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Explanatory Memorandum to the draft

Central Electricity Regulatory Commission

(Prevention of Adverse Effect on Competition)

Regulations, 2012

Contents 1. Introduction .................................................................................................................................... 2

2. Scope of Regulation of Competitive Markets and Market Participants in the Indian Electricity

Sector ...................................................................................................................................................... 3

3. What is adverse impact on Competition?....................................................................................... 5

3.1 When can an agreement be Anti-competitive? ...................................................................... 6

3.2 What are the considerations in detection of abuse of dominant position? ........................... 8

4. Defining the Appropriate Markets ................................................................................................ 11

5. Assessment of Market Power – Use of Indicators ........................................................................ 13

6. Investigations under the Regulations and Issue of Directions ...................................................... 15

7. Process for Investigations under these Regulations ..................................................................... 16

8. Securing Compliance with the Directions of the Commission and Imposition of Penalties ......... 17

9. Role of Sector Regulator and relationship with Competition Commission of India ..................... 18

Annexure: Key tests and Indicators of Market Power and Market Abuse .......................................... 20

1.1 Defining Market Power ......................................................................................................... 20

1.2 Assessment and Quantification of Market Power ................................................................ 22

1.2.1 Structural Indices .......................................................................................................... 24

1.2.2 Rationale for SSNIP Test for Market Size ...................................................................... 26

1.2.3 Behavioural Indices and Analysis .................................................................................. 33

1.2.4 Simulation Models ........................................................................................................ 37

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Statement of Reasons and Objects

1. Introduction

The Electricity Act, 2003 (“EA 2003” or “the Act”) places considerable emphasis on

competition and competitive markets as a means to achieve consumer welfare, promote

efficiency and attract investments in the Indian power sector. The law, as set out in the

preamble, inter-alia states among the objectives“....generally for taking measures

conducive to development of electricity industry, promoting competition therein, protecting

interest of consumers and supply of electricity to all areas.....”. Further, Sections 23, 60, 61,

62, 79. 86, 131, incorporate various provisions for promotion of competition. Section 66 of

the EA 2003 requires that “The Appropriate Commission shall endeavour to promote the

development of a market (including trading) in power in such manner as may be specified

and shall be guided by the National Electricity Policy referred to in section 3 in this regard”.

Thus, competition and competitive markets are an integral part of the structure of the EA

2003.

However competitive markets do not automatically produce competitive results, or protect

consumer and supplier interest. A number of potential distortions in the design and

operations of markets can result in sub-optimal results from a market efficiency

perspective. This is particularly true in the case of electricity markets. Electricity as a

commodity cannot be stored on a large scale in a cost effective manner, and must be

consumed at the instant at which it is produced. There are considerable entry and exit

barriers in the electricity sector. Investments are large and concentrated. The number of

players can at various instances or circumstances be fewer than the typical requirements of

competitive markets. The product is also not undifferentiated and at various times (peak,

off-peak) supplier and consumer behaviour can vary significantly. Finally, in the short run

the elasticity of demand is very low due to the essential nature of the commodity.

Electricity is thus differentiated from “typical” commodities and hence competition in

electricity must be managed carefully.

The Act recognises these traits of electricity as a commodity and hence entrusts the

Appropriate Commission with the important role of ensuring that electricity markets are

adequately competitive. Section 60 of the Act mandates that “The Appropriate

Commission may such issue directions as it considers appropriate to a licensee or a

generating company if such licensee or generating company enters into any agreement or

abuses its dominant position or enters into a combination which is likely to cause or causes

an adverse effect on competition in electricity industry.”

Till date, the markets have functioned without specific regulations being framed under

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Section 60. However, the competitive markets have grown rapidly in the past few years. As

the electricity sector in the country grows and competitive markets evolve, it becomes

incumbent on sector regulators to ensure that the monitoring of competition under Section

60 of the Act is orderly, balanced and objective. On the one hand the directions issued

must be circumscribed by principles that provide the consumers, suppliers and electricity

industry participants in general with sufficient clarity on how competition is to be regulated

under the provisions of Section 60. On the other hand, sufficient flexibility must be

available to the Commission to adjust to situations as they emerge. As mentioned,

electricity not being a standard commodity requires objective analysis depending on

situational aspects. However such objectivity and flexibility must be applied in a manner

that is principled and predictable to the entities regulated under Section 60 and to

consumers. The regulations, framed under Section 60 of the Act, strive to achieve this

balance.

2. Scope of Regulation of Competitive Markets and Market Participants in

the Indian Electricity Sector

As mentioned, markets may not automatically produce competitive results. However,

monitoring of markets and ensuring effective competitions is a complex task. This is due to

a variety of reasons. Part of the problem derives from the difficulty of defining the relevant

market. Broadly Electricity Supply Industry is seen as consisting of Generation,

Transmission, Distribution and Supply. While markets for generation and hence

procurement of generation capacity are seen to have some traits of competitive markets –

possibility of large number of potential suppliers and a large number of consumers - it still

involves huge sunk costs and entry and exit is not costless. The Act recognized the

competitive aspects of markets for electricity generation and de-licensed generation.

Transmission is a natural monopoly characterized by huge sunk costs, declining average

cost curves and hence costs are not sub-additive – it is not efficient to have parallel

transmission lines – owned by separate service providers serving the same region. This

again is recognized by the Act but since transmission networks are electrical highways over

which the content – electricity – flows, the need for non-discriminatory open access was

recognized. The same is true of wires business in distribution, although supply of electricity

can be competitive.

The number of different generation companies that directly compete with each other

depends on the strength of the transmission system and the capacity of interconnectors

between various states and regions. The present Indian reality is that although many states

and regions have internally densely meshed networks with mostly adequate capacity,

interconnections between regions are increasingly becoming meshed and strongly

integrated. The Long Term Open Access is granted with the guarantee that transmission

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systems shall be enhanced to cater to the demand for such access. Medium Term Open

Access and Short Term Open Access does not guarantee dispatch and hence access and

power systems fragment into smaller zones behind the congested interconnections, and

within these zones, the relevant market may be very concentrated.

Even when transmission systems are relatively free of constraints constraints markets can

be exploited by companies with generation capacity located in some parts of the country

because of either their location in the grid or because of their market share. In addition,

electricity being non-storable product with low demand responsiveness, markets are

distinguished by time – electricity at 0800 hrs is a different product that electricity at 1800

hrs on the same day. Congestion varies over time and space, changing the size of the

relevant market and the problem of market power from place to place and moment to

moment. All these special features of the nature of electricity have led to concern over the

existence of market power.

The possible consequences of such market power include not only wealth transfers

between consumers and service providers but also impacts on operational and investment

efficiency. The issue is of particular importance as the effects of market power can

substantially erode the benefits of deregulating an electricity market. Hence, as

competitive markets evolve, it is of vital importance that market power, i.e., the ability of

players either individually or in combination to set prices of electricity that is in detriment

to consumer welfare is mitigated. This would require close monitoring of market behaviour

to detect any abuse of dominant position in the market as a whole, or in any sub-market

within the overall electricity markets in the country.

The Commission is required by Section 60 of the Act to formulate regulations to prevent

abuse of market power. Under Section 60, the following conduct by Generating Companies

and Licensees is supposed to be regulated –

Dominant Behaviour,

Agreements or

Combination

Both the words “Agreement” and “Combination” are not defined in the Act. However

“Agreement” is defined in the Competition Act as

"agreement" includes any arrangement or understanding or action in concert,—

(i) whether or not, such arrangement, understanding or action is formal or in writing; or

(ii) whether or not such arrangement, understanding or action is intended to be enforceable

by legal proceedings;

The same definition has been adopted for the purposes of these regulations and also means

collusion. Combination has been defined in these regulations as:

The acquisition, directly or indirectly, of one or more generating company or licensee by

another generating company or licensee or merger or amalgamation of generating

company(s) or licensee(s) with another generating company or licensee shall be a

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combination for the purposes of this regulation.

Combination implies mergers and acquisitions, which in the case of Licensees under the Act

are regulated under the License agreements. Licensees are prohibited from entering into

merger agreements under Section 17 of the Act without the explicit permission of the

Appropriate Commission. In case of generating companies Section 17 of the Act would not

apply, but any combination or agreement by such generating companies would be open to

investigation under regulations framed under Section 60, if required.

If circumstances require, the Commission may need to monitor conduct of not only inter-

state generating companies and licensees but also deemed licenses and license exempt

entities. Certain state governments are also involved in purchase and re-sale of power. Such

state governments are also deemed licensees under the third proviso of Section 14 of the

Act, which is stated below for reference:

Provided also that in case an Appropriate Government transmits electricity or distributes

electricity or undertakes trading in electricity, whether before or after the commencement of

this Act, such Government shall be deemed to be a licensee under this Act, but shall not be

required to obtain a licence under this Act.

Insofar as such activities of deemed licensees are concerned, these regulations would

automatically extend to such deemed licensees. Further, under these regulations the

Commission may seek data from other entities like NLDC, RPC and hence in that sense

these regulations apply to entities mentioned here.

The regulations would cover both explicit and tacit combinations and agreements.

Coverage of tacit agreements or combinations is important since it is often the case that

market participants enter into informal agreements and understanding that can potentially

have negative impact on competition and consumer welfare. Thus, when there is

circumstantial evidence of any covert or tacit agreement or combinations, the process

specified under these regulations would come into effect.

As mentioned, detecting and proving the existence of market power in electricity markets

is a complex activity. A range of tools, techniques and measures - some drawn from

standard industrial organization theory, some especially developed for electricity markets -

are employed to varying degrees by the different market monitors and regulators

throughout the world. These need to be considered in the regulation of competitive

markets in India, and correspondingly the process and institutions involved have to have

the tools, knowledge and processes to undertake the same.

3. What is adverse impact on Competition?

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Through these regulations, the Regulatory Commission can issue directions in the event of

anti-competitive agreements, abuse of dominant position, or anti-competitive

combinations entered into by any Generating Company or a Licensee including

Transmission, Distribution, Traders at the inter-state and intra-state level.

Anti-trust / Competition Acts/ Regulations globally have taken either of the two stances –

to maximize (i) Total Welfare or (ii) Consumer Welfare. While the former approach seeks

to maximize efficiency, the later looks at equity. In the context of political economy of any

country, the Judges adjudicating Anti competition cases and politicians where ever involved

have asked the question – “How does it impact consumer prices and reliable provision of

quality service?” In the light of these arguments, the present regulation focuses on

“Consumer Welfare”.

However, if certain conduct is necessitated in compliance of the directions of the load

dispatch centre or any provision of the Indian Electricity Grid Code or Grid Code adopted by

any state transmission utility, such conduct shall not invite penalty under these regulations.

Appropriate LDC shall certify such conduct when directed by the Commission in the matter

of any investigation or otherwise.

Further, in case any conduct contributes to improving the generation, transmission,

distribution, supply or trade of electricity, promotes technical progress, while allowing

consumers a fair share of the resulting benefit, or affords such enterprises the possibility of

eliminating competition in respect of a substantial part of the relevant market which

results in an improvement of consumer welfare – such conduct will not be prohibited

under these regulations. This essentially connotes that if any conduct which is exclusionary

but not exploitative may be allowed by the Commission if it deems the same to be in

overall interest of consumer welfare and competition over a period of time. Thus, before

prosecuting any entity under these regulations it will be essential to demonstrate that the

conduct is exploitative and harms consumer welfare.

3.1 When can an agreement be Anti-competitive?

The list of possible impacts of an anti-competitive agreements provided in the Regulations

is indicative and not all inclusive. An agreement may be construed to have an anti-

competitive impact if, it leads to

(a) creation of barriers to new entrants in the market;

Example/Explanation: Agreements between a generator and a distribution company,

belonging to the same Group. Distribution Company may not enter into long term PPAs with

any other generator in anticipation of its own (parent company’s) generation expansion

plans.

