parthasarathy regulatory tools for capex review and ......whether opex or capex solution is more...
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wwwwwwwwwwww. . . . erranet.orgerranet.orgerranet.orgerranet.org1st Educational workshop: Energy Capital Investment Programs1st Educational workshop: Energy Capital Investment Programs1st Educational workshop: Energy Capital Investment Programs1st Educational workshop: Energy Capital Investment Programs
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Regulatory tools forCAPEX review and approval:
overview of European approaches
PreparedPreparedPreparedPrepared bybybyby
Dr Srini Dr Srini Dr Srini Dr Srini ParthasarathyParthasarathyParthasarathyParthasarathy
Principal, OxeraPrincipal, OxeraPrincipal, OxeraPrincipal, Oxera
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• what do regulators try to assess: objective and definitions
• issues with benchmarking CAPEX
• ways of measuring CAPEX
• menu of tools: top-down and bottom-up
• case studies
• key takeaways
OverviewOverviewOverviewOverview
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YYYYKKKK
MMMMM
L, OPEXL, OPEXL, OPEXL, OPEX
Exogenous factors
• input minimisationinput minimisationinput minimisationinput minimisation
– what is the minimum level of input that the unit
could operate at, given the level of output?
• output maximisationoutput maximisationoutput maximisationoutput maximisation
– what is the maximum level of output that the
unit can produce, given the level of input?
KeyKeyKeyKey
Y outputs/outcomes
K capital
L labour
M materials
(or all other inputs)
CAPEXCAPEXCAPEXCAPEX
What regulators try to assess: optimal level of spend to What regulators try to assess: optimal level of spend to What regulators try to assess: optimal level of spend to What regulators try to assess: optimal level of spend to
meet meet meet meet outputs and outputs and outputs and outputs and outcomesoutcomesoutcomesoutcomes
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Regulatory cost model: assessing Regulatory cost model: assessing Regulatory cost model: assessing Regulatory cost model: assessing efficiency and the efficiency and the efficiency and the efficiency and the
potential for cost reductionspotential for cost reductionspotential for cost reductionspotential for cost reductions
Z: country- or region-specific factors
(e.g. customer density, topography, regional wages)
L = labour
K = capitalK = capitalK = capitalK = capital
M = materials
and supplies
C, cost = w.x
w = input prices
Y = total energy delivered,
passengers transported,
water delivered, track
replaced, etc.
OutputsOutputsOutputsOutputsInputsInputsInputsInputs TransformationTransformationTransformationTransformation
Factors outside management controlFactors outside management controlFactors outside management controlFactors outside management control
X =
pppproduction frontierroduction frontierroduction frontierroduction frontier
output-oriented (OO) technical inefficiency:
output loss due to techncial inefficiency
input-oriented (IO) technical inefficiency:
the amount by which inputs can be
reduced without reducing output
inefficientinefficientinefficientinefficient
A production function describes the transformation relationship—a ‘black box’—
which converts inputs into outputs
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Technical efficiency
• what quantityquantityquantityquantity of output can be
produced, given the inputs?
• how few inputs inputs inputs inputs are required, given the
outputs?
Scale efficiency
• are firms operating at the optimal operating at the optimal operating at the optimal operating at the optimal
scale sizescale sizescale sizescale size—i.e. are they exploiting
economies of scale in production
Economic efficiency
(technical + allocative)
• what is the lowest cost of lowest cost of lowest cost of lowest cost of
productionproductionproductionproduction, given the
outputs?
• generally, the focus of
utility regulation
Allocative efficiency
• whether the observed input (i.e. resources)
combination is the optimum given the relative
prices of inputs
Other types of efficiency: dynamic, revenue
and profit efficiency
• dynamic efficiency: what is the potential rate
of improvement in economic efficiency over
time?
Regulatory cost model: notions of efficiency focused onRegulatory cost model: notions of efficiency focused onRegulatory cost model: notions of efficiency focused onRegulatory cost model: notions of efficiency focused oncost or expenditure as a function of outputs and outcomes
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Illustration of static and dynamic efficiency gainsIllustration of static and dynamic efficiency gainsIllustration of static and dynamic efficiency gainsIllustration of static and dynamic efficiency gains
Frontier shift vs catch-up
Inefficient
Efficient
0 5 TimeTimeTimeTime
Frontier
shift
Catch-up
CostCostCostCost
Overall
scope for
efficiency
CatchCatchCatchCatch----upupupup
• how relatively inefficient is the company?
– by how much of this gap can the
company catch up to current best
practice in a given timeframe?
– individual target set for each company
Frontier shiftFrontier shiftFrontier shiftFrontier shift
• what is the potential for best practice to
improve?
– new technology/management practices
– target applied to every company in the
industry
Some regulators set a ‘general’ or
a ‘combined’ productivity target
Frontier
shift
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• what do regulators try to assess: objective and definitions
• issues with benchmarking CAPEX
• ways of measuring CAPEX
• menu of tools: top-down and bottom-up
• case studies
• key takeaways
OverviewOverviewOverviewOverview
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What do regulated companies spend their money on?What do regulated companies spend their money on?What do regulated companies spend their money on?What do regulated companies spend their money on?
