Discussion Paper
Incentive Regulation: Theory
and Practice
September 2014
We wish to acknowledge the contribution of the following staff to this report:
Kian Nam Loke, Richard Creagh, Ralph Donnet, John Fallon, Dan Kelley
© Queensland Competition Authority 2014
The Queensland Competition Authority supports and encourages the dissemination and exchange of information.
However, copyright protects this document.
The Queensland Competition Authority has no objection to this material being reproduced, made available online or
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Queensland Competition Authority
SUBMISSIONS
Closing date for submissions: 12 December 2014
Public involvement is an important element of the decision-making processes of the Queensland
Competition Authority (QCA). Therefore submissions are invited from interested parties concerning its
assessment of Incentive Regulation: Theory and Practice. The QCA will take account of all submissions
received.
Submissions, comments or inquiries regarding this paper should be directed to:
Queensland Competition Authority
GPO Box 2257
Brisbane Q 4001
Tel (07) 3222 0516
Fax (07) 3222 0599
[email protected]
www.qca.org.au
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documents please contact us on (07) 3222 0582.
iii
Queensland Competition Authority
The Role of the QCA – Task, Timing and Contacts
THE ROLE OF THE QCA – TASK, TIMING AND CONTACTS
The Queensland Competition Authority (QCA) is an independent statutory authority to promote
competition as the basis for enhancing efficiency and growth in the Queensland economy.
The QCA’s primary role is to ensure that monopoly businesses operating in Queensland, particularly in the
provision of key infrastructure, do not abuse their market power through unfair pricing or restrictive
access arrangements.
In 2012, that role was expanded to allow the QCA to be directed to investigate, and report on, any matter
relating to competition, industry, productivity or best practice regulation; and review and report on
existing legislation.
Task, timing and contacts
The QCA Research team supports the QCA's regulatory and public policy work. The team focuses
on providing analysis and evidence to support regulatory and public policy decisions – which affect both
the community and industry.
Key dates
Release of Discussion Paper
26 September 2014
Submissions Due Date
12 December 2014
Registration of interest
http://www.qca.org.au/Subscribe
Contacts
Enquiries regarding this project should be directed to:
ATTN: Kian Nam Loke
Tel (07) 3222 0582
[email protected]
www.qca.org.au
ii
Queensland Competition Authority
Incentive regulation: theory and practice
INCENTIVE REGULATION: THEORY AND PRACTICE
Background
All forms of regulation are likely to impact on incentives but the term ‘incentive regulation’ has evolved to
describe a form of regulation that attempts to address two key problems with economic regulation: (i) the
incentive for a regulated firm to hide its true cost profile; and (ii) the lack of incentive for the regulated
firm to operate and invest efficiently. The economic literature refers to these two problems as ‘adverse
selection’ or ‘hidden information’ and ‘moral hazard’ or ‘hidden action’ respectively. These problems
arise due to the fundamental asymmetry of information between the regulator and the regulated firm.
The two basic forms of regulation that operate in practice are rate-of-return regulation (or cost-of-service
regulation) and price-cap regulation. In general, rate-of-return regulation (where regulated prices are
based on actual realised costs) focuses more on the adverse selection problem while price-cap regulation
(where regulated prices are set ex ante and firms have the incentive to cut costs) focuses more on the
moral hazard problem. The general approach as has been implemented in Australia is a hybrid method
that comprises features associated with both forms of regulation.
A form of incentive regulation known as ‘menu regulation’ has been developed to try to better address
both of the information problems—in particular, the perverse incentive for regulated firms to submit
exaggerated cost proposals to secure higher prices—so that over time the regulated prices will converge
to the efficient level despite the information disadvantage of the regulator.
As part of its continuing effort to keep abreast of developments that might provide ideas for revising and
modernising its regulatory tools to improve consumer welfare and improve the efficiency of regulation,
the QCA commissioned a research paper by Professor Flavio Menezes of the University of Queensland to
investigate the theory and application of incentive regulation. The research paper produced by Professor
Menezes is attached. Professor Menezes worked closely with QCA staff in developing the paper.
The purpose of this Discussion Paper is to make the research paper available for public comment. The
incentive regulation techniques discussed in the research paper are at the cutting edge of economic
regulation. While it is too early to make recommendations for change in current practices, the QCA is
interested in stakeholder views about the potential applicability of incentive regulation to sectors it
regulates.
Menu regulation
Under the menu-based approach, the regulator offers a range of options including various combinations
of a cost allowance, a sharing ratio (the percentage of underspend or overspend against the allowed
expenditure levels that the firm is allowed to retain) and an additional income component (an additional
amount added to the firm's cost allowance), where the regulated firm is given freedom to commit to one
of the options.
The menu is designed such that it is incentive compatible—the choice that maximises the firm's expected
profit coincides with the choice that best reflects its beliefs about its future costs. In other words, the
menu incentivises truth-telling from the firm.
For example, suppose a regulated firm believes that its efficient costs for the next regulatory period is $X.
Under standard price-cap regulation, this firm has the perverse incentive to exaggerate its cost
requirement to secure higher prices (hence higher profits). Under menu regulation, however, by asking
for a higher cost allowance, this firm will get a lower sharing ratio and a smaller (or even a negative)
additional income component. This means that, even if this firm greatly underspends its allowance during
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Queensland Competition Authority
Incentive regulation: theory and practice
the regulatory period (as it has chosen an inflated cost allowance in the first place), because of the low
sharing ratio and additional income component that correspond with its choice, the net return from this
underspend will also be small as a result. An incentive-compatible menu ensures that this firm will be
better off proposing $X to be its cost allowance in the first place.
In addition to truth-telling incentives, as under menu regulation the regulated firm cannot change its
decision once the regulated prices are finalised, this provides an incentive for the firm to be cost efficient
during the regulatory period in order to earn a higher return.
The menu approach has been implemented for some time at Ofgem and Ofwat in the United Kingdom.
Some aspects of incentive regulation are also being implemented by the Australian Energy Regulator
(AER) in Australia.
Ofgem
The experience of Ofgem is reviewed in the research paper. The menu approach was implemented with
an incentive scheme known as the Information Quality Incentive (IQI) which was a totex (opex and capex)
menu. A totex menu has the additional characteristic of ensuring that the regulated firm has no particular
incentive to prefer a type of expenditure (e.g. capex) over another.
The Ofgem experience provided some evidence on whether the menu approach has been effective in
providing truth-telling incentives for regulated firms. On a cumulative basis, in the regulatory period
where the IQI was first implemented, there was a total £514m underspend (6.7% of the total allowance)
for capex and a £322m underspend (9.1%) for opex. In the first year, firms underspent against the capex
allowance by a total of £359.0 million (27%) and underspent against the opex allowance by £77.6 million
(5%).
Although this indicates that the menu approach might not have addressed the issue of asymmetric
information in determining the baseline, this conclusion would be premature given this was Ofgem's first
attempt at implementing menu regulation. Companies might be unfamiliar with how the IQI would
operate, thus their decision making was distorted. Similarly, underspend could be a result of the firms’s
cost-cutting initiatives over the regulatory period rather than the issue of adverse selection.
Ofwat
The experience of Ofwat with incentive regulation covering the period 2010-15 (PR09) is also reviewed in
the research paper. In PR09, a menu-based approach was implemented by Ofwat but for capex only. For
opex, Ofwat applied an efficiency carry-over mechanism. One issue with Ofwat's regime is that there
appeared to be a stronger incentive to achieve opex efficiency relative to capital efficiency (a capex bias).
This might lead to suboptimal allocation of resources, where companies opt for capital-incentive solutions
in order to reduce opex. Recognising such an issue, Ofwat has indicated that it will adopt a totex-based
approach in the next review.
In addition to cost-efficiency incentives, Ofwat also applied a broader incentive mechanism to provide
incentives for firms to provide better services to customers. Prior to 2010, this mechanism applied was
known as the Overall Performance Assessment (OPA). The OPA entailed the specification and scoring of
15 specific performance measures including measures covering general performance, customer-focused
measures and environmental measures. While the OPA was associated with considerable improvements
in service quality, there were still a material number of complaints. As the OPA was based on a number of
narrowly defined measures, it distracted companies from the need to focus on the overall experience of
customers. The OPA has been replaced by the Service Incentive Mechanism (SIM). One important
element of the SIM is its reliance on customer surveys in addition to quantitative measures. Customer
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Incentive regulation: theory and practice
surveys could capture the overall satisfaction level of consumers, encouraging innovation from companies
to improve customers' experience.
AER
Australian regulators have made limited use of incentive regulation to address adverse selection. They
tend to rely exclusively on ex ante assessments of cost proposals to mitigate the risk of inflated cost
proposals. However, there have been some attempts to encourage cost efficiency. The AER's regime has
carry-over schemes designed to provide continuous incentives to pursue opex and capex efficiency. This
is to mitigate the issue of the periodicity of incentives caused by the introduction of periodic reviews,
where the regulated firm's incentive to cut costs falls over time within a regulatory period. The AER's
approach is similar to Ofwat's approach to opex.
Moreoever, the carry-over schemes (one for opex and one for capex) are set up such that companies have
the same level of incentives to underspend both capex and opex at any point in time, which also
eliminates or mitigates capex bias.
The fact that the AER has designed two incentive schemes to tackle the issues of periodicity of incentives
and capex bias shows that the AER acknowledges the significance of these issues in that they may lead to
distortions in the decision making of regulated firms. Also, while the AER regime does not directly
address the adverse selection problem with a menu-based approach, it has indicated that it will make
greater use of benchmarking to address this issue.
Consultation
Submissions from stakeholders on whether there is potential to improve regulation in Queensland
through the adoption of menu regulation or other incentive regulation techniques are welcome.
3
Prepared for
Queensland Competition Authority
Subject
Incentive Regulation
Author
Professor Flavio M Menezes
School of Economics, The University of Queensland
In collaboration with Kian Nam Loke and John Fallon
4 August 2014
UniQuest Project No: C01400
Title
Incentive Regulation
Disclaimer
This report and the data on which it is based are prepared solely for the use of the person or
corporation to whom it is addressed. It may not be used or relied upon by any other person or
entity. No warranty is given to any other person as to the accuracy of any of the information, data
or opinions expressed herein. The author expressly disclaims all liability and responsibility
whatsoever to the maximum extent possible by law in relation to any unauthorised use of this
report.
The work and opinions expressed in this report are those of the Author.
Report For: Queensland Competition Authority
Re: Incentive Regulation
TABLE OF CONTENTS
EXECUTIVE SUMMARY .......................................................................................................... 3
1.
INTRODUCTION ........................................................................................................ 8
2.
THE CONCEPTUAL FRAMEWORK ......................................................................... 10
2.1
Rate-of-return versus incentive regulation ................................................................. 11
2.1.1.
Rate-of-return regulation............................................................................................ 11
2.1.2.
Price caps.................................................................................................................. 12
2.1.3.
Revenue cap ............................................................................................................. 14
2.2
Optimal regulation ..................................................................................................... 15
2.3
A simple analytical framework ................................................................................... 16
2.4
Incentive regulation and service quality ..................................................................... 19
2.5
Incentive regulation and the optimal tariff structure .................................................... 19
2.6
Incentive regulation and the efficient pricing of capacity ............................................ 22
2.7
Incentive regulation and benchmarking ..................................................................... 23
2.8
The dynamics of regulation ........................................................................................ 24
3.
IMPLEMENTATION ISSUES .................................................................................... 25
3.1
The regulatory process .............................................................................................. 25
3.2
Price-cap regulation................................................................................................... 26
3.2.1.
Determination of allowed costs .................................................................................. 27
3.2.2.
Productivity measurement ......................................................................................... 28
3.2.3.
Productivity-based regulation and X-factor ................................................................ 30
3.2.4.
Service quality ........................................................................................................... 32
3.2.5.
Ex-post treatment ...................................................................................................... 32
3.3
Menu regulation ......................................................................................................... 32
3.4
Incentive strength ...................................................................................................... 40
3.4.1.
Periodicity of incentives ............................................................................................. 41
3.5
Capex bias ................................................................................................................ 43
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3.6
Partial versus comprehensive incentive schemes ...................................................... 44
4.
INTERNATIONAL EXPERIENCE WITH INCENTIVE REGULATION........................ 46
4.1
Energy sector in the UK ............................................................................................. 46
4.1.1.
General information ................................................................................................... 47
4.1.2.
Ofgem’s approach to incentive regulation .................................................................. 48
4.1.3.
Determining the cost baseline: cost assessment ....................................................... 49
4.1.4.
Incentive mechanisms: an overview .......................................................................... 51
4.1.5.
Equalising incentives ................................................................................................. 52
4.1.6.
The totex menu: ensuring incentive compatibility and equalising incentives .............. 54
4.1.7.
Preliminary assessment of the menu approach ......................................................... 56
4.1.8.
The future of electricity distribution regulation in the UK ............................................ 57
4.2
Water sector in the UK............................................................................................... 57
4.2.1.
Capex incentives ....................................................................................................... 58
4.2.2.
Opex incentives ......................................................................................................... 63
4.2.3.
Performance incentives ............................................................................................. 65
4.2.4.
Future developments ................................................................................................. 67
4.2.5.
Summary and conclusion .......................................................................................... 68
5.
THE AER APPROACH TO INCENTIVE REGULATION............................................ 70
5.1
Background ............................................................................................................... 70
5.2
Efficiency benefit sharing scheme (EBSS) ................................................................. 71
5.3
Capital expenditure sharing scheme (CESS) ............................................................. 76
5.4
Service target performance incentive scheme (STPIS) .............................................. 81
5.5
Summary and conclusion .......................................................................................... 83
6.
GLOSSARY .............................................................................................................. 85
7.
REFERENCES ......................................................................................................... 87
UniQuest File Reference: C01400
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Re: Incentive Regulation
EXECUTIVE SUMMARY
Incentive regulation is a tool to encourage the regulated firm to provide more accurate cost
forecasts and to operate more efficiently, so that over time the regulated price will converge to
the efficient level despite the information disadvantage of the regulator. This paper investigates
the theory of incentive regulation and describes how it has been implemented by regulators in
Australia and the United Kingdom.
The role of incentives in regulation
Two types of incentives are particularly important when assessing a regulatory regime. The first
is the incentive for regulated firms to make regulatory submissions that more accurately reflect
their actual expectation of cost required for providing the regulated services over the next control
period. The economic literature refers to the case where the regulated firm has an incentive to
overstate its cost forecasts as adverse selection (or hidden information). The second is the
incentive for firms to reduce costs during the regulatory period below those initially approved by
the regulator. The economic literature refers to the case where firms have no incentives to
reduce costs as moral hazard (or hidden action).
Adverse selection and moral hazard are related to a fundamental asymmetry of information
between the regulator and the regulated firm. Adverse selection may result as the regulator
cannot perfectly determine whether the regulated firm’s cost forecasts reflect best practice. For
example, some cost drivers may only be observed by the regulated firm, and not by regulators
or external experts advising the regulator. In a similar vein, the regulator may not be able to
observe the opportunities that the firm has for cost reduction, which can lead to moral hazard.
For example, the regulator may not be able to observe managerial effort to reduce costs.
This paper explains that rate-of-return or cost-of-service regulation, in its simplest form,
addresses the adverse selection problem but creates a moral hazard problem. Faced with the
certainty of being reimbursed only for costs actually incurred in providing the services (including
the return on capital and economic depreciation), a regulated firm has little incentive to
exaggerate cost forecasts. That is, the adverse selection problem does not exist. This assumes
that auditing of costs will be effective in addressing the information disadvantage of the regulator
(to prevent the firm from overstating what it has spent). However, the same guarantee of
reimbursement of costs means that the firm faces no incentive to reduce costs, as any reduction
in cost would be fully returned to consumers in terms of lower prices—that is, there is a moral
hazard problem.
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In contrast, this paper explains that price cap regulation, also in its simplest form, addresses the
moral hazard problem as, faced with a fixed price for the duration of the regulatory period, the
regulated firm is fully incentivised to produce at the least cost possible. This is because the
regulated firm retains 100 per cent of the amount that it underspends vis-à-vis the costs that it
has been allowed to recover (the gap between the cost per unit of production and regulated
price), at least until the next regulatory review. However, in a price cap regime where allowed
costs are based on forecasts of future costs, the regulated firm will have an incentive to
exaggerate such forecasts in its submissions, which is in effect an adverse selection problem.
In addition, as it is not feasible to fix prices for the duration of the life of regulated assets, price
caps are typically reviewed every three to five years. This review process raises the prospect of
the costs incurred in the previous period being used to set future prices; this also introduces
adverse selection.
Moreover, the incentives to reduce cost under price cap regulation can also lead to underprovision of quality. The nature of the trade-off is that by making the incentives for cost reduction
(vis-à-vis a baseline) stronger, price cap regulation may lead to the regulated firm reducing
production cost at the expense of service quality.
In practice, price cap regulation and rate of return regulation have many elements in common
and both are subject to some degree of moral hazard and adverse selection. For example, costs
that are reimbursed under rate-of-return regulation are often subject to ex-post, prudency (or
efficiency) tests, which can mitigate the moral hazard problem. Similarly, under price cap
regulation, cost forecasts from the regulated firm are often subject to a process of extensive
review by the regulator, consultants and interested parties, which mitigates adverse selection.
The paper also discusses intermediate forms of price regulation, or profit sharing schemes,
where incentives for cost reduction are not as strong as under a price cap regime, or nonexistent as under a rate-of-return regime. Under a profit sharing scheme, the regulated firm
shares a fraction of any cost savings (against the baseline cost set by the regulator) with
consumers. Such a mechanism can be made symmetric, such that cost overruns are also
shared with consumers. This type of regulation helps to reduce moral hazard, as the firm is still
incentivised to reduce costs, and mitigates potential adverse impacts on quality as incentives
for cost reduction are not as strong as under a pure price cap. The profit sharing fraction can be
calibrated to determine how powerful the incentives for cost reduction are.
Instead of setting a single profit sharing fraction and a single figure for the baseline costs, the
regulator may offer a menu consisting of various choices for these parameters. A key insight
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from the literature on incentive regulation, as highlighted in this paper, is that such a menu can
be designed in order to provide incentives for the firm to choose a baseline cost that is closer to
its expected cost of delivering the regulated services. While there may still be some incentive
for the regulated firm to try to inflate the baseline cost, this incentive is lower than under a pure
price cap regime. Moreover, the report covers benchmarking techniques that are useful in
determining efficiency costs under both menu and price cap regulation.
The discussion of implementation issues associated with various regulatory regimes provides
useful insights into how incentive regulation works in practice, as well as its limitations. For
instance, one feature is that the different treatment of capital expenditure (capex) and
operational expenditure (opex) may lead the regulated firm capitalising operating expenditures
(i.e. having an inefficient preference for capital solutions). This is known as a capex bias and it
is an important reason for ensuring that incentives for capex and opex are not distorted by the
form of regulation. The paper also highlights the distortion that a fixed regulatory period has on
incentives and discusses practical approaches, such as setting up an efficiency carryover
mechanism. Through this mechanism the firm is allowed to retain savings from underspend for
a fixed period of time from when the savings are realised, rather than only until the next
regulatory review.
The conceptual framework developed in this paper, which includes both theory and general
implementation issues, identifies three key potential issues arising from the incentives
embedded in existing regulatory frameworks:

the extent of asymmetric information, and the imperfect nature of ex-ante efficiency tests
(and the limited use of benchmarking), mean that adverse selection is likely to be
prevalent. This implies that the costs allowed by regulators are unlikely to reflect the full
potential for efficient costs and regulatory outcomes might not be in the best interest of
consumers;

the different treatment of capex and opex may lead the regulated firm to capitalise
operating expenditures (i.e. having an inefficient preference for capital solutions). This
capex bias means that regulated firms are not spending customer’s money to deliver the
best outcomes in the most efficient way; and

a fixed regulatory period (typically five years) distorts the regulated firm’s decision as the
strength of the incentives is reduced as the regulatory review date approaches.
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The United Kingdom experience with incentive regulation
The regulatory experience in the United Kingdom, especially in the water and electricity
industries, provides some useful insights on what can be done to address these three issues.
The review of the electricity distribution regulatory arrangements in the United Kingdom explored
the role of incentive regulation in mitigating adverse selection. Allowing the regulated firm to
choose from a menu of various combinations of allowed costs and incentive strengths provides
powerful incentives for truthful revelation of expected costs while preserving the incentives for
pursuing cost reduction opportunities. The use of a total expenditure (totex) menu, with a fixed
split between fast and slow pots, eliminates any capex bias generated by applying different
incentive rates to capex and opex.
The experience of the water regulator, Ofwat, in addressing two of the three key issues, namely
adverse selection and timing distortions, is also relevant. Instead of a totex menu to address
adverse selection, Ofwat used a menu approach only for setting capex allowances. While in
the latest review most companies proposed capex forecasts that were higher than Ofwat's
baselines (in some cases, they were more than 30 per cent larger), it is difficult to evaluate
whether this reflects gaming or truth-telling from companies. The companies’ actual
expenditures throughout the regulatory review will provide important information that will inform
the development of the menu for the next review period.
To address the timing distortion, Ofwat used rolling incentives for opex, which was largely similar
to the Australian Energy Regulator's (AER) approach, except that the scheme was asymmetric
and one-off savings would be fully retained by companies. Ofwat also allowed more efficient
companies to receive additional rewards through opex multipliers. Finally, the incentives for
opex efficiency were considerably higher than that of capex, and this might cause a capex bias.
This has motivated Ofwat to move to a totex-based approach for the next regulatory review.
Clearly, regulators in the UK have paid considerable attention to the incentives that were
embedded in previous decisions when designing new approaches to regulation. While
incentives to exaggerate forecasts to try to influence the baseline in the menu may still exist,
they are lower than under price cap regulation. Moreover, both water and electricity regulators
in the UK make extensive use of benchmarking, increasing the effectiveness of the ex-ante
assessment of the baseline.
Australian experience
There has been limited use of incentive regulation to address adverse selection by Australian
regulators. They tend to rely exclusively on ex-ante assessments to overcome adverse selection
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and make considerably less use of benchmarking than their United Kingdom counterparts.
Nevertheless, the proposed approach of the AER focuses on incentive mechanisms (carryover
schemes) designed to provide continuous incentives to pursue opex and capex efficiency. Under
the AER’s proposed regime, network services providers have the same level of incentives to
underspend both capex and opex at any point in time, which also eliminates or mitigates capex
bias.
Implications for the QCA
The QCA plays an important role in shaping the regulatory frameworks for water, retail electricity,
ports and rail access in Queensland. With the exception of electricity retail, the other three
sectors have natural monopoly characteristics and require price setting or monitoring.
