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Per AGRELL Peter BOGETOFT KVL, Economics Denmark DEA-BASED INCENTIVE REGULATION : Electricity Distribution in Scandinavia Nordic Efficiency Analysis Meeting,

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Presentation on theme: "Per AGRELL Peter BOGETOFT KVL, Economics Denmark DEA-BASED INCENTIVE REGULATION : Electricity Distribution in Scandinavia Nordic Efficiency Analysis Meeting,"— Presentation transcript:

1 Per AGRELL Peter BOGETOFT KVL, Economics Denmark DEA-BASED INCENTIVE REGULATION : Electricity Distribution in Scandinavia Nordic Efficiency Analysis Meeting, Eskilstuna, June 27, 2000

2 (c) BOGETOFT, KVL2 OUTLINE 1.BACKGROUND 2.LITERATURE 3.BASIC QUESTIONS 4.NORDIC ANSWERS 5.BASIC MODEL STRUCTURE 6.STATIC REGULATION 7.DYNAMIC REGULATION 8.EXTENSIONS 9.CONCLUSIONS

3 (c) BOGETOFT, KVL3 BACKGROUND WHO ARE WE ? Per Agrell, ph.d., docent, Linköping, Univ. of Georgia, Univ. of Copenhagen, KVL Peter Bogetoft, dr.merc, professor, Århus Univ., Odense Univ., Yale Univ, CBS, Univ. of California, KVL Decision Theory (MCDM etc), Efficiency Evaluation (DEA etc) and Incentive Theory (Agency, Contracts etc) KVL, SUMICSID HB and ECOPLAN

4 (c) BOGETOFT, KVL4 LITERATURE (1) Agrell, P., P. Bogetoft and J.Tind, Dynamic Yardstick Incentives, Working Paper, Agrell, P., P. Bogetoft and J.Tind, Incentive Plans for Productive Efficiency, Innovation and Learning, International Journal of Production Economics, forthcoming. Bogetoft, P., Strategic Responses to DEA Control, Working Paper, Bogetoft, P. Non-Cooperative Planning Theory, pp.1 ‑ 314, Springer-Verlag, Bogetoft, P, Incentive Efficient Production Frontiers: An Agency Perspective on DEA, Management Science, 40, pp , 1994.

5 (c) BOGETOFT, KVL5 LITERATURE (2) Bogetoft, P, Incentives and Productivity Measurements, International Journal of Production Economics, 39, pp , Bogetoft, P, DEA-Based Yardstick Competition: The Optimality of Best Practice Regulation, Annals of Operations Research, 73, pp , Bogetoft, P., DEA and Activity Planning under Asymmetric Information, Journal of Productivity Analysis, 13, pp. 7-48, Bogetoft, P. and D. Wang, Estimating the Potential Gains from Mergers, Working Paper, 1999.

6 (c) BOGETOFT, KVL6 BASIC QUESTIONS (1) IMMEDIATE REG. REQUIREMENTS ECONOMICAL Social Welfare JUDICIAL Enforceable, legally authoritative (court appeals) ADMINISTRATIVE Manageable administrative workload Supports concession granting, monitoring and information dissemination

7 (c) BOGETOFT, KVL7 BASIC QUESTIONS (2) FUND. ECO. ISSUES COORDINATION / EFFICIENCY Ensure that the right products are produced using the right factors and that they are available at the right time and space SR: Technical eff., scale eff., allocative eff., cost eff., LR: Structural development, Mergers, Concessions MOTIVATION Ensure that de-central agents have incentives to implement the efficient plan

8 (c) BOGETOFT, KVL8 BASIC QUESTIONS (3) BASIC ECONOMIC MEANS CONCESSION GRANTING MONITORING AND INCENTIVE REGULATION –Nationalization –Individual Contracting, Outsourcing –Cost-Plus –Marginal Cost Pricing, Ramsey Prices, –Rate-of Return, Price Cap, Revenue Cap –Yardstick Competition, Yardstick Cap INFORMATION DISSEMINATION: –Learning –Encourage structural development (mergers, take-overs etc –Self-regulation (consumer, political reactions etc)

9 (c) BOGETOFT, KVL9 BASIC QUESTIONS (4) THE ESSENTIAL PROBLEM PROBLEM Given cross section, time series or panel information: (input, output) for i=1,…,n what should we ask the agent to do and how should we pay him ? DO NOT KNOW Better find out!

