Transcript Electricity Lines Business Regulation Draft Decisions

Productivity-based Regulation:
The New Zealand Experience
8th
Presentation to
ACCC Regulatory Conference
26 July 2007
Denis Lawrence
Background
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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?
Electricity reform in NZ
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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
Rationale for productivitybased regulation
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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
Development of the
scheme
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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
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X = B + C1 + C2
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‘B’ factor reflecting the overall or average productivity
trend for DBs
‘C’ factors reflect different productivity and profitability
starting points
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3 C1 factor groupings based on relative productivity performance
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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
Productivity
measurement
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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
B factor
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X = [(TFP – TFPE) – (W – WE)]
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TFP for distribution trend rate of increase 2.0% pa
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Economy TFP trend rate of increase 1.1% pa
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Conflicting information on relative input price
movements so set this differential to zero
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Distribution B of 0.9% pa but round to 1% pa
Relative productivity:
C1 factor component
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Use 2 techniques:
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Multilateral Total Factor Productivity (MTFP)
 allows analysis of productivity levels as well as growth rates
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allows the B and C factors to be calculated in an integrated
framework
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density factors incorporated in output specification
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divide sample into high, medium and low productivity level
groups
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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
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obtain broadly similar results to MTFP
Relative productivity
performance
Efficiency Levels and Growth Rates
Efficiency
Utility A
Best practice
frontier
Efficiency target likely to be
selected if the regulator
takes account of absolute
efficiency levels of utilities
relative to best practice.
D
Efficiency target likely to be
selected if the regulator
simply compares TFP
growth rates for Utility B
and Utility A.
C
Utility B
t0
t1
t2
Time
Relative profitability:
C2 factor component
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Incorporate profitability differences between the businesses
using residual rates of economic return
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Calculated consistently with TFP from same database but
less detailed than WACC process
Divide sample into high, medium and low profitability
groups
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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%
Deriving the X Factors
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X = B + C1 + C2
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Divide distributors into groups of high, average and low
productivity levels and profitability
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Productivity C1 factor components of –1, 0 and 1 per cent
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Profitability C2 factor components of 1, 0 and –1 per cent
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Leads to overall X factor groupings of –1, 0, 1 and 2 per cent
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C factors set conservatively given quality of the data and
industry characteristics – consistent with a 10 year glide
path
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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
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X applied to each DB’s actual starting price
Assessment
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Objective, highly transparent and replicable process with relatively
low regulatory cost delivering real price reductions to consumers
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None of the vagaries of BBM (eg ‘in our professional opinion’) – less
scope for gaming
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Building blocks reviews of two of the larger DBs indicated they were
earning better returns than they would have under BBM
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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
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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
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Information Disclosure Data is now more forward looking allowing
scope for more account to be taken of forward looking information
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Ongoing role seen for productivity-based approach irrespective of
outcome of thresholds review
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Importance of having a consistent database available