An assessment of the existing regimes would examine:

the extent to which ex-ante tests are exclusively used for assessing efficiency and the
potential for more extensive use of profit sharing/menu regulation;

the extent to which benchmarking is used in ex-ante assessments of efficiency and the
extent to which this could be improved;

evidence of capex bias and, generally, whether incentives embedded (i.e. not explicit) in
the regime favour capex over opex; and

the feasibility of introducing efficiency carryover mechanisms to mitigate timing distortions.
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1.
INTRODUCTION
This paper investigates the extent to which incentive regulation could be effectively employed in
regulating firms subject to the oversight of the QCA.
The basic aim of incentive regulation is to provide incentives for the regulated firm to take
appropriate actions to deliver outcomes—in terms of cost-reducing efforts, innovation, quality
and investment—that are consistent with those that would emerge in a competitive market.
At a high level, incentive mechanisms include price and revenue caps, and profit-sharing
mechanisms. However, in practice each of these high-level incentive mechanisms is supported
by many other features that constitute the overall regulatory regime. These include the
determination of allowed costs that the regulated firm can recover from customers, the duration
of the regulatory period, the determination of the price path, and the existence of opportunities
for the firm to seek cost pass-throughs.
The interaction between various aspects of the regulatory regime determines the overall power
of incentives provided to the regulated firm. While this interaction may well lead to incentives for
cost reduction, efficient production and investment decisions, it may also create perverse or
unintended incentives for the regulatory firm, such as distorting the decision of when to invest
or what type of expenditure to undertake.
The approach of this paper is to first develop a conceptual framework to assess when incentive
regulation can be useful and the format that it should take. In order to achieve desirable
outcomes (those consistent with achieving economic efficiency), the regulatory framework and
associated tools need to ensure that:
(a)
the regulated firm has the incentive to outperform the allowed costs; and
(b)
the gap between the regulated firm's efficient cost and allowed costs is minimised
without compromising desired quality.
These requirements are related to the fundamental problem of information asymmetry.
Information asymmetry exists when the regulated firm has better information about its cost
profile and demand attributes than the regulator setting the firm's prices. At the same time, the
regulator does not observe the firm's managerial effort directly. Given the circumstances, the
best the regulator can do is to ensure that the regulated firm has sufficient incentive to pursue
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efficiency (if there is scope to do so), and attempt (within the regulator's capabilities) to reflect
any efficiency improvements in the regulated prices over time.
Clearly, these two requirements are linked. Outperformance can easily occur if the existence of
information asymmetry between the regulator and firm leads to setting allowed costs that are
greater than the expenditure required to deliver outputs, or to understating the scope for future
efficiency improvements. At the same time, regulation needs to ensure that there is no distortion
causing the firm to favour one type of expenditure over another (for example, capital expenditure
over maintenance).
Having defined a conceptual framework, the second step is to examine implementation issues
that have the potential to create a wedge between theory and practice. In general, this step
entails identifying the issues and considering the implications for designing a regulatory regime.
The third and fourth steps involve reviewing relevant international and Australian experiences
with a view to exploring how the implementation issues have been resolved in practice to date.
The focus is on experiences that are most relevant to the industries regulated in Queensland.
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2.
THE CONCEPTUAL FRAMEWORK
Consider the problem facing an economic regulator responsible for setting the price that a
regulated firm is allowed to charge customers. In particular, assume that the regulator sets a
unit price based on a unitised cost, which includes the return on assets and amortisation
(economic depreciation). That is, the firm is subject to a break-even constraint but costs include
a return on and of capital. The focus of this preliminary analysis is on setting a price for a single,
homogenous service that allows the regulated firm to recover its costs under circumstances
where the regulator knows less than the firm about the costs of providing such a service. The
optimal tariff structure for efficient allocation of fixed costs to heterogeneous consumers is not
considered in this paper.
Before exploring the details of different forms of incentive regulation, it is first helpful to explain
how incentive regulation is related to optimal natural monopoly pricing.
The standard model of natural monopoly regulation is illustrated in Figure 1. The regulated
monopolist produces a single product and faces economies of scale and a constant marginal
cost. The firm’s average cost (denoted by AC), marginal cost (denoted by MC), demand
(denoted by D), and marginal revenue (denoted by MR) curves are depicted below.
Under standard assumptions, marginal-cost pricing is the first-best option because it leads to
maximisation of social surplus (i.e. zero deadweight loss).1 However, in this example (natural
monopoly), marginal-cost pricing does not allow the regulated firm to recover its fixed costs—
the point where the demand and marginal-cost curves intersect is below the average cost curve
(see Figure 1). In this case, first-best pricing would require government transfers (subsidies) to
the firm to ensure financial sustainability of the firm. Average-cost pricing is second best in the
sense that it is the minimum common price that allows the firm to recover its costs in the absence
of government transfers.
The basic model typically assumes perfect information—the regulator has all the relevant
information and will hence set the price at P. In practice, as discussed in more detail below, the
regulator faces the problem of information asymmetry. The regulator might not know where the
cost and demand curves lie. Often, the price set by the regulator is forward looking and based,
1
Short run marginal cost is the optimal cost concept to the extent that it measures the additional cost to society of the incremental
decision. Fixed costs are not included in marginal costs and are costs that are not sensitive to the marginal output decision. They
need to be financed if the firm is to stay in operation in the long term but in terms of social welfare they are not relevant in terms
of defining the optimal level of output. The optimality of this rule from an economic efficiency perspective requires that all relevant
costs (including any external costs) be reflected in marginal costs and that the rule is applied uniformly elsewhere in the economy
(the problem of the second best). See Kahn (1995).
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at least partly, on the information provided by the firm about the expected cost of providing the
service. The firm then has an incentive to exaggerate such costs. Even if the firm provides
accurate cost forecasts, it might be inefficient and have a higher AC curve than one associated
with best practice. Incentive regulation is a tool to encourage the firm to provide more accurate
cost forecasts and to operate more efficiently so that in the long run the regulated price will
converge to the efficient level despite the information asymmetry.
Figure 1 Standard model of natural monopoly regulation.
2.1
Rate-of-return versus incentive regulation
2.1.1. Rate-of-return regulation
The problem faced by a regulator with limited information about the regulated firm’s cost profile
can be illustrated by assuming that the regulated firm can either be high cost (𝑐ℎ ) or low cost
(𝑐𝑙 ). The difficulty arises from the fact that, if the regulator ‘asks’ the firm what the cost will be of
providing the service to consumers, a low-cost firm has an incentive to pretend to be a high-cost
firm, as by doing so it secures a higher price and hence higher profits for the firm. This
phenomenon is known in economics as an adverse selection (hidden information) problem.
Rate-of-return regulation (also known as cost-of-service regulation) represents a solution to this
problem. Instead of asking the firm what the cost of providing the service would be, the regulator
simply sets the price (or resets it after a year) to allow the regulated firm to recover costs that
have actually been incurred. Since the price is based on realised costs, subject to auditing and
other requirements (for example, inputs are purchased from third parties through competitive
tendering), the issue of hidden information is no longer relevant. This assumes that auditing of
costs will be effective in addressing the information advantage of the regulated firm. As prices
are based on costs that have already been incurred, it is convenient to think of rate-of-return
regulation, at least in this stylised form, as a form of ex-post regulation.
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The guarantee of cost recovery, however, introduces another problem known as moral hazard.
Given that it is not possible for the regulated monopolist to earn additional profits above the rateof-return determined by the regulator, there will no economic incentives to exert any managerial
or cost-reducing efforts. There are no "excess profits" left on the table. In addition, as capital
attracts a regulatory rate of return, while operating and maintenance expenses do not, and to
the extent that the allowed rate of return is greater than the firm’s true cost of capital, the firm
might have an incentive on the margin to overinvest in capital assets. This is known as the
Averch-Johnson effect, which can manifest itself through gold plating or biased technology
choices.2
In practice, however, rate-of-return often includes ex-ante or ex-post prudency reviews of capital
investment and operating expenses. While it is unlikely that these reviews can completely
overcome the information asymmetry problem, they may mitigate adverse selection and moral
hazard.3 Moreover, as explained further below, the incentive on the margin to overinvest in
capital might also emerge even under price-cap regulation. Therefore, in practice the distinction
between price cap and rate of return regulation is less stark than what is assumed in the basic
stylised examples.
Rate-of-return regulation has evolved over many decades (mostly in the US given the
prevalence of privately owned utilities) through a combination of judicial and legislative
oversight, advocacy by firms, governments and other interest groups, and an increased
understanding of the challenges involved in regulating prices. This evolutionary process has
incorporated elements of incentive regulation, a theme that is explored in more detail below.
Nevertheless, as the focus of this paper is on the fundamental differences between different
regimes, it will be useful to refer to the stylised (or abstract) versions of the existing regulatory
arrangements.
2.1.2. Price caps
In contrast to rate-of-return regulation, under price-cap regulation the regulator sets a maximum
price that the firm is allowed to charge customers. The key idea is that as the price cap is
established and fixed ex-ante by the regulator based on cost and demand forecasts, such
arrangements will create incentives for the regulated firm to be cost efficient.
If the cost allowance indeed reflects the efficient level, the corresponding price cap will impose
cost discipline on the regulated firm (to deliver the service at efficient costs) as the firm does not
2
3
Averch (2008).
See, for example, Joskow (1974 and 1989) and Joskow and Schmalensee (1986).
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recover any spending above the pre-determined cost allowance.4 If the cost forecast is inflated
(i.e. inefficient) or there is an unanticipated scope for productivity improvements, the firm will be
incentivised to pursue cost efficiency as it will earn higher profits by delivering the regulated
service at cost levels lower than initial forecasts. Therefore, there is no longer a moral hazard
problem.5
The use of price caps, however, reintroduces the issue of adverse selection. The regulated firm
has the incentive to exaggerate cost forecasts the regulator uses to determine prices—higher
cost allowances translate to higher prices, hence higher profits for the firm. Higher approved
cost allowances mean there will be more room for outperformance (which increases the firm's
profits) during the regulatory period. The regulator does not have perfect information to
determine whether the regulated firm’s cost proposals reflect best practice.
Another key difficulty with a price-cap regime is that regulated assets have very long lives and
economic circumstances can change quite drastically over time. Thus it is neither desirable nor
feasible to fix the price a regulated firm can charge for the next thirty to forty years. In practice,
prices are set for much shorter periods, typically three to five years, creating opportunities for
the regulator to take account of information such as actual costs and demand during periodic
price reviews. Thus, any economic rents—excess returns above normal levels that would exist
in competitive markets—that may arise when prices are set ex-ante are only earned until the
next price review (if the productivity gain is observable to the regulator).
A shorter review period can potentially reduce the incentives for the regulated firm to initiate
long-term cost reduction for fear that it would not be able to fully benefit from such actions, as
the price cap might be adjusted downwards at the next review to reflect the firm's new cost
profile. This is one of the distortions introduced by undertaking periodic price reviews. This issue
is pervasive in the implementation of any type of incentive regulation and it involves
consideration of the optimal period length where prices are fixed. This is discussed further in
Chapter 3.
Price reviews also rely on a number of auxiliary mechanisms, such as information gathering,
auditing, and accounting systems that were traditionally associated with rate-of-return
4
While it is possible to set the cap too tightly, which could result in the regulated firm facing financial distress, in practice there is a
range of mechanisms, including automatic pass-through of certain costs and the possibility of reviewing prices prior to the end of
the next regulatory period, that minimise such risk.
5
There are additional incentives associated with price-cap regulation. The regulated firm has an incentive to maximise quantity sold
as long as the regulated price cap is above its incremental cost of increasing supply. This is why incentivising regulated firms to
invest in energy efficiency requires decoupling revenue from quantity. See, for example, Brennan (2010). The interaction between
different incentives is discussed further below.
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regulation. The use of these mechanisms reinforces the view expressed above that, in practice,
the distinction between price cap and rate of return regulation is less pronounced than what is
widely assumed in the theoretical literature.
When price caps were first introduced, mostly following the process of vertical separation and
re-regulation of infrastructure businesses that took place around the globe in the 1990s, there
was an expectation that competition might replace regulation as the governance mechanism for
the determination of prices in sectors such as electricity, telecommunications, and rail.6
Competition did not materialise in many regulated markets, and, in fact, price cap regulation was
extended to other sectors, such as termination charges for mobile telephony (the rate that mobile
companies charge other mobile companies to terminate a call in their network).
Price-cap regulation, like rate-of-return regulation, has evolved over time—a process that is
accompanied by a number of implementation challenges. The real-world application of price cap
mechanisms is complicated in practice, interacts with a range of other incentive schemes, and
deviates considerably from the stylised version described above.
Chapter 3 explores many of the implementation issues in more detail, including how to set initial
prices and the different approaches for adjusting prices until the next regulatory review under a
price cap regime. It also discusses some of the mechanisms that have emerged to address
particular shortcomings of price-cap regulation, including cost pass-throughs that allow the
regulated firm to shift certain risks to consumers, and efficiency carry-over mechanisms that
allow the firm to retain additional profits resulting from a cost reduction initiative beyond the next
regulatory review. These mechanisms, along with a legal and administrative framework that
allows for effective information gathering, have in practice been crucial for implementing a sound
regulatory regime.
2.1.3. Revenue cap
Revenue cap regulation entails the regulator setting the maximum revenue that the firm is
allowed to charge its consumers over the regulatory period. A revenue cap is similar to a price
cap, in the sense that they both provide incentives for the regulated firm to reduce costs, as long
as the firm is allowed to retain some benefits from any cost savings.
The key difference between a price cap and a revenue cap is who bears the volume risk:
6
Beesley and Littlechild (1989).
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(a)
Under a price cap, the firm bears the volume risk. A price cap is fixed prior to the start
of the regulatory period based on forecast demand. Actual revenue earned will depend
on the actual demand.
(b)
Under a revenue cap, customers bear the volume risk. The firm recovers the revenue
cap irrespective of the actual demand. Future revenue allowances are adjusted to
ensure that the firm recovers (or returns) any revenue as a result of under- (or over-)
performance in demand that has occurred previously.
This difference means that there may be a moral hazard problem under a revenue-cap regime.
While the regulated firm facing a revenue cap has the incentive to be cost efficient (if there is no
clawback of abnormal profit), it has limited incentive to improve total demand (for example, the
number of trains running in a rail network) as the firm does not benefit from any increase in
demand from its customers—the maximum revenue it can earn is capped.
2.2
Optimal regulation
As discussed above, while rate-of-return regulation can address the adverse selection problem,
it does not address the issue of moral hazard as the regulated firm faces no incentives to contain
costs. In contrast, under price-cap regulation the regulated firm is incentivised to reduce costs,
but adverse selection is reintroduced, as the firm might have a perverse incentive to exaggerate
cost forecasts the regulator uses to determine prices.
Perhaps not surprisingly, the optimal (second-best) regulatory mechanism includes both ex-ante
and ex-post elements, such that the regulated price is partially determined ex-ante but can be
subsequently adjusted to reflect certain types of deviations from predicted costs.7 This can be
implemented through a profit-sharing agreement where the firm and the regulator agree on how
to share any excess profits with customers.
Laffont and Tirole (1993) have shown that the optimal mechanisms can be implemented by a
menu of contracts with different combinations of fixed and variable components. To illustrate the
reasoning behind this result, consider a regulator that allows the regulated firm to choose
between a fixed price (price cap) and an ex-post price based on realised costs. This menu allows
the regulator to offer a lower price cap relative to the case of a pure price-cap regime. If the firm
cannot break-even (in terms of cost recovery) at the price cap offered, it will simply choose the
7 This refers to the best outcomes from a societal viewpoint taking into account existing constraints such as asymmetry of information
by the regulator who does not know the regulated firm’s costs. In the absence of asymmetric information, and considering a single
homogenous product, second best refers to average cost pricing. See Lipsey and Lancaster (1956-1957).
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ex-post arrangement. The break-even constraint still includes a return on capital and
depreciation.
In contrast, a firm with unitised cost below the specified price cap has an incentive to select the
fixed price arrangement. This is because the firm will be able to retain any excess profits from
its cost reduction efforts (at least until the next pricing review). Customers will benefit in two
ways: (1) the price cap is lower than what it would be if the firm did not have the options; and
(2) there would be lower prices in the long run, as periodic price reviews would adjust prices to
reflect any improvements in the firm's efficiency.
In reality, as there are many possible types of firms (in terms of cost attributes) and the regulator
has limited information with regard to the regulated firm’s type, it is best to offer a range (menu)
of contracts with different combinations of a fixed (ex-ante) price and an ex-post rule. These
combinations are chosen to take into account the regulated firm’s break-even constraint and to
ensure that low-cost firms choose a high-powered scheme (that is, a larger weight on a fixed
price) and high cost firms choose a lower powered incentive scheme (that is, a larger weight on
the ex-post arrangements for cost recovery).
2.3
A simple analytical framework
Following Joskow (2013), a simple analytical formulation of the optimal regulatory contract for
the basic case where the regulated firm can be either high or low cost is presented here. Note
that the firm is assumed to be operating on its efficiency frontier regardless of its cost-type (i.e.
a high-cost firm will have high efficient cost with normal managerial effort), but the frontier can
shift over time through productivity gains realised by additional managerial effort. The allowed
unit price is denoted by 𝑝, the firm’s actual realised unitised cost by 𝑐, and the regulator’s
assessment of the ‘efficient’ costs by 𝑐 ∗ . For ease of explanation, the quantity is normalised to
one so that there is no distinction between the unit price and revenue. The allowed unit price
can be expressed as:
𝑝 = 𝛼 + (1 − 𝛽)𝑐
In this formulation, the allowed unit price (which can also be interpreted as the allowed revenue)
is determined based on a fixed component 𝛼 and a second component that is contingent on the
firm’s realised costs 𝑐 and where 𝛽 is the sharing parameter that defines the responsiveness of
the firm’s revenues to realised costs.
The different regimes can be characterised as follows:
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𝜶
𝜷
Price cap
𝑐
∗
1
Rate of return
0
0
Profit sharing
0 < 𝛼 < 𝑐∗
0<𝛽<1
Regime
When 𝛼 = 𝑐 ∗ and 𝛽 = 1, a pure price cap applies. In this case, the price is set on the basis that
the firm is allowed to recover the ‘efficient costs’ (𝑐 ∗ ) based on the regulator’s estimation. The
rationale of setting a relatively high fixed price is that if the firm is indeed a high-cost type, the
price cap will allow this firm to recover its efficient realised cost (hence the firm's financial viability
is assured). Under this scenario, the firm has the incentive to be cost-efficient as it can earn
additional profits by reducing its unitised cost to below 𝑐 ∗ .
When 𝛼 = 𝛽 = 0, rate-of-return regulation applies, where the firm is fully compensated for its
realised unit cost (assuming that audits of realised costs are accurate). In this case, there is no
economic incentive for the firm to reduce its cost as the price is set on an ex-post basis.
When 0 < 𝛼 < 𝑐 ∗ and 0 < 𝛽 < 1, the price depends on both the regulator’s cost estimation and
the firm’s realised cost. This is a form of profit-sharing arrangement.
Laffont and Tirole (1993) demonstrate that the regulator could achieve better outcomes by
offering a menu of regulatory contracts to the firm. That is, rather than prescribing one specific
form of regime (e.g. price cap, rate-of-return regulation, or a fixed profit-sharing arrangement),
the regulator can offer a menu of possible pairs (𝛼, 𝛽) to the firm and allow the firm to choose a
regulatory contract.
The regulator’s problem then is to ensure that when offered the menu, the firm will self-select a
contract with high- or low-powered incentive depending on its type. If this is true, the menu is
said to be incentive compatible. A well-designed menu will make it profitable for a high-cost type
firm to choose a low-powered incentive scheme where both 𝛼 and 𝛽 are close to zero, and a
low-cost type firm to choose a high-powered incentive scheme where 𝛼 is closer to 𝑐 ∗ and 𝛽 is
closer to 1.
More specifically, and as discussed further below, in practice the menu needs to be designed
so that the firm will maximise its expected profit by choosing the option that best reflects its
expected cost. To see how this might work, consider the stylised example above where the
regulated firm’s unitised cost can either be 𝑐𝐿 = $50 (low cost) or 𝑐𝐻 = $100 (high cost). These
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are expected costs, which the firm may be able to reduce further by exerting effort. The unitised
costs include a return on capital and of capital, and the focus is on per unit profit. The regulated
firm knows what cost type it is. Likewise, the regulator is aware of the two possible cost types
but does not know the regulated firm’s cost type.
As mentioned previously, rate-of-return regulation is equivalent to setting 𝛼 = 𝛽 = 0.
Conversely, under price-cap regulation, the regulator needs to form a view with regard to the
firm’s true cost (either $50 or $100) so that 𝛼 can be set equal to the regulator’s view and 𝛽 = 1.
The issue of information asymmetry can be seen here. If the regulator can determine what the
firm’s cost type is (hence there is no information asymmetry issue), then it is clear that price-cap
regulation entails very strong incentives for cost control. However, this also illustrates how
delicate the regulator’s job is under price cap regulation. If 𝛼 is set too low, the regulated firm’s
financial viability will be compromised. If 𝛼 is set too high, there will be incentives for cost
reduction, but a low-cost firm will earn substantial monopoly rents.8 In practice, regulators are
more likely to use a conservative estimate of efficient costs (i.e. an 𝛼 that gives greater weight
to ensuring financial viability).
Below is a simple example of an incentive-compatible menu consisting of two options:
Option 1
𝛼1 = 50, 𝛽1 = 0.99
Option 2
𝛼2 = 0, 𝛽2 = 0
A low-cost firm (𝑐𝐿 = $50) choosing the second option (𝛼2 = 0, 𝛽2 = 0) earns zero economic
profit as its realised cost will be fully reimbursed. If such a firm chooses the first option (𝛼1 =
50, 𝛽1 = 0.99) instead, then it earns a unit profit equal to:
(50 + (1 − 0.99) × 50) − 50 = $. 50
Thus, a low-cost firm strictly prefers the high-powered incentives contract (𝛼1 = 50, 𝛽1 = 0.99).
Now consider a high-cost firm (𝑐𝐻 = $100). Similar to the low-cost firm, the high-cost firm earns
zero economic profits if it chooses the low-powered incentive contract (𝛼2 = 0, 𝛽2 = 0).
However, if such a firm chooses the first option (𝛼1 = 50, 𝛽1 = 0.99), then it earns a negative
unit profit equal to:
(50 + (1 − 0.99) × 100) − 100 = −$49
8
Lax regulation was one of the rationales for the introduction of the windfall tax on privatised utilities in the 1997 UK budget. See,
for example, Chennells (1997).
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This implies that a high-cost firm will choose the second option (𝛼2 = 0, 𝛽2 = 0) as suggested
above.
