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EC365 Theory of Monopoly and Regulation Topic 8: Regulation of monopoly

EC365 Theory of Monopoly and Regulation Topic 8: Regulation of monopoly. 2013-14, Spring Term Dr Helen Weeds. Lecture outline. 1. Price regulation in theory models of regulation under asymmetric information linear price rules 2. Price regulation in practice

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EC365 Theory of Monopoly and Regulation Topic 8: Regulation of monopoly

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  1. EC365 Theory of Monopoly and RegulationTopic 8: Regulation of monopoly 2013-14, Spring Term Dr Helen Weeds

  2. Lecture outline • 1. Price regulation in theory • models of regulation under asymmetric information • linear price rules • 2. Price regulation in practice • rate of return v. price cap regulation • UK experience

  3. 1. Theory of regulation • Monopoly regulation is a principal-agent problem • regulator (P) wants welfare-maximising outcomes • firm (A) has superior information: costs, own effort, etc. • Decision-making is delegated to firm • prices, outputs; cost-reducing effort; product selection, etc. • 2 types of informational problem • hidden information: firm’s (intrinsic) cost efficiency • results in adverse selection • hidden action: firm’s cost-reducing effort • generates moral hazard

  4. Regulatory objectives • 1. Allocative efficiency • price = cost (MC; AC; non-linear pricing) • optimal product variety and quality • 2. Productive efficiency • costs are minimised • dynamic as well as static • 3. Distribution of welfare • minimise excess profit (if consumerist regulator) • 4. Regulatory burden • informational requirements; monitoring • regulatory costs; lobbying

  5. Regulation with hidden action • Loeb & Magat (1979) • regulator maximises W = V + , where V = cons surplus • total cost C = C(Q, e) • regulator cannot observe C or e • regulator observes price P, demand Q(P) and V(P) • Loeb-Magat mechanism • regulator allows firm to keep entire revenue PQ(P) • and gives lump-sum transfer = V(P) • Profit = PQ(P) – C(Q, e) + V(P) = W • incentives are aligned • firm chooses P* (= MC) and e*

  6. Simple numerical example • Total cost C = 700 + 20Q; demand Q = 100 – P • Loeb-Magat: regulator gives firm transfer V = CS(P) • CS(P) = ½(100 – P)2 • Firm: π = PQ(P) – C(Q(P)) + V(P) • = P(100–P) – 700 – 20(100–P) + ½(100–P)2 • = 2300 + 20P – ½P2 • FOC: 20 – P = 0  P = 20 • Transfer V = ½(100–P)2 = 3200 • Firm’s profit = V – FC = 3200 – 700 = 2500

  7. Assessing Loeb-Magat • Measure against regulatory objectives • Allocative efficiency? • Productive efficiency? • Distribution? • what if monopoly franchise is auctioned? • Regulatory burden?

  8. Regulation with hidden information • Baron & Myerson (1982) • regulator maximises W = V +  where   [0, 1] • regulator observes demand Q(P) • constant unit production cost  ; no fixed costs •  is unobserved by regulator • regulator knows density fnf(), with support [, ] • Baron-Myerson mechanism • firm chooses P from price menu; keeps revenue PQ(P) • firm is given lump-sum transfer T(P) • NB: Loeb-Magat is special case where T(P) = V(P) • what is optimal schedule T*(P)?

  9. Baron-Myerson mechanism • Firm chooses P to max • In setting the transfer function T(P), the regulator faces a trade-off between • higher T so that firm sets P closer to MC (like Loeb-Magat) • minimising firm’s profit (if  < 1) • Outcome • for  = 1, P* = MC (as in Loeb-Magat) • for  < 1, P* > MC (except when  = , lowest cost type) • firm generally makes excess profit (“information rents”) (except when  = , highest cost type)

  10. Assessing Baron-Myerson • Measure against regulatory objectives • Allocative efficiency? • Productive efficiency? • not an issue here as no cost-reducing effort • Distribution? • Regulatory burden?

