Productivitybased Regulation: The New Zealand Experience

1
Productivity-based RegulationThe New Zealand
Experience
Presentation to 8th ACCC Regulatory
Conference 26 July 2007 Denis Lawrence
2
Background

• Many regulators acknowledge the desirability of
  moving to productivity index-based approaches to
  setting X and delinking the process from DBs own
  costs
• But most are concerned about inherent risks Is
  the system sufficiently mature? Is there
  sufficient data?
• MCE Expert Panel recommended the AEMC review the
  rules to facilitate the use of productivity-based
  approaches
• What can we learn from the use of
  productivity-based approaches elsewhere?
• New Zealand is one of the few places to have
  implemented productivity-based regulation
• How was it implemented? How were the problems
  encountered overcome? How successful has it been?

3
Electricity reform in NZ

• Distributors and retailers corporatised in 1992
  variety of ownership structures, no explicit
  regulation
• Information Disclosure required from 1995 as
  first step in light handed regulation
• Separation of distribution and retail in 1999
• Targeted control regime under Commerce Commission
  foreshadowed in 2001 and move to incentive
  regulation
• Thresholds seen as next logical step in evolution
  
• Progressive amalgamation of distributors 29 in
  2002, down from 60 in mid-1980s
• Important practical issue that Building Blocks
  Method not feasible for 29 ELBs in a small
  country so need to look at alternative of
  comparative benchmarking (regardless of whether
  it be a thresholds or a control regime)
• Pre-existing database allowed TFP approach

4
Rationale for productivity-based regulation

• Aim of mimicking competitive markets
• Productivity-based regulation by price caps
  (CPI-X)
• industry average price prevails
• not based on own costs
• response to efficiency and other changes gradual
• High power but also high risk (under or over
  earning)
• Innovation encouraged, less scope to game
  system
• Delinks prices and own costs, low regulatory
  costs
• X ? ?TFP ? ?TFPE ?W ? ?WE ?M
• Index approach can be mechanistic when firms
  starting from similar points
• Rolling X factor particularly attractive
• When there is a wide spread of efficiency levels
  will need to include stretch factors (ve for
  laggards, possibly ve for leaders) as well as
  industry average

5
Development of the scheme

• Need to allow for variety of starting points,
  particularly given no previous regulation and
  range of DB ownership
• As well as allowing for industry TFP growth, also
  need transitional factors in the X given
  different starting points
• X B C1 C2
• B factor reflecting the overall or average
  productivity trend for DBs
• C factors reflect different productivity and
  profitability starting points
• 3 C1 factor groupings based on relative
  productivity performance
• 3 C2 factor groupings based on relative
  profitability performance
• Price thresholds rather than explicit price caps
  but could be transferred to a control regime
• Based solely on results of quantitative study

6
Productivity measurement

• TFP is an index number measure which forms the
  ratio of all outputs to all inputs
• Relatively simple, robust and readily replicable
  technique
• It requires price and quantity data for all
  outputs and inputs
• Specification used includes 3 outputs energy
  throughput, customer numbers and system capacity
  (based on line length, voltage and engineering
  characteristics)
• Outputs weighted by output cost shares from cost
  function
• 5 inputs opex, O/H lines, U/G cables,
  transformers and other capital
• Use physical measures of capital input to better
  reflect depreciation characteristics of network
  assets

7
B factor

• X (TFP TFPE) (W WE)
• TFP for distribution trend rate of increase 2.0
  pa
• Economy TFP trend rate of increase 1.1 pa
• Conflicting information on relative input price
  movements so set this differential to zero
• Distribution B of 0.9 pa but round to 1 pa

8
Relative productivity C1 factor component

• Use 2 techniques
• Multilateral Total Factor Productivity (MTFP)
• allows analysis of productivity levels as well as
  growth rates
• allows the B and C factors to be calculated in an
  integrated framework
• density factors incorporated in output
  specification
• divide sample into high, medium and low
  productivity level groups
• average level of high productivity group around
  15 above average of medium group which was
  around 15 above average of low group
• Econometric cost function
• used to verify MTFP results and obtain output
  cost shares
• obtain broadly similar results to MTFP

9
Relative productivity performance
10
Relative profitability C2 factor component

• Incorporate profitability differences between the
  businesses using residual rates of economic
  return
• Calculated consistently with TFP from same
  database but less detailed than WACC process
• Divide sample into high, medium and low
  profitability groups
• Average residual rate of return of high
  profitability group was 10.3, of medium group
  was 7.3 and of low group was 3.4

11
Deriving the X Factors

• X B C1 C2
• Divide distributors into groups of high, average
  and low productivity levels and profitability
• Productivity C1 factor components of 1, 0 and 1
  per cent
• Profitability C2 factor components of 1, 0 and 1
  per cent
• Leads to overall X factor groupings of 1, 0, 1
  and 2 per cent
• C factors set conservatively given quality of the
  data and industry characteristics consistent
  with a 10 year glide path
• Mixture of business types in each X factor group
  with urban high density, urban low density, rural
  high density and rural low density businesses
  appearing in each
• X applied to each DBs actual starting price

12
Assessment

• Objective, highly transparent and replicable
  process with relatively low regulatory cost
  delivering real price reductions to consumers
• None of the vagaries of BBM (eg in our
  professional opinion) less scope for gaming
• Building blocks reviews of two of the larger DBs
  indicated they were earning better returns than
  they would have under BBM
• A few businesses have breached because they think
  they have a strong case for additional funds for
  investment it has not been a deterrent to
  investment
• 2009 reset will take lessons learnt into account
  may be role for allowing for position in asset
  lifecycle if impending wall of wire effect is
  thought to be significant in next regulatory
  period
• Information Disclosure Data is now more forward
  looking allowing scope for more account to be
  taken of forward looking information
• Ongoing role seen for productivity-based approach
  irrespective of outcome of thresholds review
• Importance of having a consistent database
  available