(b) driving existing competitors out of the market;

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Example/Explanation: A generator may sign LTOA/STOA agreement for transfer of power

from point A to point B, with the intent to congesting the transmission corridor – thereby

causing market splitting. If the generator has another power plant at location B – which, in

this case, will be the “high price” region of the congested network – then the generator

might gain from the high prices caused due to congestion.

In doing so, the generator would have driven some generators out of the market. This is

explained diagrammatically below:

Example/Explanation: In case a high capacity transmission corridor is planned in

anticipation of large generation capacity addition in a region. Initially a commitment is

received from 4 generating companies. However, two of these back out because of various

reasons (increasing coal prices / un-availability of gas, etc.) and do not set up power plants.

This could also be a strategic decision by these generators to inflict high transmission

charges on generators who actually build their power plants and make them un-competitive

in a state which has called for case-I bids.

(c) foreclosure of competition in the market;

Example/Explanation: When a PP agreement between a Generator and buyers forecloses

the market to a new entrant, long term consumer interest is likely to be adversely affected.

(d) impact on long term planning;

Example/Explanation: A tacit agreement between major power plant developers to

share states where they would set up power plants. The transmission planning would

A

B

B1

Generator B and B1 belong to the same company. Generator

A is an intrinsically a cheaper generator. Generator B gets

LTOA/STOA for transfer from node B to node B1. It

deliberately bids a very low price (close to zero) on the

exchange because it knows that if it generates at a certain

level it will be able to congest the network – and generator

A, though intrinsically cheaper, would have to be backed

down.

The loss that B generates by bidding low (and if the MCP is

also low consequently), it is able to make up the loss due to

higher price in region where B1 is located.

In this case, due to a strategic LTOA/STOA agreement, B is

able to prevent A from operating in the market – this is also

to the detriment of the consumers

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consequently change and may lead to higher costs for any new developer who desires

to set up generation capacity.

(e) impact on quality of supply;

Example/Explanation: A tacit agreement between two distribution companies (having

access to the consumers in the same region) where they decide to cut costs by lowering

quality of supply and share consumers in equal measure. Such distribution companies may

even operate in tandem to increase “information asymmetry” between the regulator and

themselves on quality and cost of supply.

(f) impact on market development;

Example/Explanation: Generators agreeing not to invest in new technology which could

have brought down the cost of producing electricity. This will restrict market development.

(g) accrual of benefits to consumers or generating company or licensee;

Example/Explanation: Any agreement between generators/developers of transmission

lines/traders which increases consumer surplus is pro-competitive.

3.2 What are the considerations in detection of abuse of dominant

position?

Essentially, when a player is capable of operating behaviourally independently of other

players in the market and misuses this capability to reduce/ suppress competition in the

market – abuse of dominant position may be construed. While the indicative mechanisms

for determination of abuse of market power are deliberated in the Annexure, this section

broadly highlights the rationale behind various considerations of the Commission as

referred to in the Regulations.

Behavioural independent operation connotes the ability to sell a quantity in the market at a

price and quality level which is “significantly” different from that of other players. Also, the

player under investigation should be able to “maintain” such levels of quality or price for a

“significant” duration.

While examining an allegation of abuse of dominant position, the Commission has to look

into two elements:

(i) Whether the accused entity is dominant in the relevant market?

(ii) If yes, whether the accused entity has abused its dominant position.

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The Commission may consider (not an all inclusive list) the following factors while deciding

whether an enterprise is dominant:

(a) market share of the licensee or generating company;

Example/Explanation: Usually a dominant player is one who has the highest market share.

This is usually the first screen in all anti-competition investigations.

(b) size and resources of the licensee or generating company;

Example/Explanation: Installed capacity, control over the supply of raw materials or control

over distribution network can be factors.

(c) size and importance of the competitors (including their ability to increase output

within the relevant time period);

Example/Explanation: Size is always relative. Accused entity can be considered dominant

only if it competitors are much smaller. For instance,in electricity markets, if a generator

reduces its output in a probable case of abuse of market power, what also needs to be

considered is the ability of other generators to ramp up their levels of generation and supply

it at the point of requirement (which will be subject to technical transmission constraints).

(d) level of concentration in the market;

Example/Explanation: Large number of similarly sized players ensures healthy competition.

Chances of abuse may be higher in a highly concentrated market. Concentration in the

market may be measured using economic instruments like HHI index, importance of which

is explained in the Annexure.

(e) supply capacity of the competitors;

Example/Explanation: It is important to analyse the capability of the competitors to fulfil

the demand while analysing the issue of dominance. If competitors have the capacity to

fulfil the demand even in the absence of the subject entity, the subject entity may not be

dominant. In electricity markets indices such as Residual Supplier Index, Benchmark Analysis

etc – which are explained in the Annexure, are used for determination of market size and

abuse.

(f) economic power of the licensee or generating company including commercial

advantages over competitors;

Example/Explanation: Transmission system ownership and operation are separate

activities. However if the ownership is the same, then impact of such joint ownership and

associated commercial interests will have to be kept into consideration in various

investigations. The Commission will have to ascertain whether the control over inputs,

generation, transmission and distribution lies in the same hands. Such groups will have

commercial advantage over those who are not so “integrated”.

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(g) vertical integration of the licensee or generating company or sale or distribution

system of such licensee or generating company;

Example/Explanation: Vertical integration between a distribution licensee and a generation

company may lead to problems of open access for IPPs / large consumers and offers

advantage over non-vertically integrated entities.

(h) Dependence of consumers or licensee or generating company for supply of

electricity and services related thereto;

Example/Explanation: Dependence of customers on a supplier is likely to make the supplier

dominant.

(i) monopoly or dominant position whether acquired as a result of any statute or by

virtue of being a Government company or a public sector undertaking or otherwise;

Example/Explanation: Certain entities may enjoy monopoly or dominant position by virtue

of a statute or being or having being a Government company or a public sector enterprise

or any other such reason. In a recently opened up sector like electricity, this becomes

important. .

(j) entry barriers including barriers such as regulatory barriers, geographical barriers,

financial risk, high capital cost of entry, marketing entry barriers, technical entry barriers,

economies of scale, high cost of substitutable service for consumers, licensee and

generating companies;

Example/Explanation: Presence of entry barriers increases the ability of an entity in the

market to become dominant. These factors are explicitly considered in the formulation of

various indices and models, as discussed in the Annexure, for defining markets and

determination of abuse.

(k) countervailing buying power;

Example/Explanation: There are very few buyers in long term markets in India – mainly the

state distribution utilities. This can give the buyers significant market power on the buying

side or countervailing buying power. Hence, a generator inspite of being a large player, may

not be in a position to exploit the distributor.

(l) market structure and size of market;

Example/Explanation: These are important considerations in determination of not only the

detailed indices – discussed in the Annexure – but also the market share and the indices of

concentration.

(m) social obligations and social costs;

Example/Explanation: Market share – may not always be acquired strategically – but may

be due to the requirement of the state government to serve all consumers including those in

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remote areas – irrespective of the commercial implications. In such cases, market share of a

player may be high because of Universal Service Obligation or due to the pressure of the

state government to supply to various categories of consumers under schemes like RGGVY.

In such instances, the entity may not be treated dominant.

(n) relative advantage, by way of the contribution to the economic development, by the

licensee or generating company enjoying a dominant position having or likely to have an

adverse effect on competition;

Example/Explanation: Development of a power plant in a certain area by a company may

be due to concerns pertaining to economic development of that area. The development by a

single firm may be because other firms are not interested in investing in that region. Such

firm may not be considered dominant in spite of scale of operation in that particular area

for the purposes of these regulations.

(o) relative advantage, by way of contribution to the security and reliability of the

power system.

Example/Explanation: A generator close to load centre may be a small marginal generator

with a small market share – but such generation may be critical for supplying reactive

power – absence of which could cause disruption in grid operation. In such a case,

irrespective of the market share, such a generator becomes a dominant player.

Considerations in the case of Combinations are similar to those discussed above.

4. Defining the Appropriate Markets1

Appropriate market definition is in most cases the starting point for anti-competition /abuse

of dominant position analysis. This is particularly true for electricity where product and

infrastructure characteristics often result in constraining the markets and splitting them into

sub-markets by time, geography, network hierarchy, and nature of service involved.

However, from a methodological perspective, defining markets is not about studying real

phenomena but rather must be understood as an instrument to reduce the complexity of

market interaction. In the words of Geroski (1998)2, “[m]arket definitions are a way of

intellectually organising the way we think about the economic activity we observe, and are

not inherent in the nature of things”. It is possible for players in such sub-markets to be

1 This section draws upon Kai Huschelrath, 2009, Competition Policy Analysis – An Integrated Approach,

Physica-Verlag Heidelberg

2 Geroski, P. (1998), Thinking Creatively About Markets, International Journal of Industrial Organization 16, 677-

695

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acting in conjunction or in tacit combinations in a manner that restricts market access for

other market participants. Hence it is often important to take an objective view while

assessing market power and impact on consumer welfare. Although there may be

measurable relationships between a lot of different products ( for example power in Long

Term, Medium Term and Short Term markets may be inter-related and hence reflect non-

zero cross-price elasticities), identifying the relevant market is about identifying the most

‘substantial’ and ‘relevant’ of these relationships. It immediately follows from this that there

cannot be an ultimate or predetermined way to delineate market boundaries, and strict and

narrow definitions need to be avoided. Choosing and applying a meaningful delineation

methodology always depends on the underlying motivations behind such an exercise.

The object of these regulations is to regulate the conduct of firms which harm or could

potentially harm competition. From the viewpoint of competitive strategy which firms

develop, for instance, market definition and market analysis are integral parts of the

strategic planning process which generally aims at creating (and sustaining) competitive

advantages. It is therefore sometimes pertinent that in order to delineate markets, regulator

thinks akin to a rational profit maximizing firm that wants to develop a competitive strategy

for itself. Such a strategic planning process typically starts with the identification of relevant

market dimensions, such as functions, technologies, customer groups, geography and time.

Combinations of these market dimensions are then taken to delineate so-called markets.

Based on such an initial categorisation of the ‘basic needs’, the company has to delineate

‘competitive arenas’ by answering the questions, “Who are our customers and what are

their needs?” (i.e., assessing demand substitution) – For Example Industrial customers could

substitute grid electricity with captive generation in medium to long term – and; “Who are

our competitors and what are their strengths and weaknesses?” (i.e., assessing supply

substitution) – For example, (1) generation in a particular region could be substituted not

only by generation in that area or geographically contiguous area but also by transmission

into that area, (2) generation from IPPs / Central Sector Generating Stations could be

substituted by generation from state owned generators, (3) Large industrial consumers

routinely replace energy from their respective DISCOMs with energy from the power

exchanges if they can procure from the exchanges below a certain price.

Subsequently, the attractiveness of the competitive “markets” need to be assessed, based,

for instance, on Porter’s (1995)3 five forces paradigm consisting of rivalry among existing

firms, the threat of substitutes, buyer power, supplier power, and the threat of new

entrants. Given this evaluation of attractiveness, the company subsequently has to make a

choice on the actual markets it would like to serve. Subsequently, customer segmentation

and product positioning within the chosen markets are important operational tools to

maximise profits.

3 Porter, M. (1995), Wettbewerbsstrategie, Frankfurt am Main.

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Finally, the success of the chosen strategy needs to be evaluated constantly by focusing on

changes in indicators such as the relative competitive position and the likely future growth

potential. As markets underlie constant changes – driven, for instance, by changes in

regulations, development of transmission networks, change in technology, changes in

customer preferences and actions of rivals (tying potential consumers into long term

contracts, new investments, acquisitions, development of coal mines etc.) – it is pivotal for

reaching a sustainable competitive advantage to constantly review and possibly redefine

market dimensions, competitive arenas and supplied markets. Firms typically see this

‘redefinition of the market’ by introducing new products or addressing the (new) needs of

(new) customers as the ‘key to strategic innovation’. Thus the definition of markets keeps on

changing even for the firms being investigated for their conduct.