• operations
– costs are generally predictable and well-explained by cost drivers
• maintenancemaintenancemaintenancemaintenance
– expenditure on maintaining existing assets; largely predictable
• renewalsrenewalsrenewalsrenewals
– expenditure on replacing assets that have reached, or are nearing, the end of
their useful lives
• enhancementsenhancementsenhancementsenhancements
– expenditure on new assets that expand the capacity or capability of the network
• ring-fenced fundsMost regulated companies are
capitalcapitalcapitalcapital----intensiveintensiveintensiveintensive
Therefore, capital costs typically account for a large
proportion of the cost base
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Forecasting the efficient level of capital investment is Forecasting the efficient level of capital investment is Forecasting the efficient level of capital investment is Forecasting the efficient level of capital investment is
difficultdifficultdifficultdifficult————enhancementsenhancementsenhancementsenhancements
• determining the efficient cost of large
capital projects is inherently difficult
– they may be one-offs and company-specific
– projects take a long time to deliver
– large inefficiencies can be baked into the
high-level specification and/or the detailed
design of the project
– market or technical innovations may not be
pursued
– history is a poor indicator of future costs
– forecasting uncertainty
– how much allowance should be made for
risk?
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Forecasting the efficient level of capital Forecasting the efficient level of capital Forecasting the efficient level of capital Forecasting the efficient level of capital maintenance could maintenance could maintenance could maintenance could
be equally difficultbe equally difficultbe equally difficultbe equally difficult————maintenance maintenance maintenance maintenance and renewalsand renewalsand renewalsand renewals
• capital maintenance and Renewals expenditure is more predictable than enhancement expenditure
• regulators still face difficulties in assessing the optimal level of capital maintenance and renewals
• examples of asset failure in most regulated sectors: Railtrack, air traffic control systems failures
(Ireland and UK), Northeast blackout 2003 (USA and Canada), Herne Hill floods…
• the impact on outputs and the probability of
failure of changing maintenance expenditure
may be unclear (particularly in the short term)
• companies typically have much better
knowledge of asset base/health
• possible bias towards higher-profile
enhancements projects
• what is the value of reliability and thus the
optimal level of asset risk?
Difficulties for regulatorsDifficulties for regulatorsDifficulties for regulatorsDifficulties for regulatorsThe costs of
failure can be
high!
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Possible CAPEX biasPossible CAPEX biasPossible CAPEX biasPossible CAPEX bias
Separate CAPEX allowance or TOTEX approach?
• instead of separate treatment of CAPEX
and OPEX, regulators may focus on cost
assessment and recovery based on total
expenditure (TOTEX)
• key aim is to combat a perceived bias
towards capital investment
– company given freedom to determine
whether OPEX or CAPEX solution is more
appropriate in the long term
– also to mitigate issues with accounting accounting accounting accounting
treatmenttreatmenttreatmenttreatment of cost items, balancing incentivesbalancing incentivesbalancing incentivesbalancing incentives
across cost categories and avoiding setting
an inequitable benchmark inequitable benchmark inequitable benchmark inequitable benchmark by assessing costs
separately
How the TOTEX approach worksHow the TOTEX approach worksHow the TOTEX approach worksHow the TOTEX approach works
• a proportion (Y%) of TOTEX is
added to the RAB and recovered
over an assumed asset life
• (1-Y)% of TOTEX is recovered as
it is incurred
• since Y% is determined ex ante,
the company should be
indifferent between CAPEX and
OPEX solutions
• also allows for a single efficiency
assessment and incentive rate
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• what do regulators try to assess: objective and definitions
• issues with benchmarking CAPEX
• ways of measuring CAPEX
• menu of tools: top-down and bottom-up
• case studies
• key takeaways
OverviewOverviewOverviewOverview
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Measuring CAPEXMeasuring CAPEXMeasuring CAPEXMeasuring CAPEX
Cash cost and capital stock approaches
CAPEX
Cash cost approach
Smoothed CAPEX
Unsmoothed CAPEX
Capital stock approach
Annuity
Depreciated historical cost
Cash cost approachCash cost approachCash cost approachCash cost approach
• simple to compute as based on outturn data
• may not take into account the long-lived nature of assets
• requires possible steady-state assumptions
• often ‘smoothed’ to account for differences in investment
profiles across comparator units (peers)
Capital stock approachCapital stock approachCapital stock approachCapital stock approach
• long-lived nature of the asset is recognised
• could be a more realistic approach to measuring CAPEX
• requires a range of assumptions and adds to the
regulatory burden
