
 Standard.  Error  0.  45  0.  54  --  --  - 
 CPST  $16.44  $16.97  $0.53  3.2%  Standard.  Error  0.  67  0.  58  --  --  - 


 Equipment  $2.85  $2.73  -$  0.12  -4.  2%  Standard.  Error  0.  14  0.  11  --  --  - 
 BST,  CPST&  Equipment  $30.63  32.25  $1.62  5.3%* 
 Standard.  Error  0.  44  0.  35  --  --  - 
 Charge  per  Channel  $0.57  $0.65  $0.08  14.0%*  Standard.  Error  0.  02  0.  01  --  --  - 


 Charge  per  Satellite  Channel  $0.80  $0.92  $0.12  15.0%*  Standard.  Error  0.  03  0.  01  --  --  - 
 Number  of  Channels  57.6  52.0  -5.6  -9.7%* 
 Standard.  Error  1.  20  0.  90  --  --  - 
 Number  of  Satellite  Channels  42.2  37.9  -4.3  -10.2%*  Standard.  Error  0.  96  0.  79  --  --  - 


 1998  BST  ---  ---  --  --  - 
 Standard.  Error  ---  ---  --  --  - 
 CPST  ---  ---  --  --  -  Standard.  Error  ---  ---  --  --  - 


 Equipment  ---  ---  --  --  -  Standard.  Error  ---  ---  --  --  - 
 BST,  CPST&  Equipment  $29.32  $30.65  $1.33  4.5%* 
 Standard.  Error  0.  41  0.  33  --  --  - 
 Charge  per  Channel  $0.57  $0.65  0.08  14.0%*  Standard.  Error  0.  02  0.  01  --  --  - 


 Charge  per  Satellite  Channel  ---  ---  --  --  -  Standard.  Error  ---  ---  --  --  - 
 Number  of  Channels  55.9  49.8  -6.1  -10.9%* 
 Standard.  Error  1.  17  0.  94  --  --  - 
 Number  of  Satellite  Channels  ---  ---  --  --  -  Standard.  Error  ---  ---  --  --  - 


 *An  asterisk  denotes  a  statistically  significant  difference  between  competitive  and  noncompetitive  groups  at  a  95.5%  level  of  confidence. 
22
 Federal  Communications  Commission  FCC  01-  49 
 23 
 ATTACHMENT  B-  2 
 COMPARISON  OF  COMPETITIVE  AND  NONCOMPETITIVE  GROUPS,  BY  SIZE  CATEGORY 
 AVERAGE  MONTHLY  RATES 


 SIZE  COMPETITIVE  NONCOMPETITIVE  $  DIFFERENCE  BETWEEN  MEANS  %  DIFFERENCE  BETWEEN  MEANS 
 2000  Very  Large  -----  $35.75  -----  ----  -Standard 
 Error  -----  0.  29 
 Other  Large  -----  $34.79  -----  ----  -Standard  Error  -----  0.  35 


 Overall  Large  $33.47  $35.16  $1.69  5.0%*  Standard  Error  0.  30  0.  33 
 Medium  $33.31  $34.48  $1.17  3.5%  Standard  Error  0.  46  0.  35 
 Small  -----  $32.04  -----  ----  -Standard  Error  -----  0.  46 
 Very  Small  -----  $26.59  -----  ----  -Standard  Error  -----  1.  03 
 Overall  Small  $28.35  $31.10  $2.75  9.7%*  Standard  Error  0.  61  0.  56 
 1999  Very  Large  -----  $33.66  -----  ----  -Standard 
 Error  -----  0.  27 
 Other  Large  -----  $33.07  -----  ----  -Standard  Error  -----  0.  31 


 Overall  Large  $31.46  $33.30  $1.84  5.8*  Standard  Error  0.  22  0.  29 
 Medium  $31.44  $32.40  $0.96  3.1%  Standard  Error  0.  40  0.  34 
 Small  -----  $30.47  -----  ----  -Standard  Error  -----  0.  42 
 Very  Small  -----  $25.46  -----  ----  -Standard  Error  -----  0.  90 
 Overall  Small  $27.30  $29.60  $2.30  8.4%*  Standard  Error  0.  61  0.  48 
 1998 
 Very  Large  -----  $31.89  -----  ----  -Standard  Error  -----  0.  24 


 Other  Large  -----  $31.43  -----  ----  -Standard  Error  -----  0.  29 
 Overall  Large  $30.01  $31.61  $1.60  5.3%*  Standard  Error  0.  21  0.  27 
 Medium  $30.21  $30.67  $0.46  1.5%  Standard  Error  0.  37  0.  33 
 Small  -----  $29.24  -----  ----  -Standard  Error  -----  0.  39 
 Very  Small  -----  $24.58  -----  ----  -Standard  Error  -----  0.  91 
 Overall  Small  $26.31  $28.43  $2.12  8.1%*  Standard  Error  0.  57  0.  48 


 Average  monthly  rates  include  BST,  CPST,  and  equipment  (i.  e.,  converter  and  remote  control).  *An  asterisk  denotes  a  statistically  significant  difference  between  competitive  and  noncompetitive  groups  at  a  95.5%  level  of  confidence. 
23
 Federal  Communications  Commission  FCC  01-  49 
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 ATTACHMENT  B-  3 
 COMPARISON  OF  COMPETITIVE  AND  NONCOMPETITIVE  GROUPS,  BY  SIZE  CATEGORY  NUMBER  OF  CHANNELS  OFFERED  AND  PER  CHANNEL  RATES 