The basic motivation for delineating markets for the regulatory commission may also be

different. Although as discussed above, regulator might develop an interest in the way the

strategically behaving firms decide their conduct, such an interest would purely be

motivated by the need to assess “the full set of competitive forces that operate in the

market”. The basic aim of the Commission is definitely not ‘to create and sustain a

competitive advantage’ but to come to conclusions on the actual or likely future anti-

competitiveness of certain suspicious conducts. Delineating the relevant market is typically

a necessary precondition to allow such conclusions as it identifies the essential competitive

constraints a firm or group of firms faces or would face. These boundaries may be needed

in certain cases to assess whether a firm or a group of firms enjoys (or would enjoy)

economic power in relation to electricity generation or open access services or other

services it supplies (or would supply). However, rigidity of such definitions should not

preclude any investigation which aims at determining the impact on consumer welfare.

Hence the Commission would prefer being flexible about the definition of markets.

5. Assessment of Market Power – Use of Indicators

In any investigation, the common theme of the questions, which the CMU may attempt to

answer are – (1) What is the harm to / distortion of competition?, (2) How does it reduce

consumer welfare? And (3) How Price, Output and Quality are impacted by the suspect or

potential abusive conduct? - If abuse is interpreted in terms of increasing prices and

reducing output – here “output restriction” could embrace issues of quality and innovation

and not just quantity.

Assessment of market power in power markets is typically based on indices and

methodologies which are classified as:

(1) Structural Indices

(2) Behavioural Indices

(3) Simulation Models

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Structural Indices

Some of the structural indices typically used are:

a. Four Firm /Eight Firm Concentration Index – Sum of the Market Shares of top four/eight

firms in the market

b. Herfindahl-Hirschman Index (HHI) – Sum of the square of market shares of all the firms in

the market

c. Pivotal Supplier Indicator and Residual Supply Index - a measure of how critical a supplier

is to reliable and secure power system operation

d. Residual Demand Analysis – Based on the demand curve faced by each supplier which is

derived by subtracting from the total demand curve, the supply by all other suppliers taken

together.

While structural indices such as four/eight firm concentration indices and Herfindahl-

Hirschman Index (HHI) depend on definition of markets and are static measures of position

of various players in the market, other measures take into account not only the dynamic

nature of power systems operation but also the behaviour of suppliers and consumers to a

certain extent. Market share based indices are therefore increasingly being used just as

“initial screens” in anti-competition investigations.

Further, the structural indices are reflective on market power and not abuse of market

power. Abuse can be inferred if the structural characteristics cause changes in behaviour or

conduct of players which is anti-competitive.

Behavioural Indices

Behavioural analyses that are typically used are:

a. Bid-Cost Margins

b. Net Revenue Benchmark Analysis

c. Withholding Analysis (Output gap analysis)

Structural indices can result in higher bid-cost margins, where players attempt to exploit

their position in the market and earn supernormal profits. However such a causation needs

to be established through various statistical techniques.

Revenue Benchmarks involve establishing the base level of revenues a firm would earn in a

competitive market.

The dominant position of a firm in the market – determined through either of the structural

indices – may result in the firm indulging in either physical or economic withholding. The

effects of the two may however be the same.

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Each of the above methods is explained in detail in Annexure 1.

Simulation Models

Simulation models do not require an a-priori definition of markets and are amenable to

direct computation of “Consumer Welfare” – which is the object of anti-competition

analysis. Simulation models are being increasing used for antitrust investigations in the US

and elsewhere. Such models facilitate modelling of consumer and producer behaviour and

also the technical constraints posed by power system operation. Some of these models also

have limitations – as some of these may result in multiple Nash Equilibria thus making the

conclusion of the impact of a conduct difficult.

Simulation models facilitate modelling of “Competitive Benchmark Models” and “Oligopolitic

Models” with transmission constraints. These mechanisms (with appropriate references) are

described in detail in the Annexure.

Thus while the Commission (and the CMU on its behalf) may rely on these methods, these

may not be used as sole tools in arriving at decisions in any investigation.

6. Investigations under the Regulations and Issue of Directions

The Commission may initiate an investigation under these regulations on receipt of a

petition or on suo-moto basis. In case of receipt of a petition on abuse of market power or

any agreement or combination that is likely to have harmful impact of competition, the

Commission will undertake the necessary process of admission of the petition as per the

Conduct of Business Regulations. If the Commission is prima-facie satisfied about the

admissibility of the case, further processes under these regulations would follow.

Even as normally the investigations of the Central Commission would be directed towards

markets and entities directly regulated by it, the Commission may investigate entities

otherwise regulated by SERCs if their conduct impacts power markets at National and

Regional levels.

Upon admitting a petition, the following steps would be involved in establishing the impact

of the proposed or possible agreement or combination:

1. The Commission will make an initial assessment on whether any agreement or

combination by the entities covered under these regulations has the potential to

adversely affect competition in the electricity sector. Qualitative and quantitative

indicators may be used for this purpose as appropriate. Potential indicators have

been discussed subsequently in this Explanatory Memorandum;

2. Once the potential to harm competition and consumer welfare is ascertained,

consistency of the actions of the entity or entities with law or policy would be

ascertained;

16

3. Thereafter, it would need to be established that the entity or entities in question

had the ability to adversely affect prices or consumer welfare;

4. If the ability to adversely affect prices (which may, for example, include short term

predatory pricing by a dominant player) or consumer welfare is established, then

the quantification of the impact would become necessary;

5. The Commission shall then provide the necessary directions under the regulations.

These directions may be accompanied by fines imposed on the investigated entities

The Commission shall monitor and secure compliance through the provisions u/s

129, 142 and 146 of the Act and appropriate regulations framed thereunder.

7. Process for Investigations under these Regulations

Investigation will commence in any case on:

(a) receipt of notice under sub-section (1) of section 17 of the Act (in the case of

combinations) ;

(b) receipt of a complaint from any person;

(c) a reference made to it by the Central Government or a State Government or a

statutory authority.

For the purpose of specific investigations under these regulations, the Commission shall

appoint an Investigating Officer (with powers as under Section 97 of the Act), under these

regulations.

On receipt of the directions of the Commission on a petition admitted or being considered

for admission, the Investigating Officer shall undertake necessary investigations on the

various facts of the case and, through a process that incorporates necessary rigour,

determine whether prices in the competitive markets or consumer welfare may have been

affected by the actions of a dominant player or by players entering into an agreement or

combination that has caused or may cause adverse effects on electricity prices in the

relevant market or on consumer welfare. The Investigating Officer, to the extent required

and is feasible, shall also compute the extent or scale of such adverse impact. Further, the

Investigating Officer shall not only look at the immediate impact on prices and consumer

welfare, but also on the long term impact that such agreements and combinations may

cause on competition, competitive markets and prices and development of the sector. The

Investigating Officer, with assistance of the support staff of the Commission and cosultants

shall conduct a case-specific enquiry in each case appropriately utilizing various indices and

techniques for assessment of abusive conduct. Indicative list of such indicators have been

discussed in Annexure of this Explanatory Memorandum.

The Commission, if it deems necessary, may also require the Investigating Officer to review

and opine on merger proposals of licensees received by it u/s 17 of the Act.

17

The Commission shall commence investigations only after ascertaining if the case has been

investigated or is under investigation or has been filed for being investigated by the CCI. In

such cases the Commission may refer the case to, or confer with, the CCI. The Commission

may seek also inputs from CCI for its investigations.

All findings of the Investigating Officer on a petition referred to it and recommendations

thereon, or on periodic review of markets, shall be presented to the Commission in writing.

The Commission may accept or modify the recommendations made by the Investigating

Officer for the issuance of final orders or directions as it deems fit.

8. Securing Compliance with the Directions of the Commission and

Imposition of Penalties

Consequent to the investigations, if the Commission, is satisfied that a licensee is

contravening, or is likely to contravene, any of the conditions mentioned in his licence or

conditions for grant of exemption or the licensee or these regulations, or if the generating

company has contravened or is likely to contravene any of the provisions of these

regulations, the Commission shall give such directions through appropriate orders as may

be necessary for the purpose of securing compliance with that condition or provision.

In accordance with Section 129 of the Act, while giving direction the Commission will duly

consider the extent to which any person or the consumers as a class is likely to sustain loss

or damage due to such contravention.

Before issuing any direction the Commission shall serve notice in the manner as may be

specified to the concerned licensee or generating company. This notice will be published on

the Commission’s website and also served to the entity being held guilty of contravention of

the regulations. The Commission shall duly consider suggestions and objections from the

concerned licensee or generating company and the persons, likely to be affected, or

affected.

If that Commission is satisfied that the licensee or generating company has contravened

with these regulations or any direction issued by the Commission under these regulations,

the Appropriate Commission may after giving such person an opportunity of being heard in

the matter, by order in writing, direct that, without prejudice to any other penalty to which

he may be liable under the Act, such person shall pay, by way of penalty, which shall not

exceed one lakh rupees for each contravention and in case of a continuing failure with an

additional penalty which may extend to six thousand rupees for every day during which the

failure continues after contravention of the first such direction. These are in accordance

with the provisions of Section 142 of the Act.

18

Whoever fails to comply with any order or direction given under this regulation

within such time as may be specified in the said order or direction, or contravenes or

attempts or abets the contravention of any of the provisions of this regulation, shall be

punishable with imprisonment for a term which may extend to three months or with fine,

which may extend to one lakh rupees, or with both in respect of each offence and in the

case of a continuing failure, with an additional fine which may extend to five thousand

rupees for every day during which the failure continues after conviction of the first such

offence, as specified in Section 146 of the Act.

Further, if any matter is referred by the Commission to the CCI, the provisions of the

Competition Act 2002 will apply, and the penalties applicable will be determined by the CCI.

9. Role of Sector Regulator and relationship with Competition

Commission of India

Promotion of competition and monitoring the conduct of players in the electricity sector

requires:

Understanding the regulations which govern and determine the conduct of various

players

Understanding of the impact of the conduct on efficiency, price, quantity and quality

of supply, innovation, investment, entry and exit in the sector

The need for regulation of competition by sector regulators in complex businesses like

electricity arises from the product and market characteristics described in the foregoing

sections. The conditions of competition in these markets can be very typical and can vary

widely by geography, scope of services of the market participants, etc. Wholesale power

markets, for example, display very different traits from retail markets. Generation is

completely differentiated from transmission and distribution. Trading as an activity displays

very different characteristics from generation of electricity (the investments, and hence

entry barriers, are considerably lower in trading). Hence it requires specific and specialised

knowledge to regulate competitive electricity markets. The Act recognises this. Having

said so, it is also important for the Commission to relate to the overall principles of

regulation of competition followed in the country. Thus sector regulators, including this

Commission, would have to work closely with the Competition Commission of India (CCI)

on issues pertaining to abuse of Market Power, agreements and combinations which are

anti-competitive and abuse of dominant position.

CCI is a specialist body designated to ensure competition across sectors in India.