• outcome of assessment can be sensitive to the approach
taken and assumptions made
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Measuring CAPEXMeasuring CAPEXMeasuring CAPEXMeasuring CAPEX
Cash cost approach
To smooth or notTo smooth or notTo smooth or notTo smooth or not
• regulators tend to smooth ‘lumpy’
patterns of CAPEX to reduce
fluctuations over time that may be
down to company need or
managerial decision
• period over which to smooth
(5 years, 10 years?) is debatable as it
may need to correspond with asset
lives
• smoothing can reduce degrees of
freedom by reducing sample size
• can introduce internal inconsistency
between inputs (smoothed CAPEX)
and outputs (outturn cost drivers)
• can result in different treatment of
OPEX and CAPEX that may not be
consistent with the objective of
TOTEX benchmarking
2012 2013 2014 2015 2016 2017
CA
PE
X
Year
A
CAPEX Industry average
2012 2013 2014 2015 2016 2017
CA
PE
X
Year
B
CAPEX Industry average
2012 2013 2014 2015 2016 2017
CA
PE
X
Year
C
CAPEX Industry average
2012 2013 2014 2015 2016 2017
CA
PE
X
Year
D
CAPEX Industry average
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Measuring CAPEXMeasuring CAPEXMeasuring CAPEXMeasuring CAPEX
Capital stock approach
Annuity approachAnnuity approachAnnuity approachAnnuity approachDepreciated Depreciated Depreciated Depreciated historical historical historical historical
cost cost cost cost approachapproachapproachapproach
������ � gross value of initial investment
x annuity factor � ������
� ���������
������ = depreciation + depreciated asset value
x WACC ��
�� � � �
�
������
Return Depreciation
0
1
2
3
4
5
6
7
8
9
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 300
1
2
3
4
5
6
7
8
9
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
Age of assetAge of assetAge of assetAge of asset
CA
PE
XC
AP
EX
CA
PE
XC
AP
EX
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• what do regulators try to assess: objective and definitions
• issues with benchmarking CAPEX
• ways of measuring CAPEX
• menu of tools: top-down and bottom-up
• case studies
• key takeaways
OverviewOverviewOverviewOverview
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Assessing Assessing Assessing Assessing CAPEX efficiencyCAPEX efficiencyCAPEX efficiencyCAPEX efficiency
Top-down approaches
YC
CC
Benchmark unit cost = CC/YC
Inefficiency
Cost, C
Output, Y
C
A
Unit costUnit costUnit costUnit cost
Cost
Inefficiency
V
Efficiency frontier
FA
B
D
E
C
O
Data Data Data Data EEEEnvelopment Analysis (DEA)nvelopment Analysis (DEA)nvelopment Analysis (DEA)nvelopment Analysis (DEA)
Regression (OLS) adjusted for noiseRegression (OLS) adjusted for noiseRegression (OLS) adjusted for noiseRegression (OLS) adjusted for noise
Stochastic Frontier Analysis (SFA) Stochastic Frontier Analysis (SFA) Stochastic Frontier Analysis (SFA) Stochastic Frontier Analysis (SFA)
Standard regression model is extendedStandard regression model is extendedStandard regression model is extendedStandard regression model is extended
InefficiencyInefficiencyInefficiencyInefficiency
Cost
Output
C
A Ordinary least squares
(OLS)
InefficiencyInefficiencyInefficiencyInefficiency
Corrected OLS
(COLS)
Noise?Noise?Noise?Noise?
B
OLS shifted to the upper
quartile
InefficiencyInefficiencyInefficiencyInefficiency
Cost
Output, Y
C
AExpected cost
NoiseNoiseNoiseNoise
B
c = a + by +
‘inefficiency’ +
‘noise’;
Stochastic frontier
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Assessing Assessing Assessing Assessing CAPEX efficiency CAPEX efficiency CAPEX efficiency CAPEX efficiency
Bottom-up approach—basket of works
• combine a group of activities in a ‘basket of works’ with the associated expenditure
compared with an ‘implied’ level of CAPEX for the complete basket of works
• avoid comparing on an activity-by-activity basis, which could be distorted by companies’
allocation policies and definitions of works
• the basket of works approach compares the unit expenditure on similar capital projects
with ‘standardised’ unit (replacement) costs
• the ‘standardised’ unit cost for each project can be set by using the lowest unit cost, or
average unit cost, or other benchmark. Some regulators apply adjustments to the unit
cost to normalise for exogenous differences (e.g. fixed costs, regional factors)
• stringency of benchmark should be proportionate to data comparability and quality
considerations and availability of suitable comparator data
• the rate of catch-up set by the regulator could be:
���������������� �∑ !"#$%��& ∗ �"%()��$��*�"+*�&&
∑ !"#$%��&& ∗ +*)�,)-,�+�,$��*�"+*�&
For company � and capital project .
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• what do regulators try to assess: objective and definitions
• issues with benchmarking CAPEX
• ways of measuring CAPEX
• menu of tools: top-down and bottom-up
• case studies
• key takeaways
OverviewOverviewOverviewOverview
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Case studiesCase studiesCase studiesCase studies
Energiavirasto (Finnish Energy Authority)
Norwegian Water Resources and Energy Directorate
Council of European Energy Regulators
UK rail, health and telecoms regulators
Ofwat—Office of Water Services
Ofgem—Office of Gas and Electricity Markets