 Number  Of  Channels  Per  Channel  Rates  SIZE  COMPETITIVE  NONCOMPETITIVE  COMPETITIVE  NONCOMPETITIVE 
 2000  Very  Large  -----  62.  9  -----  $0.  58 
 Standard  Error  -----  0.  80  -----  0.  01 
 Large  -----  60.  4  -----  $0.  58  Standard  Error  -----  0.  71  -----  0.  01 


 Overall  Large  66.5  61.4  $0.51  $0.58  Standard  Error  0.  68  0.  75  0.  01  0.  01 
 Medium  61.3  54.2  $0.56  $0.66  Standard  Error  1.  21  0.  99  0.  02  0.  01 
 Small  -----  43.  9  -----  $0.  76  Standard  Error  -----  1.  20  -----  0.  02 
 Very  Small  -----  26.  9  -----  $1.  09  Standard  Error  -----  1.  84  -----  0.  08 
 Overall  Small  44.3  41.0  $0.71  $0.82  Standard  Error  1.  45  1.  31  0.  03  0.  03 
 1999  Very  Large  -----  60.  9  -----  $0.  56 
 Standard  Error  -----  0.  85  -----  0.  01 
 Large  -----  57.  9  -----  $0.  58  Standard  Error  -----  0.  69  -----  0.  01 


 Overall  Large  64.1  59.1  $0.50  $0.57  Standard  Error  0.  76  0.  75  0.  01  0.  01 
 Medium  59.3  50.6  $0.56  $0.66  Standard  Error  1.  28  0.  94  0.  02  0.  01 
 Small  -----  41.  2  -----  $0.  77  Standard  Error  -----  1.  04  -----  0.  02 
 Very  Small  -----  25.  7  -----  $1.  09  Standard  Error  -----  1.  69  -----  0.  08 
 Overall  Small  42.2  38.5  $0.72  $0.83  Standard  Error  1.  40  1.  15  0.  03  0.  03 
 1998  Very  Large  -----  57.  9  -----  $0.  56 
 Standard  Error  -----  0.  91  -----  0.  01 
 Other  Large  -----  56.  4  -----  $0.  57  Standard  Error  -----  0.  77  -----  0.  01 


 Overall  Large  62.3  57.0  $0.50  $0.57  Standard  Error  0.  81  0.  82  0.  01  0.  01 
 Medium  57.5  47.8  $0.55  $0.67  Standard  Error  1.  27  0.  89  0.  02  0.  01 
 Small  -----  39.  6  -----  $0.  77  Standard  Error  -----  1.  08  -----  0.  02 
 Very  Small  -----  24.  9  -----  $1.  09  Standard  Error  -----  1.  69  -----  0.  08 
 Overall  Small  40.7  37.1  $0.72  $0.83  Standard  Error  1.  37  1.  19  0.  03  0.  03 
24
 Federal  Communications  Commission  FCC  01-  49 
 25 
 ATTACHMENT  B-  4 
 REGRESSION  RESULTS  SHOWING  THE  EFFECTS  OF  COMPETITIVE  STATUS,  MSO  AFFILIATION,  SYSTEM  SIZE,  NUMBER  OF  CHANNELS,  AND  HOUSEHOLD  INCOME 
 ON  AVERAGE  MONTHLY  RATES 
 VARIABLE  COEFFICIENT  Low  Penetration  Dummy  -0.  0203 
 (0.  0157) 
 LEC  Dummy  -0.0984 
 (0.  0112) 
 Municipal  Dummy  -0.  3282 
 (0.  0601) 
 Overbuild  Dummy  -0.  0177 
 (0.  0227) 
 DBS  Dummy  0.0788 
 (0.  0158) 
 MSO  Dummy  0.  1498 
 (0.  0355) 
 Reciprocal  of  Avg.  Total  Channels  -9.  7460 
 (0.  8760) 
 Log  of  Median  Household  Income  0.0194 
 (0.  0181) 
 Intercept  3.  3672 
 (0.  1954) 
 Adjusted  R  Square  .45 


 Number  of  Observations  718 
 Impact  of  LEC  Systems  -0.0937 
 Impact  of  DBS  Systems  0.  0820 
 Dependent  variable  is  log  of  average  monthly  rate.  Standard  error  of  coefficient  is  in  parenthesis. 
25
 Federal  Communications  Commission  FCC  01-  49 
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 ATTACHMENT  B-  5  COMPARISON  OF  COMPETITIVE  GROUP  BY  TEST  FOR  EFFECTIVE  COMPETITION 
 WITH  NONCOMPETITIVE  GROUP 
 WIRELINE 
 OVERBUILD 
 DBS 
 OVERBUILD 
 OVERBUILD 
 LEC 
 LOW 
 PENETRATION  MUNICIPAL 
 NONCOMPETITIVE 
 GROUP 


 2000 
 Monthly  Charge  $33.74  $33.23  $33.65  $32.21  $31.56  $22.56  $34.11  Standard  Error  0.  83  1.  22  .91  0.29  0.60  1.55  0.66 