  11. Hidden action and hidden information • Laffont & Tirole (1986) • regulator maximises W = V +  • regulator observes unit cost c • cost reduction is possible: c =  – e •  and e unobserved by regulator •  is random: density fn f() • effort is costly to firm: cost (e) where '(e) > 0, ''(e) > 0 • Asymmetric information • hidden information  • hidden action e • is low observed c due to good luck or high effort?

  12. Laffont-Tirole mechanism • Lump-sum transfer T(P, c): use both observables • trade-off between efficiency and distribution • Firm of type  chooses P and c (via choice of e) to maximise • Outcome • P = MC for all cost types • i.e. full cost-pass-through • productive efficiency is not always achieved •  = 1: e is at the optimal level (productive efficiency) •  < 1: e is below first-best (except for lowest-cost type)

  13. Assessing Laffont-Tirole • Measure against regulatory objectives • Allocative efficiency? • Productive efficiency? • Distribution? • Regulatory burden?

  14. Lessons from regulation models • Asymmetric information is crucial • constrained-optimal solution departs from first-best (full information benchmark) • information rents accrue to firm • trade-offs between regulatory objectives • Loeb-Magat Baron-Myerson Laffont-Tirole Allocative effic  sometimes  Productive effic  n/a sometimes Distribution poor sometimes sometimes

  15. Price regulation • In practice, lump-sum transfers generally unavailable • Instead, regulator controls prices • How should prices be regulated? • in particular, how should price take account of costs? • (1) Fixed price • strong incentive to minimise costs, as firm keeps benefit • but price may depart from cost • (2) Price = cost • no excess profit • but little incentive to minimise costs

  16. Linear pricing rules • Suppose cost c =  – e •  = exogenous factor [, ]; e = unobserved effort • Regulator sets P = P(c) • Fixed price regulation: P(c) = • firm exerts optimal effort e* • must exceed – e* to ensure participation, even by highest cost type • for  < , P > MC and firm makes excess profit • Regulation at cost: P(c) = c • no effort exerted, but P = MC and no excess profit

  17. Linear pricing rules (2) • Or choose something between the two extremes • Intermediate case: P(c) = + (1–)c where 0   1: degree of cost sensitivity (higher  means price cap less sensitive to costs) • Regulator chooses and  • fixed price (*= 1) if there is no cost uncertainty, or if investors are not risk-averse • more cost-sensitive (smaller *) if there is more uncertainty or greater risk-aversion • when  > 0, the firm bears some risk • trade-off between insurance and incentives

  18. 2. Price regulation in practice • Pure price-cap regulation • P = ;  = 1: no cost sensitivity • Cost-plus or rate of return (RoR) regulation • P = c (including normal return on capital) • In reality, most systems are intermediate • price caps with • cost pass-through elements • periodic reviews • rate of return with • implementation lag • cost assessment

  19. US: Rate of return regulation • Rate of return regulation historically used in the US • Price is set for the accounting period according to • ipiqi = C + sB where pi, qi = price, output for service i C = firm’s total operating costs s = allowed (“fair”) rate of return B = firm’s installed capital base (“rate base”) • Features • price = cost • guaranteed return on capital; no excess return

  20. Issues arising in rate of return regulation • Regulatory lag • some incentive to reduce costs during this time • typically short (e.g. annual); may be endogenous • Cost measurement • based on accounting information • Measurement of rate base • asset valuation: historic vs current cost • depreciation profile • Appropriate rate of return • cost of capital estimation

  21. Investment: the Averch-Johnson effect • Firm chooses capital K and labour L to • maximise  = R(K, L) – wL – rK where R = revenue fn, w = wage rate, r = cost of capital • allowed rate of return on capital [R(K, L) – wL] / K = s • assume allowed rate of return s > r • Solution: where • m = Lagrange multiplier (shadow value of s)  (0, 1) • efficient production requires MPK/MPL = r/w • regulated firm over-invests in capital: “gold plating” • Regulatory response: “used and useful” test

