Book contents
- Frontmatter
- Contents
- List of Contributors
- Preface
- 1 Sorting, Education, and Inequality
- 2 Wage Equations and Education Policy
- Empirical and Theoretical Issues in the Analysis of Education Policy: A Discussion of the Papers by Raquel
- 3 Toward a Theory of Competition Policy
- 4 Identification and Estimation of Cost Functions Using Observed Bid Data: An Application to Electricity Markets
- 5 Liquidity, Default, and Crashes: Endogenous Contracts in General Equilibrium
- 6 Trading Volume
- A Discussion of the Papers by John Geanakoplos and by Andrew W. Lo and Jiang Wang
- 7 Inverse Problems and Structural Econometrics: The Example of Instrumental Variables
- 8 Endogeneity in Nonparametric and Semiparametric Regression Models
- Endogeneity and Instruments in Nonparametric Models: A Discussion of the Papers by Jean-Pierre Florens and by Richard Blundell and James L. Powell
- Index
4 - Identification and Estimation of Cost Functions Using Observed Bid Data: An Application to Electricity Markets
Published online by Cambridge University Press: 23 December 2009
- Frontmatter
- Contents
- List of Contributors
- Preface
- 1 Sorting, Education, and Inequality
- 2 Wage Equations and Education Policy
- Empirical and Theoretical Issues in the Analysis of Education Policy: A Discussion of the Papers by Raquel
- 3 Toward a Theory of Competition Policy
- 4 Identification and Estimation of Cost Functions Using Observed Bid Data: An Application to Electricity Markets
- 5 Liquidity, Default, and Crashes: Endogenous Contracts in General Equilibrium
- 6 Trading Volume
- A Discussion of the Papers by John Geanakoplos and by Andrew W. Lo and Jiang Wang
- 7 Inverse Problems and Structural Econometrics: The Example of Instrumental Variables
- 8 Endogeneity in Nonparametric and Semiparametric Regression Models
- Endogeneity and Instruments in Nonparametric Models: A Discussion of the Papers by Jean-Pierre Florens and by Richard Blundell and James L. Powell
- Index
Summary
INTRODUCTION
This paper presents several techniques for recovering cost function estimates for electricity generation from a model of optimal bidding behavior in a competitive electricity market. These procedures are applied to actual data from the Australian National Electricity Market (NEM1) to recover cost function estimates for a specific market participant. I find close agreement between the cost functions recovered from these procedures and those obtained from engineering estimates. The techniques developed in this paper for recovering cost function estimates are not limited to markets for electricity generation. They can be used to recover cost function estimates for a participant in any bid-based centralized market.
There are number of uses for the procedures developed in this paper. The primary use is to measure the extent of market power possessed by a market participant using only bid information and market-clearing prices and quantities. A major research effort in empirical industrial organization is the measurement of market power. Bresnahan (1989) summarizes much of this research, although there has been an explosion of recent research on this general topic. The techniques presented in this paper are a logical extension of the techniques described by Bresnahan (1989) to bid-based markets.
A major challenge for designers of competitive electricity markets is to devise market rules that limit the ability of generation unit owners to exercise market power. Market power is the ability of a firm owning generation assets to raise the market price by its bidding behavior and to profit from this price increase.
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- Information
- Advances in Economics and EconometricsTheory and Applications, Eighth World Congress, pp. 133 - 169Publisher: Cambridge University PressPrint publication year: 2003
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