While this example illustrates the potential for a menu approach to overcome the regulator’s
information asymmetry, there are some key implementation issues. In practice, a menu consists
of a baseline cost (that is, the regulator’s best estimate of the firm’s efficient cost for delivering
the service), sharing ratios (the percentage of the difference between allowed cost and actual
cost that the firm can retain), and an additional income component (can be either positive or
negative) that is calculated to ensure that the menu is incentive compatible. The design should
ensure that the choice that maximises the firm’s expected profit is the choice that best reflects
its beliefs about future costs. In the above example, the cost baseline is represented by 𝑐 ∗ , the
sharing ratio is roughly represented by 𝛽, but additional income is not required in this simple
(but inexact) model. The determination of these three elements raises a number of complex
issues, which are discussed in more detail in the Section 3.3 and again in Chapter 4 when
reviewing international experience.
2.4
Incentive regulation and service quality
The discussion above assumes implicitly that the quality of the regulated service is perfectly
verifiable and it can be contracted upon. In reality, however, if quality is difficult to measure and
cannot be fully specified in the regulatory contract, then a price-cap regime, which focuses on
providing incentives for the regulated firm to reduce costs, may impact adversely on quality.
Therefore, in practice, many price cap regimes have attempted to mitigate such an effect with
additional incentives and penalties linked to the service quality delivered (for example, the
number and duration of electricity supply interruptions). These incentives interact with the overall
regulatory framework. This is discussed in Chapter 3.
2.5
Incentive regulation and the optimal tariff structure
This section discusses the relationship between incentive regulation and the optimal structure
for a tariff or price. Note that it is not the purpose of this paper to investigate what constitutes an
optimal price structure, but rather to explore any interdependency between the application of
incentive regulation and the tariff or price structure imposed by the regulated firm.
Incentive regulation aims at solving the information problem faced by the regulator by providing
incentives for the regulated firm to behave in an optimal (‘second-best’) way. The reference to
second-best recognises that ‘first-best’ regulation (that is, the regime that maximises the social
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surplus in the absence of any constraints) requires a price structure where prices for marginal
output reflect marginal costs. As the average cost of a natural monopoly firm is likely to be higher
than its marginal cost, the first-best price structure will result in the firm operating at a loss.
Hence, the second-best price structure, one that allows the regulated firm to at least break even,
is required.
To be clear, the basic aim of incentive regulation is to provide incentives for the regulated firm
to take appropriate actions—in terms of economically efficient cost reducing efforts, innovation,
quality and investment—while at the same time ensuring that the firm is allowed to earn enough
revenue to recover the efficient cost of providing the services. After the regulator establishes the
maximum revenue the firm can earn, the structure of the prices that the regulated firm is allowed
to set in order to recover the revenue must be determined. Additional economic efficiency issues
relate to the optimal structure of prices (i.e. tariff structure).
Different regulatory regimes have different levels of flexibility regarding the prices that the
regulated firms can set. For example, under a pure revenue-cap regime, the regulated firm will
typically have considerable flexibility to set its own preferred tariff structure. While such flexibility
can enhance the efficiency of the tariff structure—the standard example is a monopolist that can
perfectly price discriminate and as such avoid deadweight losses associated with uniform
monopoly pricing—a strict revenue cap regime nevertheless transfers all quantity (volume) risk
to users, which may not be optimal.
Price cap regimes also usually allow for some flexibility in setting tariffs. For example, in the
case where a regulated firm provides a number of services, instead of setting a single price cap
for each service, a global price cap can be imposed by the regulator. A global price cap is
expressed as a weighted (often by quantity) average across different prices for different
services. This in turn provides the flexibility for the firm to set a range of tariff structures (including
peak vs. off-peak and block tariffs) for services it provides. Whether such flexibility can enhance
efficiency depends on applying the correct weights to the various services in the basket.9 Note
that in practice price caps applied to electricity and gas distribution and transmission are used
mainly as an incentive mechanism, rather than as a mechanism to induce an optimal secondbest pricing structure when the different services share common fixed costs.
9
In the context of the regulated firm operating in different market segments (for example, above and below rail), a global price cap
might also allow the withdrawal of services from the price cap if effective competition develops. Moreover, having competitive
and monopolistic services in the same price control basket can lead to distortions as reductions in prices of competitive services
may be offset by rises in prices of monopoly services as discussed next.
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In telecommunications and rail, many regulated firms are given a great degree of pricing
freedom under a global price cap. In this context, global price capping refers to regulation of a
vertically integrated firm by an overall price cap that covers both the bottleneck (where the firm
has clear market power) and the downstream market (where there may be potential market
power). Under such a mechanism, the incumbent vertically integrated operator may be able to
charge different relative prices in order to maximise profits. While global price caps can in
principle facilitate more efficient pricing and at the same time provide incentives for cost
reduction, in vertically integrated industries they may also be misused by the access provider
(upstream firm) to deter downstream competition. For instance, there is scope for anticompetitive behaviour even in the case where the incumbent vertically integrated operator is
required to charge its own downstream operator the same access price that it charges other
downstream competitors. This might occur via raising the access charge for all users (in the
upstream market) and at the same time reducing its own retail prices within the cap (downstream
market), thereby subjecting competitors to a profit margin squeeze, which can lead to
foreclosure or reduced competition over time.10
The general point of this section is that the incentive regulation literature is not a substitute for
the older literature on optimal pricing for natural monopolies subject to a break-even constraint.
This can be seen in the framework developed by Laffont and Tirole (1993, Chapter 2) where the
availability of government transfers (that is, subsidies) creates a separation between optimal
pricing and optimal incentives for controlling costs. In this framework, marginal cost pricing is
possible as any shortfall of revenue to cover fixed costs can be met by government transfers.
In practice, however, such government transfers or subsidies are typically not part of the
regulator’s tool kit. This means that fixed costs need to be recovered somehow through prices
that deviate from marginal cost. When uniform prices are mandated by the regulator and the
service is homogenous the recovery of fixed costs is typically accomplished by setting prices
equal to average cost. Alternatively, regulators may use non-linear or Ramsey prices to improve
allocative efficiency.11 In any event, all of the basic second-best optimal pricing results for a
natural monopoly subject to a break-even constraint continue to be relevant along with the
10
11
This issue is often addressed by requiring that all prices lie between incremental costs and stand-alone costs. This approach has
some useful properties in limiting inefficient entry by ensuring that entrants pay at least the additional, incremental cost they
cause, and by allowing recovery of common costs where maximum prices assign all common costs to entrants. However, it also
has important limitations. First, it ignores strategic pricing; the dominant firm can drive more efficient, non-dominant competitors
from the market without lowering prices below incremental costs in competitive markets. Second, in practice the line between
stand-alone and incremental costs is often not entirely clear and is subject to manipulation. Third, it rules out legitimate reasons
for charging below incremental cost such as expanding markets and may rule out Ramsey pricing.
In the absence of equity considerations, allowing non-linear prices or Ramsey prices can improve allocative efficiency. For
example, in the case of homogenous goods two-part tariffs or inclining/declining tariffs may be used. When there are different
types of consumers and sufficient information about demand characteristics Ramsey prices can be used to recover total costs by
charging prices that are inversely related to the elasticity of demand.
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application of optimal incentive schemes (given asymmetric information) for controlling
production costs. However, as indicated above, the focus of this paper is on productive and
dynamic efficiency—the incentives for the regulated firm to truthfully reveal its opportunities for
pursuing cost efficiencies and to produce in a cost efficient manner.
2.6
Incentive regulation and the efficient pricing of capacity
Many regulated facilities, such as rail tracks, are subject to congestion. In this case, efficient
access prices include two components: the marginal production cost and an additional margin
to clear the market. This additional margin reflects congestion costs and ensures that a buyer
who is willing to pay the market-clearing price has access to the service. The relevant marginal
(social) cost is the sum of the marginal production cost and a marginal congestion cost
component.
Pricing at this marginal social cost can provide price signals to facilitate socially efficient
decisions to expand capacity. If the congestion costs are larger than the costs of expanding
capacity, and if these costs are reflected in prices, then capacity can be expanded.
In a recent paper, the QCA laid out a simple model to understand how access prices could be
set in the context of a congestible facility.12 The paper assumes homogenous consumers (for
example, only one type of shipper), lumpy capacity, and that costs are fully known so that there
are no moral hazard or adverse selection issues.13 In this framework, if demand at the current
price is below existing capacity, then there is no congestion. In this instance average cost pricing
ensures that the regulated firm recovers its fixed costs. While such a price is not efficient in a
first-best sense, it is the minimum uniform price that allows the firm to recover its cost and hence
is efficient in a second best sense.
Likewise, if demand increases and reaches capacity, then there is excess demand at the current
average cost price. In this instance, the socially optimal price will be equal to marginal production
cost and the additional margin needed to clear the market. As this price, by construction, is
larger than the average cost, the regulated firm over-recovers its costs. Pricing in this manner
recognises the scarcity value of the capacity. However, just as in the case where the quantity
demanded is less than capacity, marginal cost pricing may not be feasible due to procedural or
other constraints, or may be considered to be unfair due to the transfer of rent to the access
12
13
QCA (2013), Capacity Expansion and Access Pricing for Rail and Ports.
The presence of heterogeneous consumers (for example, two different types of shippers with different demands) complicates
the analysis and makes it more difficult to achieve efficient prices. See the discussion in Mackie-Mason and Varian (1994).
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provider. If marginal cost pricing including the marginal value of congestion costs cannot be
implemented, demand must be rationed by non-price means—for example using a rule of thumb
such as ‘first in line first in right’. In effect, there is an opportunity cost that reflects that some
excluded users value capacity more than others who are served.
The QCA paper also looks at the case when congestion costs are high enough to justify the
capacity expansion. When the costs of building and operating the additional capacity are
identical to those of the existing capacity, average-cost pricing again allows the firm to recover
its total costs. If there is only one customer, the customer would be charged a price for the
quantity up to the capacity constraint and another price for the new capacity. Multiple customers
complicate the pricing problem and both uniform pricing and different prices for new and existing
capacity introduce different distortions.
The insights provided by the QCA’s paper on the pricing of capacity expansion should be seen
as complementary to the issues of incentive regulation raised in this report. If the regulatory
regime has appropriate incentives for the truthful revelation of costs and for cost reduction, then
one can apply the principles expounded in the QCA’s paper for the determination of (secondbest) efficient prices to allow the regulated firm to recover its efficient costs. However, applying
these pricing principles to allow the regulated firm to recover exaggerated or inefficient costs will
likely lead to perverse outcomes.
2.7
Incentive regulation and benchmarking
Competitive benchmarks or ‘yardstick regulation’ can be used to reduce the asymmetry of
information between regulated firms and regulators. In particular, Shleifer (1985) shows that if
there are many identical and non-competing regulated firms providing the same service across
different jurisdictions, then the optimal regulation involves setting the price for each firm based
on the actual costs of the other firms. Under yardstick regulation, each firm will have no influence
on the price it can charge—it will be based on realised costs of other firms. When regulated
prices are set in this manner, firms are effectively competing against each other. For instance,
if firm 𝑖 does not undertake effort to reduce its costs, and other firms do, then these other firms
will profit because the prices they charge will be above their costs, but firm 𝑖 may experience
losses. Since firms are identical in this formulation, it follows that the prices set using such an
approach should never fall below the firms' efficient costs. In equilibrium, the price will converge
to a level as if the firms were competing directly with each other.
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In practice, firms in the same regulated industry (for example, water distribution) will be
considerably different across jurisdictions due to a number of factors including geography and
population density. However, there are a range of techniques including regression analysis, data
envelopment analysis, stochastic frontier analysis and other statistical techniques that can be
used to control for differences amongst heterogeneous firms, provided there are sufficient data.
While these techniques are not perfect, they can be used carefully to provide some useful
benchmarks. This is discussed in the next chapter on implementation issues.
2.8
The dynamics of regulation
The regulation of infrastructure businesses involves the interaction between the regulated firm
and the regulator over time. This dynamic link creates challenges of its own. For example, if the
regulated firm knew that information about its realised cost could be used to determine prices
for the next review under a price cap regime, then as explained above, the firm might have less
of an incentive to engage in cost reduction in order to convince the regulator that it was a highcost firm. This counteracts the incentive to cut costs in order to earn a higher return under price
cap regulation.
Moreover, this link can also distort the investment decisions of the regulated firm. For instance,
the adoption of technologies that involve significant sunk cost commitments might become less
attractive for fear of regulatory expropriation. This raises important practical issues when
applying the incentive regulation that is discussed in the next few chapters. In particular, it leads
to discussions on optimal regulatory lags, the design of incentive mechanisms, and the
implications of the regulator's ability, or lack thereof, to commit not to change the nature of
regulation.
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3.
IMPLEMENTATION ISSUES
This chapter identifies some key implementation issues (in abstract terms) for a regulator who
wants to apply incentive regulation. Chapters 4 and 5 explore how these implementation issues
manifested themselves, and were dealt with, both internationally and in Australia.
3.1
The regulatory process
In Australia, the regulatory process typically includes an initial submission by the regulated firm,
a draft decision by the regulator, further submissions by the regulated firm, consumers and other
interested parties (such as Commonwealth and State Treasuries and other government
departments), followed by the regulator’s final determination. Breunig and Menezes (2012) have
documented that this process in Australia is characterised by significant weight being given to
the regulated firm’s cost proposals (or its requested revenue requirement).
In Breunig and Menezes (2012), the authors constructed a variable which is the difference
between a firm’s proposed revenue requirement measured in dollars (denoted by 𝑌) and the
maximum allowable revenue (denoted by MAR) as determined by the regulator. They define the
following unit-free variable, 𝑃𝐷𝐶 =
𝑌−𝑀𝐴𝑅
,
𝑌
which represents the proportion of disallowed claims.
Note that in principle the condition 0 < 𝑃𝐷𝐶 < 1 holds, as at one extreme the regulator is setting
the maximum allowable revenue to exactly cover the firm’s requested revenue requirement (i.e.
𝑃𝐷𝐶 = 0), while at the other extreme, the regulator is setting the allowed revenue to zero (i.e.
𝑃𝐷𝐶 = 1). Table 1 shows the value of PDC for 115 regulatory decisions that took place in
Australia from 1998 onwards. On average, Australian regulators have allowed around 92 per
cent of a firm’s cost proposal.
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Table 1 Proportion of disallowed claims (PDC) by regulators and industries.
Industry
Electricity
transmission
Electricity
distribution
Gas
distribution
Gas
transmission
Water
Rail
Total
ACC
C
.107
VIC
NS
W
QLD
ACT
TAS
NT
Total
.107
.165
.089
.115
.116
.026
.141
.114
Regulator
WA SA
.094
.082
.103
.081
.079
.063
.014
.377
.051
.089
.087
.092
.246
.043
.055
.069
−.055 .112
.103
.081
.224
.065
.099
−.055 .082
Source: Breunig and Menezes (2012)
Joskow (2013) points out that this process of regulated firms making initial submissions followed
by a draft and a final decision by the regulator may have similarities to the regulator’s offer of a
menu of contracts. The idea is that the firm’s initial submission and the final determination are
essentially elements of a wider set of possible contract choices. The possibility of merits review,
which is available in some industries, further reinforces the ability of firms to exercise influence
on the costs that are allowed by the regulator. One can view the set of possible contract choices
(including allowed costs and incentive rates) that emerge from this process, including the
possibility of merit review, more like a menu rather than a single parameter regulatory
framework, which is what is ultimately observed. The approach taken by some UK regulators,
Ofgem and Ofwat, is to make this set of possible contract choices explicit. This is achieved by
introducing via menu regulation an incentive scheme that aims to ensure that the regulated firms’
cost claims reflect their true efficient costs. This is explored in detail later.
3.2
Price-cap regulation
This section explores the practical issues associated with the application of price-cap regulation.
As pointed out by Joskow (2013), in practice, price-cap regulation is more a complement to than
a substitute for rate-of-return regulation. As explained later, the implementation of price-cap
regulation (or incentive regulation in general) requires a good accounting system for capital and
operating costs, cost-reporting protocols, data collection and reporting requirements for
dimensions of performance other than costs, similar to the case of rate-of-return regulation. The
fundamental difference between the two regimes, however, lies in how this information is used.
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Price-cap regulation (or incentive regulation) recognises the existence of adverse selection and
moral hazard issues, and incorporates regulatory mechanisms to mitigate them.
The most common form of price-cap regulation is CPI−X (or RPI−K in the UK) regulation. Under
a CPI−X regime, the regulator sets an initial price p0 (or a global price depending on the number
of regulated services the firm provides) ex-ante that the firm is allowed to charge customers.
This price is adjusted annually for changes in inflation (rate of change in CPI) and a target
productivity change factor (represented by X). This in turn requires the regulator to establish the
allowed revenue (which is equivalent to the allowed cost) that the firm is allowed to earn from
its customers over the regulatory period. Regulators typically undertake a price review every
three to five years.
The important elements of a price-cap regime are discussed below. The incentive implications
of periodic price reviews are explored in Section 3.4.
3.2.1. Determination of allowed costs
The implementation of price-cap regulation uses some form of cost-based regulation. At the end
of each regulatory period, a new p0 and a new X factor are approved by the regulator. These
parameters are set on the basis that they will allow the regulated firm to recover its allowed
revenue (in expectation).
The building-block methodology is employed in various sectors in Australia and the United
Kingdom to establish the allowed revenue. The building blocks are cost blocks—various
components of the expected efficient costs required by the regulated firm over the regulatory
period—and are added together to form the allowed revenue. 14 A regulated firm’s cost base
comprises operating and maintenance costs, taxes, as well as the return on and return of capital.
The cost assessment involves setting up appropriate cost accounting rules, reporting
requirements, and auditing systems. Financial components such as depreciation rates, the rate
of return, the debt to equity ratio, and tax rates are also applied. Once the allowed revenue is
established, it can then be applied to establish a revenue cap, or a price cap based on forecast
volumes.
There are many implementation challenges with the building-block approach. These stem from
the fact that the notion of efficient costs is inherently abstract. What is the debt to equity ratio of
an efficient firm? What is the cost of capital for an efficient firm? How should an efficient firm
14
The efficient cost is not forward looking as a large part of capital costs are sunk and have been rolled into the Regulatory Asset
Base, which is not re-optimised at every new regulatory decision. The forward looking components are operating expenditures,
new capital expenditures and to the allowed rate of return.
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organise its operations? These questions have many possible answers and the process to
determine these answers under a building blocks approach relies on an examination by experts.
The actual values determined by the regulator interact in a complex manner with the incentives
faced by the regulated firm, a theme that is explored in several parts of this report.
In practice, cost allowances are determined on the basis of the regulated firm's cost proposals
subject to an assessment of efficiency. Efficiency assessments include bottom-up assessments
and benchmarking. Regulators typically make use of a range of assessments for determining
the efficient costs. The types of efficiency assessment available to the regulator depend on
various factors.
One factor is the structure of the regulated sector. Regulators in the UK (Ofgem and Ofwat) rely
heavily on comparative benchmarking as they have the advantage of regulating a group of
largely similar and non-competing firms operating in the same sector. Such an approach can be
used in a yardstick framework, as discussed in Section 2.7. On the other hand, some regulators
tend to focus on the firm's current levels of various costs and other dimensions of performance,
and benchmark the firm against its historical performance.
Another factor is the type of expenditure under assessment. Capex, which enters the RAB and
thus affects future return on and return of capital, tends to be lumpy and non-recurrent.
Regulators typically rely on bottom-up analysis, such as cost-benefit analysis and case studies,
when examining capex proposals. On the other hand, most opex is recurrent. Most regulators
determine opex through consideration of historical expenditure and adjust for exogenous factors
such as changes in input prices and demand (this is used by the AER—see Section 5.2).
As discussed previously, under a standard price-cap regime, the regulated firm might have the
incentive to exaggerate its cost forecasts. Ceteris paribus, higher cost allowances decrease the
chance of overspend and increase the chance of underspend. This constitutes an adverse
selection problem associated with the determination of allowed costs. Efficiency assessments
undertaken by the regulator can mitigate this issue, but they also increase the information
burden and it is unclear how effective they are. Ofgem and Ofwat have applied menu regulation
to incentivise regulated businesses to submit cost proposals that reflect their true expectation of
cost requirements. This is discussed in Section 3.3.
3.2.2. Productivity measurement
There are three broad techniques that can be used to benchmark productivity performance for
regulated businesses: Total Factor Productivity (TFP) indices, which measure productivity
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based on index numbers; Data Envelopment Analysis (DEA), which uses linear programming
(optimisation) techniques to determine the efficiency frontier; and an estimation of the production
function or cost frontier using econometrics. These are discussed in more detail in Box 1 below.15
Box 1: Benchmarking techniques
TFP indices are defined as the ratio of a particular measure of output quantity (or change
in output quantity) and a particular measure of input quantity (or change in input quantity).
Output and input quantities are weighted in different ways by means of various indices. For
example, a common TFP index is given by the ratio of Tornqvist output and input indices.
These indices can be expressed as the geometric mean of output (input) quantities
weighted by moving average revenue (cost) shares. For a detailed analysis of a range of
productivity indices, see for example Diewert, W., and Nakamura A. (2006), The
measurement of aggregate total factor productivity growth, in J. Heckman and E. Leamer,
eds., Handbook of Econometrics vol. 6, Elsevier.
The DEA method entails enveloping the data (input-output pairs observed) to determine
the best practice (efficiency) frontier by linear programming (optimisation). Under this
approach, efficiency is defined as the ratio of a linear combination of outputs to a linear
combination of inputs, where weights are chose to maximise efficiency for each firm subject
to the constraint that all efficiency scores are less than or equal to one. The most efficient
firm is the one that produces more of all outputs using less of any input.
The econometric regression method involves the estimation of a cost or production frontier
on the basis of specific assumptions about the underlying technology. Under this approach,
a firm’s distance from the frontier is either entirely due to inefficiency (deterministic frontier)
or is decomposed into a random component and an inefficiency term (stochastic frontier
analysis).
These techniques have different strengths and weaknesses. The TFP index number
methods can be implemented with a relatively small number of observations and can
accommodate a large number of outputs and inputs, provided the necessary data are
available. However, while TFP methods provide information on overall cost efficiency, they
do not allow this to be disaggregated into its component sources of efficiency such as
technical and allocative efficiency.
To obtain this more detailed break–down of efficiency performance it is necessary to use
one of the frontier methods such as DEA or stochastic frontier analysis. However, these
methods require a relatively large number of observations, particularly if several output and
several input components are included. For more details see Economic Insights (2013).
Data availability is the key challenge with benchmarking. In practice it is difficult, if not
impossible, to find a reasonable number of comparator firms. Even if this is possible, data
availability is likely to be problematic. Most firms have operations in multiple markets where their
fixed costs are shared across these markets, and they do not collect data in a way that lends
itself directly to this type of analysis. Thus, in practice, choices have to be made on how to use
available data, or if data are not available, regulators may rely on engineering and management
specialists.16 In assessing productivity performance, there is also a need to adjust for differences
15
16
See, for example, Coelli et al (2003).
Mandating firms to produce data in a way that can facilitate the use of benchmarking techniques in the future is also not without
problems. Knowing that the information provided can be used in the future to set prices can lead to incentives to misreport data.