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UKUKUKUK
Ofgem’s approach to assessing CAPEX prior to RIIO
• Ofgem used a mix of regression modelling and engineering expert analysis to review
CAPEX activities
• for example, in GDPCR1 (gas distribution price review before RIIO):
– engineering consultant reviewed the GDNs’ forecast costs to understand whether they were
based on appropriate assumptions, including justification for their workload forecasts,
assumptions for real price increases and productivity
– assessment of GDNs’ efficiency for specific CAPEX and replacement expenditure by
benchmarking costs against workload across GDNs using regression
– bottom-up analysis by PB Power to consider the appropriate costs for particular activities,
based on information submitted by the GDNs and its own engineering experience
– comparison was limited to the GB networks, which are subject to similar licence conditions and
obligations, to avoid comparability issues that might arise from using data outside a specific
data set
– Ofgem considered relevant network-specific factors that could be driving differences in the
reported costs of companies to enable an equitable comparison
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UKUKUKUK
Ofgem’s approach in RIIO
RIIORIIORIIORIIO----ED1 and ED1 and ED1 and ED1 and
RIIORIIORIIORIIO----GD1GD1GD1GD1
• historical and forecast
data from the
companies
• pre-adjusted for
company-specific
issues (one- and two-
sided adjustments)
RIIORIIORIIORIIO----ED1ED1ED1ED1
• fastfastfastfast----tracktracktracktrack: 12.5%
weighting on each of
the top-down models,
and 75% weighting on
the disaggregated
model
• slowslowslowslow----tracktracktracktrack: 25%
weighting on each of
the top-down models,
and 50% weighting on
the disaggregated
model
RIIORIIORIIORIIO----GD1GD1GD1GD1
• 25% weighting on each
of historical and
forecast data,
top-down and
disaggregated TOTEX
models
• middle-up results
ignored
RIIORIIORIIORIIO----ED1ED1ED1ED1
• 2 top-down TOTEXTOTEXTOTEXTOTEX
models (different cost
drivers)
• 1 disaggregated result
from a number of unit
cost and econometric
models
RIIORIIORIIORIIO----GD1GD1GD1GD1
• 1 top-down TOTEXTOTEXTOTEXTOTEX model
(historical and forecast
data)
• 3 middle-up models
(OPEX, CAPEX, REPEXOPEX, CAPEX, REPEXOPEX, CAPEX, REPEXOPEX, CAPEX, REPEX)
(but not ultimately used)
• 7 activity-level
disaggregated models
(forecast and historical
data)
RIIORIIORIIORIIO----ED1 and RIIOED1 and RIIOED1 and RIIOED1 and RIIO----
GD1GD1GD1GD1
• upper quartile (UQ)
efficiency
adjustment
• cost threshold
based on 75:25
weighting on
Ofgem’s view and
companies’ forecast
respectively
• immediate catch-up
set and no time-
profiled efficiency
targets
Model inputsModel inputsModel inputsModel inputs ModelsModelsModelsModelsPredicting Predicting Predicting Predicting
future costsfuture costsfuture costsfuture costsTriangulationTriangulationTriangulationTriangulation
Efficiency Efficiency Efficiency Efficiency
challengechallengechallengechallengeBaselineBaselineBaselineBaseline
Reverse cost Reverse cost Reverse cost Reverse cost
adjustmentsadjustmentsadjustmentsadjustments
RIIORIIORIIORIIO----ED1 ED1 ED1 ED1
• modelled business
plan data directly
alongside historical
data
RIIORIIORIIORIIO----GD1GD1GD1GD1
• apply coefficients
from historical data
and modelling first
2 years of business
plan data to forecast
cost drivers
RIIORIIORIIORIIO----ED1 and ED1 and ED1 and ED1 and RIIORIIORIIORIIO----GD1GD1GD1GD1
• pass-through of
‘special factors’
allowance
Predicted future Predicted future Predicted future Predicted future
efficient cost levelefficient cost levelefficient cost levelefficient cost level
Fro
ntie
r F
ron
tier
Fro
ntie
r F
ron
tier sh
iftsh
iftsh
iftsh
ift
an
d R
PE
s ove
rlay
an
d R
PE
s ove
rlay
an
d R
PE
s ove
rlay
an
d R
PE
s ove
rlay
Efficiency Efficiency Efficiency Efficiency
targetstargetstargetstargets
Special factorsSpecial factorsSpecial factorsSpecial factors
CompanyCompanyCompanyCompany----specific specific specific specific
factorsfactorsfactorsfactors
Estimation approach, model Estimation approach, model Estimation approach, model Estimation approach, model
specification and selectionspecification and selectionspecification and selectionspecification and selectionAggregating Aggregating Aggregating Aggregating
resultsresultsresultsresults
Use Use Use Use of forecast of forecast of forecast of forecast
(BP) (BP) (BP) (BP) data data data data
Level Level Level Level of of of of
aggregationaggregationaggregationaggregation
Frontier shift Frontier shift Frontier shift Frontier shift
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UKUKUKUK
Ofgem’s approach to assessing CAPEX in RIIO
• Ofgem used a combination of top-down (regression, unit cost) and bottom-up (unit cost, basket of
works) approaches to assess CAPEX of energy networks
• to account for different investment profiles across the modelling period, 7-year smoothed CAPEX
was used
• CAPEX cost drivers (workload volume) were normalised over similar periods
• to ensure comparability, apart from smoothing, certain costs were excluded where:
– these costs could not be sufficiently explained by the cost drivers used in the CAPEX models.