Cooperation between the CCI and ERCs will minimize the possibility of inconsistent

19

reasoning between sectoral and general competition regulations. Further, it makes

available, and reduces duplication of resources to deal with very specific economic issues,

such as definition of markets etc. The Competition Act provides for such a relationship

under sections 19(1) and 21(2) of the Competition Act, which are reproduced below for

reference:

“19.(1) The Commission may inquire into any alleged contravention of the provisions

contained in subsection (1) of section 3 or sub-section (1) of section 4 either on its own

motion or on—

(a) 29[receipt of any information, in such manner and] accompanied by such fee as may be

determined by regulations, from any person, consumer or their association or trade

association; or

(b) a reference made to it by the Central Government or a State Government or a statutory

authority.[Emphasis Added]”

“21.(1) Where in the course of a proceeding before any statutory authority an issue is raised

by any party that any decision which such statutory authority has taken or proposes to take

is or would be, contrary to any of the provisions of this Act, then such statutory authority

may make a reference in respect of such issue to the Commission:

31[Provided that any statutory authority, may, suo motu, make such a reference to the

Commission.]

32[(2)On receipt of a reference under sub-section (1), the Commission shall give its opinion,

within sixty days of receipt of such reference, to such statutory authority which shall

consider the opinion of the Commission and thereafter, give its findings recording reasons

therefor on the issues referred to in the said opinion.]” [Emphasis Added]

There already are instances, where cases have been referred on specific issues by

Maharashtra Electricity Regulatory Commission to the Competition Commission of India

and also references have been sought by CCI from Delhi Electricity Regulatory Commission

in investigation of various cases. This two-way cooperation – which is facilitated by the

Competition Act, is likely to grow as markets evolve and become more mature in power

sector in India.

20

Annexure: Key tests and Indicators of Market Power and Market

Abuse

1.1 Defining Market Power

While the delineation of the relevant market consciously abstracted from intra-market rivalry by

assuming a hypothetical monopolist, the assessment of market power basically has to release this

assumption and aims at assessing actual or potential market power of firms or groups of firms within

the relevant market boundaries. In general, it is no exaggeration to see the assessment of market

power at the core of anti-competition policy – simply because anti-competition policy’s main

concern is the creation, exploitation and maintenance of market power. From a practical

perspective, the concept of market power is of direct relevance in the definition and identification of

monopoly as well as in the assessment of cartels and collusion.

Furthermore, it is used in merger control as well as in the assessment of vertical restraints

(Fingleton, 2000; Hay, 19914). In particular, assessing market power is important because it is

believed to play a fundamental role in determining 1) whether transactions will likely result in future

anticompetitive effects; 2) whether ambiguous business practices could have resulted in

anticompetitive effects; and 3) whether efficiencies have been or will be passed on to consumers

(McFalls, 1997).

The importance of market or monopoly power for anti-competition analysis is reflected in a

multitude of definition and characterisation attempts by economists and lawyers (Hay, 1991;

Fingleton, 2000). A fairly general definition attempt specifies that a firm has market power if it can

act (to a significant extent) independently of competitors, entrants, suppliers or customers. Although

this ‘acting independently’ is typically related to the possibility and profitability of price increases,

market power might also be exercised if a firm is able to reduce product quality or restrict customer

choice without losing enough sales to make such a downgrading unprofitable. Daskin and Wu

(2005)5 took a closer look at definitions of market power applied by US courts over the last couple of

decades. The authors identify the following four influential definitions, each of which has different

implications for antitrust policy:

Definition 1: “The power to control prices or exclude competition”

Definition 2: “The ability of a single seller to raise price and restrict output”

Definition 3: “The ability to raise prices above the levels that would be charged in a competitive

4 Hay, G. (1991), Market Power in Antitrust, Antitrust Law Journal 60, 807-827.

5 Daskin, A. and L. Wu (2005), Observations on the Multiple Dimensions of Market Power, Antitrust, Summer

2005, 53-58.

21

market”

Definition 4: “The ability of a firm or group of firms within a market to profitably charge prices above

the competitive level for a sustained period of time”

To a certain extent, the four definitions describe the evolution of the antitrust interpretation of

market power. The first definition surely is the broadest of the four – likely too broad to act as a

helpful guide for practical antitrust policy. Almost every firm has some control over price and might

have the power to exclude some competition – without typically harming competition in a way that

would justify antitrust interventions. The second definition somehow refines the first definition by

focusing on price increases and output reductions. Although this definition comes closer to an

applicable definition of market power, it especially lacks fixing a competitive benchmark that helps

to distinguish between price increases due to cost increases and price increases due to market

power (Daskin and Wu, 2005). The third definition is a refinement of definition two because it adds

the competitive benchmark, however, without refining what might constitute such a competitive

benchmark. Finally, the fourth definition – which is actually used in contemporary antitrust policy in

US – adds two important conditions to the definition: the price increase must be profitable (i.e., the

firm must have an incentive to raise price) and the price increase must be sustainable for a long

period of time (i.e., it is unlikely that the reactions of existing or new competitors will make the price

increase unprofitable in the short or medium term; see Daskin and Wu, 2005, Stoft 20026). The

European Union defines Significant Market Power (SMP, specifically, in communications markets) as

equivalent to the concept of dominance. An undertaking is defined as having SMP if, alone or jointly

with others, it has “the power to behave to an appreciable extent independently of competitors,

customers and ultimately consumers”. There are, however, a number of variants of this definition.

Most definitions include the requirement that the exercise of market power be profitable. If this was

not the case, for example, a company with a single large base-load plant that shuts off its plant and

that has no other market positions could be defined as exercising substantial market power (in terms

of ability to affect the market price) even though this strategy would be completely unprofitable for

the company. In order to fully determine whether an action is profitable, however, one would need

to know the complete portfolio position of the company. This is a very onerous requirement. As

such, most market power indices based on company conduct typically rely on the assumption of

rationality: if we assume companies are profit-maximizing, then we can assume that observed

company conduct which alters prices is profitable for the company.

The above example also raises the question of whether a company’s behaviour that appears

to profitably exploit market power is necessarily intentional. Plants do break down and it

would seem unfair to penalize a company just because that breakdown happened to be

profitable for the company. Statistical measures can sometimes be used to examine this

issue. For example, if the breakdowns of a plant are correlated with periods when such

breakdowns significantly raise prices, then we may infer that the conduct is intentional and

not accidental. This statistical information can be used as a trigger for further investigation

6 Stoft, S. (2002), Power System Economics. Designing Markets for Electricity, New York.

22

or, depending on the burden of proof required for market power cases, used as prima facie

evidence for the existence of market power abuse.

Some definitions of market power include the provision that the ability to alter prices away from the

competitive level be maintained for a ‘significant period of time’. In the view of the U.S Department

of Justice (DOJ) and Federal Trade Commission (FTC), for example, this period is measured in years

(e.g. one or two years). However, experience with electricity markets has shown that huge transfers

of wealth can occur in the period of months rather than years. A short-lived but dramatic price

increase can injure consumers and competition as much as a longer-lived but more modest price

increase. As such, market power definitions for electricity markets, such as with FERC’s definition in

the Standard Market Design (SMD), do not include a specific time limitation. In the UK, the main

regulatory agency Ofgem (the Office of Gas and Electricity Markets) unsuccessfully tried to introduce

a so-called Market Abuse Condition in the licences of generators which included the recognition of

both the magnitude and duration of market power. The condition stated that a generator had the

ability to exercise market power if it could bring a wholesale market price change of:

1. 5% or more for a duration of more than 30 days in a one-year period;

2. 15% over ten days in a one-year period, or

3. 45% over 160 half-hours (approximately 1% of the year) in a one year period.

These periods did not have to be continuous periods. The effect of this test is to define market

power as the ability to increase wholesale market prices in such a way as to increase annual

wholesale market revenue by rather less than ½ of 1 percent. This might seem an unreasonably

stringent test of potential market power, but the idea of relating the potential price increase to

annual revenue is clearly sensible.

There are a number of implications and distinctions that arise from the above definitions of market

power. First, high prices, while often recognized as a symptom of market power, do not prove that

market power exists. High prices can be consistent with a well-performing, competitive market

where supply is scarce. Similarly, high profits for an individual generator may also be due to a

number of factors other than exercising market power. It should also be noted that market power

may be exercised so as to lower prices below the competitive level. This may occur with a dominant

generator which is operating a predatory pricing strategy or be the result of monopsony power of

consumers. Low wholesale prices may also be indicative of other structural problems with DISCOMs

shedding demand instead of purchasing electricity above their reservation levels.

Based on this delineation of the term market power, the next step on the operational level is analyse

and assess possibilities to measure market power. In general, economists have developed direct and

indirect approaches to assess and quantify market power.

1.2 Assessment and Quantification of Market Power

Assessment and quantification of market power in power markets requires an analysis of the

strategies firms may use for exercising market power. How market power is exercised depends on

the exact structure of the market, and in particular the price-setting mechanism. However, the

primary methods of exercising market power are:

23

(1) Physical or quantity withholding, which involves deliberately reducing the output that is bid into

the market even though such output could still be sold at prices above marginal cost. Withholding

can be done through not bidding, de-rating, or declaring unit outages in generation, or withholding

open access in transmission and distribution.

(2) Financial or economic withholding, which involves bidding in prices higher than the competitive

bid for the particular unit.

(3) Transmission related strategies, which involves creating or aggravating transmission congestion

in order to raise prices in a particular zone. For Example – Consider two Generators one located in

Andhra Pradesh and another in Tamil Nadu and both are owned by the same company. Generator in

Andhra Pradesh is made to bid low so as to congest the link between S1 and S2. Knowing that the

transfer capability between S1 and S2 would be constrained, the generator in Tamil Nadu –could bid

high in the DAM. This raises the DAM price in Tamil Nadu/Kerala and the generating company more

than makes up for the loss in Andhra Pradesh with the gains in Tamil Nadu. Insufficiently unbundled

generators can achieve this through outages of transmission, understating transmission

ratings/capacity, and dispatch of generation deviating from marginal cost; else generating

companies with power plants located in different regions could do this.

Detecting market power is never an easy task and doing so in electricity markets is no exception.

However, there are features of electricity markets that assist in the detection of market power that

are not present in most other markets. For example, in electricity pools and most spot-markets

generators bid their willingness to provide output for their entire range of market prices (whereas in

other markets we typically only observe the market clearing price and quantity data). One useful

consequence is that it is possible to construct actual residual demand curves for individual market

participants. The elasticity of this residual demand curve provides a direct measure of potential

market power, as discussed below. Another feature of most electricity markets is that technological

data such as generation heat rates and capacity are often available to the Regulator because most

generation units were formerly state-owned or under a cost-regulation regime or are technologically

standard units for which there is publicly available cost data. Thus forming estimates of costs is

perhaps more precise than in other industries. Another useful feature of the electricity industry is

that the overwhelming contribution to short-run variable costs is the cost of fuel, for which prices

are usually readily available.

In classifying the various methods of detecting market power a useful distinction is between

techniques that are applied ex ante - looking for the potential for market power - and those that are

applied ex-post - usually looking for the actual exercise of market power. A second useful distinction

is between those techniques that are applied over longer time horizons, often in the context of

merger analysis or market design evaluation, and those techniques that are applied close to the real

time market, often in the context of immediately mitigating market conduct. Table 1 gives some

examples of the market power detection techniques, categorize under these two distinctions, which

will be discussed subsequently.

Table 1 - Categories of Market Power Detection Techniques

24

Ex-Ante Ex-Post

Long Term Analysis Structural indices, e.g. Market

share, HHI, residual supply

index - Simulation models of

strategic behaviour

Competitive benchmark

analysis based on historical

costs - Comparison of market

bids with profit maximizing bids

Short Term Analysis Bid screens comparing bids to

references bids - Some use of

structural indices such as

pivotal supplier indicator and

congestion indicators

Forced outage analysis and

audits - Residual demand

analysis

An ideal index of market power is one that provides in a simple number a measure of the ability to

exercise market power. The test of its suitability is its ability to predict the exercise of market power,

or its correlation with the excess of the market price above a reference benchmark competitive

level. On this criterion, some measures that work well for other markets perform poorly in electricity

markets, and more sophisticated measures are therefore required. In addition to the ex-ante and ex-

post measures of market power, the indices could be classified as structural indices, behavioural

indices and those based on simulation models.