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in scale, geographical location, density and other relevant variables faced by similar but not
identical comparator firms.
3.2.3. Productivity-based regulation and X-factor
The term productivity-based regulation has evolved to describe an approach to regulation that
sets an X factor by techniques that measure total factor productivity and that make use of the
yardstick concept of measuring X based on data that the regulated firm is unable to influence
materially. For example, a productivity-based approach would estimate TFP indices for an
industry or benchmark sample as a whole, including estimates of TFP growth rates over the
regulatory period, and then apply these growth rates in setting allowed prices or revenues over
the regulatory period. Such an approach has the potential to create stronger incentives for
regulated entities to pursue cost efficiencies than a building-block approach that embeds
potential efficiency improvements in allowed forecast costs (the standard approach in Australia).
Joskow (2013) provides a comprehensive description of the concept of X:
Conceptually, assuming that RPI is a measure of a general input price inflation
index, x should reflect the difference between the expected or target rate of total
factor productivity growth for the regulated firm and the corresponding productivity
growth rate for the economy as a whole and the difference between the rate of
change in the regulated firm’s input prices and input prices faced by firms generally
in the economy. That is, the regulated firm’s prices should rise at a rate that reflects
the general rate of inflation in input prices less an offset for higher (or lower) than
average productivity growth and an offset for lower (or higher) input price inflation
(Joskow 2013, pp. 33–34).
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This can be defined as follows:
𝑋 = (∆𝑇𝐹𝑃 − ∆𝑇𝐹𝑃𝐸 ) − (∆𝑊 − ∆𝑊𝐸 ),
where a ∆ indicates a growth rate, ∆𝑊 is the input price growth rate for the industry, ∆𝑇𝐹𝑃 is
the total factor productivity growth rate for the industry and subscripts refer to economy-wide
variables. The first term shows the difference between the industry’s total factor productivity and
that for the economy as a whole. The second term shows the difference between the firm’s input
prices and those for the economy as a whole. If the firm is expected to have the same TFP
growth rate and same input price growth rate as the economy as a whole then X=0, hence the
regulated firm should increase at the same rate as CPI under productivity-based regulation.17
Productivity-based regulation with a TFP methodology has been applied in New Zealand18 and
Ontario, Canada19 and has been investigated by the AEMC.20 The AEMC (2011) proposed that
a TFP methodology be developed in two stages for electricity and gas service providers. The
first stage would involve the provision of relevant data and testing of a suitable methodology.
The second stage would involve detailed design of the methodology and making of an
appropriate rule. The AER has responded by making greater use of benchmarking including
TFP type benchmarking while still applying a building-block approach.21
Typically in Australian regulation (such as the AER), the building-block approach incorporates
target/forecast improvements in opex and capex directly into the allowed cost. Under this
approach, the initial price p0 and X are then set so that the present value of revenues over the
regulatory period is equal to the present value of the allowed cost over the same period. In this
case, X is effectively an escalation rate for the regulated price, and is not related to efficiency
changes. The choice of the specific values for p0 and X that satisfies the revenue equivalence
requirement is a matter of judgement about the optimal price profile over the regulatory period.
17
For more detailed explanation, see Queensland Competition Authority (2012) and Bernstein and Sappington (1999).
Lawrence and Diewert (2006).
19
Pacific Economics Group (2013).
20
See AEMC (2011) and Economic Insights (2010).
21
See Economic Insights (2013).
18
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3.2.4. Service quality
Many price cap regimes around the world, including in Australia, incorporate explicit incentives
to counter any potential adverse impact of the price regulatory regime on quality. This might take
the form of an additional factor in the price cap formula. This implies that the regulator will need
to define the relevant quality dimensions and identify the performance criteria, which then need
to be assessed vis-à-vis actual quality. In setting up the quality incentive scheme, regulators will
need to form a view about how much consumers value various dimensions of service quality
and the likely costs to meet certain quality thresholds. As with any incentive scheme, lack of
sufficient attention to the details can lead to perverse outcomes. For example, an incentive
scheme where penalties for not achieving specific targets (or payments for achieving them) are
too high can lead to perverse outcomes such as misreporting.
As discussed in Section 4.2, customer surveys have been used extensively in the regulation of
the United Kingdom water sector for establishing the overall satisfaction level of customers with
regard to service quality. The AER has also used results from a customer survey to determine
the levels of rewards for the performance incentive scheme (see Section 5.4).
3.2.5. Ex-post treatment
Under some price-cap regimes, the regulated firm's realised spending is subject to an ex-post
assessment. This type of assessment typically takes the form of a prudence review, and is
designed to mitigate the problem of moral hazard. For instance, the AER might write off part of
realised capex spending if they deemed such spending to be imprudent.
Ex-post review is generally considered to be ineffective in mitigating moral hazard. It could
become litigious for the regulator to write off a large amount of capex even if the regulator could
prove that the spending was indeed imprudent and inefficient. If the regulator has no track record
of disallowing realised spending, then the ex-post review may not be perceived as a credible
threat against imprudent spending.
3.3
Menu regulation
Under price-cap regulation, the regulated firm has the incentive to exaggerate its cost forecasts
in order to secure higher prices. This is known as the adverse selection problem. Menu
regulation represents a complement to the price-cap regime to incentivise regulated firms to
submit cost proposals that reflect their true expectation of cost forecasts. This approach can be
applied to setting opex, capex or both.
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Under the menu-based approach, the regulator offers a range of options including various
combinations of an allowed level of expenditure and a sharing ratio (the percentage of
underspend or overspend against the expenditure levels that the firm is allowed to retain). The
firm then chooses the combination and this affects the final levels of cost allowances approved
by the regulator.
A menu that satisfies the firm’s incentive-compatibility constraint incentivises truth-telling from
the firm. An incentive-compatible menu ensures that the choice that maximises the firm’s
expected profit is the choice that best reflects its beliefs about its future costs. This is further
explained below.
In practice, a regulatory menu, in the form of a matrix, is underpinned by the following:
(a)
a cost baseline, which represents the regulator's view of the firm's efficient expenditure
required for the next control period; this involves the regulator determining what costs
are covered (costing manual) and whether to set separate menus for opex and capex
(as applied by Ofwat), or a totex menu that treats all types of spending the same (as
applied by Ofgem);
(b)
a range of allowed expenditure that includes the regulator’s baseline, where the firm
can propose a level of cost allowance within this range;
(c)
a range of possible actual expenditure outcomes;
(d)
an additional income component associated with each level of proposed expenditure,
which is needed to ensure incentive compatibility (i.e. the firm will maximise its
expected profit by choosing the option (proposing a level of cost allowance) that best
reflects its expected cost);and
(e)
a sharing ratio (sometimes referred to as the incentive rate) for over- and
underperformance associated with each level of proposed expenditure, to encourage
efficient cost reduction during the regulatory period.
Some of the components are determined outside the menu framework, such as the cost baseline
and the incentive rate at the break-even point (that is, at the point where the firm earns zero
economic profits). This means that the regulator is still required to form a view of the 'efficient'
cost of the firm, as is the case in a standard price-cap regime. Other components such as
allowed costs and the additional income are endogenous to the menu in the sense that they are
determined to ensure incentive compatibility.
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The example in Table 2 is based on the Capex Incentive Scheme (CIS) introduced by Ofwat in
its PR09 decision. The emphasis here is on the explanation of how the menu is determined and
implemented. The next chapter will present a full description of this menu approach applied by
Ofgem and Ofwat.
A menu, in practice, will look as shown in Table 2:
Table 2 Example of an incentive menu.
Ratio of a firm’s proposed expenditure to the
regulator’s baseline (multiplied by 100)
Sharing ratio
Allowed expenditure
Additional income
Actual expenditure (selected numbers)
80
90
100
110
120
90
100
110
37.5%
30%
25%
97.50
100.00
102.50
0.69
0
−0.88
Net income from the incentive scheme
7.25
6.00
4.75
3.50
3.00
2.25
−0.25
0
−0.25
−4.00
−3.00
−2.75
−7.75
−6.00
−5.25
Source: Ofwat (2009, p. 149)
All numbers in this table are ratios (or percentages) relative to the cost baseline specified by the
regulator. Nevertheless, it is convenient for the purpose of this example to interpret them as
dollars.
To understand how the menu is constructed, consider the shaded column. The ‘100’ in the top
row indicates that the firm has proposed a cost allowance of $100, and it matches exactly the
baseline determined by the regulator (recall that ‘100’ actually represents a ratio of 100 relative
to the regulator’s cost baseline). Hence, since the baseline cost was set at $100, choosing this
column would entail the firm presenting a proposal to spend $100 for the next regulatory period
to provide the regulated services.
The next three rows, in relation to the shaded column, indicate, respectively, that the regulator
has specified an incentive rate of 30 per cent, an allowed expenditure of $100, and an additional
income of $0, associated with this option. First, this means that when the firm proposes a cost
allowance of $100, the firm will be given an allowed expenditure of $100 (this one-to-one
relationship is not always the case; see other columns in Table 2), exclusive of the additional
income that may apply.22 Second, the incentive rate associated with this option is equal to 30
22
The reason why this relationship might not be one-to-one is related to the regulator’s uncertainty regarding whether, in this
example, $100 is the right number for the baseline. For example, suppose that the regulator is perhaps being too strict with their
choice of efficient cost (i.e. allowed expenditure) and $100 may understate the true baseline. In this instance, the regulator may
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per cent. This rate refers to the percentage of the difference between the allowed and actual
expenditure that the firm is allowed to retain. For example, if over the next regulatory period, the
firm ends up spending only $80, there is $20 underspend. Given an incentive rate of 30 per cent,
the firm is allowed to keep 30%*($100−$80)=$6. Finally, the additional income associated with
this option is $0. This is an amount that the firm gets (added into the allowed revenue) by simply
proposing a cost allowance of $100, regardless of the final outcome (i.e. how much it ends up
spending).23
To understand the role of the 30 per cent incentive, it is convenient to refer to the analytical
framework developed in Section 2.3. Recall that under a pure price-cap the incentive rate is 100
per cent—the firm can keep the full amount of its underspend until prices are reset in the next
regulatory review. This of course provides very high-powered incentives for cost reduction. As
discussed in Chapter 2, the pure price cap approach is predicated on the idea that the regulator
can come to a view of what the efficient costs are for providing the regulated services. If the
regulator allows costs that exceed the actual efficient costs, then the firm is earning monopoly
rents. The more significant is the asymmetry of information between the firm and the regulator,
the more likely it is that the price cap regime can lead to excessive rents.
The menu approach instead attempts to overcome the asymmetry of information by offering the
firm the choice between different types of contracts embedding different incentive rates. In this
example, the firm can trade off incentives (from the highest rate of 37.5 per cent to the lowest
rate of 25 per cent) against a guaranteed expenditure allowance (from the lowest at $90 to the
highest at $100). An incentive-compatible menu leads the firm choosing a contract that best
reflects its expected costs. This is discussed in greater detail below.
Based on the example above, it can be seen that the actual expenditure of the firm over the
regulatory period will determine the return the firm receives. The diagram below shows the net
income for a firm that has proposed an expected expenditure of $100 for values of actual
expenditure varying from $60 to $140.
22
23
instead set a baseline of $100 and a positive income. This way if the firm’s true expected cost is actually higher than $100, then
the firm is allowed to recover more than $100 and break even.
In practice, different regulators have implemented incentive rates differently. Ofgem, for example defines the incentive rate in
terms of two components. The first component is expenditure that will be recouped within the regulatory period (fast money).
The second component is expenditure to be recovered over 20 years (slow money). Fast money carries a 100% incentive rate
as savings in fast money are fully retained by the firm. Thus, an incentive rate of 30%, with a 85/15 split between slow and fast
money, entails an incentive rate of 17.6% for slow money. That is, 0.85 × 0.176 + 0.15 × 1 = 0.30. See Section 4.1 below. may
instead set a baseline of $100 and a positive income. This way if the firm’s true expected cost is actually higher than $100, then
the firm is allowed to recover more than $100 and break even.
In practice, different regulators have implemented incentive rates differently. Ofgem, for example defines the incentive rate in
terms of two components. The first component is expenditure that will be recouped within the regulatory period (fast money).
The second component is expenditure to be recovered over 20 years (slow money). Fast money carries a 100% incentive rate
as savings in fast money are fully retained by the firm. Thus, an incentive rate of 30%, with a 85/15 split between slow and fast
money, entails an incentive rate of 17.6% for slow money. That is, 0.85 × 0.176 + 0.15 × 1 = 0.30. See Section 4.1 below.
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Figure 2 The firm’s net income as a function of actual expenditures.
Net income (for ratio = 100) ($)
$12
60
100
140
Actual expenditures
-$12
If a firm has initially proposed $100 as forecast expenditure, and over the regulatory period it
spends a total of $140, it will have a net return of 30%*($100−$140)=−$12. While the overspend
amounts to $40, this overspend will be shared between the firm ($12) and its consumers ($28)
given the incentive rate of 30 per cent. Similarly, if the firm ends up spending $110, it will receive
30%*($100−$110)=−$3.
Referring back to Table 2, with the exception of the first column, the numbers below the ‘Actual
expenditure’ line represent the net return from the incentive scheme that the firm receives for a
given combination of cost proposal and expenditure outcome. When the cost proposal is ‘100’
and the actual expenditure is ‘110’, it yields a final return of ‘−3’, as explained above. Note that
the incentives for a ratio of 100 are symmetric: the firm’s penalty for overspending $y is identical
to the reward the firm earns by underspending $y. That is, if instead, the firm had underspent
and its actual expenditure was ‘90’, it would be allowed to retain ‘3’, which is equal to 30 per
cent of the difference between 100 and 90. This number is symmetric to the case where the
firm’s actual expenditures were equal to ‘110’. Making incentives symmetric is an
implementation choice.24
24
For example, asymmetric incentives may make sense when consumers value uninterrupted services but do not want an improved
service. In this instance it may be better to penalise the firm for not achieving certain target levels but provide no reward if the
target is exceeded.
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Note that while the proposed expenditures cover the entire regulatory period, they are converted
to yearly amounts (see Section 4.1). If the firm is allowed to keep the savings only until the next
regulatory review, then it might have a reduced incentive to realise efficiencies. A possible
solution, as discussed in Section 3.4, is to provide a rollover incentive where savings are kept
for five years rather than until the next regulatory review.
Now consider how the other two columns were constructed, with a focus on only two other
possible ratios (90 and 110) (in practice ratios are defined across a much larger range). To
understand how the numbers from the two columns were generated, it is helpful to define the
net income from the menu as follows:
𝑁𝑒𝑡 𝐼𝑛𝑐𝑜𝑚e = (𝐴𝑙𝑙𝑜𝑤𝑒𝑑 𝐸𝑥𝑝𝑒𝑛𝑑𝑖𝑡𝑢𝑟𝑒 − 𝐴𝑐𝑡𝑢𝑎𝑙 𝐸𝑥𝑝𝑒𝑛𝑑𝑖𝑡𝑢𝑟𝑒 ) × 𝐼𝑛𝑐𝑒𝑛𝑡𝑖𝑣𝑒 𝑅𝑎𝑡𝑒 + 𝐴𝑑𝑑𝑖𝑡𝑖𝑜𝑛𝑎𝑙 𝐼𝑛𝑐𝑜𝑚𝑒
The allowed expenditure, incentive rate and additional income need to be defined such that the
regulated firm has the incentive to choose the ratio that best reflects its view of expected cost.
As mentioned previously, this means that the firm will maximise its expected profit by choosing
such an option. These variables (i.e. allowed expenditure, incentive rate and additional income)
will be a function of both the actual expenditures and the ratio chosen by the firm. There are a
number of mathematical ways to achieve this, but the parameters selected by Ofwat in its PR9
decision are as follows:25
For 𝑟𝑎𝑡𝑖𝑜 > 100,
𝐴𝑙𝑙𝑜𝑤𝑒𝑑 𝐸𝑥𝑝𝑒𝑛𝑑𝑖𝑡𝑢𝑟𝑒 = 75 + 0.25 × 𝑟𝑎𝑡𝑖𝑜
𝐼𝑛𝑐𝑒𝑛𝑡𝑖𝑣𝑒 𝑟𝑎𝑡𝑒 = 0.8 − 0.0005 × 𝑟𝑎𝑡𝑖𝑜
𝐴𝑑𝑑𝑖𝑡𝑖𝑜𝑛𝑎𝑙 𝐼𝑛𝑐𝑜𝑚𝑒 = −5 + 0.175 × 𝑟𝑎𝑡𝑖𝑜 − 0.00125 × 𝑟𝑎𝑡𝑖𝑜 2
For 𝑟𝑎𝑡𝑖𝑜 ≤ 100,
𝐴𝑙𝑙𝑜𝑤𝑒𝑑 𝐸𝑥𝑝𝑒𝑛𝑑𝑖𝑡𝑢𝑟𝑒 = 75 + 0.25 × 𝑟𝑎𝑡𝑖𝑜
𝐼𝑛𝑐𝑒𝑛𝑡𝑖𝑣𝑒 𝑟𝑎𝑡𝑒 = 1.05 − 0.0075 × 𝑟𝑎𝑡𝑖𝑜
𝐴𝑑𝑑𝑖𝑡𝑖𝑜𝑛𝑎𝑙 𝐼𝑛𝑐𝑜𝑚𝑒 = −10 + 0.2875 × 𝑟𝑎𝑡𝑖𝑜 − 0.001875 × 𝑟𝑎𝑡𝑖𝑜 2
Thus, when a ratio of 100 is chosen, allowed expenditure equals 100, the incentive rate is equal
to 30 per cent, and the additional income is equal to zero as indicated by the highlighted column
in Table 2. Similarly, if a ratio of 90 is chosen, allowed expenditure equals:
25
Broadly speaking, these functions have to be chosen so that the firm breaks even at the desired ratio (that is when the baseline
cost equals the firm expected cost) and the firm must strictly prefer to choose the desired ratio. This latter requirement imposes
the technical restriction that choosing the desired ratio generates the highest profits for the firm (equal to zero). This means that
the net income must achieve a maximum at the desired ratio. A strictly concave net income function with a maximum at the
desired ratio, for example, satisfies this condition. For more details see, Cambridge Economic Policy Associates Ltd (2012).
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75 + 0.25 ∗ 90 = 97.5,
the incentive rate equals:
1.05 − 0.0075 ∗ 90 = 37.5%
and the additional income equals:
−10 + 0.2875 ∗ 90 − 0.001875 ∗ 902 = 0.6875
The equivalent values when the chosen ratio is equal to 110 can be similarly computed. Net
incomes for each value of actual costs, given the choice of a ratio, are also easily calculated.
To show that this menu is incentive compatible, consider how the net income of a firm with given
actual cost changes, as depicted in Table 3 below.
Table 3 Example of net income for various levels of actual relative to allowed expenditure.
Choice of ratio
90
100
110
Net income if actual
expenditure is equal to
90
100
110
3.50
−0.25
−4.00
3.00
0.0
−3.00
2.25
−0.25
−2.75
A firm is better off by choosing a ratio that matches its expected expenditure (meaning it believes
that it is most likely to be spending y over the regulatory period). The shaded values above
indicate the best ratio choices given the actual expenditures, which yield the highest values for
each column. The last column indicates that a high cost firm has the incentive to reveal that it is
high cost. For instance, if a firm thinks that it is likely to spend 110, it is best to propose a cost
of 110, as such it will yield a net return of −2.75, which is less than −4.00 and −3.00 associated
respectively with proposing a cost allowance of 90 and 100.
In addition to incentivising ex-ante truth telling, the menu also provides ex-post incentives for
the regulated firm to be cost efficient during the control period. Referring again to Table 2,
assume that a firm chooses to propose a ratio of 100 (highlighted column). Once this has been
finalised, the firm cannot change its decision. The prices have been set such that they will allow
the firm to earn the allowed expenditure of 100 (in expectation). This means that if the firm ends
up spending 100 (and its demand forecast is realised), it will get a net return of 0 (it will still earn
the allowed return on and return of capital). However, if it manages to outperform its expectation,
meaning to spend below the allowed expenditure of 100, it will end up with a positive net return.
This means that during the regulatory period, the firm has the incentive to be cost efficient, in
order to maximise its net return given its initial proposal.
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This example illustrates that the selection of appropriate parameters satisfying incentive
compatibility is clearly an important implementation issue for menu regulation. While the
determination of the allowed revenue, incentive rate and additional income, which followed
Ofwat’s equation-driven approach, may seem complex, ad hoc and not transparent, there are a
number of techniques that can be used to generate these values.26
Another important implementation issue for menu regulation is equalising incentives across
different types of expenditures (e.g. capex versus opex) to avoid creating biases through the
regulatory design.27 Ideally, incentive regulation, either implemented through a menu, price cap
or other mechanisms, should make the cost of underperformance to the firm (and the benefit
from outperformance) independent of the firm’s choice of action (e.g. one-off opex, recurring
opex, capex, or any combination of these).
There are different approaches for equalising incentives. This can be done, for example, through
the cost recovery process introduced by Ofgem in the regulation of electricity in the UK. Ofgem
uses a single menu for opex and capex and an 85:15 split between slow and fast recovery. That
is, 85 per cent of total cost (regardless of the actual types of spending) will enter the Regulatory
Asset Base (RAB) and receive an allowed rate of return for 20 years; the remaining 15 per cent
will be expensed (treated as opex) during the regulatory review. Another alternative is to
equalise the incentive rates. This can be done either at the break-even points for capex and
opex (partial calibration) or across the entire menu (full calibration).
The issues associated with the need for providing balanced incentives are considered more
generally in Section 3.5 below and also in relation to the international experience in electricity
and water in the UK in Sections 4.1 and 4.2, respectively.
To summarise, a regulatory menu is essentially a way of expressing the relationship between
the level of expenditure, the expected return at that level of expenditure and the treatment of
out- and under-performance. While a menu provides some incentives for firms to provide
accurate business plans, it still contains limitations.
In addition to the complexities associated with ensuring that incentives are equalised so as not
to favour one type of expenditure over another, a key implementation issue is that the regulated
firm will still have the incentive to exaggerate costs as long as it has the ability to influence the
26
27
See, for example, Cambridge Economic Policy Associates Ltd (2012).
One such bias is the known as capex bias. See section 3.5 below.
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regulator’s determination of the baseline.28 This depends mainly on how the regulator
establishes the cost baseline. Moreover, the relationship between the business plans that a firm
submits for a given regulatory period and future decisions by the regulator may not be fully
understood. For example, to the extent that a more accurate forecast today might imply less
ability to extract rents in the future, firms will be less willing to make accurate forecasts. However,
while these implementation issues are substantive, price cap regulation faces even more
stringent implementation challenges and provides no clear incentives for firms to accurately
forecast costs.
