Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.
15th June 2012 – EUI, Florence   Incentive regulation with bounded regulatorsJean-Michel Glachant, Haikel Khalfallah (FSR-...
Do we really know how to apply incentive regulation               in the power sector?The assumptions of thetextbook model...
An analytical framework to choose in practice        between the incentive regulation tools How to align the regulatory t...
The real regulators are endowed with less abilities                than the textbook assumes   In the economic literature...
The regulatory tools require minimum abilities to be                usefully implemented                                  ...
The regulator regulates the network operator for         various tasks and not for a single task   The textbook regulator...
Regulating a task (a cost) is betting on its controllability,predictability, & observability to choose appropriate regulat...
1° The regulator incentivises the TSO on tasks/costs              that the TSO can control Controllability measures the T...
2° The regulator can only incentivise the TSO on            tasks/costs that are predictable Predictability measures the ...
3° The regulator can only incentivise the TSO on            tasks/costs that are observable Observability measures the qu...
A decision tree to align regulatory tools with the tasks’                    No                                      chara...
… and alignment with the regulator’s abilities                    No                                                      ...
Examples of regulatory tools on …                    No                                                               Regu...
… example #1 Transmission maintenance                                                                                     ...
… example #2a Transmission losses volume in an isolated system                                                            ...
… example #2b Transmission losses volume in an interconnected system                   No                                 ...
… example #3 RD&D e.g. Meshed DC grid                                                                                     ...
Conclusion Textbook regulation assumes an “unlimitedly endowed” regulator  targeting a single type of TSO’s task (cost)  ...
15th June 2012 – EUI, Florence   Incentive regulation with bounded regulators                    Thank you for your attent...
Have          a look  the in           at        ternat      journ     ionalI am c       al        hief-e               di...
Appendixes             21
A reminder of the 5 standard regulatory tools   Cost +     –   The network operator is then paid based on its cost-of-ser...
The real regulators are not always endowed with a full range of judicial powers                      The European example ...
The real regulators are not always endowed with the highest amount of ressources                        The example of bud...
The regulator might be unable to distinguish between the effect        of the network operator’s effort and the effect of ...
Upcoming SlideShare
Loading in …5
×

Incentive Regulation With Bounded Regulators 15 June2012

288 views

Published on

Incentive regulation is key in the energy sector to frame the behavior of grid companies. We argue that it has to be assessed more closely. Gird companies do not have a single task to perform and incentive regulation covers several tools. Therefore a workable matching of each type of grid task with the more relevant incentive tool is key to regulation performance. This matching criterion should take into account the difficulty of implementation for a given regulatory authority.