 %  Difference  1.  1%  2.  6%  1.  4%  5.9%*  8.  1%*  51.2%*  --Number 
 of  Channels  56.5  38.6  53.4  66.3  45.9  50.3  54.8  Standard  Error  1.  79  3.  84  2.  14  0.  61  1.  91  3.  03  0.  92 
 %  Difference  -3.0%  42.0%*  2.  6%  -17.3%*  19.4%*  8.  9%  --Charge 
 per  Channel  0.62  0.96  0.68  0.49  0.74  0.46  0.66  Standard  Error  0.  02  0.  07  0.  03  0.  01  0.  03  0.  03  0.  01 
 %  Difference  6.  5%  -31.3%*  -2.9%  34.7%*  -10.8%*  43.5%*  --1999 
 Monthly  Charge  $31.49  $32.90  $31.73  $30.40  $30.17  $21.54  $32.25 
 Standard  Error  0.  70  1.  22  0.  79  0.  23  0.  60  1.  56  0.  35 
 %  Difference  2.  4%  -2.0%  1.6%  6.1%*  6.  9%*  49.7%*  --Number 


 of  Channels  53.2  35.1  50.1  64.5  43.5  48.9  52.0  Standard  Error  1.  81  3.  16  20.  4  0.  65  1.  77  3.  26  0.  90 
 %  Difference  -2.3%  48.1%*  3.  8%  -19.4%*  19.5%*  6.3%  --Charge 
 per  Channel  0.62  1.02  0.69  0.48  0.74  0.46  0.65  Standard  Error  0.  02  0.  07  0.  03  0.  01  0.  03  0.  03  0.  01 
 %  Difference  4.  8%  -36.3%*  -5.8%  35.4%*  -12.2*  41.3%*  --1998 
 Monthly  Charge  $29.76  $31.40  $30.04  $29.26  $28.88  $20.58  $30.65 
 Standard  Error  0.  62  1.  09  0.  70  0.  21  0.  57  1.  39  0.  33 
 %  Difference  3.  0%  -2.3%  2.0%  4.8%*  6.  2%*  48.9%*  --Number 


 of  Channels  51.0  31.9  47.7  62.9  42.5  46.8  49.8  Standard  Error  1.  64  2.  70  1.  82  0.  69  1.  77  3.  42  0.  94 
 %  Difference  -2.4%  56.1%*  4.  4%  -20.8%*  17.2%*  6.4%  --Charge 
 per  Channel  0.61  1.07  0.69  0.48  0.73  0.47  0.65  Standard  Error  0.  02  0.  07  0.  03  0.  01  0.  03  0.  04  0.  01 
 %  Difference  6.  6%  -39.3%*  -5.8%  35.4%*  -11.0*  38.3%*  --Weighted 
 average  of  wireline  and  DBS  overbuild  using  weights  shown  in  Attachment  A.  Average  monthly  rates  are  for  BST,  CPST,  and  equipment  (i.  e., 
 converter  and  remote  control). 
   Percent  difference  between  competitive  subcategories  and  noncompetitive  group. 
 *An  asterisk  denotes  a  statistically  significant  difference  between  competitive  subcategories  and  noncompetitive  group  at  a  95.5%  level  of  confidence. 
26
 Federal  Communications  Commission  FCC  01-  49 
 27 
 ATTACHMENT  B-  6 
 AVERAGE  MONTHLY  CHARGES  FOR  OTHER  SERVICES 


 COMPETITIVE  GROUP  NONCOMPETITIVE  GROUP 


 1999  2000  1999  2000 
 Installation  $26.44  $27.65  $37.16  $37.76 
 Standard  Error  1.66  1.58  1.22  1.24 
 Observations  299  299  389  389 


 Reconnection  $21.16  $21.76  $23.39  $24.01 
 Standard  Error  1.03  0.98  0.78  0.78 
 Observations  237  237  363  363 


 Tier  Change  $6.13  $6.40  $8.49  $8.76 
 Standard  Error  0.95  0.96  0.97  0.99 
 Observations  281  281  346  346 


 Represents  the  stratum-  weighted  average  for  operators  who  reported  a  non-  zero  charge  in  1999  and  2000.  Data  on  disconnection  charges 
 were  also  collected,  but  are  not  being  reported  in  this  table  since  so  few  (less  than  1%)  operators  surveyed  reported  having  such  a  charge. 
27
 Federal  Communications  Commission  FCC  01-  49 
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 ATTACHMENT  B-  7 
 OPERATORS'  EXPLANATION  FOR  CHANGES  IN  MONTHLY  RATES  FOR  COMPETITIVE  AND  NONCOMPETITIVE  GROUPS 


 2000  1999 
 RATE  CHANGES  ATTRIBUTED 


 TO: 
 Competitive  %  of  Total  NonComp  %  of  Total  Competitive  %  of  Total  NonComp  %  of  Total 