3.4
Incentive strength
Standard price-cap regulation involves the regulator setting a price path (initial price and X
factor) for the firm applicable over the regulatory period. As discussed previously, the price path
is set to allow the firm to recover its estimated efficient cost, which in Australia is commonly
established using the building-block approach. This delinking of actual cost from prices creates
an incentive for the firm to become more cost efficient. Specifically, as the firm is allowed to earn
revenue over the regulatory period equal to the allowed costs determined by the regulator, it will
earn additional profits by underspending the cost allowances.
In the context of cost efficiency, the proportion of efficiency savings retained by the firm is one
way of measuring the incentive strength (or incentive rate) of a regulatory regime.29 All else
being equal, the incentive to pursue cost efficiency will be higher if the firm retains a higher
percentage of efficiency savings. Cost efficiency pertains to both capex and opex, but for
expositional convenience the examples below are based on opex only.
Under the standard price-cap regulation which incorporates periodic pricing reviews, the power
of incentives associated with opex is affected by the following factors:
(a)
the nature of the opex reduction (i.e. one-off or on-going);
(b)
the length of the regulatory period;
(c)
the prevailing cost of capital; and
(d)
how future cost allowances are determined.
28
29
The use of external benchmarking can ensure that the baseline determined by the regulator is independent of the firm’s
projections. This issue was raised by the UK Competition Commission in the review of one of Ofwat’s decisions. See Competition
Commission (2010, Annexes, p. H2).
It is worthwhile to note that a possible definition of an incentive rate of x% involves the firm retaining x% of the present value of
any cost saving it makes where the full value of the gain is its value into perpetuity. However, this is not a universal definition.
Ofgem defines the incentive rate in a different way, for example, by valuing the costs savings that are to be shared in the first
year of the next control period and not into perpetuity. In this section we try to avoid referring to incentive rate and instead refer
to incentive strength.
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(e)
A one-off reduction in opex, barring an ex-post clawback, will have an incentive strength (rate)
of 100 per cent, as the entire saving is passed through to the firm in the form of a higher profit
(before-tax basis) for that particular year. In contrast, if there is a permanent reduction in
recurring opex, the incentive strength will be determined by the prevailing cost of capital as well
as the amount of time until the next pricing review, which may then result in the efficiency gain
being passed onto customers in the form of lower prices (if this efficiency gain is observable).
(This is shown in the next section.) Note that the firm will continue benefiting from this recurring
opex underspend until the efficiency gain is recognised by the regulator.
3.4.1. Periodicity of incentives
To illustrate how the incentive strength for reducing recurrent opex changes over time within the
regulatory period, consider the following example: a firm has a weighted average cost of capital
(WACC) of six per cent (real) and its forecast annual opex in the first regulatory period is $100
million. For simplicity assume there is no output, real price or productivity growth. The regulatory
period is five years, meaning that a new cost allowance is set in year six. Assuming that there
is no information asymmetry problem, the regulator resets the opex allowance at year six based
on the firm's prevailing efficient cost.
During the first regulatory period, the firm is in a position to make a permanent opex reduction
of $10 million, where once this efficiency gain is realised the firm can produce the same level of
output with annual opex of $90 million.
Tables 4 and 5 demonstrate the impact of this permanent cost reduction when it occurs either
at the end of year one or year three. For simplicity, only 10 years of opex expenditures are
shown below.
Table 4 Impact of a permanent opex reduction in year one ($ million).
Forecast opex
Actual opex
Underspend
Discount factor
NPV of underspend
NPV of opex reduction (in
perpetuity)
Benefit retained (in %)
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Year
1
2
3
4
5
6
7
8
9
10
100 100 100 100 100
90
90
90
90
90
90
90
90
90
90
90
90
90
90
90
10
10
10
10
10
0
0
0
0
0
1
0.94 0.89 0.84 0.79 0.74 0.70 0.67 0.63 0.69
44.7
176.7
25.3
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Table 5 Impact of a permanent opex reduction in year three ($ million).
Year
1
2
3
4
5
6
7
8
9
10
Forecast opex
100 100 100 100 100
90
90
90
90
90
Actual opex
100 100 90
90
90
90
90
90
90
90
Underspend
0
0
10
10
10
0
0
0
0
0
Discount factor
1.12 1.06
1
0.94 0.89 0.84 0.79 0.74 0.70 0.67
NPV of underspend
28.3
NPV of opex reduction (in
176.7
perpetuity)
Benefit retained (in %)
16.0
Evaluated at the time it is initiated (either at the end of year one or year three), an opex saving
of $10 million in perpetuity is worth $176.7 million in NPV using a six per cent discount rate. In
this example, the proportion of the ongoing efficiency saving retained by the firm (i.e. the
incentive strength) declines from 25.3 per cent to 16.0 per cent when the cost reduction is
achieved at the end of year three rather than at the end of year one (the decline varies with the
WACC applied).
The problem of falling incentive strength is known as 'periodicity of incentives', and it is caused
by the fact that the period the firm can retain the additional income shortens as time passes.
When the efficiency gain is realised in year one, the firm earns an extra return of $10 million for
five years (year one to five), while the retention period becomes three years (year three to five)
if the opex reduction occurs in year three. There is an inverse relationship between the incentive
for cost cutting and the proximity to the start of the next control period.
A firm facing an opportunity to reduce recurring costs a year out from the next review might
decide to delay the savings so that it can benefit for the entire duration of the next period, rather
than for only 12 months. It is also unsure whether a control period of three to five years is
sufficient to incentivise the regulated firm to find it worthwhile to engage in any long-term cost
reduction.
Capex is associated with a similar issue. Note that capex is funded through a return on and of
capital, and the capex forecast is used to determine the allowed return on and return of capital
when setting regulated prices for the next period. If the regulated firm underspends this forecast
during the regulatory period, again barring any ex-post clawback, it will earn higher profits—it
will still be allowed to earn revenue over the regulatory period to cover the allowed financing
costs (the return on capital and the return of capital) based on the capex forecast, although the
firm has not spent the full amount that was allowed for capital expenditure. Similarly, if the firm
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overspends the capex forecast, it will bear the additional financing costs that have not been
included in the allowed revenue.
The firm will continue benefiting (or incurring a loss) from this capex underspend (or overspend)
until at the start of a new regulatory period where typically the actual capex is rolled into the
RAB.30 It can be seen that the incentive power associated with capex efficiency reduces over
time within the regulatory period, similar to the case of opex. A capex underspend in year one
is worth more than an equivalent amount of underspend in year five, given that in the former the
regulated firm earns additional profits for a longer period. This may result in an uneven capex
program, if the firm shifts most of its planned capex to latter stages of the regulatory period to
game the system.
In light of these issues, regulators have implemented efficiency carryover mechanisms to
provide continuous incentives for capex and opex efficiency. A carryover scheme allows the firm
to retain a fixed percentage of any cost savings, irrespective of when the efficiency gain is
initiated. This is done by adding a carryover component as one of the building blocks when
establishing the efficient cost base for the next period. This carryover amount reflects the
additional income that the firm would have retained had the cost allowance not been reset at
the end of the regulatory period.
The AER applies the Efficiency Benefit Sharing Scheme (EBSS) and Capital Expenditure
Sharing Scheme (CESS) to companies under its jurisdiction. These schemes, which separately
incentivise cost efficiency for opex and capex, are applications of carryover mechanisms. Ofwat
also has a similar scheme for opex. These schemes are discussed further in Chapters 4 and 5.
3.5
Capex bias
The periodicity of incentives—caused by the introduction of periodic reviews—is merely one of
the distortions that can exist in a regulatory framework. In practice, there are many other
potential distortions depending on various aspects of the regulatory regime.
A common incentive distortion is the capex bias. Capex bias refers to the regulated business
having an inappropriate preference for capex over opex to achieve or supply a given outcome.
30
It is possible that the regulator considers the capex overspend to be inefficient and decides not to include the full amount of the
actual capex into the RAB. In this case, the regulated firm’s loss will be more than just the financing costs it has occurred in the
regulatory period.
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For example, a regulated business might decide to spend more on asset renewals than
maintenance.
The bias can be caused by a number of factors (they are not mutually exclusive):
(a)
differing incentive rates between operating and capital expenditure; and/or
(b)
the Averch-Johnson effect (the allowed cost of capital is above the true and efficient cost
of capital).
If such bias does exist, it means the regulated business is not pursuing best solutions (the
efficient allocation of resources) for its customers. That is, they are not spending customer’s
money to deliver the best outcomes in the most efficient way.
Ofwat, for example, identified that different degrees of bias potentially exist under different
circumstances and some of this is linked to the regulatory framework.31 Pointon and Matthews
(2014) provide empirical evidence that such bias exists in the UK for the water industry. 32
Regulators have attempted to mitigate this capex bias either by equalising the efficiency
incentives for opex and capex, or setting an ex-ante ratio in relation to how expenditure is
recovered.
3.6
Partial versus comprehensive incentive schemes
Costs, quality, investment and technological choices interact in complex ways. For instance, a
higher quality service is typically more costly to produce compared with a lower quality service.
Similarly, higher capital costs may imply lower operating and maintenance costs. The difference
between an operating cost and a capital cost is not usually defined under the regulatory
arrangements by their inherent economic characteristics, but instead by accounting rules. Thus,
an independent, separate incentive scheme to reduce costs may result in lower quality, or an
isolated attempt to incentivise the firm to reduce capital costs may result in higher operating
costs or gaming of the system by expensing capital costs.
These observations explain why an important premise of the theory of incentive regulation is
that it is possible to design a comprehensive incentive regulation mechanism that takes into
account these complex interactions both in a static sense and over time. In reality, however,
designing such comprehensive schemes will place substantive information and implementation
31
32
Ofwat (2011).
Pointon and Matthews (2014).
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burdens on the regulator. Partial mechanisms are typically combined in an overall incentive
regulation framework. Therefore, it is common (or even prevalent) in Australia for the rules
governing operating and capital costs to be different, resulting in different power of the incentive
schemes applicable to operating and capital costs as, for example, in the case of the efficient
carryover mechanism described in Section 3.4 above. In a similar vein, quality regulation usually
takes the form of an add-on to a price cap, with the firms being either penalised or allowed
additional returns if given quality targets are missed or met.
Many regulators recognise that both capex bias and quality issues can arise and so set up some
preventative measures to mitigate these two effects. The approach by the Australian Energy
Regulator to mitigate capex bias and quality concerns is reviewed in Chapter 5.
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4.
INTERNATIONAL EXPERIENCE WITH INCENTIVE REGULATION
This chapter focuses on the electricity, water and rail industries in the UK where incentive
regulation has been widely used. The emphasis is on how the regulators have resolved the
implementation issues identified above.
4.1
Energy sector in the UK
There are seven firms controlling 14 electric distribution networks in the UK. These firms,
referred to as Regional Electricity Companies (RECs), provide electricity distribution services in
specific franchise areas.33 Ofgem regulates the sector.
As is the case in Australia, Ofgem’s regulatory mechanism encompasses setting the maximum
revenue that the regulated firm is allowed to earn during the five-year regulatory period, an initial
price (P0), an exogenous input price index (Retail Price Index or RPI) for adjusting price levels
for inflation, and a productivity factor ‘X’ which further adjusts prices over time. However, as is
typically the case in Australia, the X factor is a price smoothing factor rather than an efficiency
factor, since efficient costs are already estimated in the building blocks.
Determining the value of maximum revenue is based on an evaluation of each firm’s operating
costs, the firm’s current capital stock (the regulatory asset base) adjusted for depreciation and
inflation since the previous price review, forecasts of future capital expenditures, depreciation of
investment expected to take place in the coming regulatory period, determination of allowable
costs of debt and equity, assumptions about the firm’s debt to equity ratio, tax allowances and
other variables.
The allowed revenue for the firm over the five-year period is then the sum of allowed operating
costs and allowed capital costs (depreciation and after-tax return on investment) determined in
each year. The actual regulatory process is designed to determine what the forward-looking
efficient costs of providing the service are. This includes submissions by the regulated firm, a
draft decision, consultation and a final decision. A particular innovation by UK regulators is to
use the menu approach as discussed in general terms in Section 3.3 (and addressed further
below) to incentivise the regulated firm to present a business plan with costs that are as close
as possible to the true efficient costs of providing the service.
33
As in Australia, electricity retail and distribution are also functionally separate in the UK.
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Once the baseline is chosen, the values of P0 and X are determined so that the present
discounted value of revenues over the five-year period is equal to the present discounted value
of the expected total operating and capital-related charges that have been determined for each
distribution company. That is, as in Australia, the values of X and P0 are determined to allow the
firm to recover the present value of the efficient costs of providing the service taking into account
relevant price inflation. There is an implicit relationship between P0 and X. The higher is the P0,
the higher the X and vice-versa, so that over the five years the firm’s revenue is capped at the
MAR. In earlier regulatory decisions, a high P0, implying jumps in existing electricity distribution
charges, was chosen to allow the regulated firms some time to adjust to achieve required
efficiencies. In more recent decisions, and this is also true in Australia, the X factor has been
used mostly as a smoothing factor so that regulated prices do not change substantially during
the regulatory period and between regulatory reviews.
The subsection below explores how these principles were applied in the fifth regulatory review
(DPCR5) covering the 2010–15 period. Particular emphasis will be placed on a review of the
range of incentive schemes introduced in DPCR5, some of which may be relevant for some of
the industries regulated by the QCA.34
4.1.1. General information
Ofgem allowed revenues of around £22 billion for the 2010–15 regulatory period and £14 billion
worth of expenditures on the network. Prices would increase on average by 5.6 per cent per
annum varying from −4.3 per cent to 11.1 per cent across the different distribution networks.
The new charges are intended to better reflect the costs of serving distinct customers and reward
consumers who make less use of the network, by either installing generation or becoming more
energy efficient. Retailers will decide on how to reflect these charges in their consumers’ bills.
Revenue increases (and, therefore, increases in charges) were kept as a constant percentage
per annum for each distributor throughout the regulatory period. This confirms the abandonment
of the glide path approach—characterised by an initial high P0, and high X so that prices initially
rise rapidly then rise at much lower rates—that applied for the first three price reviews. As
indicated above, the impact of DPCR5 on a customer’s bill will depend on their particular
electricity tariff. To keep this in perspective, distribution charges account for up to 15 per cent of
a domestic consumer’s electricity bill and approximately 20 per cent of a business customer’s
bill.
34
This discussion is based on Office of Gas and Electricity Markets (OFGEM) (2009a).
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4.1.2. Ofgem’s approach to incentive regulation
In general terms, Ofgem’s approach consisted of first determining the baseline cost for each
firm: the regulator’s view of the efficient cost of providing the regulated service over the control
period. A range of incentive schemes was then designed to achieve goals varying from quality
of service to customer service and the environment. A key incentive scheme was a totex (opex
plus capex) menu specifying the incentive rates, allowed revenues and additional payments that
the firm faced for different ratios between the business plan submitted by the firm and their
actual realised costs over the regulatory period. Once the menu is specified, the allowed costs
for the five-year period are then transformed into annual amounts (for example, by dividing by
five and adjusting for inflation). Moreover, roughly speaking the menu only covered expenditures
that were actually under the control of the firm. Expenditures outside of the firm’s control are
passed through to customers automatically.
The incentive rate, which varies with the ratio of business plans submitted to their actual costs,
determines the fraction of the underspend or overspend that the regulated firm is allowed to
retain.35 For example, consider an incentive rate of 30 per cent and suppose the firm has
underspent by $100. The firm will be allowed to retain $30 from the year the underspend took
place. Similarly, if the firm has overspent by $100, it is allowed to recover an additional $30 from
consumers in future years. 36
The Ofgem menu was designed to achieve three goals. The first was to give firms the incentives
to submit business plans that actually reflected their true efficient costs of providing the service.
The second was to incentivise the firm to be cost-efficient during the regulatory period. The third
was to equalise incentives between capex and opex. The first aim was achieved by designing
an incentive-compatible menu (see Section 3.3.2). The second aim was achieved by setting the
menu parameters such that the firm will earn a higher return by outperforming its expected cost.
The third aim was achieved by splitting allowed total costs into two groups: 85 per cent of allowed
costs will enter into the Regulated Asset Base and, therefore, be recovered over the life of the
asset set at 20 years (described as ‘slow pot’), and the remaining 15 per cent will be fully
expensed and funded in the year of expenditure (described as ‘fast pot’). This split is
35
36
This determines the incentive strength and it is often a choice between allowing the firm to retain the underspend only until the
next regulatory review or for a fixed period (typically five years). See discussion in Section 3.4.
In practice, as explained further explain below, Ofgem defines the incentive rate in terms of two components. The first component
is expenditure that will be recouped within the regulatory period (fast money). The second component is expenditure to be
recovered over 20 years (slow money). Fast money carries a 100% incentive rate as savings in fast money are fully retained by
the firm. Thus, an incentive rate of 30%, with an 85/15 split between slow and fast money, entails an incentive rate of 17.6% for
slow money. (That is, 0.85 × 0.176 + 0.15 × 1 = 0.30.)
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independent of the actual choice of capex and opex by the firm; in this way, behaviour is not
distorted.37
The diagram below indicates how the different components of Ofgem’s approach fit together.
Each of these will be discussed below in detail.
Figure 1 Ofgem's approach to menu regulation.
Determining the
baseline: cost
assessment
Introducing incentive
schemes—including
expenditures to be
covered and behaviour to
be penalised/rewarded
Equalising
incentives to
avoid distorting
behaviour
Designing the totex menu
including determining
additional revenue,
incentive rates and
strength
4.1.3. Determining the cost baseline: cost assessment
Ofgem relied on a review of company business plans and its own modelling and benchmarking,
with support from consultants to determine the baseline cost estimates. The process included
rounds of questions on company plans, and a range of benchmarking techniques, including time
series regression, unit cost analysis and individual review of projects over £15m.38 The
distribution network operators DNOs provided initial indicative forecasts for DPCR5 in August
2008, and formal forecasts in February 2009, which were updated ahead of Initial Proposals in
June 2009, and updated again prior to the submission of their Final Proposals in December
2009.
37
38
The split 85/15 is Ofgem’s estimate of the proportion of the respective costs that would have been funded under the previous
determination arrangements. See Ofgem (2009), pp. 28-29. This approach, combined with a set life of 20 years for expenditures
recovered through slow money, creates a disconnect between the firm’s asset register and the RAB. The financiability work done
for the PIC-X@20 project (see Section 4.1.8 below) suggested that the Ofgem might reconsider these percentages and instead
the split would still be determined ex-ante but based on the amount of capex-like costs submitted in a company’s business plan.
See Ofgem (2010a).
Ofgem applied Ordinary Least Squares (regression) techniques for benchmarking of operating expenditures. In addition, DEA
and Stochastic Frontier Analysis (SFA) were used as an alternative for the purpose of cross checking. Regression analysis and
DEA were explained in Section 3.3 and, in particular, Box 2. The SFA approach to the analysis of efficiency is based on specific
assumptions on the structure of technology and, unlike the deterministic frontier approach (regression analysis), allows accounting
for exogenous shocks beyond the control of the firm as it encompasses both noise and inefficiency into the model specification.
For a more detailed review of Ofgem’s approach, see Ofgem (2009b), Electricity Distribution Price Control Review, Initial
Proposals - Allowed Revenue - Cost Assessment, especially Appendix 9.
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Costs were analysed at different levels of disaggregation, but Ofgem also carried out top-down
regression analysis on total operational activities, defining as the benchmark for opex the top
quartile in terms of efficiency for the regulated firms.39 For capex, asset replacement was
considered using historic profiles, comparative distribution networks data and consideration of
the age profile of assets. Asset replacement unit costs were benchmarked at the median level
in recognition of data imperfections. Network investment was reviewed using Ofgem’s network
reinforcement model.
Turning to the determination of efficient costs, and using the terminology of Section 3.1, the
proportion of disallowed claims (PDC) was eight per cent with substantial variation between
distributors. While the PDC for the two most efficient companies (WPD and SSE) was zero
(meaning the allowed expenditure defined in the baseline matched the expenditure proposed
by the firm), the PDC for the least efficient firm (EDF) was 14 per cent. The bulk of the PDC was
due to reductions in network investment expenditure associated with asset replacement unit
costs and general reinforcements, but also significant reductions in the estimates of real price
effects.40 Given the importance of fixed costs (capex), the determination of the cost of capital
was an important part of DCPR5. The real vanilla WACC was set at 4.0 per cent post-tax. The
cost of debt was set at 3.6 per cent and the gearing ratio at 65 per cent. The baseline return on
equity was set at 6.7 per cent post-tax but it is subject to an efficiency scheme (the regulatory
menu), as will be described in Subsection 4.1.5, that could result in returns as high as 13 per
cent or as low as three per cent.
Having defined the baseline, the regulatory menu is designed to ensure that firms have the
incentive to submit a business plan that is closer to their actual (or at the stage of submission,
expected) costs. Nevertheless, the firms still have an incentive to try to convince the regulator
to set higher baseline costs. This is because a higher baseline will imply, ceteris paribus, higher
profits for the regulated firm. This is the reason why the Competition Commission (2010) has
emphasised the need to make the determination of the baseline independent from the firm’s
plans.
39
The regression model specified normalised operating costs as the dependent variable and a composite scale independent variable
(weighted mean of customer numbers, network length and units of energy delivered). The normalisation involved making
adjustments for uncontrollable cost drivers. In addition, time dummies were used to capture movement in the data between years,
and a range of other variables including MEAV (Median Equivalent Asset Value) and some measures of direct activities for
assessing costs, such as using fault numbers for fault costs, and using asset numbers for asset inspection costs. The regression
was undertaken for the pooled sample and then estimates of the independent variables for regulated firms were used to predict
the normalised costs. It appears that the difference between actual and normalised costs was then used to determine the efficient
benchmark of the top quartile, although this is not clear from the documentation. See Ofgem (2009a).
40
Real price effects refer to increases in prices over and above increases in the general price index (CPI). This may happen, for
example, if labour or copper or steel costs increase above the CPI.
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As a matter of practical implementation, however, it is unlikely that the baselines will be
determined exclusively through a benchmark exercise, at least for electricity distribution. The
reason is the difficulty in defining appropriate comparators and controlling for differences, which
can only be done imperfectly.
4.1.4. Incentive mechanisms: an overview
As with previous pricing reviews, a key objective of DCPR5 is for Ofgem to discharge its statutory
duties having regard to best regulatory practice. However, three new objectives stand out in
DCPR5. These include: to place incentives on distributors to control their impact on the
environment (directly or indirectly); to better handle worse served customers and improve
communications with consumers when there are power cuts or when they are seeking a
connection to the network; and to ensure efficient investment in the network given the need to
replace ageing assets.