Such costs were either assessed separately or added back as an adjustment
– there was a substantial change in the nature of the activity between price reviews
– these were company-specific and not comparable across companies
• composite scale variables (CSVs) were often used to simplify the models to assess expenditure
– these were weighted geometric means of various scale and activity drivers
• costs were normalised for differences in operating circumstances and regional labour prior to
modelling
– density/urbanitydensity/urbanitydensity/urbanitydensity/urbanity: applied a 15% productivity adjustment to the labour cost element of REPEX
and CAPEX mains reinforcement and connections, based on the proportion of work that is
carried out within the M25
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UKUKUKUK
Ofgem’s approach in RIIO-GD1
Cost areaCost areaCost areaCost area SubSubSubSub----cost cost cost cost categorycategorycategorycategory DriversDriversDriversDrivers
TopTopTopTop----down TOTEXdown TOTEXdown TOTEXdown TOTEX OPEX +7-year smoothed CAPEX CSV of MEAV, REPEX workload, mains reinforcement and
connections workload, external conditions reports, maintenance
MEAV and emergency servicing CSV. and time trend
MiddleMiddleMiddleMiddle----upupupup TOTEXTOTEXTOTEXTOTEX
(ultimately not used)(ultimately not used)(ultimately not used)(ultimately not used)
OPEX CSV of MEAV, external condition reports, maintenance MEAV and
the emergency CSV
CAPEXCAPEXCAPEXCAPEX CSV of MEAV, connectionCSV of MEAV, connectionCSV of MEAV, connectionCSV of MEAV, connections workload and mains reinforcement s workload and mains reinforcement s workload and mains reinforcement s workload and mains reinforcement
workloadworkloadworkloadworkload
REPEX Weighted average REPEX workload
BottomBottomBottomBottom----up regressionsup regressionsup regressionsup regressions Work management MEAV
Emergency service CSV based on customer numbers and external condition reports
Repairs External condition reports
Maintenance Maintenance MEAV
Mains reinforcement Mains reinforcement Mains reinforcement Mains reinforcement Weighted averageWeighted averageWeighted averageWeighted average workload (calculated by multiplying the work workload (calculated by multiplying the work workload (calculated by multiplying the work workload (calculated by multiplying the work
volume for each pipe diameter by an industry average unit cost for volume for each pipe diameter by an industry average unit cost for volume for each pipe diameter by an industry average unit cost for volume for each pipe diameter by an industry average unit cost for
each diameter)each diameter)each diameter)each diameter)
ConnectionsConnectionsConnectionsConnections Weighted average workloadWeighted average workloadWeighted average workloadWeighted average workload
Tier 1 REPEX Weighted average tier 1 workload
Ofgem used a ‘toolkit’ approach to assess the costs submitted by the GB GDNs in their
business plans, with relatively greater emphasis placed on econometric modelling
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UKUKUKUK
Ofgem’s approach in RIIO-ED1
Cost areaCost areaCost areaCost area SubSubSubSub----cost cost cost cost categorycategorycategorycategory DriversDriversDriversDrivers
TopTopTopTop----down TOTEXdown TOTEXdown TOTEXdown TOTEX
(macro model)(macro model)(macro model)(macro model)
OPEX + 7-year smoothed CAPEX CSV of MEAV and customer numbers using a statistical approach
and time trend
TopTopTopTop----down TOTEX down TOTEX down TOTEX down TOTEX
(bottom(bottom(bottom(bottom----up model)up model)up model)up model)
OPEX + 7-year smoothed CAPEX CSV of MEAV, units distributed, network length, customers, faults,
spans cut and customer numbers using industry spend proportions
and time trend
BottomBottomBottomBottom----up regressionsup regressionsup regressionsup regressions Tree cutting Spans cut, spans inspected
Trouble call Faults
Closely Associated Indirects (project
management, network policy, vehicles &
transport, system mapping, etc.)
MEAV and value of network additions
Business support costs (finance & reg, IT,
CEO and management, etc.)
Ratio benchmarking using MEAV
NonNonNonNon----op CAPEX (property, IT&T, small tools op CAPEX (property, IT&T, small tools op CAPEX (property, IT&T, small tools op CAPEX (property, IT&T, small tools
& equip, etc.)& equip, etc.)& equip, etc.)& equip, etc.)
Ratio benchmarking usingRatio benchmarking usingRatio benchmarking usingRatio benchmarking using MEAVMEAVMEAVMEAV
20+ other disaggregated models:20+ other disaggregated models:20+ other disaggregated models:20+ other disaggregated models:
connections, reinforcement, asset connections, reinforcement, asset connections, reinforcement, asset connections, reinforcement, asset
replacement, I&M, etc.replacement, I&M, etc.replacement, I&M, etc.replacement, I&M, etc.
Ratio benchmarkingRatio benchmarkingRatio benchmarkingRatio benchmarking or regressionor regressionor regressionor regression
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Case studiesCase studiesCase studiesCase studies
Energiavirasto
Norwegian Water Resources and Energy Directorate
Council of European Energy Regulators
UK rail, health and telecoms regulators
Ofwat—Office of Water Services
Ofgem—Office of Gas and Electricity Markets
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UKUKUKUK
Ofwat’s approach in the 2004 price review (PR04)
Econometric Econometric Econometric Econometric models models models models
Maintenance expenditure was split into four categories, three of which were modelled using statistical analysis. For
example on water, the following models were developed:
• water distribution infrastructure
– log unit cost model with length of mains as the scale driver and properties per length of mains as a key cost
driver
• water distribution non-infrastructure
– log unit cost model with booster pumping station capacity as the scale driver and ratio of storage capacity to
pumping station capacity as a key cost driver
• water management and general
– log cost model with total number of billed properties as the scale driver and proportion of billed properties
that are non-household as a key cost driver
Adjustments to costs were made after modelling to account for leakage expenditure, company-specific factors and
deviations in future expenditure
Cost Cost Cost Cost base (basket of works)base (basket of works)base (basket of works)base (basket of works)
Ofwat compiled a dataset of the unit costs for 120 standardised projects and used the basket of goods approach to
compare cost predictions. The benchmark was set at the most efficient company
Setting allowanceSetting allowanceSetting allowanceSetting allowance
Results from the two approaches were weighed equally. In determining the allowance, Ofwat assumed that companies
would close 40% of the gap to the econometric benchmark and 50% to the cost base benchmark over the price control
period
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UKUKUKUK
Ofwat’s approach in the 2009 price review (PR09)
Econometric models were dropped from the efficiency analysis and the focus was instead
on the cost base approach
The benchmark was relaxed from the frontier company to the median company. Where data
comparability might have been an issue, a company only had to close 50% of the gap
The Capital Incentive Scheme (CIS) was introduced to encourage robust business plans and
incentivise target outperformance. This involved:
• setting the baseline level of expenditure
• comparing a company’s forecast to the baseline and using this to calculate an expenditure
allowance
• providing an incentive for further outperformance which declines as the ratio of a company’s
forecast to baseline increases
• calculating ex post rewards/penalties as the difference between allowed and outturn expenditure
multiplied by the incentive rate
Ofwat noted that CAPEX menu regulation increased the quality of the data available for the analysis and
limited the need to set a stringent, one-company-based benchmark
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UKUKUKUK
Ofwat’s approach in the 2014 price review (PR14)
Full
TOTEX
COLS
2
(50%)
(50%)
Triangulate
Refined TOTEX
RERefined
TOTEX
top-down
1
Triangulate Base
Refined
base RE
Refined
base COLS
Enhancements unit
costs
Enhancements
unmodelled costs
Add
Add
Add
(50%)
(50%)
(33%)
(33%)
TriangulateWater
TOTEX
TOTEX
bottom-up
3
(33%)
Source: Ofwat (2014), ‘Final price control determination notice: policy chapter A3 – wholesale water and wastewater costs and revenues’, December.
