1. The Use of Oligopoly Equilibrium for 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 q i 2, c = mc(q) = q i Market supply = Q = q 1 + q 2 Linear demand Q = a-b*p = 10 – p NO CAPACITY CONSTRAINTS

11. 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

12. 12 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

13. 13 Cournot Equilibrium and Competitive Market Price for Base Case - Elasticity = -.1

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

15. 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-q c ) = C’

16. 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)

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

19. Simulation Results California 2000

21. Impact of Further Divestiture (summer 2000)

24. 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

25. Simple Example –2 firms, c(q) = 1/2 q i 2, c = mc(q) = q i –Market supply = Q = q 1 + q 2 –Linear demand Q = a-b*p = 10 – p –NO CAPACITY CONSTRAINTS –Firm 2 has contracts for quantity q c 2

28. Green and Newbery (1992)

29. 0 $ D max D min Bound on NC Equilibrium outcomes Cournot competitive Bounds on Non-Cooperative Outcomes Q supplied

30. 0 $ D max D min Bound on NC Equilibrium outcomes Cournot competitive Contracts Reduce Bounds Contract Q

31. 0 D max D min Bound on NC Equilibrium outcomes Cournot competitive Contract Q Q supplied $ “Over-Contracting’ can drive prices below competitive levels

32. 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

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

37. 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-q c ) = C’

43. 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