DCPR5 included a range of incentives and mechanisms to encourage particular behaviours of
distributors in relation to the three key priorities: the environment, customer service and quality
of the network. These incentive mechanisms were calibrated to reflect a range of factors
including customer’s willingness to pay for improved services, and the cost of carbon. For the
first time, agreed outputs were established for each distributor to deliver in return for the
revenues they are allowed to collect from customers.41 This was to ensure that greater returns
in this regulatory period are not obtained via allowing the network to deteriorate, which would
result in higher costs and prices in the future.
Penalties for not achieving particular levels of service quality (reliability and customer
satisfaction) were also established. In addition, a £500m Low Carbon Network Fund was
introduced to stimulate culture change, innovation and trialling of new technologies, and the
commercial and operating arrangements that the distributors would need to deliver a low or zero
carbon electricity sector. Table 6 summarises the mechanisms available, their materiality and
the caps and collars on the incentive payments/penalties (if any). Many of the incentive
mechanisms are soft, such as requirements for information disclosure, with no attached values
or explicit incentives.
The menu approach is embedded in the Information Quality Incentive (IQI), which will be
described in Section 4.1.6. The next subsection describes the process through which a balanced
41
This includes a load index (related to general reinforcement expenditure), a health index (related to asset replacement
expenditure), and fault rates. These output measures will need to be achieved by the end of 2015. If a distributor can demonstrate
it has delivered its outputs, no further action will be taken. Otherwise, the distributor would not be able to retain the full amount of
the underspend achieved over the period.
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set of incentives was provided so that performance on one dimension did not occur at the
expense of performance on other dimensions.
Table 6 Incentive mechanisms adopted by Ofgem for DNOs.
Mechanisms
Environment
Low Carbon Networks Fund
Mandatory information provision - Distributed generation
(DG) incentive
Hybrid mechanism: pass through with incentive for general
network reinforcement and one-off high value connections
(for example, to accommodate the take up of electric
vehicles).
Revised incentive scheme to minimise network losses based
on an output mechanism
Annual reporting and comparative performance league tables
Allowance for undergrounding in areas of outstanding natural
beauty
Customer satisfaction
Broad measure: customer satisfaction, complaint handling
and stakeholder engagement
Telephone incentive (based on satisfaction scores from a
survey of consumers who contacted the distributor by phone)
Allow margin to be earned in new competitive connections
Overarching licence condition for new competitive
connections
Customer service reward scheme
Worst service reward scheme: cap of £1,000 per consumer
to be spent to improve interruptions to this class of customers
Interruptions incentive scheme
Networks
Information Quality Incentive (IQI): Equalisation of incentives
for operating and capital costs: to overcome existing
incentives to solve network performance or constraint
problems via further investment in the network rather than
through reduced load via DG contracting or Demand Side
Management.42 These are discussed below
Continuation of innovation funding incentive mechanism;
distributors are allowed to spend up to 0.5% of MAR on R&D
Allowance for workforce renewal
Value
at
stake
(£)
Regulated rate of
return exposure
(base points)
Upside
Downside
500m
97
97
42
42
1
7
0
100
uncapped
139
61m
40m
5m
42m
100m
213m
Source: Ofgem (2009)
4.1.5. Equalising incentives
Ofgem’s experience in the previous regulatory review (DPCR4) suggested that the different
incentives for capex and opex might have distorted the regulated firms’ decisions to favour
42
A price cap regime rewards firms that distribute more electricity and so often a cheaper energy efficiency alternative to reduce
network constraint or to improve network performance, such as DG procurement or DSM, is rejected in favour of more expensive
further investment in transformers and cables. See, for example, J. Dutra, F. Menezes and X. Zheng (2013).
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capex over opex (capex bias) or to classify opex as capex (Ofgem 2009, p. 107). The solution
adopted by Ofgem in its DPCR5 was to pre-set the split between expenditures irrespective of
spending category. Under the IQI, firms recover 15 per cent of their allowed expenditures as
fast pot money (fully expensed) while the rest will be added to the RAB (amortised over 20
years) irrespective of what their business plans or actual expenses are.43 This approach entails
equalising incentives via a cost recovery mechanism and can be contrasted to possible
alternative approaches where the incentive rates for opex and capex menus are equalised either
at the break-even point (that is, when the firm’s business plan coincides with the baseline
determined by the regulator) or across the entire menu.
To see how the overall incentive rate is applied to the two different types of pots, focus on the
incentive rate faced by a firm that chooses a ratio of 100 in the totex menu reproduced in Table
9. The firm faces an incentive rate of 50 per cent. The approach adopted entails a 100 per cent
incentive rate on the 15 per cent assigned as fast pot money (fully expensed each period). Then
to determine the incentive rate that will apply to the slow pot, in order for the total expenditure
to be subject to a 50 per cent incentive rate, the following equation needs to be solved:
0.5 = 0.15 × (1 + 𝑦) × .85
Where 𝑦 is the incentive rate that applies to the slow pot, which accounts for 85 per cent of
allowed expenditures. Thus, solving the equation for 𝑦 yields 𝑦 = 0.4117 and, therefore, the
implicit capex incentive strength is 41.17 per cent.
In summary, this approach ensures that a firm’s choice on spending opex and capex is
independent of the revenue that it is allowed to recover. This both solves the capex bias and
eliminates any incentives for firms to misclassify opex as capex.
43
This 85:15 split is based on Ofgem’s estimate of the proportion of costs that would have been funded as capex and opex
respectively, under the previous determination arrangements. See Ofgem (2009), Electricity Distribution Price Control Review
Final Proposals, pp. 28-29.
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4.1.6. The totex menu: ensuring incentive compatibility and equalising incentives
The objective of the IQI is to incentivise the provision of good quality information by the
distributors when they make their submission of costs to be claimed. The IQI is a menu that
applies to all expenditures (opex and capex). It works, as described in Section 3.3, by providing
firms with incentives and penalties that are related to the ratio of the cost claims (forecasts) by
the firms and the baseline calculated by the regulator. Table 7 describes the menu, including
the ratios, allowed expenditures, incentive rates, and additional income.
There are some costs, broadly speaking those that are not under the control of the firm, that are
not covered by the IQI but are still subject to equalisation. An allowance for these costs will
either be set at the time of the next review or could trigger a reopener (or cost pass-through).
This allowance is split between a slow and a fast pot using the same percentages as in the IQI
mechanism (85:15).
The numbers in shaded cells indicate the net income for a firm that has chosen a ratio of y and
for whom actual (or expected at the time of their choice) expenditures are equal to y. To check
that the menu is incentive compatible it suffices to check that the highlighted number is the
highest number in that particular row. As an illustration, a firm that expects the expenditure to
be 105 is worse off than when choosing a ratio that differs from 105.44
44
Note that the 100 ratio is not a break-even point in the menu below as there is an additional income of 2.5 when the firm’s actual
costs match the ratio of 100. This does not affect the incentive compatibility of the menu. Instead, it simply indicates that the
incentive strength at 100 is slightly over 50 per cent.
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Table 7 Information quality incentive (IQI).
Ratio of
forecast to
baseline
95
100
105
110
115
120
125
130
135
140
Incentive
rate
0.53
0.50
0.48
0.45
0.43
0.40
0.38
0.35
0.33
0.30
Allowed
expenditure
98.75
100.00
101.25
102.50
103.75
105.00
106.25
107.50
108.75
110.00
Additional
income
3.09
2.50
1.84
1.13
0.34
- 0.50
- 1.41
- 2.38
- 3.41
- 4.50
Actual expenditure
90
7.69
7.50
7.19
6.75
6.19
5.50
4.69
3.75
2.69
1.50
95
5.06
5.00
4.81
4.50
4.06
3.50
2.81
2.00
1.06
0.00
100
2.44
2.50
2.44
2.25
1.94
1.50
0.94
0.25
−0.56
−1.50
105
−0.19
0.00
0.06
0.00
−0.19
−0.50
−0.94
−1.50
−2.19
−3.00
110
−2.81
−2.50
−2.31
−2.25
−2.31
−2.50
−2.81
−3.25
−3.81
−4.50
115
−5.44
−5.00
−4.69
−4.50
−4.44
−4.50
−4.69
−5.00
−5.44
−6.00
120
−8.06
−7.50
−7.06
−6.75
−6.56
−6.50
−6.56
−6.75
−7.06
−7.50
125
−10.69
−10.00
−9.44
−9.00
−8.69
−8.50
−8.44
−8.50
−8.69
−9.00
130
−13.31
−12.50
−11.81
−11.25
−10.81
−10.50
−10.31
−10.25
−10.31
−10.50
135
−15.94
−15.00
−14.19
−13.50
−12.94
−12.50
−12.19
−12.00
−11.94
−12.00
140
−18.56
−17.50
−16.56
−15.75
−15.06
−14.50
−14.06
−13.75
−13.56
−13.50
145
−21.19
−20.00
−18.94
−18.00
−17.19
−16.50
−15.94
−15.50
−15.19
−15.00
Source: Ofgem (2009, p. 111)
To recap, for each of the cost elements subject to the IQI, Ofgem has produced a baseline and
the distributors (DNOs) have submitted a forecast. These are aggregated across the DPCR5
period and a ratio of these two elements is taken to provide the dno:Ofgem ratio. The
disaggregated costs no longer matter for determining the allowed costs.
Allowed expenditures are split into a fast pot and a slow pot in a ratio of 15:85. The fast pot
receives a 100 per cent incentive, 15 per cent of the expenditure allowance and all of the
additional income. The slow pot is allocated an incentive strength such that the weighted
average between the two pots is equal to the IQI incentive strength, and the remaining 85 per
cent of the expenditure allowance. This has been explained in Section 4.1.5 above.
The fast and slow pots, along with the additional income, are allocated across the five years,
according to the profiles submitted by the regulated business.
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Actual expenditures in the fast pot are fully exposed to market risk so that there are no
mechanisms to compensate the distributor for any over- or under-recovery. The distributor
receives the additional income through the fast pot. In contrast, actual expenditure in the slow
pot is subject to the incentive strength. Thus, the distributor is able to keep the allowed
percentage of savings for a period of five years through an efficiency carryover mechanism
(denoted by rollover incentive in the DCPR5).45
4.1.7. Preliminary assessment of the menu approach
Ofgem (2012) provides some evidence on whether the menu approach has been effective in
ensuring that regulated firms submit business plans that are closer to their actual costs. The
most recent information that is publicly available is shown here.46 On a cumulative basis, in
DPCR4, in total there was a £514m underspend (6.7% of total) for capex and a £322m
underspend (9.1%) for opex. For the first year of DPCR5 (2010-11), DNOs underspent against
the capex allowance by a total of £359.0 million (27 per cent) and underspent against the opex
allowance by £77.6 million (five per cent).
Although this indicates that the menu approach might not have addressed the issue of
asymmetric information in determining the baseline, it would be premature to arrive at this
conclusion, as timing may be an issue, and actual expenditures may move closer to business
plan expenditures at a later stage. Similarly, underspend could be a result of the firm’s costcutting initiatives over the regulatory period, rather than being an issue of adverse selection.
The key issue, however, is how the menu approach compares with price-cap regulation in terms
of providing incentives for truthful revelation of the baseline costs (that is, for the submission of
business plans that are closer to true expected costs as perceived by the firm at the time of its
submission). It is almost certain that a well formulated menu approach offers better incentives
for more accurate submission of business plans than a price cap regime. There are two reasons
for this. First, under a standard price-cap regime (where there is no ex-post clawback) firms
have an even bigger incentive, vis-à-vis a menu approach, to convince the regulator that the
baseline costs are high. This is because regulated firms can keep 100 per cent of their
underspend until the next regulatory review (that is, the benefits from exaggerating baseline
costs are higher under price cap regulation). In addition, given that there is no mechanism to
recoup losses under a price cap regime, while losses are shared under a menu approach, the
negative financial consequences of proposing baseline costs that are too low are substantially
45
46
A working example can be found at Ofgem (2009).
OFGEM (2012).
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higher under price cap relative to menu regulation. Considering these two effects together, the
implication is that firms are more likely to propose higher baseline costs (that is, a bigger wedge
between proposed baseline costs and expected costs) under price cap regulation than under
menu regulation.
4.1.8. The future of electricity distribution regulation in the UK
Finally, it is worth mentioning that the new regulatory regime will be applied from 2015 onwards.
In recognition of the need to attract significant investment to adapt and change the existing
networks to accommodate a structural shift in the nature of the industry, Ofgem introduced the
“RIIO” (Revenue=Incentives+Innovation+Outputs) model as part of its RPI-X@20 project.47 This
structural shift includes the connection of more home-based micro generation and small-scale
renewables to the low voltage distribution network, the extension of the transmission grid to
connect renewable generation in remote areas, and the management of an increasing amount
of intermittent generation capacity.
RIIO, which will be implemented for the next regulatory review, exhibits a number of novel
features. It sets longer, eight-year price controls and offers incentives focused on achieving
particular outcomes including customer satisfaction, reliability and availability, safe networks
services, connection terms, environmental impact, and certain social obligations. At the same
time, RIIO retains several features of the existing regime, such as upfront price control so firms
know the revenue they are allowed to earn, the adjustment for inflation and a return on the
regulatory asset base. Some key innovations include the potential early completion of price
control reviews for companies that innovate and deliver appropriate levels of service, and higher
returns for companies that deliver at lower costs. Firms that do not perform well will face more
intrusive regulation and lower returns.
4.2
Water sector in the UK
Ofwat is the economic regulator of the water and sewerage industry in England and Wales. The
industry comprises 32 regulated companies—some companies are water-only businesses while
others provide both water and sewerage services. Most customers (except large-use customers)
are served by monopoly suppliers.
Due to limited competition in the industry, Ofwat sets price limits for companies. Ofwat carries
out a price review every five years. The most recent review (PR09) was finalised in November
47
See Office of Gas and Electricity Markets (OFGEM) (2010a).
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2009, setting price limits for 10 water and sewerage companies and 12 water-only companies,
for the period between 2010 and 2015.
Ofwat's incentive framework based on the regulator's final determinations in PR09 is considered
in this section. Specifically, the focus is on efficiency incentives for capex and opex, as well as
performance incentives to improve service quality. Given that the next price review is underway
as of writing, this section also discusses Ofwat's planned approach as indicated in the regulator's
methodology paper released in 2013.
4.2.1. Capex incentives
Prior to PR09, Ofwat applied efficiency carry-over mechanisms for both capex and opex.
Companies were allowed to retain outperformance (against approved capex and opex
allowances) for at least five years before being passed to customers. In PR09, Ofwat
incorporated a menu-based approach for setting capex. This is referred to as the 'Capex
Incentive Scheme' (CIS).
In Chapter 3, it is explained that a well-designed regulatory menu incentivises the regulated
business: (1) to submit cost forecasts that best reflect its views of cost requirements; and (2) to
deliver regulated services efficiently (i.e. at the lowest costs possible) once the allowances have
been fixed. Indeed, these reasons were cited by Ofwat (2008) to justify the introduction of the
CIS. Ofwat (2008) pointed out that it would first apply the menu approach to capex because it
felt that this was where the information asymmetry problem was most prevalent. Large capex
tends to be non-recurrent and lumpy, which means that historical costs provide less useful
information for the regulator.
The CIS process adopted by Ofwat for PR09 was as follows:
(a)
regulated companies submitted their draft business plans;
(b)
Ofwat reviewed the draft business plans and subsequently published the CIS matrix and
draft capex baselines;
(c)
regulated companies submitted their final business plans; and
(d)
Ofwat reviewed the final business plans and allowed justified changes to the capex
baselines. It then published the draft determinations which included revised baselines.
Each company's position in the CIS matrix was determined by comparing their final
business plans to the revised baselines. Ofwat did not allow wholesale changes or
rebidding (e.g. companies submitting new capex plans and forecasts) between the draft
and final determinations.
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CEPA (2012) raises the point that in practice the menu system might be less effective in
eliminating the incentive for companies to inflate cost proposals due to the iterative nature of
regulatory process such as the one described above. As observed by CEPA, in PR09 most
companies that had initially proposed large capex forecasts subsequently adjusted their
estimates downwards through a number of iterations (from draft to final business plans). This
mirrors a negotiation between the regulator and companies, where both parties started at
extreme ends of forecasts, and eventually converged to an agreed mid-point (CEPA 2012).
According to CEPA, the truth-telling incentive from menu regulation is only effective if the
regulator's baselines are largely (if not completely) independent of the company estimates,
which is unlikely in practice.
Capex baseline
Recall that one of the key elements of a regulatory menu is the cost baseline, which represents
the regulator's view of cost requirement. The cost baseline is embedded in the menu such that
most numbers (except the sharing ratios) in a typical menu are percentages of the cost baseline.
The ratio of the regulated firm's cost forecast to the regulator's baseline determines, inter alia,
the incentive rate (i.e. the sharing ratio), allowed expenditure and additional income allocated to
such a business.
Ofwat's approach to setting capex baselines for companies in PR09 was not drastically different
from its previous approach (prior to the introduction of the CIS) to establishing ex-ante capex
allowances. Ofwat's primary sources of information continued to be company cost base
submissions and draft and final business plans. In establishing these baselines, the regulator
scrutinised company submissions, applied relevant tests (e.g. cost-benefit analysis and
benchmarking), and made appropriate adjustments to company forecasts.
In previous price reviews Ofwat set capex allowances by estimating the efficient capex for a
business close to the efficiency frontier. One important change in PR09 is that Ofwat (2009) set
capex baselines based on 'central' efficiency benchmarks: that is, the regulator considered the
capex requirement of an average-performing company. Thus, Ofwat (2008) had expected
company cost submissions to be distributed on either side of the regulator's capex baselines
prior to its draft decisions. The new approach also differs from Ofgem's approach which sets the
cost baselines by using 'frontier' efficiency benchmarks for both capex and opex (CEPA 2009).
In PR09 Ofwat (2009) made adjustments for two efficiency improvement factors when
determining company cost allowances. These factors were intended to estimate how real costs
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and productivity would change over the next control period and to reflect them in the cost
allowances. For capex, these adjustments were embedded in the CIS baselines. Efficiency
factors can be interpreted as challenges set by Ofwat—companies would earn higher profits if
they outperformed efficiency improvement targets.
The first efficiency adjustment reflected expected economy-wide efficiency improvements
common to all firms. The second adjustment factor was firm specific—companies
underperforming relative to the benchmark firm (in this case a 'median' company) were
challenged to catch up. At the industry level (covering both water-only and water and sewerage
companies), a total reduction of £363 million from Ofwat's capex baselines was made, which
amounted to approximately 1.6 per cent of the pre-adjusted total. Ofwat (2009) pointed out that
the reduction would have been much higher if its previous 'frontier' approach had been applied.
CIS matrix
Table 10 illustrates the final CIS matrix used by Ofwat in PR09. Refer to Section 3.3.2 for
detailed explanation of how a regulatory menu operates.
Note that the CIS ratios (the first row) are ratios of the company's capex forecast to Ofwat's view
of required capex for such a company. For example, a CIS ratio of 120 would imply that the
company's capex forecast is 20 per cent higher than Ofwat's capex baseline. The sharing ratio
(the second row) determines the percentage of capex over- or underspends that would be
retained or borne by the regulated company. A company with a lower CIS ratio (hence a lower
capex allowance) would have a higher sharing ratio, and vice versa. This is consistent with the
reasoning that companies with smaller allowances have less room for outperformance relative
to those with larger allowances, hence should be allowed to retain a bigger percentage of any
underspend that they achieve.
As seen in Table 8, the break-even point of this menu is at the CIS ratio of 100 (see shaded
cell). That is, if a company had submitted a capex forecast equivalent to the regulator's baseline
(hence the CIS ratio is 100), and subsequently spent the full amount of its capex forecast, it
would just earn the allowed rate of return, with no additional income from the CIS. This
contrasted with Ofgem's approach of setting a break-even point above the CIS ratio of 100 (see
Table 9 in Subsection 4.1.6). In that case, a company would earn more than the allowed rate of
return if it had bid the regulator's baseline and subsequently spent that amount.
CEPA (2012) explains that the break-even point is related to the form of cost assessment
undertaken for establishing the baseline. If the regulator uses the frontier-efficiency approach
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(Ofgem's approach), the baseline will reflect the expected cost for a company operating at the
efficiency frontier. As not all companies will be operating at such levels in the short run, it can
be considered appropriate to set a break-even point above 100 to reflect this: companies that
end up spending more than the regulator's baseline but below the break-even point will not be
penalised. Likewise, if the baseline is derived using 'central' efficiency benchmarks (Ofwat's
approach), the baseline will reflect the average cost of delivery—it will be appropriate to set the
break-even point at the baseline.
Table 8 PR09 CIS matrix.
CIS ratio
80
85
90
95
100
105
110
115
120
130
Sharing
ratio (%)
45.00
41.25
37.50
33.75
30.00
27.50
25.00
22.50
20.00
15.00
Allowed
expenditu
re
95.00
96.25
97.50
98.75
100.0
0
101.2
5
102.5
0
103.7
5
105.0
0
107.5
Additional
income
1.00
0.89
0.69
0.39
0.00
−0.41
−0.88
−1.41
−2.00
−3.38
Actual expenditure
70
12.25
11.72
11.00
10.09
9.00
8.19
7.25
6.19
5.00
2.25
80
7.75
7.59
7.25
6.72
6.00
5.44
4.75
3.94
3.00
0.75
85
5.50
5.53
5.38
5.03
4.50
4.06
3.50
2.81
2.00
0.00
90
3.25
3.47
3.50
3.34
3.00
2.69
2.25
1.69
1.00
-0.75
95
1.00
1.41
1.63
1.66
1.50
1.31
1.00
0.56
0.00
−1.50
100
−1.25
−0.66
−0.25
−0.03
−0.00
−0.06
−0.25
−0.56
−1.00
−2.25
105
−3.50
−2.72
−2.13
−1.72
−1.50
−1.44
−1.50
−1.69
−2.00
−3.00
110
−5.75
−4.78
−4.00
−3.41
−3.00
−2.81
−2.75
−2.81
−3.00
−3.75
115
−8.00
−6.84
−5.88
−5.09
−4.50
−4.19
−4.00
−3.94
-4.00
−4.50
120
−10.2
5
−8.91
−7.75
−6.78
−6.00
−5.56
−5.25
−5.06
−5.00
−5.25
130
−14.7
5
−13.0
3
−11.5
0
−10.1
6
−9.00
−8.31
−7.75
−7.31
−7.00
-6.75
140
−19.2
5
−17.1
6
−15.2
5
−13.5
3
−12.0
0
−11.0
6
10.25
−9.56
−9.00
−8.25
Source: Ofwat (2009)
Under the CIS, both over- and underspends against the capex allowances would be treated
symmetrically. This means that companies would pay or receive the same percentage
(determined by the sharing ratio) of the difference between their respective allowed and actual
capex. In previous reviews, any capex overspends would have been fully borne by companies
while outperformance against the regulator's allowances would have been retained for a limited
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period. Interestingly, in the PR09 final determinations, Ofwat (2009) reduced the allowed cost of
capital on the ground that the aforementioned symmetrical approach would reduce risks faced
by regulated companies. Part of the risk was shifted to customers as they would now bear part
of the capex overspend.