Refined TOTEX
OLS
TOTEX = OPEX + 5555----year average year average year average year average
CAPEXCAPEXCAPEXCAPEX
Base TOTEX = OPEX + 5555----year year year year
average maintenance CAPEXaverage maintenance CAPEXaverage maintenance CAPEXaverage maintenance CAPEX
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UKUKUKUK
Ofwat’s approach in the 2014 price review (PR14)
Ofwat modelled three types of capital enhancement expenditure. Certain exclusions/adjustments (e.g.
grants and contributions) were removed from data prior to modelling
Four different ways to model unit costs were
used:
• average of the unit costs for each company
• weighted average of the unit costs for each
company
• OLS regressions of costs against volume
• OLS regression of log costs against log volumes
A significant proportion of enhancement expenditure could not be modelled ‘adequately’, so an uplift
of 8.4% was considered. This was calculated by:
a) finding the industry total modelled enhancement expenditure
b) finding the industry total unmodelled enhancement expenditure
c) finding the ratio of b) to a)
Source: Ofwat (2014), ‘Basic cost threshold model Appendix C Enhancement modelling’, December.
Enhancement expenditureEnhancement expenditureEnhancement expenditureEnhancement expenditure VolumeVolumeVolumeVolume measuremeasuremeasuremeasure
Enhancements to the supply–
demand balance (e.g. building
a new reservoir to cope with
increased peak demand)
Total enhancement to the
supply–demand balance
Lead reduction Number of lead pipes replaced
New developments Number of new connections
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Case studiesCase studiesCase studiesCase studies
Energiavirasto
Norwegian Water Resources and Energy Directorate
Council of European Energy Regulators
UK rail, health and telecoms regulators
Ofwat—Office of Water Services
Ofgem—Office of Gas and Electricity Markets
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UKUKUKUK
Other regulators’ approach to assessing CAPEX (I)
Office of Rail and Road (ORR), 2013 price reviewOffice of Rail and Road (ORR), 2013 price reviewOffice of Rail and Road (ORR), 2013 price reviewOffice of Rail and Road (ORR), 2013 price review
• PR13 econometric analysis used a subset of the Lasting Infrastructure Cost
Benchmarking (LICB) data set developed and maintained by the International Union of
Railways (UIC) for 14 European rail infrastructure managers (IMs), including Network
Rail, for the period 1996 to 2008
• CAPEX (renewals expenditure) is measured as annual reported costs plus a ‘steady-state’
adjustment to ensure comparability of historical costs across international IMs
• the adjusted cost is the renewals expenditure that would have been incurred had
Network Rail renewed 2.5% of its track. This was necessary as there had been systematic
underinvestment in renewals historically
• the analysis considered a total of 21 econometric models, including a variety of
approaches (simple to advanced)
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UKUKUKUK
Other regulators’ approach to assessing CAPEX (II)
National Health Service Improvement (NHSI), MonitorNational Health Service Improvement (NHSI), MonitorNational Health Service Improvement (NHSI), MonitorNational Health Service Improvement (NHSI), Monitor
• top-down econometric models with a particular focus on advanced econometric models
to assess CAPEX
• TOTEX modelled based on reference reference reference reference costscostscostscosts. The following factors were controlled for in the
model: hospital hospital hospital hospital outputs outputs outputs outputs (case mix-adjusted hospital activity, the degree of specialisation in
Trusts, and the quality of service based on NHS staff surveys); TrustTrustTrustTrust----specific specific specific specific driversdriversdriversdrivers
(including local disease prevalence, demographics of the patient population, the
proportion of emergency admissions, and a market forces factor); location location location location and type of and type of and type of and type of
Trust Trust Trust Trust (that control for differences in trust categorisation and former Strategic Health
Authority regions)
OfcomOfcomOfcomOfcom
• used advanced econometric models to assess TOTEX of BT’s Openreach activities
• using publicly available information, BT was compared with the US local exchange carriers
(LECs) by normalising BT’s data to be comparable with that of the US companies
• CAPEX was measured using the depreciated historical cost approach (depreciation and
cost of capital)
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Case studiesCase studiesCase studiesCase studies
Energiavirasto
Norwegian Water Resources and Energy Directorate
Council of European Energy Regulators
UK rail, health and telecoms regulators
Ofwat—Office of Water Services
Ofgem—Office of Gas and Electricity Markets
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• TSOs have a natural and legalised monopoly
• tariffs need to be based on efficient rather than incurred cost
• no or limited domestic peer companies in most countries
• input is TOTEX = OPEX + annuitised CAPEX
Council Council Council Council of European Energy Rof European Energy Rof European Energy Rof European Energy Regulatorsegulatorsegulatorsegulators
Pan-European benchmarking of gas and electricity TSOs (I)
Source: Sumicsid, Swiss Economics (2016), ‘Benchmarking European Gas Transmission System Operators’, Project E2Gas, June.