1.2.1 Structural Indices

A natural starting point in discussing measures of market power is the structural indices of

traditional industrial organization theory. Some of the earliest work in market power in electricity

markets (e.g. Schmalensee and Golub, 1984)7 was based on analyzing market share and the

Herfindahl-Hirschmann Index (HHI). Criticisms of these measures, in particularly the appropriateness

of these static measures in a dynamic market such as electricity, has led to the development of other

indices which take into account demand conditions and not just the supply side (e.g. the pivotal

supply index). The aim of this section is to briefly review the features and applications of these

indices.

1.2.1.1 Market Share

Concentration indices are usually simple scalar metrics that measure the supplier concentration of a

market. The motivation behind these indices is that the more concentrated a market, the more

likely is the ability of its participants to exercise market power. The two most commonly used

concentration indices are market share and Herfindahl-Hirschman Index (HHI).

The market share concentration ratio is the percentage of market share of the largest n companies

in the industry. The number of companies, n, is often 4, but for the purposes of discussion here we

will assume that the index is used for a single company. Thus, if company A is producing 30 MW in a

7 Schmalensee, R. and Golub, B.W, (1984) “ Estimating Effective Concentration in Deregulated

Wholesale Electricity Markets ” RAND Journal of Economics, vol 15, N.1

25

market of 100 MW, company A is said to have a market share of 30%. Shapiro (1989)8 provides a

theoretical justification for the use of this index as a measure of potential of market power by

showing that a company’s profit is maximized in a Cournot equilibrium when the price-cost margin

(a measure of the exercise of market power, discussed later) is proportional to the market share of

the company and inversely proportional to the market-wide price elasticity of demand.

In order to calculate this index, some preliminary definitions need to be made which are not

uncontroversial. Firstly, the relevant product needs to be identified. In electricity markets the

choices can include energy production, energy plus reserves, short-term capacity or long-term

capacity. As mentioned above, electricity in different-15 minute blocks may not be readily

substitutable, so a time dimension may also be needed. As it is not always clear what is the most

appropriate product, many studies include a number of different market share indices based on

these products. The second preliminary definition concerns the geographic boundaries of the

market: who should be considered competitors of a company? A number of methods have been

employed. Two of the traditional approaches have been the classical ‘law of one price’ test and the

‘small but significant non-transitory increase in price’ (SSNIP) test.

In order to prosecute a company, regulatory authorities must show that the market share of the

company in question is above a certain threshold (market share screen) and that prices are excessive

relative to marginal production costs (price-cost test discussed latter). However, it is argued that in

the electricity market it may be more difficult to apply the market share screen than in other sectors.

In the US, FERC identified 20% as the benchmark for finding lack of market power, although there

were a number of cases where it approved market-based rates even where this threshold is

exceeded. European case law in normal markets defines significant market power (SMP) as

equivalent to dominance, and notes that market shares are not conclusive, but if no company has a

share greater than 25%, there is a presumption of a lack of SMP, and a finding of SMP normally

requires a market share of greater than 40%, with a share above 50% presumptive of SMP. Clearly

this is unlikely to be a useful test for electricity markets, which have very different characteristics

from normal markets. Indeed, in a recent merger inquiry, the Dutch Competition Commission (NMa)

imposed remedies to offset concerns of market power when the merged company would have had

less than 30% of the Dutch electricity market.

US regulator, Federal Energy Regulatory Commission, has relied on concentration measures to

analyze market power in the US electricity markets.

8 Shapiro, Carl (1989) „Theories of Oligopoly Behavior.‟ In Handbook of Industrial Organization, ed. R.

Schmalensee and R. D.Willig, vol. 1 (Elsevier Science Publishers) pp. 329–414.

26

1.2.2 Rationale for SSNIP Test for Market Size

Under the assumption that economic power exercised by firms is typically transformed into elevated

prices, the key for the derivation of anti-competitive markets lies in getting an understanding of

what factors constrain the pricing behaviour of firms. From a firm perspective, a price rise is

profitable as long as the increased price charged on the new lower quantity is greater than the lost

margin on the decrease in quantity.

It follows that the decrease in quantity caused by a price increase is the basic constraint a firm faces.

If the actual decrease in quantity is large following a small increase in price, it is likely that the ‘lost

margin’ effect overcompensates the ‘higher margin’ effect and – as a consequence – the respective

price increase would be unprofitable.

Application of the Market Share screen by the FERC

The US Congress introduced competition in wholesale power markets with the Energy Policy Act of 1992. The FERC

shifted its focus from cost-based ratemaking to attempting to create the conditions for competition. This transition

required FERC to modify its approach toward market power issues.

FERC has responsibility to ensure that rates for wholesale power sales are “just and reasonable”. FERC states that,

“market-based rates can be just and reasonable when the seller has no market power”. Therefore, FERC has the

responsibility to ensure that market power is not exercised. In 1992, FERC established a 20% market share threshold

for antitrust concern (safe harbor). FERC has revised its use of concentration measures in a merger review policy. The

core of FERC’s Merger Policy Statement of December 1996 was called a Competitive Screen.

Procedure of the Competitive Screen analysis

1. Identify relevant products:

• Short term capacity / Energy

Medium term capacity / Energy

Long term capacity / Energy

Other

2. Identify customers likely to be affected:

3. Identify feasible suppliers: Must be able to deliver product

• The delivered price test (physical delivery) - The Delivered Price Test is used to identify feasible suppliers. The test defines feasible suppliers as those suppliers that can deliver to a destination market at a price equal to or less than a five percent premium over the destination market price.

• Sufficiency of transmission

4. Analyze concentration:

Market shares and HHI’s

27

The consequential follow-up question which needs to be investigated is what factors determine the

decrease in quantity following a price increase?

1. On the demand side, DISCOMs resorting to load shedding, consumers switching to

alternative products (Long term /Medium Term/Short Term) or replacing DISCOM supply

with supply from short term markets might lead to the unprofitability of a certain price rise.

Further, high Day Ahead Market prices could trigger heavy unscheduled drawal.

2. On the supply side, rivals may begin to look for alternative products (say, if the entire LT

market is captured by a certain firm, rivals may invest in capacities which are better suited to

serve the requirements of MT/ST markets). This may lead to a decrease in quantities sold in

LT markets. Similarly when the prices in ST markets increase, the demand for advance

contracting capacities for supplying load following/peaking requirements may increase – if

there is an obligation to serve.

Based on this initial characterisation of the basic competitive constraints – supply and demand

substitutability – the small but significant non-transitory increase in price test (the SSNIP test) has

become the standard technique to identify the relevant anti-competitive market. The SSNIP test

asks: If all the generators in a particular geographical location combined into a single company,

could a price rise, say 5%, in that region be sustainable? The SSNIP test starts with a small candidate

market containing one or a narrow set of products and asks whether a hypothetical monopolist

controlling the product(s) in this hypothesised market could raise prices profitably and permanently

(i.e., at least twelve months) by a significant amount (i.e., usually 5-10%). If the answer is Yes, the

(set of) product(s) in the candidate market represent a well-defined market, because the constraints

by other products on the price-setting behaviour of the hypothetical monopolist are too weak to

make the price increase unprofitable. If, however, the hypothetical monopolist in the candidate

market cannot raise the price (profitably and permanently) by, for example, 5%, this speaks for an

effective constraint of its behaviour by the considered substitute, and it should therefore belong to

the same relevant market. When conducted in the context of electricity markets, the substitution

between long term, medium term and short term products is possible only when transmission

system is explicitly modelled.

This procedure of adding potential substitutes (downward sorted by assumed substitution potential)

has to be continued until a product is added which does not hinder the hypothetical monopolist to

raise its price permanently and profitably by 5%. This product remains in the candidate market and

the relevant market is constituted.

Consequently, following this methodology of the SSNIP test, the relevant market is defined as the

smallest collection of products with which a hypothetical monopolist could extract and maintain

some degree of market power (here 5% above the competitive price). In the words of Bishop and

Walker (2002)9, a relevant market is “the smallest set of products worth monopolising.”

The general usefulness of the SSNIP test for the delineation of markets is reflected in the adoption of

this methodology by many antitrust authorities worldwide (see Bishop and Walker, 2002, for an

9 Bishop, S. and M. Walker (2002), The Economics of EC Competition Law, London.

28

overview). Furthermore, the usefulness of the general framework can be exemplified by many

practical examples (see Stenborg, 2004)10. One prominent area where the application of the SSNIP

methodology helps to avoid flawed reasoning is the role of technical product characteristics in

market delineation. While earlier antitrust decisions often applied such technical characteristics of

products as a key guide for the delineation of markets, the application of the SSNIP methodology

immediately brings to light that technical product characteristics as such are of no immediate

interest for antitrust market delineation. The only relevant question that needs to be assessed is

whether enough customers are ‘marginal customers’ in the sense that they would reduce or cut

out their demand in the event of a significant price increase to make this price increase

unprofitable. Inframarginal customers, those that do not adjust their demand as response to a price

increase, are of no particular help for market delineation (Stenborg, 2004).

From a theoretical perspective, the SSNIP test can be operationalised by estimating own-price

elasticities and cross-price elasticities and by applying the formula for the price-cost margin for a

differentiated good (Neumann, 2000, and a slightly different approach developed in Schulz, 2003):

The SSNIP test aims at identifying the narrowest market for which a certain degree of market power

– measured by an increase in the price-cost margin – can be profitably and permanently exercised.

Although data availability might foreclose the application of this theoretical approach in practice, it

allows interesting insights into some specifics of the SSNIP test. For example, SSNIP test helps to

understand the significance of fixing the percentage price increase for the resulting market

boundaries. If, for example, a price rise of 10% would be assumed – instead of the 5% applied so far

–such a market would be broader than under a 5% threshold. Furthermore, as described in more

detail in Neumann (2000)11, it is important to note that the 5% increase refers to the competitive

price level; that is, the initial price-cost margin is zero. If, however, the initial product price is already

above the competitive level, the underlying hypothetical price increase is correspondingly higher

leading to broader market boundaries. Furthermore, the theoretical concept of the SSNIP test

simultaneously considers supply substitution as well as the geographical dimension of the relevant

market, because all relevant substitution goods of actual or potential competitors (independent of

their geographical location) are considered in the analysis. In that respect, it is important to remark

that the SSNIP test basically analyses an increase in price of a product i while assuming that the

prices of all other identified substitutes remain constant, that is, the supply elasticities are assumed

as infinitely high. Neumann (2000) remarks that such an assumption is seldom matched in real cases,

especially if handicaps to trade between countries are considered.

Even if the data at hand does not allow deriving estimates of own demand elasticities as well as

cross-price elasticities, the collection of other forms of quantitative evidence often allows sketching

a reasonably good picture of supply- and demand- substitutability. Bishop and Walker (2002) and

Lexecon (2004)12 identify inter alia price correlation analysis, stationary analysis, switching analysis

and price-concentration analysis as simple quantitative techniques, which might be of use to assess 10 Stenborg, M. (2004), Biases in the Market Definition Procedure, Working Paper, Research Institute of the

Finnish Economy, Helsinki. 11 Neumann, M. (2000), Wettbewerbspolitik. Geschichte. Theorie und Praxis, Wiesbaden. 12 Lexecon (2004), An Introduction to Quantitative Techniques in Competition Analysis, London.

29

the market definition problem.

In a nutshell, this section showed that market definition is typically an important analytical step in an

anti-competition investigation as it helps to identify the essential competitive constraints a firm or

group of firms face or would face. However, it cannot be overemphasised that market delineation is

not an end in itself but only a necessary precondition for the (indirect) assessment of market power

(which in turn is key to the determination of whether a certain business conduct raises

anticompetitive concerns).