  • Be the first to comment

  • Be the first to like this

Incentive Regulation With Bounded Regulators 15 June2012

  1. 1. 15th June 2012 – EUI, Florence Incentive regulation with bounded regulatorsJean-Michel Glachant, Haikel Khalfallah (FSR-EUI), Yannick Perez (LdP chair-EUI) Vincent Rious, Marcelo Saguan (Microeconomix, LdP chair-EUI) 1st Annual Conference on the Regulation of Infrastructure Industries 1
  2. 2. Do we really know how to apply incentive regulation in the power sector?The assumptions of thetextbook model of regulation The reality for regulator –e.g. considering the national regulatory agencies for the power sectors but the rationale is also applicable to other sectorsThe regulator always has the She does not always have as manyrequired powers, resources and powers, resources and abilities asabilities to implement any regulatory the textbook model assumesscheme The regulator applies distinctThe regulator incentivises a TSO as regulatory tools to different TSO’sa whole with a single tool tasks 2
  3. 3. An analytical framework to choose in practice between the incentive regulation tools How to align the regulatory tools, the regulator’s endowment and the targeted tasks (“costs”)? The textbook model of incentive regulation proposes no solution to choose the regulatory tools considering – The regulator’s abilities to implement it – And the targeted network tasks (“costs”) and their characteristics We propose a way to align regulatory tools, endowment and tasks in practice, considering and combining – The actual bounded regulators’ endowment and abilities – And the actual characteristics of the network operator’s tasks 3
  4. 4. The real regulators are endowed with less abilities than the textbook assumes In the economic literature proposing and building regulatory tools, regulator is always thought to have all the desired cognitive, computational and judicial abilities to use any tool easily and efficiently – In particular, she knows ex nihilo how to choose the most efficient regulatory tools and she has all the desirable abilities to implement it But in reality, the regulators were endowed with tight resources (budget, staff, skills and judicial powers) which are likely to hamper their abilities to do their job “perfectly” Furthermore, regulators learn from experience how to use the different regulatory tools identified by our academic theory. How to: – To reduce their information asymmetry – To adapt tools to uncertainty and risk – To gain computational skills needed to design the regulatory tools 4
  5. 5. The regulatory tools require minimum abilities to be usefully implemented Regulator’s abilitiesCost + Price cap PBR Menu Yardstick 5
  6. 6. The regulator regulates the network operator for various tasks and not for a single task The textbook regulator controls the TSO’s tasks (cost) as a whole while there are different tasks with different characteristics. The basis tasks for an El. TSO: – Operation of electricity system: Balancing + Reserves + Congestion + Losses + Market Operation – Maintenance of the existing grid – Investment and grid connection: Planning + Construction – Customer relationship The network operator may have to undertake new or renewed tasks because of new regulatory objectives from – The integration of massive renewables in electricity – Concerns about security of supply – Europeanization of markets with a key TSO role in market building + RD&D in infrastructures and services (“smart” everything) 6
  7. 7. Regulating a task (a cost) is betting on its controllability,predictability, & observability to choose appropriate regulatory tool  Considering the diversity of tasks, systems and environments that TSOs may encounter, they should be targeted with distinct regulatory tools in a building block approach  Other things being equal, that is to say with a regulator having all the desired abilities to use any tool, the appropriate regulatory tool to choose for a given task/cost should depend on the tasks’ regulatory characteristics being – (Task outcome) Controllability – (Task outcome) Predictability – (Task outcome) Observability 7
  8. 8. 1° The regulator incentivises the TSO on tasks/costs that the TSO can control Controllability measures the TSO’s ability to control a cost/task or a combination of costs/tasks for a given output Input A NO Output A Controllable? AND/OR internal Input B process Output B Controllable? If the task/cost is not controllable, the regulator should implement a cost plus scheme If the task/cost is controllable, the regulator could incentivise the TSO – Under the constraints relative to predictability and observability 8
  9. 9. 2° The regulator can only incentivise the TSO on tasks/costs that are predictable Predictability measures the possibility to foresee the influence of external factors on costs/tasks and the relationship between the costs/tasks and the outputs Input A NO Output A Predictable? internal Predictable? Input B process Output B Predictable? If the task/cost and its relationship with the outputs are not enough predictable, the regulator should implement a cost plus scheme Otherwise the regulator can implement an incentive scheme whose risk for her and the network companies depends on the degree of predictability – “Low predictability implies high risk” versus “High predictability implies low risk” 9
