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The Use of Oligopoly Equilibrium for Economic and Policy Applications

The Use of Oligopoly Equilibrium for Economic and Policy Applications. Jim Bushnell, UC Energy Institute and Haas School of Business. A Dual Mission. “Research Methods” - how oligopoly models can be used to tell us something useful about how markets work Potentially very boring

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The Use of Oligopoly Equilibrium for Economic and Policy Applications

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  1. The Use of Oligopoly Equilibriumfor Economic and Policy Applications Jim Bushnell, UC Energy Institute and Haas School of Business

  2. A Dual Mission • “Research Methods” - how oligopoly models can be used to tell us something useful about how markets work • Potentially very boring • What makes electricity markets work (or not)? • Blackouts, Enron, “manipulation,” etc. • A new twist on how we think about vertical relationships • Potentially very exciting

  3. Oligopoly Models • Large focus on theoretical results • Simple oligopoly models provide the “structure” for structural estimation in IO • Seldom applied to large data sets of complex markets • Some markets feature a wealth of detailed data • Optimization packages make calculation of even complex equilibria feasible

  4. A Simple Oligopoly Model • Concentration measures where m is Cournot equilibrium margin.

  5. Surprising Fact: Oligopoly models can tell us something about reality • Requires careful consideration about the institutional details of the market environment • Incentives of firms (Fringe vs. Oligopoly) • Physical aspects of production (transmission) • Vertical & contractual arrangements • Recent research shows actual prices in several electricity markets reasonably consistent with Cournot prices • Cournot models don’t have to be much more complicated than HHI calculations

  6. Empirical Applications • Analysis of policy proposals • Prospective analysis of future market • Merger review, market liberalization, etc. • Market-level empirical analysis • Retrospective analysis of historic market • Diagnose sources of competition problems • Simulate potential solutions • Firm-level empirical analysis • Estimate costs or other parameters (contracts) • Evaluate optimality of firm’s “best” response • Potentially diagnose collusive outcomes

  7. Oligopoly equilibrium models • Cournot – firms set quantities • many variations • Supply-function – firms bid p-q pairs • infinite number of functional forms • Range of potential outcomes is bounded by Cournot and competitive • Capacity constraints, functional form restrictions reduce the number of potential equilibria • Differentiated products models (Bertrand)

  8. Green and Newbery (1992)

  9. Simple Example • 2 firms, c(q) = 1/2 qi2, c = mc(q) = qi • Market supply = Q = q1 + q2 • Linear demand Q = a-b*p = 10 – p • NO CAPACITY CONSTRAINTS

  10. Three Studies of Electricity • Non-incremental regulatory and structural changes • Historic data not useful for predicting future behavior • Large amounts of cost and market data available • High frequency data - legacy of regulation • Borenstein and Bushnell (1999) • Simulation of prospective market structures • Focus on import capacity constraints • Bushnell (2005) • Simulation using actual market conditions • Focus on import elasticities • Bushnell, Saravia, and Mansur (2006) • Simulation of several markets

  11. Western Regional Markets • Path from NW to northern California rated at 4880 MW • Path from NW to southern California rated at 2990 MW • Path from SW to southern California rated at 9406 MW (W-O-R constraint) • 408 MW path from northern Mexico and 1920 MW path from Utah

  12. Cournot Equilibrium andCompetitive Market Price for Base Case - Elasticity = -.1

  13. Table 1: Panel A, California Firm Characteristics HHI of 620

  14. Methodology for Utilizing Historic Market Data • Data on spot price, quantity demanded, vertical commitments, and unit-specific marginal costs. • Estimate supply of fringe firms. • Calculate residual demand. • Simulate market outcomes under: • 1. Price taking behavior: P = C’ • 2. Cournot behavior: P + P’ * q = C’ • 3. Cournot behavior with vertical arraignments: P + P’ * (q-qc) = C’

  15. Modeling Imports and Fringe • Source of elasticity in model • We observe import quantities, market price, and weather conditions in neighboring states • Estimate the following regression using 2SLS (load as instrument) • Estimates of price responsiveness are greatest in California (>5000) relative to New England (1250) and PJM (850)

  16. Residual Demand function • The demand curve is fit through the observed price and quantity outcomes.

  17. Simulation ResultsCalifornia 2000

  18. Impact of Further Divestiture(summer 2000)

  19. The Effect of Forward Contracts • Contract revenue is sunk by the time the spot market is run • no point in withholding output to drive up a price that is not relevant to you • More contracts by 1 firm lead to more spot production from that firm, less from others • More contracts increase total production • lower prices • Firms would like to be the only one signing contracts, are in trouble if they are the only ones not signing contracts • prisoner’s dilemma

  20. Simple Example • 2 firms, c(q) = 1/2 qi2, c = mc(q) = qi • Market supply = Q = q1 + q2 • Linear demand Q = a-b*p = 10 – p • NO CAPACITY CONSTRAINTS • Firm 2 has contracts for quantity qc2

  21. Green and Newbery (1992)

  22. Bounds on Non-Cooperative Outcomes $ Cournot Dmax Bound on NC Equilibrium outcomes Dmin competitive Qsupplied 0

  23. Contracts Reduce Bounds $ Dmax Cournot Bound on NC Equilibrium outcomes Dmin competitive 0 Qsupplied Contract Q

  24. “Over-Contracting’ can drive prices below competitive levels $ Dmax Cournot Dmin Bound on NC Equilibrium outcomes competitive 0 Qsupplied Contract Q

  25. Vertical structure and forward commitments • Vertical integration makes a firm a player in two serially related markets • Usually we think of wholesale (upstream) price determining the (downstream) retail price • Gilbert and Hastings • Hendricks and McAfee (simultaneous) • In some markets, retailers make forward commitments to customers • utilities – telecom services – construction • In these markets a vertical arrangement plays the same role as a forward contract • a pro-competitive effect

  26. Methodology • Use market data on spot price, market demand and production costs. • Simulate prices under: • Price taking behavior • Cournot behavior • Cournot with vertical arraignments (integration or contracts) • The first order condition is:

  27. Methodology • Data on spot price, quantity demanded, vertical commitments, and unit-specific marginal costs. • Estimate supply of fringe firms. • Calculate residual demand. • Simulate market outcomes under: • 1. Price taking behavior: P = C’ • 2. Cournot behavior: P + P’ * q = C’ • 3. Cournot behavior with vertical arraignments: P + P’ * (q-qc) = C’

  28. Summary • Oligopoly models married with careful empirical methods are a useful tool for both prospective and retrospective analysis of markets • Careful consideration of the institutional details of the market is necessary • In electricity, vertical arrangements (or contracts) appear to be a key driver of market performance • The form and extent of these arrangements going forward will determine whether the “success” of the markets that are working well can be sustained

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