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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.

Suggested Citation

  • 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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    1. repec:taf:jnlbes:v:30:y:2012:i:1:p:67-80 is not listed on IDEAS
    2. Severin Borenstein & James Bushnell & Christopher R. Knittel & Catherine Wolfram, 2008. "Inefficiencies And Market Power In Financial Arbitrage: A Study Of California'S Electricity Markets," Journal of Industrial Economics, Wiley Blackwell, vol. 56(2), pages 347-378, June.
    3. Borenstein, Severin & Bushnell, James & Wolak, Frank, 2002. "Measuring Market Inefficiencies in California's Deregulated Electricity Industry," Staff General Research Papers Archive 13136, Iowa State University, Department of Economics.
    4. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    5. Nils-Henrik M. von der Fehr, Eirik S. Amundsen and Lars Bergman, 2005. "The Nordic Market: Signs of Stress?," The Energy Journal, International Association for Energy Economics, vol. 0(Special I), pages 71-98.
    6. Perloff,Jeffrey M. & Karp,Larry S. & Golan,Amos, 2007. "Estimating Market Power and Strategies," Cambridge Books, Cambridge University Press, number 9780521011143, January.
    7. Iwata, Gyoichi, 1974. "Measurement of Conjectural Variations in Oligopoly," Econometrica, Econometric Society, vol. 42(5), pages 947-966, September.
    8. Green, Edward J & Porter, Robert H, 1984. "Noncooperative Collusion under Imperfect Price Information," Econometrica, Econometric Society, vol. 52(1), pages 87-100, January.
    9. Severin Boreinstein & Andrea Shepard, 1996. "Dynamic Pricing in Retail Gasoline Markets," RAND Journal of Economics, The RAND Corporation, vol. 27(3), pages 429-451, Autumn.
    10. Brander, James A. & Zhang, Anming, 1993. "Dynamic oligopoly behaviour in the airline industry," International Journal of Industrial Organization, Elsevier, vol. 11(3), pages 407-435, September.
    11. Abhiman Das & Subal C. Kumbhakar, 2016. "Markup and efficiency of Indian banks: an input distance function approach," Empirical Economics, Springer, vol. 51(4), pages 1689-1719, December.
    12. Nevo, Aviv, 2001. "Measuring Market Power in the Ready-to-Eat Cereal Industry," Econometrica, Econometric Society, vol. 69(2), pages 307-342, March.
    13. Fabra, Natalia & Toro, Juan, 2005. "Price wars and collusion in the Spanish electricity market," International Journal of Industrial Organization, Elsevier, vol. 23(3-4), pages 155-181, April.
    14. Seunghwa Rho & Peter Schmidt, 2015. "Are all firms inefficient?," Journal of Productivity Analysis, Springer, vol. 43(3), pages 327-349, June.
    15. Jamasb, Tooraj & Orea, Luis & Pollitt, Michael, 2012. "Estimating the marginal cost of quality improvements: The case of the UK electricity distribution companies," Energy Economics, Elsevier, vol. 34(5), pages 1498-1506.
    16. Hausman, Jerry, 2015. "Specification tests in econometrics," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 38(2), pages 112-134.
    17. Wang, Wei Siang & Schmidt, Peter, 2009. "On the distribution of estimated technical efficiency in stochastic frontier models," Journal of Econometrics, Elsevier, vol. 148(1), pages 36-45, January.
    18. Grigorios Emvalomatis & Spiro E. Stefanou & Alfons Oude Lansink, 2010. "A Reduced-Form Model for Dynamic Efficiency Measurement: Application to Dairy Farms in Germany and The Netherlands," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 93(1), pages 161-174.
    19. Tran, Kien C. & Tsionas, Efthymios G., 2009. "Estimation of nonparametric inefficiency effects stochastic frontier models with an application to British manufacturing," Economic Modelling, Elsevier, vol. 26(5), pages 904-909, September.
    20. Catherine D. Wolfram, 1999. "Measuring Duopoly Power in the British Electricity Spot Market," American Economic Review, American Economic Association, vol. 89(4), pages 805-826, September.