In addition to views that interpret market definition as obsolete, other commentators, such as

Fingleton (2000)13, observe that the focus on market definition and the corresponding analysis of

concentration measures might hinder the often more fundamental analysis of the competitive

effects of a certain suspicious conduct. Canoy and Weigand (2001)14 acknowledge that market

definition is an important first step in an antitrust investigation; however, they also recommend

concentrating on the study of relevant economic factors – such as entry barriers, vertical and

lateral links, dynamic considerations and business strategies – as it is often more important to

study such areas intensively in order to develop an understanding of the competitive forces in the

market, rather than devoting too many resources into ‘getting market delineation exactly right’.

This is also emphasized by Scheffman (2004)15, who reminds of the interrelationship of market

definition and competitive effects analysis and the danger of fixing the relevant market first and only

assessing competitive effects within these boundaries. Sometimes the competitive effects analysis

reveals that the relevant market analysis was wrong. Salop (199916) concludes his essay on ‘The first

principles approach to antitrust’ by remarking that “[i]t will be clear that the first principles

approach has become firmly established when the first analytical question antitrust practitioners

ask themselves is no longer ‘what is the relevant market’, but instead ‘what is the alleged

anticompetitive effect?’”

1.2.2.1 The Hirschmann-Herfindahl Index (HHI)

The Hirschmann-Herfindahl Index is the sum of the square of market shares of all the firms in the

market.

When only one firm occupies an industry, the index attains the maximum of 1 or 10000 (Square of

100% is 10000). The value declines with increases in the number of firms and increases with rising

inequality among the given number of firms. By squaring the market shares, the HHI index weights

more heavily the values for large firms than for small. How desirable or undesirable this weighting

scheme is depends upon the relevant theory as to how market structure conduct and performances

are related.

13

Fingleton, J. (2000), Undefining Market Power, Working Paper 2000/4, Trinity College, Dublin.

14 Canoy, M. and J. Weigand (2001), How Relevant Is the Relevant Market? Lessons from Recent Antitrust

Cases, Working Paper, Otto Beisheim School of Management, Vallendar

15 Scheffman, D. (2004), Efficiencies-Dynamic Analysis-Integrated Analysis, LECG Presentation, Boston. 16 Salop, S. (1999), The First Principles Approach to Antitrust, Kodak, and Antitrust at the Millennium,

Georgetown University Law Center, Working Paper No. 195490, Washington.

30

In extremely competitive markets, in which each firm holds 1% of the market, the HHI value

approaches 0. Ten equal sized competitors would have each 10%. The Hirschmann-Herfindahl Index

would be 102 * 10 = 1000. Five equal competitors would give a Hirschmann-Herfindahl Index of 202

*5 = 2000. Two big players with 40% and ten with 2% would give an index of 2* 402 + 10*22 = 3240.

There is no universal agreement on how much concentration is too much, although 1500 to 2500 is

used as a screen.

In addition to using each company’s capacity, one can also use each company’s potential to generate

power during the coming year. This potential may be estimated on a plant-by-plant basis. Each plant

is characterized by its capacity, and an “availability factor”. For a hydroelectric plant, the potential to

generate power during a year is estimated by the “annual inflow” (in MWh/year), indicating how

much power can be generated by the plant on a sustainable basis, assuming normal hydrological

conditions during the upcoming year. The annual inflow is thus equating the normal power

production if the reservoir were to maintain an average level assuming a normal weather. Plus any

extra power that can be generated by getting the reservoir level back to its normal level at that

moment of the year (if the reservoir level is higher than normal), or minus the avoided production it

would take to bring the reservoir level back to normal (if the reservoir level is lower than normal).

Each plant’s availability, differentiating between plants that are designed to run base-load, plants

that are designed to run mid-merit, and plants that are designed to run only during peak.

HHI indices only identify situations where some firms may possess enough market power to reduce

workable competition. They cannot indicate whether firms will actually exercise that market power,

or the possible implications for prices and profits.

One justification for use of the HHI is that under certain conditions, most critically constant marginal

costs and no capacity constraints, the HHI divided by the elasticity of demand is equal to the Cournot

equilibrium Lerner index, which is another indicator of market power discussed below (Tirole, 2002).

In evaluating the significance of a particular HHI, the results can be broadly characterized into three

regions:

• unconcentrated (HHI below 1000),

• moderately concentrated (HHI between 1000 and 1800), and

• highly concentrated (HHI above 1800).

In an early study, Schmalensee and Golub (1984) calculated values of the Herfindahl-Hirschmann

Index (HHI) for electricity markets throughout the United States for 170 generation markets serving

nearly three-quarters of the U.S. population. They found that, depending on the cost and demand

assumptions used, 35 percent to 60 percent of all generation markets had HHI values above 1800.

Cardell, Hitt and Hogan (1997)17 suggest that electricity markets are highly concentrated. Using 1994

data and a narrower definition of the geographic scope of electricity markets, they calculate HHI

values for 112 regions based on State boundaries and North American Electric Reliability Council

17

Cardell,J., Hitt,C., Hogan,W. (1997) “Market Power and Strategic Interaction in Electricity Networks ”

Ressource and Energy Economics,Vol 19.

31

(NERC) sub-regions. Approximately 90 percent of the markets examined in this study had HHI values

above 2500.

A major criticism of market share and HHI analysis for electricity markets is that even where the

most dominant net seller has a relatively small market share (say less than 10%) they may still be

able to exercise market power. This is seen as a consequence of being a static measure and

examining only the supply side of the market. Electricity market conditions change hour by hour due

to changing demands levels, generation outages, transmission failures, etc. Most significantly, during

periods when the system demand is close to capacity, a supply can become ‘pivotal’ and exercise

market power even with a relatively small market share. Sheffrin (2001)18 points out that under

certain definitions of the relevant market, no single supplier in California had a 20% market share

during the California crises, yet many would argue that the market was not workably competitive.

William and Rosen (1999)19 found that a daily HHI based on actual power delivered had no ability to

predict actual market power as measured by the price-cost margin index (discussed below).

CERC, therefore, based on global experience may use market share / HHI indices only as

“indicative screens” (along with the Pivotal Supplier Indicator discussed below) to determine

whether anti-competition/abuse proceedings should be initiated. Further, the Commission

believes that it would not be prudent to ascribe any threshold value – because in electricity

markets even a small player could have market power and abuse it. Putting a value to any of these

indices may limit the scope of CERC’s investigations. Therefore any investigation under these

regulations will consider multitude of factors.

1.2.2.2 Pivotal Supplier Indicator

The pivotal supplier indicator is an attempt to incorporate demand conditions, in addition to supply

conditions, in a measure of potential market power. This indicator examines whether a given

generator is necessary (or ‘pivotal’) in serving demand. In determining whether a generator is pivotal

or not, different view needs to be taken for short/long term markets. While in long term markets, it

asks whether the capacity of a generator is larger than the surplus supply (the difference between

total supply and demand) in the market, in the short term markets, the criticality of a generator

could be judged in terms of its importance for system security and reliability of supply. Pivotal

Supplier Index (PSI) is a binary indicator for a supplier at a point in time which is set equal to one if

the supplier is pivotal, and zero if the supplier is not pivotal. The PSI from each block of 15 minutes

over a period of time (e.g. one year) can then aggregated to determine the percentage of time for

which a company achieves pivotal status.

The Supply Margin Assessment (SMA) is the name of the pivotal supplier indicator adopted by FERC

in 2001 as a market power screen to replace the 20% market share screen.

18

Sheffrin, A. (2001) “Critical Actions Necessary for Effective Market Monitoring” Draft Comments Dept of

Market Analysis, California ISO, FERC RTO Workshop, October 19, 2001

19 Williams, E., and Rosen,R. (1999) “A Better Approach to Market Analysis” Tellus Institute, Boston, July 14,

1999, mimeo.

32

1.2.2.3 Residual Supply Index

The Residual Supply Index (RSI) is similar to the PSI but is measured on a continuous scale rather

than a binary scale. As such the index addresses the criticism of the PSI in that it may be possible for

a company to exercise market power when it is nearly, but (as the PSI shows) it is not actually

pivotal. The RSI was developed by the California Independent System Operator (CAISO).

The residual supply index for a company i measures the percent of supply capacity remaining in the

market after subtracting company i’s capacity of supply.

RSIi = (Total Capacity - Company i’s Relevant Capacity)/Total Demand

where:

Total Capacity is the total regional supply capacity plus total net imports,

Company i’s Relevant Capacity is company’s i’s capacity minus company i’s contract

obligations, and

Total Demand is metered load plus purchased ancillary services.

When RSI is greater than 100 percent, the suppliers other than company i have enough capacity to

meet the demand of the market, and company i should have little influence on the market clearing

price. On the other hand if residual supply is less than 100 percent of demand, company i is needed

to meet demand, and is, therefore a pivotal player in the market. As well as calculating an individual

company’s RSI, an RSI can be calculated for the market and a whole. It is usually defined as the

lowest company RSI among all the companies in the market and will correspond to the largest

supplier in the market.

Empirically, the RSI has been used successfully in predicting actual market power as measured by the

price-cost mark-up. CAISO analysis of actual hourly market data found a significant relationship

between hourly RSI and hourly price-cost markup in the California market. The relationship indicates

that on average an RSI of about 120% will result in a market price outcome close to the competitive

market benchmark. (Sheffrin, 2001). CAISO has also evaluated the market power mitigation benefit

of the expansion of a transmission path by analyzing the market benefits of more imports into a

region which can increase RSI and reduce prices. The price-cost-RSI analysis can also be used to test

the level of reserve margin necessary to yield competitive market results. (Sheffrin 2001)

Based on this analysis, Sheffrin argues for the usefulness of market screening rules of the type:

• RSI must not be less than, say, 110% for more more than 5% of the hours in a year (about

438 hours); or

• RSI must be more than, say, 110% for 95% of the hours in a year

The advantage of using the RSI over PSI is that there is flexibility is setting thresholds compared with

the PSI, which is implicitly set at 100%. Thus using a higher threshold (e.g 110%) may account for

possible collusion. Furthermore, RSI thresholds can be adjusted on the base of experience

33

especially in the Indian context where the state distribution companies regularly shed load to alter

demand.

1.2.2.4 Residual Demand Analysis

Residual demand analysis is a more sophisticated measure of the incentive of a company to exercise

market power that is derived from examining the residual demand curve faced by a company. The

residual demand curve is calculated by subtracting from the total demand curve all the offer curves

bid into the market by other participants. Of course, in real time the company does not know exactly

the residual demand curve it faces. However, it can be constructed ex-post. One of the advantages

of electricity markets is that such data for constructing residual demand curves actually exists. Under

the provisions of these Regulations, the CMU will be directed by the Commission to collect such

data on a regular basis from all relevant market players.

An interesting feature of the ex-ante uncertainty of the residual demand curve that a company

faces, is that it in turn affects the elasticity of its own bid curve. The more uncertainty a company

faces, the range of possible equilibrium supply curves narrows away from both the high price supply

curve (full Cournot pricing) and the competitive pricing supply curve. This feature is an important

part of Klemperer and Meyer’s (1989)20 supply function equilibrium analysis.

In a competitive market, a company will face a highly elastic residual demand curve and will have no

ability to raise prices above the competitive level via any amount of withholding. At the other

extreme, if a company is pivotal (as defined above), then it faces a highly inelastic residual demand

curve and will suffer little loss in sales by charging a high price. In the intermediate cases, a company

may not be strictly pivotal (in terms of total market capacity) but may still face a range of prices for

which it may be able to exercise some market power depending of the degrees of residual demand

elasticity.