 Programming  $0.77  43.5%  $0.75  40.3%  $0.63  48.1%  $0.78  48.8%  Standard  Error  0.06  0.07  0.07  0.07 
 Copyright  Fees  $0.01  0.6%  $0.02  1.1%  $0.01  0.8%  $0.01  0.6%  Standard  Error  0.02  0.02  0.01  0.01 
 Channel  Additions  $0.06  3.4%  $0.09  4.8%  $0.06  4.6%  $0.07  4.4%  Standard  Error  0.02  0.04  0.03  0.03 
 Upgrades  $0.16  9.0%  $0.23  12.4%  $0.18  13.7%  $0.17  10.6%  Standard  Error  0.06  0.05  0.04  0.05 
 Equipment  $0.12  6.8%  $0.20  10.8%  $0.15  11.4%  $0.11  6.9%  Standard  Error  0.02  0.04  0.04  0.02 
 Franchise  $0.00  0.0%  $0.00  0.0%  $0.01  0.8%  $0.01  0.6%  Standard  Error  0.0  0.00  0  0.00 
 Inflation  $0.10  5.6%  $0.18  9.7%  $0.10  7.6%  $0.15  9.4%  Standard  Error  0.02  0.02  0.02  0.02 
 Unspecified  Costs  $0.38  21.5%  $0.14  7.5%  $0.04  3.1%  $0.08  5.0%  Standard  Error  0.11  0.05  0.04  0.03 
 Non-  Cost  Increases  $0.17  9.6%  $0.25  13.4%  $0.13  9.9%  $0.22  13.7%  Standard  Error  0.04  0.07  0.05  0.05 
 $  Change  in  Rate  $1.77  100%  $1.86  100%  $1.31  100%  $1.60  100% 
28
 Federal  Communications  Commission  FCC  01-  49 
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 ATTACHMENT  C-  1 
 AVERAGE  NUMBER  OF  CHANNELS  DEVOTED  TO  EACH  CATEGORY  OF  PROGRAMMING 
 COMPETITIVE  GROUP  NONCOMPETITIVE  GROUP 
 Category  of  Programming  1999  2000  %  Change  1999  2000  %Change 


 Total  Number  of  Channels  59.2  63.0  6.4%  53.6  57.3  6.9%  Standard  Error  1.20  1.22  0.90  0.94 
 Access    3.1  3.4  9.7%  3.4  3.6  5.9% 
 Standard  Error  0.30  0.31  0.18  0.18 


 Broadcast  12.1  12.3  1.7%  10.6  10.6  0.0%  Standard  Error  0.40  0.40  0.33  0.33 


 Total  Satellite  Programming  44.0  47.3  7.5%  39.6  43.1  8.8% 
 Standard  Error  0.96  0.98  0.79  0.82 


 Children's  Programming  3.8  4.1  7.9%  3.2  3.7  15.6% 
 News  Programming  6.4  6.7  4.7%  5.9  6.3  6.8% 
 Sports  Programming  4.3  4.8  11.6%  3.6  4.0  11.1% 
 General  Entertainment  29.5  31.7  7.5%  26.9  29.1  8.2% 


 Number  of  Survey  Responses  248  248  ---  366  366  --  - 
 Includes  public,  educational,  governmental,  and  commercial  leased  access. 
   Includes  childrens,  news,  sports,  and  general  entertainment  satellite  programming,  excluding  premium  and  pay-  per-  view 
 channels.  Note:  These  numbers  differ  from  numbers  reported  in  Tables  5  and  6,  and  Attachments  B-  1  and  B-  3,  because  the  channels  in  this  table 


 encompass  all  CPST  tiers,  rather  than  the  most  highly  subscribed  CPST,  as  well  as  satellite  channels  in  the  BST. 
29
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 ATTACHMENT  C-  2 
 OPERATORS  THAT  INCREASED  ACTIVE  ANALOG  CHANNELS  BETWEEN  1999  AND  2000 
 Responses  Competitive  Group  Noncompetitive  Group 


 No  Increase  383  145  238 
 Increased  Channels:  Between  1  and  5  229  141  88 


 Between  6  and  10  36  7  29 
 Between  11  and  15  28  5  23 
 Between  16  and  20  18  10  8 
 Between  21  and  30  21  9  12 
 Between  31  and  50  6  1  5 
 Total  Observations  721  318  403 
30
 Federal  Communications  Commission  FCC  01-  49 
 31 
 ATTACHMENT  D-  1 
 Regression  Results  Showing  The  Effects  of  Clustering,  Competitive  Status,  Median  Household  Income,  and  Number  of  Channels  on  Average  Monthly  Rates 


 VARIABLE  COEFFICIENT  STANDARD  ERROR 
 Low  Penetration  Dummy  -0.  0251  0.0157 
 LEC  Dummy  -0.  0992  0.0111 
 Municipal  Dummy  -0.  3259  0.0600 
 Overbuild  Dummy  -0.  0179  0.0225 
 DBS  Dummy  0.0799  0.0154 
 MSO  Dummy  0.1374  0.0360 
 Reciprocal  of  Avg.  Total  Channels  -9.  8906  0.8682 
 Log  of  Median  Household  Income  0.0104  0.0184 
 Cluster  Dummy  0.0236  0.0090 
 Constant  3.4590  0.1983 
 Adjusted  R  Square  .47 
 Number  of  Observations  708 


 Notes  on  Attachment  D-  1: 
 This  equation  is  intended  to  measure  the  effects  of  clustering  on  average  monthly  rates.  The  form 
 of  the  equation  is  analogous  to  that  of  the  Benchmark  equation  shown  in  Attachment  B-  4  except  that  a 
 cluster  dummy  variable  was  added  to  measure  the  effects  of  clustering.  We  assigned  a  value  of  one  for 
 each  operator  that  was  part  of  a  cluster  and  a  value  of  zero  for  those  operators  that  were  not  part  of  a 
 cluster.  The  dependent  variable  (log  of  average  monthly  rates)  is  the  same  in  both  equations. 