  22. Figure 1: The Averch-Johnson effect

  23. Utility privatisation in the UK • 1984: British Telecom • 1986: British Gas • 1989: Water industry (10 regional companies) • 1990-91: Electricity industry • 2 generation cos (+ later nuclear power) • national (high voltage) transmission grid • 12 regional distribution & supply cos • separate companies for Scotland (2) and N Ireland (1) • 1995-97: Railways • Railtrack (1996) • regional train operating franchises (1995-97) • rolling stock companies; maintenance companies

  24. UK: Littlechild Report (1983) • Criteria for assessing regulatory regimes • protect against monopoly • encourage efficiency & innovation • minimise burden of regulation • promote competition • proceeds from privatisation and prospects for the firm • Considered various regulatory schemes • three forms of profit regulation • rate of return regulation • output-related profits levy • profit ceiling • price controls: RPI – X system

  25. Littlechild’s assessment • Profit regulation undesirable • poor efficiency incentives; distorts investment • covers whole business, not focused on monopoly services • Recommended RPI – X • protects against monopoly by capping prices • good incentives for efficiency & innovation • low burden: calculate simple price indices • no need to measure asset base & rate of return, determine cost allocation, forecast costs & demand • entry incentives for long-distance market (if unreg’d) • foresaw regulatory withdrawal in due course • good prospects for firm; high privatisation proceeds

  26. RPI – X price cap regulation • Increases price caps at RPI rate less X • applies to a basket of prices (weighted average) for monopoly services • X may vary across firms in sector, and from year to year • some restrictions on tariff rebalancing: subsidiary caps; non-discrimination clauses (but cross-subsidies persisted) • Regulatory lag • X’s pre-specified for period between reviews • significant lag between reviews: typically 5 years • Some cost pass-through elements • certain costs beyond control of firm (esp. if volatile) • e.g. generation costs for electricity supply companies

  27. Regulatory review • X factors must be reset periodically • Regulatory review typically takes account of • operating costs; expected productivity and demand growth • asset values; allocation between reg’d and unreg’d business • cost of capital • future investment requirements • extent of competition (possible regulatory withdrawal) • Initially considerable regulatory discretion • possibility of appeal to MMC (now CC) • Now a more formalised process

  28. Quality of service regulation • Consumer surplus V(P, S); V/S > 0 (S = service quality) • Firm chooses S to max (P, S) • FOC: /S = 0 • Welfare W = V +  • FOC: V/S +  /S = 0 • S chosen by firm istoo low: ignores effect on CS • Price cap based on given quality level • reduction in S may be difficult to monitor • firm may S to  profit margin

  29. Investment incentives: A hold-up problem • Underinvestment due to lack of regulatory commitment • Period 1: Firm chooses investment • sunk investment K reduces marginal cost c0c1 • investment is efficient: (c0 – c1)Q > rK • firm will invest iff can gain return  rK • Period 2: Periodic review of price cap P • ex ante: regulator promises P = c1 + rK/Q • ex post: incentive to set P = c1 • foreseeing that K will not be recouped, firm will not invest • Solutions: reputation (repeated game); transparency over criteria; appeal to MMC (CC); regulatory duties (finance operations)

  30. RPI – X regulation in practice • Price trends • prices fell significantly in most industries (except water) • initial efficiency gains and “asset-sweating” • Price structure • elimination of many historic cross-subsidies • Scope of price control • has not “withered away” but tended to widen (early on): leased lines; gas supply to large users; elec generation • recently: retail market deregulation in gas, elec, telecoms • Tougher approach to cost pass-through • Tendency to cut prices / profits between reviews

  31. Summary: rate of return v. price cap regulation • Price adjusts continuously • Pre-specified price path • Good for allocative efficiency • Poor for allocative efficiency • Poor for productive efficiency • Good for productive efficiency • Over-investment incentive • Under-investment incentive • Possible quality over-provision • Incentive to cut quality

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