1.2.3 Behavioural Indices and Analysis

Whereas structural indices look to find the potential for market power, behavioural indices typically

examine the actual conduct of companies, looking for evidence of the exercise of market power. This

often involves examining individual bid prices and quantities. As mentioned earlier, high prices (or

low quantities offered) are not, in and of themselves, evidence of market power. The challenge

therefore is to develop meaningful indices and analyses that can discriminate between high prices

resulting from genuine scarcity as opposed to the exercise of market power.

1.2.3.1 Bid-Cost Margins

In a competitive market, price-taking companies should bid at marginal cost. Therefore, the

comparison of a generator’s bid with its marginal cost is an important measure in determining the

exercise of market power in electricity markets. If a company is frequently bidding at prices well in

excess of marginal cost (whether it is setting the system price or not), it may well be exercising

market power. Therefore there have been a number of empirical studies examining bid and cost

20

Klemperer, P.D., and Meyer,M.A. (1989). “Supply Function Equilibria in Oligopoly Under Uncertainty,”

Econometrica. November. 57(6): 1243-77.

34

data seeking to determine the extent to which market power has been exercised. The results of

these studies are usually expressed in terms of the Lerner Index (LI) or Price-Cost Margin Index

(PCMI):

LI = (Price – Marginal Cost)/Price

PCMI = (Price – Marginal Cost)/Marginal Cost

Under a uniform price auction, the indices can be applied to individual company bids, in which case

the appropriate marginal cost is that of the bidding company. Under discriminatory price auctions,

the application of price-cost margin is only appropriate to the marginal generator. In either case, a

perfectly competitive market is presumed to offer no margin above marginal cost, and hence the LI

and PCMI are zero.

One of the earliest examples of price-cost margin analysis was by von der Fehr and Harbord (1993)

who analysed bid and marginal cost data for the two large conventional generating companies in the

England and Wales pool from May 1990 to April 1991, using the electricity pool bid data and

generator cost estimates derived from published thermal efficiencies and fuel prices. Their evidence

showed that for the first 7-9 months of the market’s operation, both National Power and PowerGen

bid very close to their (estimated) marginal costs in most periods. By early 1991 however, bidding

behaviour had changed and both of the generators were increasingly bidding above their costs

One of the great difficulties of this empirical work is determining the appropriate marginal cost. The

approximation most commonly used is the variable fuel cost of the generator, calculated from fuel

prices and thermal efficiencies (heat rates). However there are problems with this approach:

• There are other variable costs that are difficult to quantity, such as commitment decisions

and increased cost of equipment degradation if used outside of designated parameters.

• Variable costs do not necessarily approximate marginal costs for units with substantial

opportunity costs (e.g. hydro electricity resources, generation with significant environmental

restrictions, export market alternatives)

• Variable costs data may be confidential and difficult to obtain and audit.

• Questions remain over whether the appropriate measure is long run marginal cost rather

than short run marginal cost.

Furthermore, even in a perfectly competitive market, the market price can exceed the marginal cost

of the marginal producer if supply is constrained. The above-cost pricing is sometimes referred to as

scarcity pricing and is not a demonstration of market power. Furthermore it fluctuates and cannot

be easily ‘factored out’. In many electricity markets, the design of the electricity auction is such that

the market price is set at the offer price of the last accepted supply bid. If this price does not clear

the market (demand is still greater than supply), then raising the bid of the marginal generator has

the beneficial effect of raising the price towards the competitive price. Stoft (2002) describes this as

“negative market power”.

35

Thus given all these issues, even if a study uncovers a large price-cost margin, it is still difficult to say

conclusively whether this is due to abuse of market power or estimation error. This was well

illustrated in the highly contentious hearings to determine the refunds to utilities from suspected

market power abuse by a number of generators during the California crises, 2000-2001.

An alternative to comparing bids with estimates of marginal costs is to compare bids with prior bids

submitted by the same company when the market was assessed to be competitive. However,

variations in bids are still possible, given changes in costs, even in a competitive market, so prior bids

or ‘reference’ bids are usually indexed to fuel and other costs, thus reintroducing most of the

previous criticisms of estimating marginal costs. Nevertheless, screening tools using such

approximated reference bids can be used to identify changes in bidding patterns that fall outside of

established thresholds.

1.2.3.2 Net Revenue Benchmark Analysis

Another type of analysis employing cost data is net revenue benchmark analysis. As was mentioned

earlier, high net revenue is not proof of market power (just as high prices are not proof).

Nevertheless, net revenue is still considered by many to be a useful figure to monitor and some

empirical work has been conducted to attempt to estimate the net revenue of classes of generation.

As well as indicating the possibility of abnormal profits due to market power, tracking net revenue in

markets with price-cap mitigation may also useful to determine if peak generation earns enough

revenue to cover fixed costs.

In the long run, the revenues from the energy and capacity should cover the costs of a new

generating plant, including a competitive return on investment. Revenues consistently below this

level would discourage entry into the market, eventually putting upward pressure on prices. On the

other hand, revenues above this level should lead to new entrants and exert downward pressure on

prices. The margin between a plant’s market revenues and its variable costs (primarily fuel for fossil

units) contributes to the recovery of its fixed costs, including non-variable operating and

maintenance expenses and capital costs. This margin can be estimated, given the variable costs of a

typical new generating unit, 15-minute energy-clearing prices in the region, and estimates of

capacity revenue. In a competitive market without market failures competitive entry would occur

with the most cost effective technology, this suggests that net-revenue does not need to cover fixed

costs of existing technologies.

1.2.3.3 Assessment of Economic Withholding

Stoft has argued that the most basic approach to detecting market power is to look for “missed

opportunities”: If a generator would profit (in expectation) from the sale of an additional unit of

electricity, assuming the market price would not change, and the generator chooses not to sell, it

has exercised market power. Thus, according to this view, the focus on assessment of market power

in electricity should not be on price but on output, looking for generation capacity that would have

been profitable to run at prevailing market prices, but was not.

The aim of ‘withholding analysis’ is to identify generation capacity that would have been profitable

at prevailing market prices but was withheld from sale. As mentioned earlier, there are two types of

36

withholding – economic withholding, where output is reduced because it is bid into the market

above competitive prices, and physical withholding, where output is not bid into the market at all.

Economic withholding is examined here and physical withholding is discussed in the next section.

Economic withholding is measured by estimating an “output gap”, which is defined as the difference

between the unit’s capacity that is economic at the prevailing market price and amount that is

actually produced by the unit. This measure was introduced by Joskow and Kahn (2002)21 in an

analysis of market power in the California electricity market.

In order to determine the economic level of output, a proxy is required for the competitive bid for

the unit. As with the bid-cost margin discussion above, this is usually based on estimating the

variable costs of the unit (fuel, etc) and/combined with previous bids from presumed competitive

periods. Obviously, all the previously mentioned criticisms of these estimates similarly apply. In

order to avoid this issue, Joskow and Kahn (2002) only examined those hours where prices were very

high, such that it could be presumed that most or all of the production units would have competitive

bids below the market price. The actual production of a unit also needs to be adjusted in order to

take account of transmission constraints, forced outages, and other factors that affect the actual

production which are not due to market power conduct.

A positive value of an estimate of the output gap implies the existence of economic withholding, to

the extent that there is no other explanation for the gap. Where this gap is small (e.g. less than 1% of

capacity) it may provide some comfort that economic withholding is not a serious problem.

However, as with price-cost margins, the margin of error in estimating a number of inputs to this

index leaves open to question the significance of any particular result. What may be more useful is

relating the output gap to incentives to exploit market power. Here it might be useful to examine the

variation in the gap and determine if it is related to factors that are theoretically known to influence

the ability to exercise market power. For example, Patton et.al., (2002)22 proposed two empirical

hypotheses in their analysis of the output gap:

• the incentive to withhold should increase during periods of high demand when prices are

relatively sensitive to changes in output and thus, ceteris paribus, withholding should

increase under high demand;

• the incentive to withhold should be greater in a company with a larger generation portfolio

and thus, ceteris paribus, withholding will be greater in larger companies.

1.2.3.4 Assessment of Physical Withholding

With physical withholding, the generator’s resources are not bid into the market (physically

withdrawn) by declaring a ‘derating’ of the generating unit, i.e., lowering the unit’s high operating

limit (“HOL”). There are generally two categories of generator deratings – generator outages where

21

Joskow, P. and Kahn, E. (2002) “A Quantitative Analysis of Pricing Behavior in California’s Wholesale

Electricity Market During Summer 2000” The Energy Journal, Vol 23, No. 4

22 Patten, D. B., Sinclair, R. A. and Pallas, M. (2002) Competitive Assessment of the Energy Market in New

England, Potomac Economics, May 2002.

37

the HOL is generally reduced to zero, and other deratings where the HOL is set at a positive value

below the unit’s maximum capability (Patton et.al., 2002).

The derating quantities analyzed usually exclude planned outages and long-term forced outages

because they are much less likely to constitute strategic physical withholding and including them

could mask true physical withholding.

Using deratings data to determine the exercise of market power faces very similar issues to output

gap analysis: unit outages and other deratings occur under perfectly competitive conditions as well

as noncompetitive condition. The evidence of deratings alone cannot provide evidence for the

exercise of market power. However, similar statistical methods to those described in output analysis

can be used to evaluate the pattern of deratings that may signal a physical withholding concern. The

main problem here is estimating the counterfactual reliability of each unit, which may depend on

the intensity of previous use and the care with which it has been maintained. The first question is

whether the observed outage rate over some period can be demonstrated to be significantly higher

than that expected for this unit (observed over a comparable period in the past) or a similar unit

(type, age, maintenance history). There may be disagreements on what the counterfactual reliability

is (e.g. because the unit may be claimed to be less worth maintaining than “comparable” units), in

which case it may be preferable to look for a systematic relationship between outage and periods

when the outage raised company profits.

The difficulty of such analysis is illustrated by the debate on the California crisis. Joskow and Kahn

(2002) identified evidence of companies withholding output. However, Hogan et.al. (2004)23 were

provided with a data set of a company involved in California. Outage rates of the selected plants

increased during the crisis -as suggested by Joskow and Kahn. But Hogan et.al. (2004) suggest that

higher utilisation could explain the increased outage rate. If utilisation is assumed to be the main

driver for outage rates, then a hazard rate analysis explains the higher outages during the crisis. The

effect of sample selection bias, the question about the relationship between utilisation and outage

rate, the expected impact of liberalisation to increase availability, and the expected impact that

higher demand would induce generators to postpone and accelerate maintenance etc. might still be

addressed in further work on this topic - the discussion illustrates the challenge of identifying and

proving physical withholding.

1.2.4 Simulation Models

Most of the above indices are constructed as simple ratios or differences using market or structural

data. In this section more sophisticated modelling exercises which attempt to simulate some aspects

of the market for the purposes of ex-post comparison with actual market outcomes or ex-ante

simulations of possible market outcomes given a particular market structure and design are

discussed.

23

Hogan, W., Scott Harvey and Todd Schatzki (2004) “A Hazard Rate Analysis of Mirant’s Generating Plant

Outages in California”, Toulouse Conference paper.

38

1.2.4.1 Competitive Benchmark Analysis

The basic idea of competitive benchmark analysis is to develop an estimate of the market price that

would result if all companies behaved as price-takers (i.e. if no company attempted to exercise

market power) and to compare that price to the observed market price. Compared to the simple

application of the Lerner Index to the actual price-setting (marginal) producer (as discussed above

with bid-cost margins), this form of analysis does not assume that the marginal producer in reality is

the same as the marginal producer under competitive conditions. As with simple bid-cost margin

indices, the determination of an appropriate competitive benchmark is not uncontroversial.

The most common form of competitive benchmark analysis involves estimating the marginal cost of

production of the marginal generator by simulating a hypothetical competitive market. This is done

by collecting data on the generation technologies that are present in the market and then estimating

a supply curve for each trading period by stacking generators from least expensive to most

expensive.