 We  expected  the  clustering  variable  to  have  a  negative  coefficient,  i.  e.,  an  inverse  relationship  between 
 clustering  and  average  monthly  rates.  As  a  positive  change  is  noted  in  the  clustering  variable,  we  would 
 expect  to  find  lower  average  monthly  rates  due  to  increasing  economies  of  scale.  When  we  estimated  the 
 equation,  we  found  the  opposite  effect,  the  coefficient  for  the  clustering  variable  was  positive.  This 
 means  that  as  clustering  increased,  average  monthly  rates  also  increased. 


 We  also  tested  a  regression  equation  estimating  the  effects  of  clustering  on  monthly  rates  suggested  by 
 AT&  T  in  its  comments  in  response  to  Notice  of  Inquiry,  CS  Docket  No.  00-  132.  In  this  revised  cluster 
 regression  equation,  log  of  franchise  subscribers,  log  of  average  subscriber  taking  most  popular  service 
 (e.  g.,  subscribers  taking  BST,  CPST,  remote,  and  a  converter),  and  Internet  service  were  added  to  the 
 variables  shown  in  Table  D-  1.  The  revised  regression  equation  had  the  following  coefficients:  3.4477   
 .1015  LEC  -  .0180  low  penetration  -  .0297  overbuild  -  .0653  DBS  -  .3233  municipal    9.2487  reciprocal  of 
 average  total  channels  +  .1362  MSO  +  .0085  log  of  median  household  income  +  .0151  log  of  subscribers 
 taking  most  popular  service  -  .0150  log  of  franchise  subscribers  +  .0237  cluster  +  .0146  telephony  service  + 
 .0266  Internet  service.  We  note  that  the  coefficient  for  the  clustering  variable  remains  fairly  constant  -- 
 .0237  compared  with  .0236  in  this  version  of  the  model. 
31
 Federal  Communications  Commission  FCC  01-  49 
 32 
 Since  our  revised  cluster  regression  equation  included  subscribers  as  independent  variables,  this  may  have 
 introduced  a  simultaneous  relationship  between  average  monthly  rate  (the  dependent  variable)  and  the 
 subscriber  variables.  For  example,  the  number  of  subscribers  in  a  franchise  are  affected  by  the  average 
 monthly  rate  charged  which  in  turn  is  affected  by  the  number  of  subscribers  taking  the  service.  To  handle 
 this  simultaneity  problem,  we  replaced  subscriber  variables  in  the  revised  regression  equation  with  number 
 of  households  passed  in  a  franchise  area,  which  generally  is  not  directly  affected  by  average  monthly  rates. 
 The  regression  equation  using  a  household  passed  variable  yielded  the  following  relationship:  3.5174   
 .0966  LEC  -  .0243  low  penetration  -  .0297  overbuild  -  .0666  DBS  -  .3233  municipal    8.1319  reciprocal  of 
 average  total  channels  +  .1404  MSO  +  .0003  log  of  median  household  income    11.  9948  log  of  reciprocal  of 
 franchise  household  passed  +  .0214  cluster  +  .0156  telephony  service  +  .0291  Internet  service.  The  fact  that 
 the  coefficients  from  both  regression  equations  are  similar  indicated  that  no  significant  simultaneity  exists  in 
 our  revised  regression  equation.  Since  the  estimated  coefficient  for  the  clustering  variable  in  the  revised 
 regression  equation  was  positive  and  was  statistically  significant,  we  conclude  that  as  clustering  increases, 
 average  monthly  rates  also  increase.  A  number  of  studies  also  found  a  similar  relationship  between 
 clustering  and  rates.  See,  for  example,  Ford,  George  and  John  Jackson,  Horizontal  Concentration  and 
 Vertical  Integration  in  the  Cable  Television  Industry,  Review  of  Industrial  Organization,  12:  501-  518,  1997; 
 Tasneem  Chipty,  Horizontal  Integration  for  Bargaining  Power:  Evidence  from  the  Cable  Television 
 Industry,  Journal  of  Economics  &  Management  Strategy,  Volume  4,  Number  2,  375-  397,  Summer  1995. 
32
 Federal  Communications  Commission  FCC  01-  49 
 33 
 ATTACHMENT  D-  2 
 TWO-  STAGE  LEAST  SQUARES  REGRESSION  COEFFICIENTS  FOR  DEMAND  EQUATION 
 Dependent  Variable  Independent  Variables 
 Log  of  Franchise 
 Subscribers 
 Constant  Competitive 
 Status 
 Log  of  ratio  of 
 Non-  urban 
 Population 


 Log  of  Average 
 Monthly  Rate 
 Log  of  Median 
 Household 
 Income 


 Log  of  Number 
 of  Households 
 Passed 


 Log  of  Number 
 of  Satellite 
 Channels 
 Coefficient  0.4684  -0.  5799  -0.  1275  -1.  9470  0.6192  1.0042  0.0065 


 Standard  error  (2.  0955)  (0.  1085)  (0.  0538)  (0.  7346)  (0.  1262)  (0.  0157)  (0.  2012) 


 Adjusted  R  2  =  .94 
 Number  of  Observations  =  432.  The  number  of  observations  are  based  on  the  number  of  valid  responses  that  provided  complete  information 
 for  the  variables  included  in  the  model. 