10 (c) BOGETOFT, KVL10 BASIC QUESTIONS (5) THE NAIVE TECHN. SOLUTION DO KNOW, e.g. Estimate cost function: C(output) Find Benefit Function: B(output), Choose to maximize Benefit minus Costs Pay estimated costs, actual costs, yardstick costs etc NEW QUESTIONS How estimate C(.) ? Use DEA ? Econometrics ? What is the optimal payment ? How should additional information feed into the process ? etc

11 (c) BOGETOFT, KVL11 THE NORDIC ANSWERS (1) NORWAY COST MODEL: DEA cost model to estimate individual inefficiencies and general productivity development PAYMENT SCHEME Revenue cap with rate-of-return restrictions and an efficiency incentive. 2 year review period 5 year regulation period Deviations (+/-) accounted for in next regulation period

12 (c) BOGETOFT, KVL12 THE NORDIC ANSWERS (2) NORWAY (Cont.) Core of the regulatory scheme: R t =PI t,t-1 QI t,t-1 (1-  - G t ) R t-1 C t +  min X t  R t  C t +  max X t where Rrevenue Ccosts PIprice index QIquantity index Gadjusted DEA efficiency min{(1-E 0 )/(1-E low ),1}  general productivity improvement (1,5%, Malmquist based)  catch up coefficient (max 38.24% eliminated in 4 years)  rate-of-return bounds (2%-15%)

13 (c) BOGETOFT, KVL13 THE NORDIC ANSWERS (3) FINLAND COST MODEL: DEA model VRS with two inputs, two outputs, 2-5 non- controllable factors PAYMENT SCHEME Rate of return Idea: C = CE DEA C Controllable 1 year review period 1 year regulation period

14 (c) BOGETOFT, KVL14 THE NORDIC ANSWERS (4) DENMARK COST MODEL: Cost norm (net-volume) based on simple linear regression with density correction. Individual eff. impr. reqr.: set by cost norm General prod. impr. reqr.: set by minister PAYMENT SCHEME Revenue cap with an efficiency incentive and some rate-of-return restriction. 4 year review period 4 year regulation period Deviations (+/-) accounted for in next regulation period

15 (c) BOGETOFT, KVL15 THE NORDIC ANSWERS (5) DENMARK (Cont.) Core of cost model: Net-volume: C * i =  1 Net Low1 ……  17 Costumers Initial eff.:F initial i = C actual i / C * i Corr. regres.:F initial i =k 2 +k 1 Costumer density i + noise Corr.factor:K i =k 2 +k 1 Costumer density i Correction factor is used to adjust all net-component until 10kV in net-volume, i.e approximately Efficiency:F i = C actual i / (C * i K i ) (Note, low value corresponds to high efficiency)

16 (c) BOGETOFT, KVL16 THE NORDIC ANSWERS (6) DENMARK (Cont.) Core of regulation model (details to be verified;based on reading of legal document) Revenue cap with an efficiency incentive and some rate-of-return restriction. R t = (1-  )(1/ F)(C 0 Contr Pi t,t-1 +Depr 0 )+Interests 0 + C t Non-Contr  t = C t Contr + Depr t. -(1-  )(1/ F)(C 0 Contr Pi t,t-1 +Depr 0 ) where  t : extraordinary efficiency gain Not full cap can always be claimed: Max keep 5% R t of  t Max on return on equity

17 (c) BOGETOFT, KVL17 THE NORDIC ANSWERS (7) SWEDEN COST MODELS: Net-utility model: : Simple parametric model cost model with “optimal” network as input C * i = k 1 (Net Low ) k2 + k 3 (Net High ) k4 + k 5 (InstPower) k6 DEA models: Five outputs, 3 or 2 non - controllable factors, SR (VRS) and LR (CRS) models PAYMENT SCHEME ??

18 (c) BOGETOFT, KVL18 THE NORDIC ANSWERS (8) SWEDEN (Cont.) SUMICSID CONSULTANCY PROPOSAL COST MODELS: Modeling principle: Controllability SR model: VRS, technical, allocative and cost efficiency LR model: CRS, technical, allocative and cost efficiency PAYMENT SCHEME (NO PROJECT – JUST DREAMS) DEA based –Learning –Self-regulation –Auditing priorities –Incentive system using income cap or efficiency regulated return on equity (REO)

19 (c) BOGETOFT, KVL19 THE NORDIC ANSWERS (9) SWEDEN (Cont.) SHORT RUN VARIABLE INPUT LONG RUN EXOGENOUS INPUT OUTPUT FIXED INPUT MODELLING PRINCIPLE: controllability!

20 (c) BOGETOFT, KVL20 THE NORDIC ANSWERS (10) SWEDEN (Cont.) DISTRIBUTOR [SHORT RUN] DISTRIBUTOR [SHORT RUN] LABOR OP. COST EX LOSS COST ENERGY LC ENERGY HC CUSTOMERS LC CUSTOMERS HC MAX DEL. POW. NET LENGTH INSTALLED DISTRIBUTION STATIONS/INSTALLED POWER (MW) CLIMATE MODEL (SR)

21 (c) BOGETOFT, KVL21 THE NORDIC ANSWERS (11) SWEDEN (Cont.) DISTRIBUTOR [LONG RUN] DISTRIBUTOR [LONG RUN] VAR COST TR. LOSSES OPTIMAL NETLENGTH CLIMATE ENERGY LC ENERGY HC CUSTOMERS LC CUSTOMERS HC MAX DEL.POW. REAL CAP. (NUAK) MODEL ( LR )

22 (c) BOGETOFT, KVL22 THE NORDIC ANSWERS (12) SWEEDEN (Cont.) INCENTIVE SYSTEM “Reasonable” profit –135% of risk-free rate (Edin-Svahn, 1998) Participation –No net operative losses Non-controllable costs –Passed on to consumers Tariff structure –“Light-handed regulation”