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Restricting the costs/functions of a TSO can help in comparability across TSOs, but can also introduce
errors
• OPEX
– grid planning, grid construction, grid maintenance, gas transport and metering, and
administrative support
– included costs: labour costs of direct personnel, cost of third-party services, indirect cost of
management and other costs
– labour costs are adjusted to reflect country-specific input prices (wages)
• CAPEX
– investment streams are annualised using a standard annuity factor
• all costs are subject to inflation adjustment (CPI) and currency conversion
– the average exchange rate is used and national currencies are converted into euros. PPP is
used as a sensitivity
• additional discussions on cost construction underway
– e.g. a depreciated historical cost approach to measuring CAPEX could be considered and
benefit of doubt (i.e. higher of resultant efficiency values) could be set on TSOs
Council Council Council Council of European Energy Rof European Energy Rof European Energy Rof European Energy Regulatorsegulatorsegulatorsegulators
Pan-European benchmarking of gas and electricity TSOs (II)
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• cost driver selection based on engineering expertise and statistical analysis
• the core model includes only three cost drivers:
– normalised normalised normalised normalised gridgridgridgrid
– grid length adjusted by various complexity factors to account for land use, sub-surface
features, topography and soil humidity
– normalised grid is clearly an important variable, but there does not appear to be any
sensitivity analysis with respect to its definition
– total number of connection total number of connection total number of connection total number of connection pointspointspointspoints
– grid capacitygrid capacitygrid capacitygrid capacity
• additional discussions on cost drivers underway
– can three variables capture the key differences between TSOs? What is missing?
How can this be mitigated?
– does the normalised grid adequately take into account firm-specific factors relating to the
environment?
• modelling approaches: top-down methods, in particular, optimisation approaches such as DEA
and econometric techniques such as SFA, are the main methods used
Council Council Council Council of European Energy Rof European Energy Rof European Energy Rof European Energy Regulatorsegulatorsegulatorsegulators
Pan-European benchmarking of gas and electricity TSOs (III)
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Case studiesCase studiesCase studiesCase studies
Energiavirasto
Norwegian Water Resources and Energy Directorate
Council of European Energy Regulators
UK rail, health and telecoms regulators
Ofwat—Office of Water Services
Ofgem—Office of Gas and Electricity Markets
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NorwayNorwayNorwayNorway
Three-stage approach
• separate regulation of networks between 33kV and 132kV (86 companies – regional
distributors), and local distributors from 0,230kV to 22kV (136 companies)
• three-stage process for arriving at allowed revenue – revenue cap method
Benchmarking
(DEA) models
Adjustment
for operating
environment
Calibration
processCost norm
C***C***C***C*** C**C**C**C** C*C*C*C*
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NorwayNorwayNorwayNorway
Modelled cost
• benchmarking analysis benchmarking analysis benchmarking analysis benchmarking analysis –––– CCCC************
– top-down approach (DEA)
– constant returns to scale (CRS)
– the frontier is estimated using 5-year-averaged data
• the modelled cost Ct (inputinputinputinput) is:
( ) tttttt
tttt WACCRABDEPPL
CPI
CPIVOLLOMC ×++×+×+= −−−
−−− 222
222 )(
Where:
OMt-2= operating and maintenance costs in year t-2
VOLLt-2 = value of lost load (customer interruption costs) in year t-2
CPIt= consumer price index in the year t
CPIt-2= consumer price index in the year t-2
Lt-2 x Pt = value of network losses in MWh, year t-2, considering local area prices at Nord Pool Spot in year t
DEP t-2= depreciation in year t-2
RABt-2 = regulatory asset base, considering book value in year t-2
WACCt = weighted average cost of capital in year t
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NorwayNorwayNorwayNorway
Treatment of CAPEX
RABRABRABRAB
• since 2007, there has been strong criticism of using the book value of the RAB as the
measure of CAPEX
• two companies with equivalent assets, maintenance costs and efficiencies will have
different DEA scores if the timing of investment differs
Replacement costReplacement costReplacement costReplacement cost
• in 2012, NVE considered moving to a replacement cost measure of CAPEX
• while it may offer a more ‘correct’ measure of CAPEX, it was deemed inapplicable in a
regulatory framework as it gave too strong an incentive to reinvest
Reducing the age effect while maintaining incentivesReducing the age effect while maintaining incentivesReducing the age effect while maintaining incentivesReducing the age effect while maintaining incentives
• elements of the third stage of calculation changed in order to reduce the age effect
• in the first stage (DEA), a higher RAB punishes a company, while in the third stage (cost
calibration) a higher RAB rewards a company
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NorwayNorwayNorwayNorway
The DEA model
Outputs of the DEA modelOutputs of the DEA modelOutputs of the DEA modelOutputs of the DEA model
• the weighted values take into account different costs of each type of grid component,
while the costs of transformers, switches and compensation devices include the value
of substations
• there is recognition that some of these outputs may technically be under management
control, but they are practically exogenous since many decisions are determined by
other regulations
Local distributorsLocal distributorsLocal distributorsLocal distributors Regional distributorsRegional distributorsRegional distributorsRegional distributors
Length of HV network (km) Weighted value of overhead lines
Number of network substations Weighted value of ground cables
Number of subscriptions (customers) Weighted value of sea cables
Weighted value of substations
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NorwayNorwayNorwayNorway
The Norwegian Water Resources and Energy Directorate
• calibration calibration calibration calibration reaching C*reaching C*reaching C*reaching C*