FERC’s Standard Market Design Notice of Proposed Rule-making (2002) has recommended that the

annual assessment of market performance should include the comparison of actual market results

with a simulated benchmark for competitive market, but does not specify how the benchmark

should be obtained.

Thus in a review of a number of competitive benchmark market simulation models, Harvey and

Hogan (2002)24 conclude:

Drawing inferences regarding competition based on comparisons between actual prices and

those simulated in these simple models could produce substantial errors. The difference

between the actual and simulated prices could arise from the real-world constraints omitted

from the model in conjunction with purely competitive behavior, or the difference could arise

from the exercise of market power by sellers that are able to raise prices because of

constraints omitted from the model. One simply cannot tell from these simulations. The error

is larger than the effect being estimated.

As with bid-cost margin indices, another means of calculating a competitive benchmark which tries

to avoid cost data is to base it on some estimate from in-merit bids during prior periods that are

deemed competitive (FERC 2002). The advantage of this approach is that the data needed are easier

to obtain in the normal course of business and raise fewer issues of information confidentiality than

approaches based on detailed generator production costs. However, reliance on generator bids

rather than independent assessment of costs leaves open the relationship between competitive

benchmark and the costs of production, raising the issue of whether this approach satisfies the need

to assess whether loads are being served at least cost.

1.2.4.2 Oligopoly Simulation Models

Oligopoly simulation models are perhaps one of the most powerful tools in exploring market

power by explicitly incorporating into one model many of the structural, behavioural and market

24

Harvey, S. and Hogan, W. (2002) “Market Power and Market Simulations”, Mimeo.

39

design factors that are related to market power, including concentration, demand elasticity,

supply curve bidding, forward contracting, and in some cases transmission constraints. Using a

game theoretic framework these models can be calibrated with cost data to predict the market

prices or Lerner Index of a market with a given structure and design.

Probably the most popular model of behaviour is Cournot competition under which companies

choose their levels of output knowing that their strategy and the strategies of other companies will

affect the market equilibrium. However, it is not clear whether it is the best model of the behaviour

of electricity generators, as generally companies can also choose the prices at which they offer

electricity. The well known alternative is the Bertrand model of oligopoly in which participants

choose prices to sell their output. However, Borenstein et al. (1999)25 contend that Bertrand

competition is inappropriate because it assumes that each company can expand output sufficiently

to serve the entire market, which is unlikely to be the case in electricity markets. Indeed, Tirole

(2002)26 has shown that models of Bertrand competition with capacity constraints may have

equilibria that are closer to the Cournot outcome. Klemperer and Meyer (1989) provide a solution to

a model of oligopoly in which companies choose a “supply function” relating their quantity of output

to the market price, which is close approximation of what usually happens in electricity marketplace.

However, a drawback of this method is that there may be a wide range of possible equilibria.

The cost of such flexibility in modelling market power is the difficulty associated with determining a

number of inputs into the model. For example, the level of forward contracting or demand elasticity

is often an educated guess and unfortunately the results are often sensitive to these assumptions.

However, to the extent that these assumptions remain constant under comparative analysis (e.g.

how will the competitiveness of the market change if the number of market participants increase

from 2 to 4) the analysis is still valuable.

Harbord and von der Fehr (1995) undertook the first large-scale simulation study of the potential for

the exercise of market power in a wholesale electricity market for the Industry Commission of

Australia.

An interesting recent European example of a market simulation model, especially since it has been

developed by a TSO (Eltra) in conjunction with regulatory authorities, is the MARS model of the Nord

Pool area. The model accounts for thermal, hydro, nuclear and wind power, and includes

transmission constraints. Prices, exchanges, etc. are calculated on an hourly basis. The model has

been applied to investigate the market power potential of the dominant producers in the region.

Transmission constraints can isolate markets and enhance market power. Several models of strategic

interaction on networks have been developed. Most models of generator competition take a general

approach of defining a market equilibrium as a set of prices, generation amounts, transmission

flows, and consumption that satisfy each market participant's first-order conditions for maximizing

their net benefits while clearing the market. If a market solution exists that satisfies this set of

25

Borenstein, S. and Bushnell, J. (1999) “An Empirical Analysis of the Potential for Market Power in California’s

Electrcity Industry”, Journal of Industrial Economics, 47

26 Tirole, J. (2002), The Theory of Industrial Organization, Cambridge, MA: MIT Press.

40

conditions, it will have the property that no participant will want to alter their decisions unilaterally

(as in a Nash equilibrium). Although it is recognized that no modelling approach can precisely

predict prices in oligopolistic markets, there appears to be agreement that equilibrium models are

valuable for gaining insights on modes of behaviour and relative differences in efficiency, prices,

and other outcomes of different market structures and designs (Smeers, 1997).

Cardell, Hitt and Hogan (1997) show that, if strategic generators own generation assets at node A

and B of a three-node network, they might increase output at node A relative to a competitive

scenario if this reduces the total energy delivered to node B due to loop flows and therefore

increases prices at node B. This is a likely possibility in India too, where generators on either side of

the constrained system in Day Ahead Market could strategically bid to abuse their market power. In

the literature on modeling strategic behavior in electricity markets, alternative representations have

been used to model the conjectures of competing players. Hobbs27 assumes Cournot conjectures

between gencos in active power markets where generators sell power to the grid at the locational

marginal price (LMP). Day et al.28 use a conjectured supply function (CSF) model to demonstrate

strategic behavior in active power markets. Wang et al.29 also use a CSF approach to model an

equilibrium problem with equilibrium constraints (EPEC) to determine the equilibrium strategies of

various generators. The CSF model, as opposed to the Cournot model, allows the rivals to alter their

supplies in response to price changes. All the above models use the dc load flow in their analysis.

Bautista et al.30 analyze imperfect competition in active power markets using ac load flow model.

The consideration of nonlinear ac load flow allows analysis of the impact of strategic behavior on

reactive power and voltage constraints. The multi-leader-follower game presented in the paper has

been formulated as a nonlinear programming (NLP) problem. In the paper by Chitkara et. al.

(2009)31, a strategic bidding model considering ac load flow is presented that simulates the behavior

of generators participating in reactive power procurement by the ISO. The game is formulated as a

multi-leader-follower game. The ISO is assumed to be the follower, while the leaders are the gencos

supplying reactive power. The gencos are assumed to have conjectures about the supply functions of

their rivals; hence the solution represents the supply function equilibrium between gencos (leaders).

The proposed model can be used to analyze the strategic behaviour of gencos in the system. Based

on the results, some regulatory mechanisms are proposed that can restrict the effects of their

strategic behavior. In the case studies, the effectiveness of the proposed alternative price cap

regulation in alleviating abuse of market power is examined.

The Commission believes that investigating cases of anti-competitive conduct, abuse of dominant

position, abusive agreements or combinations requires analysis of various considerations –

technical, economic and behavioural. These methodologies help model these considerations

27 B. F. Hobbs, “Linear complementarity models of Nash-Cournot competition in bilateral and POOLCO power markets,” IEEE Trans.

Power Syst., vol. 16, no. 2, pp. 194–202, May 2001. 28 C. J. Day, B. F. Hobbs, and J. S. Pang, “Oligopilistic competition in power networks: A conjectured supply function approach,” IEEE

Trans. Power Syst., vol. 17, no. 3, pp. 597–607, Aug. 2002 29 X. Wang, Y. Li, and S. Zhang, “Oligopolistic equilibrium analysis for electricity markets: A nonlinear complementarity approach,” IEEE

Trans. Power Syst., vol. 19, no. 3, pp. 1348–1355, Aug. 2004 30 G. Bautista, M. F. Anjos, and A.Vannelli, “Formulation of oligopolistic competition in AC power networks: An NLP approach,” IEEE

Trans Power Syst., vol. 22, no. 1, pp. 105–115, Feb. 2007 31

P. Chitkara, J. Zhong, and K. Bhattacharya, “Oligopolistic Competition of Generators in Reactive Power Ancillary Service

Provision”,IEEE Trans.Power Syst, Vol. 24, no. 3, pp. 1256-1265, Aug. 2009

41

simultaneously and provide useful insights into various investigations. However, the results of

various simulations will need to be supported by case-specific facts which may not be amenable to

modelling. Hence the overall decision of the Commission may rely on a combination of the results

of these methodologies and case-specific considerations.

The relative strengths, weaknesses and popularity of various techniques for assessment of market

power and its abuse is summarized in the table below:

Category Strengths Weaknesses Popularity

Structural Indices and Analysis Market Share and HHI Ex-ante Easy to understand.

Theoretical justification under certain assumptions.

Simplest versions only require sales or capacity data.

Little empirical justification.

Ignores demand side, strategic incentives and often congestion issues.

Does not fit well to dynamic market conditions.

Difficulties in determining appropriate geographic region.

Standard tool for many decades.

Increasingly recognized as a limited metric.

Pivotal Supplier Indicator and Residual Supply Index

Ex-ante Ex-post Takes into account demand side conditions.

Can track dynamically changing markets.

Applicable at local market level as well as system level.

Some empirical support.

Difficulties in determining appropriate geographic region.

Ignores potential of correlated behaviour (e.g. Cournot or collusive behaviour).

Ignores elasticities and market contestability (entry/exit) factors.

Recent tool but increasingly being applied.

Residual Demand Analysis

Ex-post Takes into account elasticities of supply and demand.

Theoretical justification – link to Lerner Index.

Requires bid data.

So far limited empirical work.

Recent tool Uncertain as to future popularity.

Behavioural Indices and Analysis Bid-Cost Margins (Lerner Index)

Ex-ante Ex-post Easy to understand

Does not require a geographic market definition.

Useful metric for ex-ante theoretical models as well as ex-post empirical analysis.

Difficulties in determining costs or appropriate competitive ‘reference’ levels.

Margins affected by factors other than market power -interpretation difficulties.

Standard tool.

Confidence should grow as cost estimation techniques continue to improve.

Net Revenue Benchmark Analysis

Ex-post Considers long run considerations such as investment incentives and entry/exit issues.

Difficulties in determining costs.

Results are difficult to interpret in light of other factors affecting profits.

Relatively recent tool but may grow in popularity.

Withholding Analysis (Output gap analysis)

Ex-post Focuses directly on most basic MP strategy – withholding

Under certain assumptions can avoid cost

Accounting for all ‘small’ details of production decision (e.g. ramp rates etc) is difficult.

Actual auditing of deratings/outages is

Recent tool and still controversial, but its important complementary role to price analysis will ensure continued development.

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Category Strengths Weaknesses Popularity

estimation.

Correlation analysis can trigger further analysis without preliminary auditing of outages.

difficult.

Initial empirical results still controversial.

Simulation Models Competitive Benchmark Analysis

Ex-post Takes account of entire market in a refined version of price-cost margin analysis.

Can provide quantitative estimate of efficiency and welfare loss from market power.

Difficulties in determining costs or appropriate competitive ‘reference’ levels.

Cannot identify individual generators exercising market power.

Introduced in 1999 and has lead to numerous studies since.

Still controversial given the many estimation issues.

Oligopoly Models Ex-ante Integrates many market power factors into one framework (e.g. demand, contracting incentives, transmission constraints).

Large number of assumptions negates certitude of quantitative conclusions.

Introduced in early 1990s and applied widely since.

Still controversial.

Transmission Monitoring

Ex-ante Ex-post Transmission constraints are an important issue in market power monitoring and are often ignored.

Analysis usually requires data on bidding, output, transmission rights ownership and constraints.

Given the interaction with market design and network structure, case specific analysis is very often required.

An important aspect of many analyses of market power, but will continue to be constrained by the difficulties of carrying out analysis.