In PR09, the weighted average CIS ratios (against Ofwat's capex baselines in final
determinations) at industry level were 109 for the water service and 105 for sewerage service.
This means that on average company final business plan capex forecasts were higher than
Ofwat's estimates (Ofwat 2009). Furthermore, three companies had CIS ratios higher than 130.
This is despite Ofwat setting these baselines based on the efficiency of an average-performing
benchmark firm.
CEPA (2009) provides the following possible explanations for high CIS ratios for some
companies in PR09:
(a)
Ofwat's capex baselines might not be representative. Ofwat still faced issues of
asymmetric and incomplete information when setting capex baselines;
(b)
companies might be unfamiliar with how the CIS would operate, thus their decision making
was distorted; or
(c)
there might be other existing incentives (other than profit) to inflate capex forecasts. For
instance, a company might simply prefer to outperform a slightly higher allowance than to
underperform against a lower allowance, even though proposing a lower capex forecast
in the first place would yield a higher return.
As mentioned previously, the sharing ratio faced by the regulator decreases with the company's
CIS ratio. Due to concerns that companies with high CIS ratios might face inappropriately low
incentives to reduce capex (due to corresponding low sharing ratios), Ofwat (2009) decided that
companies that had CIS ratio above 130 would all be allowed a sharing ratio of 15 per cent.
This ensures that those companies with high CIS ratios would retain an appropriate level of
efficiency incentive for under- or outperformance during the regulatory period. However, while
there would be incentives for cost-cutting, this change might undermine the incentives for truthtelling. This is also reflects the complexity (and risks) associated with designing a menu.
At this stage, it is difficult to assess whether the CIS has indeed induced truth-telling from
companies. This requires at least a comparison between actual and allowed capex. This
question is worth revisiting when the PR09 control period concludes in 2015. It will be interesting
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to see if the overall CIS ratio changes in the next review given that companies are now more
familiar with the menu approach.
The next subsection discusses Ofwat's approach to opex in PR09.
4.2.2. Opex incentives
For PR09, Ofwat retained its previous approach used in the 2004 price review (PR04) for setting
opex allowances. Ofwat had considered extending the menu approach to opex but had
concluded that the potential benefits were insufficient to justify the change in approach.
Ofwat's approach to setting opex allowances in PR09 was largely similar to the AER's approach
(detailed discussion in Chapter 5). It involved rolling forward the company's actual operating
costs in the base year (i.e. a particular year in the previous control period; Ofwat used the
penultimate year), and adjusting for efficiencies and costs associated with new services that
companies would be required to provide.
Similar to the case of capex, Ofwat applied two efficiency improvement factors—a catch-up
improvement factor and a continuing improvement factor—when setting opex allowances. As
pointed out by CEPA (2012), Ofwat utilised a range of analyses to establish these efficiency
factors, including single year cross-section econometric analysis (for determining the relative
opex efficiency) and time series based approach (for determining the trend of overall efficiency).
Under Ofwat's regime, companies would retain opex incremental outperformance for six years
(this includes the year where the efficiency gain first occurs). The carry-over mechanism applied
by Ofwat was mostly similar to the AER's approach (illustrated in Chapter 5), with the exception
that under Ofwat's regime incremental overspends would not be carried forward to the next
period. This has two key implications:
(a)
one-off opex savings are fully passed through to the company—the incentive strength is
100 per cent (this differs from the AER's framework). On the other hand, the incentive
strength for recurring opex savings would depend on the WACC parameter. CEPA (2012)
estimates that the incentive strength for recurring opex savings would be 23.7 per cent
using a real WACC of 4.5 per cent; and
(b)
the treatment for opex was asymmetric in that only underspends would be shared between
companies and their customers.
In addition, Ofwat (2009) included additional rewards:
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(a)
a 1.5 outperformance multiplier for companies at the relative efficiency frontier; and
(b)
a 1.25 outperformance multiplier for companies within 5 per cent of the efficiency frontier.
Consider the following example: a company at the relative efficiency frontier achieved an
incremental gain of £2 million in year one. Without the opex multiplier effects, this company
would earn £2 million from year one to six (six years in total). With a 1.5 outperformance
multiplier, this company would be given an additional reward of £6 million (50%*£12 million).
This additional benefit would be added to next period's cost allowance.
As shown by the example above, the opex multipliers increase the total outperformance benefits
received by the most efficient companies under Ofwat's jurisdiction. The rationale for these
multipliers is that it is generally more difficult for companies close to or at the relative efficiency
frontier to underspend against their opex allowances, and hence these companies should
receive higher rewards for any underspends achieved.
Balance of incentives
It is important to consider the balance of incentives under Ofwat's regime. If a regulated firm
faces different incentive strengths for opex and capex, there is a perverse incentive for the firm
to prefer one type of expenditure over another. This will lead to suboptimal allocation of
resources.
It can be seen from Table 10 that, under the CIS, companies face different sharing ratios for
capex depending on their CIS ratios. At the break-even point (i.e. CIS ratio of 100), the sharing
ratio is 30 per cent. For PR09, the average CIS ratio at industry level was above 100, meaning
most companies would face an incentive rate below 30 per cent for capex in the period between
2010 and 2015.
For opex, the incentive strength faced depends on whether the cost saving is one-off or
recurring. Notwithstanding the potential opex multiplier effects (additional rewards for relatively
efficient companies), the effective overall incentive for opex would be 61.9 per cent if half of the
company's opex is recurring while the remainder is non-recurring, using a WACC of 4.5 per cent
(CEPA 2012). Similarly, if the ratio of recurring opex to non-recurring opex is 75:25, the effective
opex incentive rate would be 42.8 per cent.
These estimates suggest that there might be a capex bias within the incentive framework applied
by Ofwat. While the effective incentive rates for opex and capex faced by a particular company
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are uncertain (they depend on a number of factors), it appears that, for PR09, incentives for
opex efficiency are considerably higher than that of capex, especially if one considers the effects
of outperformance multipliers for opex.
4.2.3. Performance incentives
Ofwat applies the Service Incentive Mechanism (SIM) to provide incentives for companies to
provide better services to customers. Prior to mid-2010, these performance incentives were
provided through the Overall Performance Assessment (OPA).
Under the OPA, companies would be scored based on 15 specific performance measures,
including:
(a)
general performance type measures such as frequency of leakages, low pressures, and
unplanned interruptions;
(b)
customer focused measures such as frequency of and responsiveness to customer
complaints and enquiries; and
(c)
longer term issues such as environmental performance (Ofwat 2004).
Financial incentives were limited to between −1 per cent to +0.5 per cent of allowed revenue for
the first year of the next regulatory period. Rewards/penalties were determined based on where
the company's score fell relative to other companies. Ofwat also used company’s scores to
construct league tables so customers could compare the performance of their suppliers to
others.
According to Ofwat (2010), the OPA has contributed to considerable improvements in service
quality. For example, the frequency of leakages has fallen by 35 per cent between the mid1990s and 2010. Moreover, in 2009, 99.6 per cent of written complaints were responded to
within 10 working days, while in 2000 it was only 97 per cent. CEPA (2009) suggests that
financial, peer pressure and reputational effects have all played an important role in the
performance improvement.
Nonetheless, despite these improvements, Ofwat (2010) believed that the OPA had reached the
limit of its effectiveness for the following reasons:
(a)
the OPA was based on a number of narrowly defined quantitative measures. This might
discourage companies from innovating in their communications and dealings with
customers. There was a need to focus on the overall experience of customers;
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(b)
there were still a material number of complaints about service received by companies and
the Consumer Council for Water (the independent representative of household and
business water consumers); and
(c)
many company OPA scores were around the top end of the maximum achievable score.
This suggested that the OPA would not drive further material improvements in service
quality.
For these reasons, Ofwat developed the SIM and announced that the OPA would be replaced
from April 2010. One important element of the SIM is its reliance on customer surveys. The SIM
measures customer service delivery in two ways:
(a)
a quantitative measure based on the number of complaints (phone or written) the company
received, and whether the company was able to resolve the consumer's issue in the first
instance. Each complaint is scored based on its impact on consumers. For instance, a
written complaint to the company will carry less weight than a case that requires
investigation by the Consumer Council for Water; and
(b)
a qualitative measure based on a survey of consumers and those who have had direct
contact with their companies. Customers are asked how satisfied they were with the
service and how companies dealt with their issues and complaints.
Ofwat (2010) points out that these measures are intended to incentivise companies to (1) to
minimise the number of unwanted contacts; and (2) limit their impacts on customers by resolving
these issues quickly and effectively when service failures occur. A pilot consumer experience
survey found that only 63 per cent of consumer complaints were resolved at the first point of
contact (Ofwat 2010).
Customer surveys used by Ofwat will capture the overall satisfaction level of consumers,
especially those who have made contact with companies. Consumers will also be asked about
their views on how service can be improved. Ofwat (2010) emphasises that they have designed
the SIM to be outcome focussed, as to encourage innovation from companies to improve
consumers' experience.
The company will be rewarded or penalised based on its performance in these two measures.
Both measures are given equal weightings. Financial incentives are kept the same as the OPA—
between −1 per cent to +0.5 per cent of allowed revenue for the first year of the next regulatory
period. Ofwat (2010) also continues to publish companies' results in league tables.
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4.2.4. Future developments
Ofwat is undertaking a price review as of this writing, scheduled to be finalised by the end of
2014. This price review is referred to as PR14. This subsection discusses two major elements
of Ofwat's planned approach for PR14: proportionate regulation and a totex menu.
Proportionate regulation
The Ofwat (2013) methodology paper indicates an intention to move away from a prescriptive
approach to business plans. Under Ofwat's new approach companies will be expected to
produce high-quality business plans and will be held accountable for them. For this reason, in
PR14 Ofwat has not issued detailed guidance on business plans. Rather, Ofwat has created a
regulatory framework that incentivises companies to submit high-quality business plans and
returns ownership of those plans to companies.
A key element of the new price review process is a risk-based review of business plans. The
assessment determines the level of scrutiny required for a company's business plan. Very highquality business plans (granted the 'enhanced' status) would be subject to less scrutiny from
Ofwat, while some plans (the 'resubmission' status) would be returned to their companies to be
reworked and would face more intensive scrutiny and challenge. Such arrangements allow
Ofwat to focus its attention on areas where it is most likely to yield the greatest benefits for
consumers, hence reducing the burden of regulation.
According to Ofwat (2013), there are different incentives for companies to produce high-quality
business plans under the new arrangements:
(a)
Reputational incentives: Ofwat plans to publish each company's overall business plan
quality. Investors and other stakeholders will be able to identify companies that have (or
have not) submitted high-quality business plans.
(b)
Procedural incentives: business plans deemed as high-quality will be subjected to less
scrutiny from Ofwat. These companies will benefit from a reduced regulatory burden. They
also potentially receive early draft and final determinations.
(c)
Financial incentives: Ofwat intends to allow higher sharing ratios for companies granted
the 'enhanced' status, meaning that these companies will retain a higher percentage of
savings they achieve during the regulatory period.
Ofwat (2013) emphasises that the level of customer engagement will be an important
determinant of business plan quality. A high-quality business plan should reflect the customer’s
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views and priorities. Companies also need to demonstrate that their plans are both affordable
and financeable in order to be granted the 'enhanced' status.
Totex menu
Another key element of PR14 is that Ofwat (2013) has adopted a totex-based approach to
setting capex and opex allowances. As discussed previously, there might be a capex bias under
Ofwat's previous approach in PR09. It appeared that incentives for opex efficiency were
considerably higher than that of capex, and this might lead to companies having an inappropriate
preference for capex solutions. The totex approach represents a possible solution to this issue.
Note that Ofgem has also applied a totex-based approach.
The methodology paper revealed that Ofwat's new approach would involve setting a baseline
level of totex and an ex-ante PAYG:RCV ratio. The PAYG:RCV ratio determines the percentage
of total cost that enters directly into the revenue requirement (think of how opex is typically
treated) and the remaining portion that enters the RCV and recovered in long term (think of how
capex is typically treated).48 By fixing the PAYG:RCV ratio irrespective of the composition of
total spending, companies cannot influence the level of efficiency incentives by switching
between capex and opex. This mitigates the capex bias.
Unlike Ofgem, Ofwat (2013) stated that it would allow companies to propose PAYG:RCV
ratios—that is, there would not be an industry-wide split. By allowing firms to nominate different
splits, Ofwat has reintroduced adverse selection, in that firms may have incentives to propose
splits that deviate from efficient levels. This may happen if firms face an incentive structure that
favours one type of expenditure over another. Perhaps to mitigate this possibility, Ofwat (2013)
decided to equalise incentive rates between capex and opex (a single totex incentive rate).49
4.2.5. Summary and conclusion
Section 4.2 reviews Ofwat's approach to incentive regulation based on its final determinations
for PR09. It examines incentives for capex and opex efficiency, and service performance
incentives embedded in Ofwat's regulatory regime. It also looks at Ofwat's planned approach
for PR14 in the context of incentives.
48
49
Ofgem uses the fast and slow money terminology.
Note that under the Ofgem regulatory framework, there is no presumption that the incentive strength is the same for capex and
opex. The reason this is not necessary is that regardless of the incentive rate, the ratio of capex to opex used to determine total
revenue is fixed. More specifically, under the Ofgem framework, electricity distributors face an incentive strength determined by
the company’s choice from within the menu. At the breakeven point, the incentive strength faced under the CIS is equal to 30%.
For opex, the incentive strength faced is different depending on whether the cost saving is a recurring or non-recurring cost.
Roughly speaking, if the cost saving is a one-off, the incentive strength is equal to 100% as the saving is passed through to the
company. If the cost saving is in perpetuity, the incentive strength is determined by the length of the rolling incentive, how the
baseline is reset and the discount rate applied.
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In PR09, Ofwat applied a menu-based approach, referred to as the CIS, to setting capex
allowances. A well-designed menu should induce truth-telling from companies and incentivise
them to be cost efficient during the regulatory period. In PR09 most companies proposed capex
forecasts that were higher than Ofwat's baselines, and in some cases, they were more than 30
per cent larger. At this point, it is difficult to evaluate if high CIS ratios observed in PR09 reflected
gaming or truth-telling from companies. A comparison between actual outturns and the proposed
costs of companies is required.
This section also explores the rolling incentives for opex under Ofwat's regime. The carry-over
mechanism applied by Ofwat was largely similar to the AER's approach (see next chapter),
except that the scheme was asymmetric and one-off savings would be fully retained by
companies. Ofwat also allowed more efficient companies to receive additional rewards through
opex multipliers.
It appears that the incentives for opex efficiency were considerably higher than that of capex,
and this might cause an inappropriate preference for capex solutions (i.e. a capex bias). This
motivated Ofwat to mitigate this issue by moving to a totex-based approach in PR14.
Ofwat replaced the OPA with the SIM in 2010. The OPA was considered by Ofwat to have
reached its limit in terms of incentivising companies to improve their service quality. One major
difference between the OPA and SIM is the latter's use of customer surveys. The SIM is
outcome-focussed (on the overall satisfaction level of consumers) which encourages innovation
from companies to improve consumers' experience rather than focussing on narrowly-defined
measures.
Ofwat also revealed that it would move away from a prescriptive approach to business plans.
In PR14, Ofwat has not issued detailed guidance on business plans. Rather, Ofwat has created
a regulatory framework that incentivises companies to submit high-quality business plans and
returns ownership of those plans to companies. The new arrangements included a risk-based
assessment to determine the quality of business plans.
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5.
THE AER APPROACH TO INCENTIVE REGULATION
This chapter focuses on the AER’s approach to incentive regulation. Specifically, three separate
incentive schemes designed to incentivise network businesses to improve capex and opex
efficiency, and service performance are explored. The chapter discusses the linkages between
issues raised in previous chapters and the application of incentive regulation in the context of
the Australian electricity industry.
5.1
Background
The National Electricity Market (NEM) consists of the wholesale electricity market and the
associated electricity transmission and distribution network in eastern and southern Australia.
The AER regulates the electricity transmission and distribution network businesses—referred to
as Network Service Providers (NSP)—in the NEM. The Australian Energy Market Commission
(AEMC) is responsible for determining and maintaining the National Electricity Rules (NER),
which includes a framework for the economic regulation of NSPs that the AER is required to
follow.
The AER applies the building-block approach, in conjunction with the use of opex and capex
forecasts, for establishing the allowed revenue each NSP can earn over the regulatory period.
Most NSPs operate under a revenue-cap regime. The delinking of actual costs from prices
creates an incentive for regulated firms to be cost efficient in order to earn higher profits.
The AER implements two mechanisms (CESS and EBSS, respectively) to separately incentivise
capex and opex efficiency.50 Indeed, under the AER's regime, NSPs have continuous incentives
to underspend both capex and opex allowances over the regulatory period, and any efficiency
gains and losses are shared between NSPs and their customers. Sections 5.2 and 5.3 examine
how these incentive mechanisms operate.
The AER also applies the Service Target Performance Incentive Scheme (STPIS) to NSPs. As
suggested by its name, the STPIS aims to encourage NSPs to improve or maintain the
performance of their networks. This is achieved by linking NSPs' allowed revenues to their
performance against defined service level measures. This scheme is explored further in Section
5.4.
50
The EBSS has been in place for a number of years, while the CESS will apply to all NSPs by 2016.
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Throughout this chapter, the interaction between the AER's incentive frameworks and its
approaches to expenditure assessment are highlighted. Expenditure forecasting plays a vital
role in the implementation of incentive regulation, as outperformance can easily occur if the
initial cost allowance is set greater than the expenditure required to deliver a defined level of
outputs.
5.2
Efficiency benefit sharing scheme (EBSS)
The AER51 applies the EBSS to incentivise NSPs to pursue efficiency improvements in opex.
As explained in Section 3.4, standard price-cap regulation, in conjunction with periodic pricing
reviews, suffers from the problem of 'periodicity of incentives' in relation to cost efficiency (both
opex and capex)—that is, incentives to pursue efficiency gains reduce over time within a
regulatory period. Recognising this issue, the AER first introduced the EBSS for transmission
network businesses in 2007, followed by distribution network businesses in 2008.
The EBSS is an application of efficiency carryover schemes, and has key two purposes:
(a)
providing continuous incentives for NSPs to pursue opex efficiency; and
(b)
sharing efficiency gains and losses associated with opex between NSPs and customers.
The EBSS achieves these aims through an incremental rolling mechanism where NSPs retain
any 'incremental' efficiency gains and losses for a fixed period (known as the carryover period,
typically equal to the length of the regulatory period). The incremental efficiency gain (or loss) in
a particular year is defined as the difference between forecast and actual opex in that year, less
the difference in the preceding year. When an NSP makes an incremental gain (or loss), it sets
off a series of annual carryover gains (or losses). The carryover amounts will be added into the
NSP’s allowed revenue for next regulatory period.
This mechanism ensures that NSPs retain a fixed percentage of any efficiency gains in NPV
terms, irrespective of the nature of the opex reduction (i.e. one-off or recurrent) and the time the
efficiency gain occurs. In other words, NSPs have continuous incentives to pursue opex
efficiency. The EBSS operates on a symmetric basis in the sense that both out- and underperformance are shared between NSPs and their customers.
The EBSS is linked to the AER's approach for setting the opex allowance where the regulator
typically applies the revealed-cost approach. Put simply, the AER uses actual opex in a base
51
AER (2013a).
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year (either the penultimate or the final year of the previous regulatory period) as a starting point
for forecasting opex. This actual opex is then adjusted downwards for any past inefficient costs
(if identified), and scaled to reflect forecast changes in input costs, productivity and output
growth, in order to establish a cost benchmark. The AER52 argues that actual opex from the
previous period would be an appropriate efficient benchmark if the regulated firm had operated
under an effective incentive framework (such as the EBSS) and had behaved in a profitmaximising manner. If adjustments are made to actual opex, this implies that the incentive
framework was not fully effective (e.g. there are distortions affecting the company's decision
making). It is also noted that the effectiveness of the incentive framework should encompass
the extent to which the firm behaves in a profit-maximising manner.
Note that efficiency incentives are designed to recognise that the NSPs can underspend their
opex allowances (hence earning additional profits), and face no clawback in the future. The
EBSS is simply a mechanism that complements the existing revenue cap to ensure that these
incentives are balanced (continuous) over time. The fundamental problem of adverse selection
still exists under the AER’s regime, although it is partially addressed by the revealed-cost
approach used by the AER, as explained above. The relationship between the EBSS and
revealed-cost approach is discussed further below.
Tables 10 and 11 illustrate an application of the EBSS in two separate scenarios: (1) the NSP
makes a one-off opex underspend in year three; and (2) the NSP makes a permanent opex
reduction in year three. The assumptions are largely similar to those in Section 3.4. The NSP
earns a real WACC of six per cent and its forecast annual opex for the first regulatory period is
$100 million. There is no output, real price or productivity growth. The regulatory period is five
years, meaning that a new opex allowance is set in year six. Any efficiency gains (or losses) are
assumed to occur at year end. One important distinction here (compared with Section 3.4) is
that the new opex allowance in year six is set based on actual opex in year four (as opposed to
an assumption of no information asymmetry).53 This practice is consistent with the AER's
standard approach to forecasting opex, as mentioned previously.
For the case of a one-off opex saving, the EBSS allows the NSP to retain the whole amount of
the saving in that year, but is then required to pay it back in nominal terms in six years’ time. In
the first example below, the NSP makes a one-off opex underspend at the end of year three
(which leads to higher income in that year), and subsequently ‘returns’ this amount to customers
52
53
AER (2013b)
The examples in Section 3.4 are based on an assumption that the regulator can observe the regulated firm’s prevailing efficient
cost when setting new opex allowances. In reality, efficiency gains are not as easily observed due to information asymmetry.
The AER uses the revealed-cost approach in conjunction of the EBSS.
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at the end of year nine. The present value the saving in year three less the present value of the
amount returned in year nine is in effect the benefit that the NSP is allowed to retain. An
accounting mechanism (through the workings of incremental gains and carryover payments)
has been specified to keep track of the amount that is in effect required to be paid back.
Likewise, when the NSP achieves a permanent reduction in opex, the business retains the
difference between actual and forecast opex for a total of six years (the year of the gain plus
five years) before the efficiency gain is passed onto customers in the form of lower opex
allowances. In the second example, the NSP retains the additional income arising from an
ongoing opex reduction from year three to eight.