 TWO-  STAGE  LEAST  SQUARES  REGRESSION  COEFFICIENTS  FOR  DEMAND  EQUATION  SHOWING  THE  EFFECT  OF  DBS  ON  DEMAND  FOR  CABLE  SERVICES 
 Dependent  Variable:  Independent  Variables 
 Log  of  Franchise 
 Subscribers 
 Constant  Competitive 
 Status 
 Log  of  Ratio 
 of  Non- 
 urban 
 Population 


 Log  of 
 Average 
 Monthly  Rate 


 Log  of 
 Median 
 Household 
 Income 


 Log  of 
 Number  of 
 Households 
 Passed 


 Log  of 
 Number  of 
 Satellite 
 Channels 


 Log  of 
 Number  of 
 DBS 
 Subscribers 
 Coefficient  -1.  1363  -0.  6031  -0.  0996  -1.  4520  0.6148  1.1023  -0.  0301  -0.  1358 


 Standard  error  (2.  0280)  (0.  1188)  (0.  0538)  (0.  7311)  (0.  1241)  (0.  0603)  (0.  2031)  (0.  0779) 


 Adjusted  R  2  =  .94 
 Number  of  Observations  =  432 
 The  number  of  observations  are  based  on  the  number  of  valid  responses  that  provided  complete  information  for  the  variables  included  in  the 
 model. 
33
 Federal  Communications  Commission  FCC  01-  49 
 34 
 Notes  on  Attachment  D-  2: 
 Attachment  D-  2  shows  our  econometric  estimates  of  the  demand  for  cable  services.  Estimating  a 
 demand  equation  provides  information  about  the  sensitivity  of  cable  subscriptions  to  the  price  of  service 
 and  also  permits  examination  of  substitutability  between  cable  and  other  services.  The  first  table  in 
 Attachment  D-  2  contains  our  basic  demand  equation,  and  the  second  table  augments  that  with  a  DBS 
 variable  in  order  to  measure  the  effects  of  DBS  on  cable. 


 Our  residual  demand  equation  for  cable  services  uses  a  set  of  variables  similar  to  those  used  in 
 previous  academic  studies.  49  In  our  demand  equation,  the  number  of  cable  subscribers  is  the  dependent 
 variable  (i.  e.,  the  variable  determined  by  the  other  variables  in  the  equation).  This  variable  is  a  function 
 of  several  independent  variables  (i.  e.,  those  that  determine  the  dependent  variable).  The  independent 
 variables  selected  for  this  model  are:  (a)  average  monthly  rate  for  programming  services  and  equipment; 
 (b)  median  household  income;  (c)  number  of  households  passed;  (d)  ratio  of  non-  urban  population  to  total 
 population;  (e)  average  number  of  satellite  channels  offered;  and  (f)  competitive  status.  We  selected  these 
 independent  variables  for  the  following  reasons.  Economic  theory  shows  that  price  and  consumer  income 
 should  be  selected  as  independent  variables  when  constructing  a  demand  equation.  The  number  of 
 satellite  channels  was  selected  as  a  quality  factor  since  it  represents  a  proxy  for  the  quality  of  cable 
 services  received  by  consumers.  The  remaining  variables  capture  demographic  and  other  factors  that 
 influence  the  demand  for  cable  services.  These  variables  also  serve  as  a  proxy  to  capture  the  effects  of 
 the  prices  of  competing  services  as  well  as  the  prices  of  all  other  goods  and  services  which  were  not 
 included  in  our  study. 


 In  general,  the  coefficients  in  our  estimated  demand  function  were  expected  to  have  a  positive  or 
 negative  influence  on  the  demand  for  cable  service  (i.  e.,  signs),  as  follows.  The  average  monthly  rate  for 
 programming  services  and  equipment  was  expected  to  have  a  negative  sign  which  would  indicate  a 
 decreasing  demand  for  cable  as  the  price  of  cable  service  rises.  The  sign  for  the  coefficient  of  median 
 household  income  was  expected  to  be  positive  because  we  would  expect  the  demand  for  cable  services  to 
 increase  as  consumers  income  rises.  The  number  of  households  passed  was  expected  to  have  a  positive 
 sign;  as  the  number  of  households  passed  increases  the  potential  market  increases  and,  as  a  result,  we 
 would  expect  a  larger  number  of  subscribers.  The  ratio  of  non-  urban  population  to  total  population  was 
 expected  to  have  a  negative  sign  because  there  is  generally  a  lower  penetration  of  cable  service  in  rural 
 areas  and  there  may  be  a  greater  presence  of  non-  cable  video  providers  (mainly  Direct-  to-  Home  satellite 
 providers)  in  those  areas.  50  The  average  number  of  satellite  channels  offered  was  expected  to  have  a 
 positive  sign  because  we  believe  that,  as  more  channels  are  offered,  consumers  will  associate  this  with  a 
 higher  quality  of  service  and,  as  a  result,  demand  more  cable  service.  The  competitive  status  of  the  cable 
 operator  was  expected  to  have  a  negative  sign.  We  believe  that  the  presence  of  competitors  in  the  market 
 will  take  subscribers  away  from  the  incumbent  operator  and  thus  lead  to  lower  cable  demand  for  the 


