1 paul twomey richard green karsten neuhoff david newbery the cambridge-mit institute part of the...

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Paul Twomey

Richard Green

Karsten Neuhoff

David Newbery

The Cambridge-MITInstitute

Part of the research was funded by the Association of European Transmission Operators ETSO.

A Review of the Monitoring of Market Power

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Outline

• Classifying the various market power detection tools

• Is there evidence for market power?– Latest work from Europe

• Is market power a problem?– Wealth transfer and deadweight loss calculation– Technological Bias

• What to do about market power?• Data issues• Outstanding Issues and Conclusions

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Market Power Detection Tools – Classifications

Different Market Power Detection Tools for

Different Tasks:

• Ex-ante versus ex-post• Long-term analysis versus short-term/real time

analysis• System-level market power versus local market

power• Horizontal market power versus vertical market

power

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Market Power Detection Tools – Classifications

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

Inspired by a similar table in Helman (2004)

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Market Power Detection Tools – Potential Applications

Ex-Ante Ex-Post

Long-Term Analysis

- Merger rulings- Assessing applications for market-based rates - Determining potential must-run generators

- Litigation cases (e.g. California refund case)- Changing market design

Short-Term Analysis

- Spot market bid mitigation- Must-run activation & other system operator contracting

- Short term price re-calculations- Penalties for withholding

Inspired by a similar table in Helman (2004)

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Market Power Detection Tools – List

• Structural Indices and Analysis– Market Share and HHI– Pivotal Supplier Indicator and Residual Supply

Index– Residual Demand Analysis

• Behavioral Indices and Analysis– Bid-Cost Margins (e.g. Lerner Index)– Net Revenue Benchmark Analysis– Withholding Analysis

• Simulation Models– Competitive Benchmark Analysis– Oligopoly Models

• Transmission Related Analysis

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Is there Evidence for Market Power? - State-of-the-Art Examples from Europe

• Müsgens (2004) Ex-post competitive benchmark model of German Electricity Market– Multi-regional approach– Dynamic (including hydro & start-up costs)– >400,000 variables and equations!

• ECN (2004) COMPETES. Ex-ante oligopoly simulation model of Netherlands, Belgium, France and Germany – Cournot and Conjectured Supply Functions (CSF)– Results influential in Nuon-Reliant Merger Case in

the Netherlands (along with Frontier’s SPARK model – a supply function equilibrium model)

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German EEX Prices and Estimated SMC (Müsgens, 2004)

0

10

20

30

40

50

Jun

Jul

Aug

Sep Oct

Nov

Dec Ja

nF

ebM

arA

prM

ay Jun

Jul

Aug

Sep Oct

Nov

Dec Ja

nF

ebM

arA

prM

ay Jun

Jul

Aug

Sep Oct

Nov

Dec Ja

nF

ebM

arA

prM

ay Jun

2000 2001 2002 2003

Monthly Base EEX

Monthly Base SMC

1. Period:Average deviation betweenmarginal costs and pricesabout 2%

2. Period:Average deviation betweenmarginal costs and pricesnearly 50%

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Is Market Power a Problem?

• Can distort efficient dispatch• Can distort long-term investment• Wealth transfers • Potential technological bias

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Wealth Transfers and Deadweight Loss – Back of the Envelope Calculation

• UK 300 TWh per year– wholesale 25£/MWh, retail 50£/MWh– £15 billion retail value– Elasticity on retail demand 0.1, 10%

penalty on wealth transfers from consumers to producers

– Assume 20% wholesale price rise arising from market power

• Welfare loss of £192 million– Equivalent to 1.8 hours lost of total system

at current VOLL– £3 per person

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Market Power and Technological Bias

• Market power is sometimes argued to be tolerated to cover fixed costs and encourage new investment

• Usually assumed that all generators benefits equally from increased prices

• Intermittent generation, with exogenously varying production, benefits less than conventional generation (Twomey and Neuhoff 2004)

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Average Wind Price is Slightly Less than Average Market Price in a Competitive Market

0

20

40

60

80

100

0 10 20 30 40 50

Demand

Pric

e (£

/MW

h)

MC ConventionalGeneration

Demand

Residual ConventionalDemand (Average Wind)

Average Market Price

Volume Weighted Wind Price

DT - QWo DT

Price - Low Wind

Price - High WindMC

High Wind Low Wind

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Average Wind Price is Much Less than Average Market Price in a Monopoly

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20

40

60

80

100

0 10 20 30 40 50

Demand

Pric

e (£

/MW

h)

MC ConventionalGeneration

Demand

Residual ConventionalDemand (Average Wind)

Monopoly PriceFunction

Average Market Price

Volume Weighted Wind Price

DT - QWo DT

Price - Low Wind

Price - High WindMC

Monopoly Price Function

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Average price and volume weighted price for wind - 90% contract level

0

10

20

30

40

50

60

70

Conv. Wind Conv. Wind Conv. Wind

Pric

e (£

/MW

h)

Market Pow erMargin

PerfectCompetition Price

Monopoly Duopoly w ith Forw ard

Contracting

Duopoly w ith Option

Contracting

Demand Elasticity 0.1, wind 30% market share, wind volatility 100% uniform distribution around average

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So what to do about Market Power?

• Standard Solutions:– Structural

e.g. divestiture, removing entry barriers, transmission expansion, demand responsiveness

– Regulatorye.g. vesting contracts, virtual power plant

auctions, sunshine regulation

– Market Rulese.g. unit-specific bid caps (e.g. AMPS)

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The Big Question

• Do we make best efforts to create a contestable market (e.g. divestiture, functioning contract market) and then let the market operate with only long run monitoring and minimal regulatory interference?

OR• Do we try to micro-manage the market to recreate the

competitive outcome?

• Dangers of too heavy-handed price intervention– Investment problems (Joskow 2003, New England)– Can capacity payments solve this?

• Is ex-ante or ex-post regulation more effective?• Europe versus USA approach

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Market Monitoring Units – Institutional Features

• Market Monitoring Units. Different approaches:– Regulator– Unit attached to Market Operator

• Desirable Features– Forward-looking and preemptive– Support from regulator to respond to

recommendations– Consistent approach to ensure that the market

monitors actions are understood by all participants– Transparent approach to promote confidence in

the operation of the market and allow outside analysis

– Independence from stakeholders

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Data Issues

• TSO/ISO requires all physical transaction data and so is well placed to hold a complete, centrally stored record.

• Data should be held for sufficient time to allow ex-post investigations.

• Homogenous format for data across all nations/states would reduce cost of analysis and increase the integrity of data.

• Access rights to data should be clearly specified. Regulatory authorities should receive access to data either automatically or on request without the need for legal proceedings.

• As much data as possible should be made publicly available to facilitate third party market analysis.

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Conclusions

• Simple MP tools have drawbacks but more complex techniques require considerably more effort to construct and often use difficult-to-obtain data.

• Desirable to employ a range of techniques as no one technique provides definitive results. Further work needs to be conducted on confidence intervals.

• As much data as possible should be published to allow independent analysis to refine techniques for the detection, and hence the deterrence of market power.

• More empirical work needs to be conducted on evaluating the efficiency effects of AMP-type mechanisms, particularly the effect on investment decisions.

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Conclusions

• Ex-ante versus ex-post mitigation issue still to be resolved. Using both is feasible.

• Such work should lead us to a better understanding of the acceptable levels of market power in light of our ability to both detect and mitigate market power.

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Postscript

• Student: “So Master, what is the path of least resistance to electricity deregulation enlightenment”

• Zen Master: “Ohm”