Table 9 shows the impact of a one-off opex savings under the EBSS. The EBSS mechanism is
specified as follows:
(a)
when the NSP underspends the allowance by $10 million at the end of year three, it
registers as an incremental gain of equivalent amount. This sets off a series of annual
carryover gains, each worth $10 million, from year four to eight;
(b)
at the end of year four, actual opex reverts to $100 million. This is recorded as an
incremental loss of $10 million. This sets off a series of annual carryover losses, each
worth $10 million, from year five to nine;
(c)
only carryover amounts that fall in the next period are relevant, as they will be included
into the allowed revenue for the next period (note that carryover payments in the first
period are always zero). For year six to eight, the net carryover amount is zero, as the
gain (arising from the incremental gain in year three) is offset by the loss (arising from the
incremental gain in year four). For year nine, the net carryover amount is −$10 million.
This amount will be included into the cost base for year nine; and
(d)
as a result of these effects, the NSP earns an additional income of $10 million in year three
(by underspending the allowance) and incurs a loss of $10 million in year nine (due to the
negative carryover amount). In NPV terms (evaluated at the end of year three), the NSP
gains $2.95 million out of a possible $10 million (the value of this efficiency gain). This
gain reflects the impact of the discount rate. Thus the NSP retains approximately 30 per
cent of the efficiency gain, while customers receive the remaining 70 per cent, from a
present value perspective.
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Table 9 Impact of a one-off opex reduction in year three under the EBSS ($ million).
Year
1
2
3
4
5
6
7
8
9
10
Forecast opex
100
100
100
100
100
100
100
100
100
100
Actual opex
100
100
90
100
100
100
100
100
100
100
Underspend
0
0
10
0
0
0
0
0
0
0
Incremental gain
0
0
10
−10
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
10
10
10
10
10
−10
−10
−10
−10
−10
0
0
0
0
0
Carryover of gains made
in year
1
2
3
4
5
Total carryover payment
0
0
0
0
0
0
0
0
−10
0
Total additional income
0
0
10
0
0
0
0
0
–10
0
Discount factor
1.12
1.06
1
0.94
0.89
0.84
0.79
0.74
0.70
0.67
NPV of additional
income
2.95
NPV of opex reduction
Benefit retained (in %)
10
29.5
In the second example (Table 10), the NSP initiates an ongoing opex reduction at the end of
year three. Actual opex falls to $90 million once this occurs. The incremental gain at the end of
year three is $10 million, which sets off a carryover amount of $10 million for the next five years.
There is no incremental gain or loss for the remaining years as actual opex remains at $90
million. Notice that although the opex allowance is adjusted downwards to $90 million in the
second regulatory period, the NSP still receives additional income (which reflects the annual
savings had the opex allowance not been adjusted) through the EBSS carryover amounts for
year six to eight. For years four and five, the carryover amounts are not relevant as the NSP
automatically retains each year's underspend because the respective opex allowances are fixed
at $100 million. As shown in Table 10, in NPV terms, the NSP receives $52.12 million, which is
equivalent to 29.5 per cent of the efficiency gain.
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Table 10 Impact of an ongoing reduction in year three under the EBSS ($ million).
Year
1
2
3
4
5
6
7
8
9
Forecast opex
100
100
100
100
Actual opex
100
100
90
Underspend
0
0
Incremental gain
0
10
100
90
90
90
90
90
90
90
90
90
90
90
90
10
0
0
0
0
0
0
0
0
10
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
10
10
10
10
10
0
0
0
0
0
0
0
0
0
0
Carryover of gains made
in
1
2
3
4
5
Total carryover payment
0
0
0
0
0
10
10
10
0
0
Total additional income
0
0
10
10
10
10
10
10
0
0
Discount factor
1.12
1.06
1
0.94
0.89
0.84
0.79
0.74
0.70
0.67
NPV of additional
income
52.12
NPV of opex reduction
(in perpetuity)
176.7
Benefit retained (in %)
29.5
These examples show that, under the EBSS, the NSP retains approximately 30 per cent (this
varies with the value of the WACC) of any increase or decrease in opex, irrespective of whether
the change in efficiency is short-term or long-term in nature. While not illustrated above, the
EBSS also ensures that the NSP has a continuous incentive to reduce opex—that is, the
percentage share of benefits or losses (i.e. the incentive strength) does not vary with the time.
The NSP has the same level of incentives to pursue opex efficiency over time within a regulatory
period.
As mentioned previously, the EBSS operates in close association with the revealed-cost
approach. In fact, the AER (2013) states that it will exclude any categories of opex that are not
forecasted using such an approach from the EBSS.
If the revealed-cost approach is used when the EBSS is not in place, the NSP has an incentive
to spend more in the expected 'base year' in order to secure higher opex allowances for the next
regulatory period (this would result in negative carryover amounts under the EBSS which
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penalise such overspend). Without the EBSS, there may be distortions to spending patterns as
the incentive to reduce recurring opex falls over time within the regulatory period (the problem
of 'periodicity of incentives') but increases after the base year as actual opex after would not be
reflected in the opex forecast.
On the other hand, if the EBSS is implemented but the revealed-cost approach is not used to
forecast opex, the EBSS may not achieve the sharing ratio of 30:70 between NSPs and
customers. There may be windfall gains or losses to the NSP as a result of carryover payments.
For example, if opex allowances in the new period are not adjusted downwards to reflect an
efficiency improvement that has occurred, the NSP will benefit by underspending in the new
period, while at the same time it will also receive carryover payments arising from the previous
period's efficiency gain. The revealed-cost approach is more likely to recognise a recurring opex
reduction than alternative forecasting approaches.
5.3
Capital expenditure sharing scheme (CESS)54
When the EBSS was first introduced in 2007, there was a concern that the additional incentives
for opex savings would lead to capex bias—NSPs would have an inappropriate preference for
capex solutions or have perverse incentives to misclassify opex as capex. There was no similar
incentive scheme for capex, hence NSPs faced discontinuous incentives for pursuing capex
efficiency (see Section 3.4). While an NSP would incur additional financing costs if it overspent
the capex allowance, actual capex would automatically be rolled into the RAB at the end of the
regulatory period without being subjected to any ex-post assessments.
The NSP could
potentially underspend opex (and benefit from the EBSS) by shifting to capex (and incur
temporary additional financing costs).
In 2012, the AEMC made a number of changes to the NER in response to these issues. The
changes provide the AER with the following responsibilities:
(a)
to develop an incentive scheme for capex efficiency;
(b)
to undertake ex-post efficiency review of actual capex; and
(c)
to disallow inefficient capex from the RAB.
The AER has since developed guidelines on the capex incentive scheme, known as the CESS,
and a new ex-post test that NSPs' actual capex will be subject to. These measures will apply to
all NSPs by 2016. This section draws from these guidelines.
54
This section is largely based on AER (2013c)
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Similar to the EBSS, the CESS is an application of efficiency carryover schemes. While both
incentive schemes lead to similar outcomes—that is, NSPs retain approximately 30 per cent of
efficiency gains and losses—they operate differently. Under the EBSS, NSPs retain any
'incremental' efficiency gains or losses for a fixed period via carryover payments. The exact
percentage of benefits retained by NSPs will depend on the value of the WACC as well as the
carryover period. This can be described as an incremental rolling mechanism.
The CESS operates on a fixed-sharing basis. At the end of each regulatory period, the sharing
ratio of 30 per cent is applied to the cumulative capex underspend or overspend to determine
the NSP's share. The AER then deducts the net benefit that the NSP has already earned in the
regulatory period from the NSP's share to derive the CESS payment. This amount is added to
the next period's allowed revenue. In contrast to the EBSS, the sharing ratio under the CESS
does not vary with the WACC. Customers are better off given the RAB is lower (hence lower
return on and return of capital in the future) than what it would have been if the NSP had spent
the full capex allowance. As both CESS and EBSS have approximately the same sharing ratio
of 30 per cent (given a six per cent real WACC), there are limited incentives for the NSP to prefer
one type of expenditure to the other.
The following example illustrates an application of the CESS. The NSP has a real WACC of six
per cent. The regulatory period is five years. Capex is assumed to occur mid-year (consistent
with the standard assumption used by the AER). The NSP's forecast and actual capex are
shown in Table 11.
Table 11 NSP's forecast and actual capex ($ million).
Year
1
2
3
4
5
Forecast opex
100
150
120
130
100
Actual opex
85
160
90
98
125
Underspend
15
−10
30
32
−25
Discount factor
1.064.5=1.30
1.063.5=1.23
1.062.5=1.16
1.061.5=1.09
1.060.5=1.03
NPV of underspend
19.50
−12.26
34.70
34.92
−25.74
Accumulated underspend (in
NPV terms)
51.12
NSP's share (30%)
15.34
In order to calculate the NSP's total share of efficiency gains (or losses), annual underspends
are converted into an NPV, evaluated at the end of year five. As shown above, the accumulated
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underspend has an NPV of $51.12 million. A sharing ratio of 30 per cent implies that the NSP
should retain $15.34 million in total.
As pointed out previously, capex forecast is used to determine the allowed return on and return
of capital when setting regulated prices. An NSP that underspent would already earn some
benefits during the regulatory period (i.e. the return on and return of unspent capex). Similarly,
an NSP would incur additional financing costs (for not receiving a return on capex above
allowance) if it overspent. The net benefit (referred to as the financing benefit by the AER) needs
to be deducted from the NSP's total share.
The net financing benefit to the NSP will depend on whether forecast or actual depreciation is
used when actual capex is rolled into the RAB. Forecast depreciation is the allowed depreciation
of forecast capex while actual depreciation is the depreciation of actual capex incurred. In most
circumstances, the AER rolls forward the RAB taking actual capex less forecast depreciation.
When forecast depreciation is used, the net financing benefit is equal to the NPV of the return
on capital calculated on the undepreciated value of the unspent capex (or the amount above
allowance).55 Table 12 shows the financing benefits received by the NSP.
Table 12 Financing benefits ($ million).
Year
1
Financing benefits from Year 1 underspend
0.44
Financing benefits from Year 2 underspend
2
3
4
0.90
0.90
0.90
0.90
−0.30
−0.60
−0.60
−0.60
0.89
1.80
1.80
0.95
1.92
Financing benefits from Year 3 underspend
Financing benefits from Year 4 underspend
−0.74
Financing benefits from Year 5 underspend
Total financing benefits
0.44
0.60
1.19
3.05
3.28
Discount factor
1.30
1.23
1.16
1.09
1.03
NPV of financing benefits
0.58
0.74
1.37
3.32
3.38
Accumulated financing benefits (in NPV terms)
55
5
9.39
When an NSP underspends its capex allowance, it earns excess income from the return on unspent capex (underspend means
less capital cost) plus depreciation of that capex in each year (earning a return of capital for money not spent). The NPV of this
excess income is the net financing benefit when actual depreciation is used, when actual capex is rolled into the RAB.
Nevertheless, when forecast depreciation is used, the RAB will be rolled forward to a lower amount (forecast depreciation is larger
than actual depreciation), meaning that the NSP earns a lower return on and of such capex over the remaining life of the asset.
In this case, the net financing benefit is equal to the NPV of the return on capital calculated on the undepreciated value of the
unspent capex.
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For any underspend, the NSP gains a half-year financing benefit in the first year (the year the
underspend occurs), followed by a full-year financing benefit in each of the remaining years until
the end of the regulatory period. In this example, the NSP underspends the capex allowance by
$15 million in year one. As capex occurs in mid-year, this means that the NSP earns a half-year
financing benefit of:
$15 𝑚𝑖𝑙𝑙𝑖𝑜𝑛 ∗ (1.060.5 − 1) = $0.44 𝑚𝑖𝑙𝑙𝑖𝑜𝑛
in year one. For the remaining years, the NSP earns a full-year financing benefit arising from
this underspend in year one.
$15 𝑚𝑖𝑙𝑙𝑖𝑜𝑛 ∗ 0.06 = $0.9 𝑚𝑖𝑙𝑙𝑖𝑜𝑛
Similar calculations are taken for underspends that occur in years two to five.
As shown in Table 13, the accumulated financing benefit in NPV terms (evaluated at the end of
year five) is $9.39 million. Deducting this amount from the accumulated underspend yields a
CESS payment of:
$15.34 𝑚𝑖𝑙𝑙𝑖𝑜𝑛 − $9.39 𝑚𝑖𝑙𝑙𝑖𝑜𝑛 = $5.95 𝑚𝑖𝑙𝑙𝑖𝑜𝑛
Hence, $5.95 million will be added to the NSP's allowed revenue for the next regulatory period.
The CESS ensures that the NSP receives 30 per cent of the accumulated capex underspend
(in NPV terms). This means that the NSP has balanced incentives to pursue efficiency for both
capex and opex.
Inter-period deferral of capex
The AER recognises that the introduction of the CESS will lead to stronger incentives to defer
capex from one regulatory period to the next. This is because the percentage of benefits retained
by NSPs is fixed over time within a regulatory period.
As pointed out by the AER (2013), inter-period deferrals of capex are not necessarily inefficient.
For example, if an NSP developed a way to utilise current assets productively for a longer period,
this would lead to postponement of planned renewal assets. Similarly, an NSP might find it
efficient to bring forward future capex projects due to a change in circumstances.
The issue, however, lies in the regulator’s ability to differentiate between a permanent efficiency
improvement (e.g. the final cost of a capex project is less than expected cost) and a short-term
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deferral of capex. Unlike the latter, an efficiency improvement would not lead to a subsequent
increase in the next period’s capex requirement.
Without any adjustment to the CESS payments, if a material amount of capex is deferred and
subsequently included into the next period's capex allowance, this would lead to customers
paying higher prices in the long run. This is because customers would end up bearing 30 per
cent of the capex underspend (the CESS payments), plus the cost recovery associated with this
capex once it occurs in the next period. This concern was the key reason why the AER decided
not to apply a carryover scheme for capex when the EBSS was first introduced (AER 2008).
Based on the guideline, the AER will have the flexibility to adjust the CESS payments.
Specifically, adjustments will be made if the NSP significantly underspends the capex allowance
in a regulatory period, and the deferred capex is found to cause an increase in the next period's
capex forecast (subject to materiality threshold). These are considered by the AER when
assessing the NSP’s capex forecast. These criteria ensure that the NSPs will have the incentive
to reshuffle capex projects within and between regulatory periods, and retain the benefits in the
case of efficient deferrals (in NPV terms).
The AER (2013) also acknowledges that the CESS may strengthen the perverse incentive for
NSPs to inflate their capex forecasts. The AER, however, states that the risk of forecasting bias
should be reduced by the introduction of a range of new techniques that the AER intends to use
for assessing NSPs’ expenditure forecasts.
Ex-post measures
The rule changes made by the AEMC in 2012 allow the AER to review actual capex. Prior to
these changes, the AER was required by the NER to include all actual capex into the RAB.
Notwithstanding the incentives for opex efficiency, an NSP could benefit from such
arrangements by simply shifting planned capex from the beginning to the end of the regulatory
period.
According to the AER's guideline, the regulator will release a statement on the efficiency and
prudency of actual capex at the end of each regulatory period. There are three scenarios where
the AER may exclude capex from being rolled into the RAB:
(a)
capex above the allowance may be excluded if the AER considers such overspend does
not satisfy the capital expenditure criteria;
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(b)
capex that represents a margin paid by the NSP may be excluded if the AER considers
the margin is a result of arrangements that do not reflect arm's length terms; or
(c)
capex that was originally classified as opex in the NSP's regulatory proposal may be
excluded from the RAB and included into actual opex.
Together with the CESS, this implies that the NSP bears 30 per cent of efficient capex
overspend, and faces a total write-off for inefficient capex overspend. This may increase the
incentive for NSPs to exaggerate their cost forecasts to avoid penalty associated with capex
overspend. This is again related to the issue of adverse selection.
5.4
Service target performance incentive scheme (STPIS)
The AER applies the STPIS for both transmission and distribution network service providers to
provide incentives to improve or maintain service quality. Different measurements of
performance and service standards apply to both types of businesses. This section focuses on
the version of the STPIS applied for transmission network service providers (TNSP).
When the AER first introduced the STPIS in 2007, it was based on the service standards
guidelines developed by the Australian Competition and Consumer Commission (ACCC). The
ACCC's guidelines were designed to address the incentives provided to TNSPs under a revenue
cap to reduce opex at the expense of service quality, by linking TNSP’s allowed revenues to
their performance against defined service level measures.
The STPIS has since undergone three major rounds of amendments. The latest version of the
STPIS has three key components:
(a)
the service component, which is designed to incentivise TNSPs to reduce the frequency
of unplanned outages and the duration of these events. This can lead to a maximum
reward or penalty worth one per cent of the MAR;
(b)
the market-impact component (MIC), which provides an incentive to TNSPs to reduce the
impact of planned and unplanned outages on wholesale market outcomes. This has an
incentive of zero to two per cent of the MAR; and
(c)
the network-capability component, which encourages TNSPs to undertake low-cost
projects (can cost up to a total of one per cent of the MAR per year) that deliver
improvements in the network capability, availability or reliability.
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According to the AER (2013), the reward (penalty) is based on the consumer’s willingness to
pay for service and reliability improvements.56 NSPs are provided sufficient allowances to
maintain the required level of service quality. Any expenditure associated with achieving higher
levels of service quality is funded through STPIS rewards. This provides an incentive for NSPs
to fund improvements only if their value to customers exceeds their associated costs.
Performance targets for the first two components are set based on historical levels. The MIC is
a bonus-only scheme, meaning that no revenue is at risk should a TSNP fail to achieve the
performance target. The performance target for the MIC is a three-year rolling target while the
performance measure is a two-year rolling average. As pointed out by the AER, NSPs could
potentially game a bonus-only scheme by artificially spiking their performance in one year
(hence receiving large incentive payments) at the expense of another (i.e. 'zig zagging' their
performance). A rolling performance measure over a two-year period addresses this perverse
incentive arising from a bonus-only scheme.
The network capability component is designed to fund low-cost projects aimed at improving the
capability of existing network assets. TSNPs are required to submit a network capability
incentive parameter action plan (NCIPAP) along with their revenue proposals. The Australian
Energy Market Operator is expected to play a consultative role in the development of NCIPAPs.
An NCIPAP includes a list of projects proposed by the TNSP and an improvement target for
each project. The total annual average costs could be up to one per cent of the MAR. These
projects would be approved by the AER if they are consistent with the requirements of the
network capability component and the STPIS. The TSNP would receive an incentive payment
up to 1.5 per cent of its MAR to fund the approved projects in each year apart from the final year
of the regulatory period. In the final year, the incentive payment would be 1.5 per cent of the
MAR, or up to a minimum of minus two per cent of the MAR if the TSNP fails to achieve the
project improvement target(s).
56
The rewards for service and reliability improvements are set with reference to 'value of customer reliability' (VCR) data based on
a study done by CRA in 2008, in the context of Victorian networks. The VCR is expressed in $/MWh of unserved energy (or value
of lost load) and is escalated annually by the inflation rate. One of the methodologies CRA used is customer surveys. The
Australian Energy Market Operator is currently doing a fresh study into VCR for each state and these results will probably feed
into the STPIS incentive rates in future. See CRA (2008) and AER (2009) for more information on the VCR study and how it is
applied in the context of STPIS.
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5.5
Summary and conclusion
This chapter reviews three incentive schemes under the AER’s regulatory regime: the EBSS,
CESS and STPIS. The EBSS and STPIS have been in place for a number of years, while the
CESS will apply to all NSPs by 2016.
The EBSS and CESS are applications of efficiency carryover schemes, designed to provide
continuous incentives for NSPs to pursue opex and capex efficiency. Under the AER’s proposed
regime, NSPs have the same level of incentives to underspend both capex and opex at any
point in time, as they retain 30 per cent of benefits arising from efficiency gains in NPV terms.
NSPs should have no perverse incentives to opt for a particular type of expenditure. The CESS
and EBSS operate on a symmetric basis, in the sense that both out- and underperformance are
shared between NSPs and their customers.
While together the EBSS and CESS address the issues of periodicity of incentives and capex
bias, there are still concerns in relation to information asymmetry (more specifically adverse
selection). Under the EBSS, if the regulator fails to recognise efficiency gains that have occurred
in the previous regulatory period when setting the new opex allowance, the NSP will benefit not
only from the carryover payments, but also from continual underspend in the new period. The
AER uses the revealed-cost approach in setting the opex allowance. This approach is crucial in
sustaining the sharing ratio of 30:70 for opex efficiency. Likewise, for the CESS the AER needs
to ensure that material deferrals of capex are recognised; otherwise it will lead to customers
paying higher prices in the long run. The AER does not rely on a specific method for setting
capex forecasts.
The AER states the actual expenditure should be largely efficient if the regulated firm operates
under an effective incentive framework. If this is indeed the case, the regulator can obtain useful
information from actual expenditure. This is especially useful in the case of opex, where most
expenditure is recurrent, as compared with capex where there are large scale projects.
Regulators in the UK have implemented menu regulation to address the issue of adverse
selection. On a related note, as part of the Better Regulation reform program, the AER (2013)
released a guideline outlining its approach to expenditure assessment. This guideline outlines
a range of new techniques, in addition to the existing ones, that the AER intends to use to assess
NSPs’ cost proposals. The AER states that it will make greater use of benchmarking in the
future. This should reduce the risk of forecasting bias.
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The STPIS is designed to incentivise NSPs to improve or maintain their service quality. It has
three separate components. The rewards are set based on the customer’s willingness to pay,
hence providing an incentive for NSPs to pursue improvements only if they cost less than the
value they bring for users. It is also noted that not all of the components of the STPIS have a
symmetric reward structure.
The AER’s proposed regime represents a comprehensive application of incentive regulation.
The fact that the AER has designed two incentive schemes to tackle the issues of periodicity of
incentives and capex bias shows that the AER acknowledges the significance of these issues
in that they may lead to distortions in the decision making of NSPs.
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6.
GLOSSARY
A
ACCC
AEMC
AER
Australian Competition and Consumer Commission
Australian Energy Market Commission
Australian Energy Regulator
B
C
CAPEX
CEPA
CESS
CIS
CRA
D
DG
DNOs
E
EBSS
F
Capital Expenditure
Cambridge Economic Policy Associates Ltd
Capital Expenditure Sharing Scheme
Capex Incentive Scheme
Charles River Associates
Distributed Generation
Distributed Network Operating System
Efficiency Benefit Sharing Scheme
G
H
I
IQI
J
Information Quality Incentive
K
L
M
MAR
MIC
N
NCIPAP
NER
NPV
NSP
O
OFGEM
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Network Capability Incentive Parameter Action Plan
Office of Gas and Electricity Markets
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OFWAT
OPA
OPEX
P
PDC
Q
QCA
R
RAB
RECs
S
SFA
SIM
T
TFP
TNSP
TOTEX
U
V
VCR
W
WACC
X
Office of Water Services
Overall Performance Assessment
Operational Expenditure
Proportion of Disallowed Claims
Queensland Competition Authority
Regional Electricity Companies
Stochastic Frontier Analysis
Service Incentive Mechanism
Total Factor Productivity
Transmission Network Service Provider
Total Expenditure
Value of Customer Reliability
Weighted Average Cost of Capital
Y
Z
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