 49  The  previous  studies  using  similar  sets  of  independent  variables  include:  Rubinovitz,  Robert  N.,  Market  Power 
 and  Price  Increases  for  Basic  Cable  Service  Since  Deregulation,  Rand  Journal  of  Economics,  Vol.  24,  No.  1, 
 Spring  1993;  Mayo,  J.  W.,  and  Y.  Otsuka,  Demand,  Pricing,  and  Regulation:  Evidence  from  the  Cable  TV 
 Industry,  Rand  Journal  of  Economics,  Vol.  22,  No.  3,  Autumn  1991;  Chipty,  T.,  Horizontal  Integration  for 
 Bargaining  Power:  Evidence  from  the  Cable  Television  Industry,  Journal  of  Economics  and  Management  Strategy, 
 Vol.  4,  No.  2,  Summer  1995;  Video  Economics,  Bruce  M.  Owen  and  Steven  Wildman,  Harvard  University  Press, 
 1992.  Residual  demand  for  cable  services  takes  into  account  the  prices  and  quantities  set  by  other  firms  selling 
 similar  services.  Since  we  dont  have  information  on  the  prices  of  competing  services,  these  influences  are  captured 
 by  instrument  variables  in  our  model.  Price  data  are  available  for  DBS  service,  but  there  is  no  geographic  variation. 


 50  See  Chipty,  T.,  Horizontal  Integration  for  Bargaining  Power:  Evidence  from  the  Cable  Television  Industry, 
 Journal  of  Economics  and  Management  Strategy,  Vol.  4,  No.  2,  Summer  1995. 
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 35 
 incumbent.  51  All  the  estimated  coefficients  had  the  expected  signs  except  for  the  coefficient  for  number 
 of  satellite  channels,  and  all  coefficients  were  significantly  different  from  zero.  The  estimated  coefficient 
 for  average  number  of  satellite  channels  had  a  negative  sign  and  it  was  not  statistically  significant. 


 Some  of  these  variables  produce  simultaneous  (or  two-  way)  relationships.  For  example,  as 
 mentioned  above,  we  believe  that  the  demand  for  cable  service  is  sensitive  to  changes  in  average  monthly 
 cable  rates  and  to  the  number  of  satellite  channels  offered.  At  the  same  time,  as  demand  increases,  this 
 may  enable  cable  operators  to  offer  more  channels  and  charge  higher  rates  for  their  service.  To  handle  this 
 simultaneity  problem,  we  chose  a  two-  stage  least  squares  (  TSLS)  procedure,  which  addresses  this 
 problem  in  estimating  the  demand  equation.  52  The  TSLS  procedure  uses  a  two-  step  method  to  purge  the 
 simultaneous  relationship  among  the  variables.  In  the  first  stage,  we  derive  predicted  values  for  certain 
 variables  and  then  we  use  those  predicted  values  as  independent  variables  in  the  second  stage.  53 
 Specifically,  in  the  first  stage,  we  estimated  predicted  values  for  average  monthly  rates  and  number  of 
 satellite  channels.  Next,  in  the  second  stage,  we  regress  our  dependent  variable  (number  of  cable 
 subscribers)  on  the  predicted  values  for  these  variables  and  on  the  actual  values  of  the  remaining  variables 
 (average  household  income,  non-  urban  population,  competitive  status,  and  number  of  households  passed 
 in  the  service  area)  to  estimate  our  demand  equation  for  cable  service. 


 The  estimated  coefficients  shown  in  the  first  table  of  Attachment  D-  2  were  derived  using  this 
 TSLS  procedure.  The  predicted  values  used  in  the  second  stage  were  estimated  in  separate  first  stage 
 regressions  of  the  monthly  rate  and  satellite  channel  variables  on  a  set  of  instrument  variables  which 
 served  as  independent  variables  in  the  equations.  The  set  of  instrument  variables  included  log  of  median 
 household  income,  and  a  number  of  demographic  and  regional  variables  that  affect  demand  for  cable. 
 The  demographic  variables  include  log  of  county  population  density,  log  of  ratio  of  non-  urban  population 
 to  total  population,  log  of  percent  of  county  families  in  poverty,  log  of  ratio  of  county  population  with  a 
 bachelors  degree,  log  of  county  population  living  in  owner  occupied  housing,  log  of  percent  of 
 population  under  the  age  of  16,  and  log  of  percent  of  population  living  in  condominiums.  54  These 
 demographic  variables  have  been  found  to  be  important  determinants  of  cable  demand  by  other 
 researchers  in  their  studies  of  the  cable  industry.  55  The  regional  instrument  variables  included  in  the 


 51  The  competitive  status  variable  reflects  a  relationship  suggested  by  the  dominant  firm-  competitive  fringe  model 
 where  demand  for  a  product  depends  upon  demand  and  cost  conditions  affecting  both  the  dominant  and  fringe 
 providers  of  that  product.  For  a  further  discussion  of  the  dominant  firm-  competitive  fringe  model,  see  Blank,  L., 
 D.  L.  Kaserman,  and  J.  W.  Mayo,  Dominant  Firm  Pricing  with  Competitive  Entry  and  Regulation:  The  case  of 
 IntraLATA  Toll,  Journal  of  Regulatory  Economics,  14,  1998  at  35-  53. 


 52  In  ideal  terms,  we  would  prefer  that  all  the  influences  captured  in  a  demand  equation  go  in  one  direction  only,  i.  e., 
 that  the  influences  go  from  the  independent  variables  to  the  dependent  variable.  In  this  case,  the  influences  go  in 
 both  directions.  In  economic  terms,  this  is  called  simultaneity.  Failure  to  deal  with  this  problem  will  result  in 
 biased  estimations  of  the  demand  function. 