  10. 10. 3° The regulator can only incentivise the TSO on tasks/costs that are observable Observability measures the quantity of available information to the regulator about efficiency gains on tasks, either in terms of tasks themselves, or inputs or outputs Input A NO Output A Observable? internal Observable? Input B process Output B Observable? The regulatory tool should then be chosen depending on the level of observability – When there is no observability, cost plus should be implemented – When input is observable, price cap or a menu of contracts should be implemented – When output is observable, PBR or a menu of contracts should be implemented – When information is available from several network operators, one should benchmark them 10
  11. 11. A decision tree to align regulatory tools with the tasks’ No characteristics …Controllability? Cost + Yes Price cap NoPredictability? PBR ility r vab to bse No u utp Menu Yes ho servab ility Hig t) ob pu t or outpu High (inObservability? Data from several o Yardstick perators 11
  12. 12. … and alignment with the regulator’s abilities No Regulator’sControllability? Cost + abilities Yes Price cap NoPredictability? PBR ility r vab to bse No u utp Menu Yes ho servab ility Hig t) ob pu t or outpu High (inObservability? Data from several op Yardstick e rators 12
  13. 13. Examples of regulatory tools on … No Regulator’sControllability? Cost + abilities Yes Price cap NoPredictability? PBR ility r vab to bse No u utp Menu Yes ho servab ility Hig t) ob pu t or outpu High (inObservability? Data from several o Yardstick perators 13
  14. 14. … example #1 Transmission maintenance Regulator’sControllability? Cost + abilities Yes Price capPredictability? PBR ) t put y (ou u alit No le q vab bility Menu Yes s er lity) observa Ob sts or qua inten a nc e c o Hi gh (maObservability? Data from several o Yardstick perators 14
  15. 15. … example #2a Transmission losses volume in an isolated system Regulator’sControllability? Cost + abilities YesPredictability? PBR t utpu ble o No se rva Ob Menu Yes ility servab High obObservability? Data from several o Yardstick perators 15
  16. 16. … example #2b Transmission losses volume in an interconnected system No Regulator’sControllability? Cost + abilitiesPredictability?Observability? 16
  17. 17. … example #3 RD&D e.g. Meshed DC grid Regulator’sControllability? Cost + abilities Yes Price cap NoPredictability? PBR ility r vab to bse No u utp Menu Yes ho servab ility Hig t) ob pu t or outpu High (inObservability? Data from several op Yardstick e rators 17
  18. 18. Conclusion Textbook regulation assumes an “unlimitedly endowed” regulator targeting a single type of TSO’s task (cost) – Yes: the practical successes of incentive regulation are maximised when the regulator is able to mimick the expected theoretical behaviour However reality is not with unlimited regulatory power or resources – Regulator may have tight resources and only limited abilities – Distinct regulatory tools have to be applied to different targeted costs/tasks Regulatory tools should be aligned with – The regulatory characteristics of the targeted tasks (costs): controllability, predictability and observability – And the regulator’s endowment 18
  19. 19. 15th June 2012 – EUI, Florence Incentive regulation with bounded regulators Thank you for your attention! Comments and questions are welcomeJean-Michel Glachant, Haikel Khalfallah (FSR-EUI), Yannick Perez (LdP chair-EUI) Vincent Rious, Marcelo Saguan (Microeconomix, LdP chair-EUI) 1st Annual Conference on the Regulation of Infrastructure Industries 19
  20. 20. Have a look the in at ternat journ ionalI am c al hief-e ditor of!!
  21. 21. Appendixes 21
  22. 22. A reminder of the 5 standard regulatory tools Cost + – The network operator is then paid based on its cost-of-service Price cap – The network operator has then a maximum allowed tariff level Performance (Output) regulation – The network operator has then an efficiency target and is rewarded or penalised depending on its over- or under- performance Menu of contracts – The regulator proposes different regulatory contracts to the network operator with different degrees of incentives Yardstick or benchmarking techniques – These techniques can only be applied if the regulator controls the cost of several homogeneous network companies – The regulator sets the efficiency target to a network company as a function of its performance relative to the other network companies’ performance 22
  23. 23. The real regulators are not always endowed with a full range of judicial powers The European example before the 3rd directive 5An example of 4 or 4½evaluation of theEuropeanregulators’ 3 or 3½abilities 0 or 2 Ex ante Regulation (=1) Independency from government (= 1 or ½ or 0) TPA setting (=1) Ability to solve conflicts (=1) Ability to acquire information (=1) Source : EU, 2004. 3rd Benchmarking Report on implementation of electricity and gas internal market. N.B.: Information for Germany is up to date and taken from the German regulator’s website 23
  24. 24. The real regulators are not always endowed with the highest amount of ressources The example of budget and staff in 2009 (for 100 TWh) LegendSources: Own calculus and•Budget & staff from www.iern.net•Annual load fromhttp://epp.eurostat.ec.europa.eu/portal/page/portal/energy/data/main_tables#•Power Purchase Parity fromhttp://data.worldbank.org/indicator/PA.NUS.PRVT.PP 24
  25. 25. The regulator might be unable to distinguish between the effect of the network operator’s effort and the effect of uncertainty Effect on Effect oncongestion cost congestion cost of the effort by of the effort by the network the network operator NOT operator detectable by detectable bythe regulator in - - Without any NO’s effort the regulator in presence of _ With NO’s effort presence of low high uncertainty uncertainty 25

×