23 (c) BOGETOFT, KVL23 THE NORDIC ANSWERS (13) SWEEDEN (Cont.) POTENTIAL INCENTIVE SYSTEM “Green” operator –Full “reasonable” profit (ROE) “Yellow” operator –ROE = (risk free rate)CE “Red” operator –Potential audit by STEM –ROE = 0%

24 (c) BOGETOFT, KVL24 THE NORDIC ANSWERS (14) SWEEDEN (Cont.) Green = OK Yellow = Remark Red = Audit? “ANNUAL ECONOMIC NET-INSPECTION”

25 (c) BOGETOFT, KVL25 BASIC MODEL STRUCTURE A Principal – Agent Framework with Technological Assumptions: Underlying min. cost fu.: C(y) Actual Costs:: x=C(y)+slack Benefits (assume given demand today): B(y) n obs. of past/similar DMUs : (x i,y i ), i=1,..,n Informational Assumptions: Agent knows: everything Principal knows: CLASS of cost fu., x, y and data (x i,y i ), i=1,..,n, CLASS can be linear function, convex functions or any class in between

26 (c) BOGETOFT, KVL26 BASIC MODEL STRUCTURE (2) Behavioral Assumptions: Agent chooses x to max U = profit +  slack = (R-x) +  ( x - C(y) ) where R is payment plan and   1 Agent participates if U  U * (=0 wlog) Principal chooses y and b to max B(y) – R Or given y, choose R–plan to minimize implementation cost (production plus incentive costs) R

27 (c) BOGETOFT, KVL27 BASIC MODEL STRUCTURE (3) Adverse selection and moral hazard problem: Because of asymmetric information (hidden action slack and hidden information C(.)), the principal must give the agent private incentives to implement the desired behavior. Contract Design Problem: Principal solves: Min Expected Payment R s.t. Individual Participation (IR) Incentive Compatibility (IC) The exact formulation depends on what additional information is available.

28 (c) BOGETOFT, KVL28 STATIC REGULATION (1) STANDARD NO COMMUNICATION SETTING: Opt. Tech. : cost efficient – no slack Opt. Payment R: C DEA (y) Opt. Prod.: max B(y)-C DEA (y) Hence DEA gives optimal revenue cap !!! Extensions: Relax IR (Allow bankruptcy) – same structure – just introduce ”rationing” constraints

29 (c) BOGETOFT, KVL29 STATIC REGULATION (2) VERIFIABLE COSTS x: Opt. Tech. : cost efficient – no slack Opt. Payment R: x+  ( C DEA (y) –x ) actual costs plus  of cost saving Opt. Prod.: max B(y)-(  C DEA (y)+(1-  )E(C(y)) )

30 (c) BOGETOFT, KVL30 STATIC REGULATION (3) COMPARISONS: Cost Plus: R = (1+  )x –No cost minimization incentives Revenue Cap: R = R * –Cost min. incentives, –Potentially high info. rents –Potential bankruptcy

31 (c) BOGETOFT, KVL31 STATIC REGULATION (4) COMPARISONS (Cont): Simple DEA Revenue Cap: R = C DEA (y) –Cost min. incentives –Minimal total costs (rents+prod) given –No bankruptcy (or optimal bankruptcy) DEA Based Yardstick Revenue Cap: x+  ( C DEA (y) –x ) –Cost min incentives –Lower total costs (lower rents) –No bankruptcy (or optimal bankruptcy)

32 (c) BOGETOFT, KVL32 STATIC REGULATION (5) FURTHER EXTENSIONS: If B(.) can be communicated: –A decentralized scheme can improve allocative efficiency. –Agent makes trade-offs between true costs and B(.) –Optimal payment R: x+  ( C DEA (y DEA ) –x ) actual costs plus  of cost saving Note: y DEA solves min C DEA (.), so harder cost norm If C(.) can be communicated: –Opt. prod. plan is biased towards y DEA

33 (c) BOGETOFT, KVL33 DYNAMIC REGULATION Limited catch-up capability –Time delay a la Norwegian Scheme Ratchet effect –Handled optimally by DEA yardstick revenue Use new information efficiently –Blueprint (Norwegian, Danish): gives stability but under- utilize info. and general risk not eliminated –Sequential Updating Scheme : makes full use of info. and eliminate general risk. DEA yardstick optimal. Control the information generation process –Optimal Adaptive Control: makes full use of info., eliminates general risk and controls the learning process. Support Learning – Innovation – Teaching Cycle -Reward catch-up, frontier movements and others catch-up

34 (c) BOGETOFT, KVL34 EXTENSIONS MERGERS –DEA model can determine potential efficiency, scale and scope gains –Convex models have scope effects –Naive aggregations and regulation procedures may discourage efficient mergers –Share scope gains between firms and costumers AUCTIONS –DEA yardstick to aggregate multi-dimensional bids

35 (c) BOGETOFT, KVL35 CONCLUSIONS DEA useful technique in regulation – supports –Concession Granting –Monitoring and Incentive Regulation –Information Dissemination DEA based yardstick revenue often provides optimal regulatory scheme Norwegian scheme has some of the features - but far from all !


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