Sustainable Energy Systems Theory of Regulation PhD, DFA Filomena Garcia and M. Victor M. Martins...

Sustainable Energy Systems

Theory of Regulation

PhD, DFA

Filomena Garcia and M. Victor M. Martins

Semester 22011/2012

SustainableEnergySystems


Slide 2

Yardstick regulation

Models of regulation in practice ( cont )¡ Yardstick regulation¡ Partial cost adjustment¡ Menu of contracts¡ Performance based regulation

¡ Bibliography¡ Shleifer, A. 1985, "A Theory of Yardstick

Competition," Rand Journal of Economics, Vol. 16, No. 3, pp. 319-327



Slide 3


In the yardstick regulation the performance of a regulated utility is compared against of a group of comparable utilities: for example, the mean of the costs of a peer group of firms can serve as performance benchmark.

Equation:

Where: Pi= overall price cap for firm i ; = share of firm's own cost information; Ci = unit cost of firm; fj revenue or quantity weights for peer group of firms j ; Cj = unit cost ( or prices ) for peer group of firms j; n= number of firms in peer group

, , , )1

(1 ) ( )n

i t i t i j j tj

P C f C



Slide 4


Outline Yardstick regulation

Regulatory framework and benchmarking Benchmarking methods DEA COLS

Yardstick regulation and incentives Yardstick regulation in practice



Slide 5


What is it?

In yardstick regulation the allowed prices or revenues of a company depend on the performance of other companies.

The performance can be regarded in three main aspects: productivity, efficiency and quality

Productive efficiency and in particular cost efficiency are the most commonly used measures in the yardstick regulation of electric sector



Slide 6


Value of yardstick competition Company level

Improve technical and cost efficiency Industry level

Detect and follow up technology development Regulation

Incentive system Control of tariffs Structural development



Slide 7


Efficiency measurement methodsThe methods used for measuring efficiency are referred to as frontier approaches

Parametric Non-Parametric

DEA FDHdetermini

stic( COLS )

stochastic

(SFA )

Extensions

Frontier Analysis



Slide 8


DEA - In a sample of companies with a k-input-m-output production function with variable returns to scale ( VRS) the measurement of cost efficiency using DEA method reduces to the following minimization problem:

w – vector of input prices ;x - vector of input quantities ; y – vector of output bundle;X and Y are matrices; N and are vectors

´

: 0

0

1, 0

´,

i

i

i

st y Y

x X

i iw xMin

xi



Slide 9


Efficiency frontierExampleDistributor A B C DOperating cost (M€) 72.5 80 140 120Deliv power ( MWh) 1115.51379 1500

1200

Benchmark Cost/MWh 65 58 93 100

Questions Is D an efficient utility? Who is efficient? Who are the peers to D?



Slide 10


Decomposing efficiency:

Technical efficiency To avoid waste and slack

Scale efficiency To operate at the right scale

Cost efficiency To apply least cost technology



Slide 11


Efficiency frontier

Technical Eff.: 75/120= 62.5%

1500

1200

70 75

A

B

C

D

OutputMWh

InputM€

140120



Slide 12


Efficiency frontier

Scale Eff.: 70/75= 93%

1500

1200

70 75

A

B

C

D

OutputMWh

InputM€

140120



Slide 13


Information Technical Efficiency : 62.5% Scale efficiency : 93%

Input target- OPEX 75 ( - 45, i.e. 120-75)



Slide 14


The minimization problem can be solved by LP methods. The LP finds a piece-wise linear isoquant in the input space, which corresponds to the minimum costs of producing the given output at any given point.

The solution gives the minimum feasible costs for each company namely, w´ix0i , where xi* is the optimal output bond for firm i. The cost efficiency of each production plan is then estimated as the distance to the envelope. Namely, firm i´s cost efficiency is therefore obtained by: ´ *

´ 0i

w xi iEffw xi i



Slide 15


Example

Distribution Company

A B C D

Opex (M€) 72.5 80 140 120

Labor (€/h) 87 77 70 135

Output( MWh) 1200 1200 1200 1200

Totex (M€) 90 95.4 175 187.5

Labor/MWh 73 64 58 113

Opex/MWh 60 66 117 100

Cost/MWh 75 80 146 156



Slide 16


Cost efficiency

140

135

35 75 120 14084

84A

B

C

D

labor €/h

OpexM€

187M€63M€



Slide 17


Information Cost efficiency : 187M€/63 M€=» 33,5% Cost targets:

Operating costs: 35M€ ( -85) Labor: 140€/h ( +5) Total cost: 63m€ (-124M€ )

Yardstick regulation offers: Real targets, norms and peers Cost norms, low information rents Observed technologies Participation



Slide 18


Regression Method- COLS ( corrected ordinary least squares )

Model: ln Ci = f( yi,wi )+ui Ci – actual cost incurred by the company i f( …) – cost function ui-Stochastic error

After correcting the error term so that all residuals ui become positive the COLS model can be written as:ln Ci= f( yi,wi)+mini(ui)+vi with vi=ui-mini(ui) >0

where vi represents the firm inefficiency.