• further further further further calibration for deviation between actual and expected costs (with twocalibration for deviation between actual and expected costs (with twocalibration for deviation between actual and expected costs (with twocalibration for deviation between actual and expected costs (with two----year lag):year lag):year lag):year lag):
– at this stage the Z factor-corrected DEA scores are ‘calibrated’ to set the aggregate of cost
norms equal to the sum of the observed costs in the sector. The savings in the sector come
through the distributors’ incentives for cost reduction
– the calibration is as follows:
Where:
Ci* = cost norm of distributor i, considering the cost of capital defined by NVE
Ci** = cost norm adjusted for operating environment
RABi = regulatory asset base of distributor i
��∗ = ��
∗∗ + ∑ ��� �∑ ��∗∗
�/012
∑ /0122
• final calibration between proposed costs and cost norm to accommodate possible modelling
limitation and balance trade-off between cost-reduction incentive and rent transfer to the
end-customer
• there is no specific requirement of efficiency. This is because if a DSO improves its position relative
to the average, it will have a higher rate of return. This is the main feature of the model that aims
to encourage efficiency in operation, usage and development of the distribution network
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Case studiesCase studiesCase studiesCase studies
Energiavirasto
Norwegian Water Resources and Energy Directorate
Council of European Energy Regulators
UK rail, health and telecoms regulators
Ofwat—Office of Water Services
Ofgem—Office of Gas and Electricity Markets
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Finland Finland Finland Finland
Energiavirasto
Up until 2011 the efficiency score was calculated as an average of scores from two models:
an NDRS DEA model and a linear SFA model
The input to the models was:
TOTEX = OPEX + CAPEX + DCO
Where:OPEX = controllable operating costs
CAPEX = straight-line depreciation from the replacement value of t network
DCO = a monetary disadvantage caused by outage for electricity customers
• for 2012–15, an advanced econometric method, stochastic non-smooth envelopment of data
(StoNED), was used to assess TOTEX
• CAPEX was dropped from the efficiency target and investment was monitored separately
• only half of DCO was added to OPEX to generate TOTEX
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Finland Finland Finland Finland
Energiavirasto
• in the fourth (2016–19) and fifth (2020–23) regulatory periods, the efficiency challenges will
continue to be estimated using the StoNED method, as informed by the regulator
• the input–output variables and the operating environment variable are modified as follows:
• DCO has moved as an undesirable output
• modelled cost (input) is limited to OPEX only
• CAPEX (based on replacement value) is used as a fixed input fixed input fixed input fixed input in that an efficiency challenge is only
set on OPEX, however the impact of investment on OPEX (i.e. the trade-off) is still captured
• the Z variable is still intended to capture differences between urban and rural networks using a
connection density measure defined as number of connections per metering point
Source: Energiavirasto (2015), ‘Regulation
methods in the fourth regulatory period of 1
January 2016 – 31 December 2019 and the
fifth regulatory period of 1 January 2020 – 31
December 2023’, October.
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• what do regulators try to assess: objective and definitions
• issues with benchmarking CAPEX
• ways of measuring CAPEX
• menu of tools: top-down and bottom-up
• case studies
• key takeaways
OverviewOverviewOverviewOverview
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HighHighHighHigh----level messages (I)level messages (I)level messages (I)level messages (I)
• CAPEX construction: plethora of approaches but with limited understanding of CAPEX construction: plethora of approaches but with limited understanding of CAPEX construction: plethora of approaches but with limited understanding of CAPEX construction: plethora of approaches but with limited understanding of
the gapsthe gapsthe gapsthe gaps
– UK energy and water regulators tend to use a cash cost approach where outturn
CAPEX is ‘smoothed’ or left unsmoothed over a sufficiently long period to mitigate
volatility and differences in investment profiles
– among EU regulators, the capital cost approach seems to be preferred. Two
approaches are taken to measuring CAPEX—annuity and depreciated historical
cost
– all approaches appear to have limitations. For example, asset condition/health, as
well as service quality measures, are often ignored, while the inflation measure
and the WACC assumptions affect the capital cost approaches
– cash cost approach will also require careful consideration of the state of the
networks, investment profile and base year of analysis
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HighHighHighHigh----level messages (II)level messages (II)level messages (II)level messages (II)
• CAPEX assessment: no agreed approach among European and UK regulators CAPEX assessment: no agreed approach among European and UK regulators CAPEX assessment: no agreed approach among European and UK regulators CAPEX assessment: no agreed approach among European and UK regulators
– CAPEX assessment is inherently difficult and regulators tend to be relatively
conservative
– in a number of regulatory applications, assumptions underlying the assessment
approach do not appear sufficiently justified (e.g. the correspondence between
CAPEX and its drivers)
– moreover, there could be inconsistencies in the treatment of CAPEX in the
benchmarking exercises and how a TSO is remunerated, which governs its
investment decisions
– different approaches to measuring and treatment of CAPEX should be examined,
to ensure outcomes are not skewed by assumptions or limitations with particular
approaches
– similarly, more disaggregated, bottom-up or operational evidence is often used as
a cross-check in a regulatory context
– lastly, any benchmarking exercise rests on certain simplifications and assumptions
and due allowance must be made for a ‘margin of error’
W
THANK YOU FOR YOUR ATTENTION!
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Srini ParthasarathySrini ParthasarathySrini ParthasarathySrini Parthasarathy
EEEE----mail: mail: mail: mail: [email protected]@[email protected]@oxera.com
Web: Web: Web: Web: www.oxera.comwww.oxera.comwww.oxera.comwww.oxera.com