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Estimating Market Power in Homogenous Product Markets Using a Composed Error Model: Application to the California Electricity Market

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  • Orea, Luis
  • Steinbuks, Jevgenijs

Abstract

This study contributes to the literature on estimating market power in homogenous product markets.We estimate a composed error model, where the stochastic part of the firm’s pricing equation is formed by two random variables: the traditional error term, capturing random shocks, and a random conduct term, which measures the degree of market power. Treating firms’ conduct as a random parameter helps solving the issue that the conduct parameter can vary between firms and within firms over time. The empirical results from the California wholesale electricity market suggest that realization of market power varies over both time and firms, and reject the assumption of a common conduct parameter for all firms. Notwithstanding these differences, the estimated firm-level values of the conduct parameter are closer to Cournot than to static collusion across all specifications. For some firms,the potential for realization of the market power unilaterally is associated with lower values of the conduct parameter.

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  • Orea, Luis & Steinbuks, Jevgenijs, 2012. "Estimating Market Power in Homogenous Product Markets Using a Composed Error Model: Application to the California Electricity Market," Efficiency Series Papers 2012/02, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    • Handle: RePEc:oeg:wpaper:2012/02
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    4. Bhattacharyya, Aditi & Kutlu, Levent & Sickles, Robin C., 2018. "Pricing Inputs and Outputs: Market prices versus shadow prices, market power, and welfare analysis," Working Papers 18-009, Rice University, Department of Economics.
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    6. Mydland, Ørjan & Størdal, Ståle & Kumbhakar, Subal C. & Lien, Gudbrand, 2022. "Modeling markups and its determinants: The case of Norwegian industries and regions," Economic Analysis and Policy, Elsevier, vol. 76(C), pages 252-262.
    7. Wan, Yi & Kober, Tom & Densing, Martin, 2022. "Nonlinear inverse demand curves in electricity market modeling," Energy Economics, Elsevier, vol. 107(C).
    8. Levent Kutlu & Robin C. Sickles & Mike G. Tsionas & Emmanuel Mamatzakis, 2022. "Heterogeneous decision-making and market power: an application to Eurozone banks," Empirical Economics, Springer, vol. 63(6), pages 3061-3092, December.
    9. Ruiz-Moreno, Felipe & Mas-Ruiz, Francisco J. & Sancho-Esper, Franco M., 2021. "Strategic groups and product differentiation: Evidence from the Spanish airline market deregulation," Research in Transportation Economics, Elsevier, vol. 90(C).
    10. Robert Germeshausen & Timo Panke & Heike Wetzel, 2020. "Firm characteristics and the ability to exercise market power: empirical evidence from the iron ore market," Empirical Economics, Springer, vol. 58(5), pages 2223-2247, May.
    11. Devin Garcia & Levent Kutlu & Robin C. Sickles, 2022. "Market Structures in Production Economics," Springer Books, in: Subhash C. Ray & Robert G. Chambers & Subal C. Kumbhakar (ed.), Handbook of Production Economics, chapter 13, pages 537-574, Springer.
    12. Chiara Lo Prete and Benjamin F. Hobbs, 2015. "Market power in power markets: an analysis of residual demand curves in Californias day-ahead energy market (1998-2000)," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    13. Dibyendu Maiti & Chiranjib Neogi, 2020. "Endogeneity Corrected Stochastic Frontier with Market Imperfections," Working papers 313, Centre for Development Economics, Delhi School of Economics.
    14. Kutlu, Levent & Tran, Kien C. & Tsionas, Mike G., 2020. "A spatial stochastic frontier model with endogenous frontier and environmental variables," European Journal of Operational Research, Elsevier, vol. 286(1), pages 389-399.
    15. Mustafa U. Karakaplan & Levent Kutlu, 2019. "Estimating market power using a composed error model," Scottish Journal of Political Economy, Scottish Economic Society, vol. 66(4), pages 489-510, September.
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    More about this item

    Keywords

    market power; random conduct parameter; composed error model; asymmetric distributions; California electricity market;
    All these keywords.

    JEL classification:

    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • L13 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Oligopoly and Other Imperfect Markets
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities

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