Slide 19


Technique of COLS ( corrected ordinary least squares )

C,c

Composite scale variable

B

E

F

EfficientFrontier

EF/BF



Slide 20

Regulation of utilities in selected countries

Country

Regulation Method

Benchmarking: Method and sample

Inputs and outputs

From benchmarking to X-factor

Great Britain

Revenue cap

COLS / OPEX

14 Recs in GB

I: OPEXO: Composite variable( 50% nº of cust; 25% el dist; 25% length of network

High cost utilities must move 75% of the distance to efficient frontier during reg. period

Norway

Revenue cap

DEA: total controlable costsRegional networks and distribution

I: Capital+goods & services +laborO: Nº of customers, en. del. Length lines and cables

Utilities revenue cap for 1998-01 is reduced 38.2%

Netherlands

Ex-ante tariff regulation

DEA/Revenue I: Total costO: Units, demand

( peak) network length, customers

OPEX and X: from 8 to -2 for individual companies.

Spain Revenue Reference network/revenue

I: Total costsO: Electricity distributed, demandCustomer volume

Eff. Requirement: individual+ general 1,5%



Slide 21

Incentive regulation -Partial cost adjustment

Another approach to incentive regulation is to link the price adjustment to changes in utility's own cost observed in a reference year.

The cost minimization is provided by price periodic adjustments that are less than proportional to the actual changes in the cost.

The following equation shows a partial cost adjustment scheme:

Where: Pi = adjusted price; C*i= reference cost per unit output ; Ci= actual cost and lambda = sharing parameter

* *, , )( )i t i i t iP C C C



Slide 22

Incentive regulation - Menu of contracts

The menu of contracts method is an innovative approach to reduce the information asymmetry between the regulator and the regulated firm

Under this scheme the regulator offers the utility a menu of incentive plans with constant consumer welfare. The utility can choose among the incentives and the flexibility in choosing among the alternatives reveals its welfare-enhancing preferences

For example, a menu of incentives can be designed where the utility's share of profits or some specified reward is a function of the deviation of the X-factor ( or price cap ) chosen by the utility form a base X*:*( )f X X



Slide 23

Incentive regulation - Targeted regulation

Targeted incentive regulation pursue narrower objectives than the broad incentive regulation discussed in the above

The aim of these schemes is to target specific aspects of the operation of the utility and achieve an outcome that would not necessarily result from broad incentive schemes

Targeted incentive regulation may be used to promote environmental standards, technical efficiency and improvement in the quality of service

These schemes have been criticized on the ground that they distort efficient allocation of resources.



Slide 24

Performance based regulation

Performance-Based Regulation ( PBR) has become increasingly popular in many regulated industries in the US and can be defined as the implementation of rules, including financial incentives, that encourage a firm to achieve certain performance goals, while affording the firm significant discretion in how the goals are schived.

An effective PBR regime incorporates mechanisms to overcome information asymmetries and decrease the need for detailed regulatory intervention

A full PBR regime is characterized by two elements: De-linking a utility's own costs with its own allowed

prices or revenues, Linking the utility's own allowed prices or revenues

with the costs of other, comparable utilities



Slide 25

Performance based regulation ( cont)

The advantages of PBR over ROR are the following: By not linking authorized revenues directly to realized

operating costs, PBR plans can provide companies with strong incentives to control costs and increase other aspects of performance

PBR can provide improved rate predictability for customers especially through plans like rate freezes and rate case moratoria

PBR such as earnings sharing plans can secure timely customer participation in a company's improved financial performance thereby making customers “ stakeholders” in the company's operations

PBR plans can reduce administrative and regulatory costs by avoiding regulatory micromanagement of company's operations and by reducing the number of litigated rate cases

By providing an electric utility with incentives similar to those faced by firms in competitive markets, well structured PBR Plans can serve both as a tool to regulate traditional utility operations and as a transitional mechanism to more competitive electricity markets



Slide 26

The evolution pattern of regulation

Rate of returnregulation

Incentive regulationMenu of contracts

regulation

Ince

ntiv

es

First incentivesfor cost

reduction

efficiencyrequirements

Qualityrequirements

Company specificincentives



Slide 27

Method of regulation of utilities in selected countries

Country Model of regulation

Great Britain Revenue cap

Netherlands Revenue cap

Norway Revenue cap

Australia Revenue cap

California - Southern

Price cap

Chile Yardstick regulation



Slide 28

Conclusion

Based on the experiences in several European countries, the acceptability of regulatory models among interest groups seems to be an essential part of the development process It has proven to be difficult to implement models that

have been unacceptable to the regulated companies Difficulties in accepting regulatory models may

sometimes be due to the fact that they have become very complicated Regulatory models have often been developed piece

by piece New adjustments, e. g. efficiency and quality have

been added on top of the existing regulatory formulas

There are some signs indicating that regulatory models should become more simpler.

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Sustainable Energy Systems Theory of Regulation PhD, DFA Filomena Garcia and M. Victor M. Martins...

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