 53  For  a  further  explanation  of  this  technique,  see  Intriligator,  Michael  D.,  Econometric  Models,  Techniques,  & 
 Applications,  Prentice-  Hall,  1978  at  368-  428. 
 54  The  natural  log  of  these  variables  is  used  to  capture  departures  from  purely  linear  relationships  between  the 
 variables.  Put  another  way,  using  logs  of  the  variables  assumes  a  curvilinear  relationship  instead  of  a  linear  one. 
 This  is  a  common  procedure  and  is  followed  in  almost  every  demand  estimation  study  of  the  cable  industry.  Several 
 of  these  variables  may  have  supply  side  influences  as  well  as  demand  influences.  These  variables,  however,  were 
 used  by  previous  researchers  in  their  development  of  demand  equations.  See,  for  example,  Chipty,  T.,  Horizontal 
 Integration  for  Bargaining  Power:  Evidence  from  the  Cable  Television  Industry,  Journal  of  Economics  and 
 Management  Strategy,  Vol.  4,  No.  2,  Summer  1995;  Video  Economics,  Bruce  M.  Owen  and  Steven  Wildman, 
 Harvard  University  Press,  1992. 


 55  See  fn.  49. 
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 36 
 model  include  dummy  variables  representing  the  south-  Atlantic,  mid-  Atlantic,  and  mountain  regions. 
 These  variables  were  used  to  account  for  regional  differences  in  taste  and  consumer  preferences  for  cable 
 as  well  as  other  services.  We  also  used  MSO  affiliation  and  whether  or  not  the  cable  system  was  part  of  a 
 cluster  as  additional  instrument  variables. 


 Since  the  data  used  in  our  model  are  taken  from  a  stratified  sample,  econometric  theory  indicates 
 that  the  estimates  will  most  likely  be  heteroskedastic.  Hetroskedasticity  is  a  common  problem  in 
 econometric  estimation  of  models  that  use  data  similar  to  our  data.  Econometric  theory  assumes  that  the 
 differences  between  the  estimated  value  and  the  actual  value  at  each  data  point  are  independent  of  one 
 another.  With  heteroskedastic  estimates,  by  contrast,  the  differences  between  the  estimated  values  and 
 actual  values  vary  systematically,  e.  g.,  grow  larger  as  one  of  the  variables  grows  larger.  This  problem,  if 
 it  is  not  corrected,  will  cause  some  of  the  statistical  characteristics  of  the  model,  such  as  the  standard 
 errors,  to  be  unreliable.  To  deal  with  this  influence,  we  used  a  procedure  suggested  by  Halbert  White  that 
 corrects  for  the  problems  introduced  by  hetroskedasticity.  56  The  estimated  standard  errors  shown  in  the 
 tables  are  hetroskedasticity  consistent  . 


 As  shown  in  the  first  table  of  Attachment  D-  2,  the  coefficient  for  average  monthly  rates  is  minus 
 1.45.  This  suggests  that  the  demand  for  cable  service  is  somewhat  price  elastic  (i.  e.,  has  a  price  elasticity 
 of  minus  1.45)  and  suggests  that  there  are  substitutes  for  cable  service.  In  order  to  investigate  the  extent 
 to  which  DBS  may  be  one  of  those  substitutes,  we  added  a  DBS  variable  to  our  demand  model.  The 
 coefficients  shown  in  the  second  table  are  based  on  a  demand  equation  identical  to  the  one  discussed 
 above  with  the  single  exception  that  a  DBS  variable  was  added.  57  Since  the  price  for  DBS  service  does 
 not  vary  geographically,  we  used  the  number  of  DBS  subscribers  as  the  additional  independent  variable  in 
 this  model.  We  hypothesized  a  negative  coefficient  for  this  variable  suggesting  that  as  the  number  of 
 DBS  subscribers  increases,  the  demand  for  cable  service  decreases. 


 Since  there  may  be  simultaneity  between  the  number  of  DBS  subscribers  and  the  demand  for 
 cable  services,  we  used  a  two-  stage  least  squares  procedure  for  this  model  similar  to  that  explained  above. 
 Also,  since  the  data  used  in  our  model  are  taken  from  a  stratified  sample,  which  tends  to  introduce 
 heteroskedasticity,  we  used  the  procedure  suggested  by  White  to  deal  with  this  influence.  The 
 coefficients  estimated  from  this  model  are  shown  in  the  second  table  of  Attachment  D-  2. 


 As  hypothesized,  the  sign  for  the  DBS  coefficient  is  negative  and  is  significantly  different  from 
 zero.  This  implies  that  DBS  is  a  substitute  for  cable  service  and  it  exerts  a  small  (shown  by  the  small 
 magnitude  of  DBS  coefficient)  but  statistically  significant  influence  on  the  demand  for  cable  service. 


 56  White,  H.,  A  Heteroskedasticity    Consistent  Covariance  Matrix  Estimator  and  a  Direct  Test  for 
 Heteroskedasticity,  Econometrica  48,  1980,  at  817-  838. 
 57  The  addition  of  the  DBS  variable,  like  the  inclusion  of  a  competitive  status  variable,  can  be  rationalized  by 
 reference  to  the  dominant  firm-  competitive  fringe  model.  See  fn.  51. 
36