    21. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    22. Douglas Staiger & James H. Stock, 1997. "Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, vol. 65(3), pages 557-586, May.
    23. Itaya, Jun-ichi & Shimomura, Koji, 2001. "A dynamic conjectural variations model in the private provision of public goods: a differential game approach," Journal of Public Economics, Elsevier, vol. 81(1), pages 153-172, July.
    24. Charles Figuières & Alain Jean-Marie & Nicolas Quérou & Mabel Tidball, 2004. "Theory of Conjectural Variations," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 5453, June.
    25. Borenstein, Severin & Rose, Nancy L, 1994. "Competition and Price Dispersion in the U.S. Airline Industry," Journal of Political Economy, University of Chicago Press, vol. 102(4), pages 653-683, August.
    26. Kumbhakar, Subal C. & Parmeter, Christopher F. & Tsionas, Efthymios G., 2013. "A zero inefficiency stochastic frontier model," Journal of Econometrics, Elsevier, vol. 172(1), pages 66-76.
    27. Olson, Jerome A. & Schmidt, Peter & Waldman, Donald M., 1980. "A Monte Carlo study of estimators of stochastic frontier production functions," Journal of Econometrics, Elsevier, vol. 13(1), pages 67-82, May.
    28. Rotemberg, Julio J & Saloner, Garth, 1986. "A Supergame-Theoretic Model of Price Wars during Booms," American Economic Review, American Economic Association, vol. 76(3), pages 390-407, June.
    29. Reiss, Peter C. & Wolak, Frank A., 2007. "Structural Econometric Modeling: Rationales and Examples from Industrial Organization," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 64, Elsevier.
    30. Delis, Manthos D. & Tsionas, Efthymios G., 2009. "The joint estimation of bank-level market power and efficiency," Journal of Banking & Finance, Elsevier, vol. 33(10), pages 1842-1850, October.
    31. Paul L. Joskow & Edward Kohn, 2002. "A Quantitative Analysis of Pricing Behavior in California's Wholesale Electricity Market During Summer 2000," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 1-35.
    32. Appelbaum, Elie, 1982. "The estimation of the degree of oligopoly power," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 287-299, August.
    33. Michael Koetter & James W. Kolari & Laura Spierdijk, 2012. "Enjoying the Quiet Life under Deregulation? Evidence from Adjusted Lerner Indices for U.S. Banks," The Review of Economics and Statistics, MIT Press, vol. 94(2), pages 462-480, May.
    34. Steven L. Puller, 2007. "Pricing and Firm Conduct in California's Deregulated Electricity Market," The Review of Economics and Statistics, MIT Press, vol. 89(1), pages 75-87, February.
    35. Gallet, Craig A. & Schroeter, John R., 1995. "The Effects of the Business Cycle on Oligopoly Coordination: Evidence from the U.S. Rayon Industry," Staff General Research Papers Archive 5250, Iowa State University, Department of Economics.
    36. Dae‐Wook Kim & Christopher R. Knittel, 2006. "Biases In Static Oligopoly Models? Evidence From The California Electricity Market," Journal of Industrial Economics, Wiley Blackwell, vol. 54(4), pages 451-470, December.
    37. Robert H. Porter, 1983. "A Study of Cartel Stability: The Joint Executive Committee, 1880-1886," Bell Journal of Economics, The RAND Corporation, vol. 14(2), pages 301-314, Autumn.
    38. Glenn Ellison, 1994. "Theories of Cartel Stability and the Joint Executive Committee," RAND Journal of Economics, The RAND Corporation, vol. 25(1), pages 37-57, Spring.
    39. Jaumandreu, Jordi & Lorences, Joaquin, 2002. "Modelling price competition across many markets (An application to the Spanish loans market)," European Economic Review, Elsevier, vol. 46(1), pages 93-115, January.
    40. Gollop, Frank M. & Roberts, Mark J., 1979. "Firm interdependence in oligopolistic markets," Journal of Econometrics, Elsevier, vol. 10(3), pages 313-331, August.
    41. Antonio Alvarez & Christine Amsler & Luis Orea & Peter Schmidt, 2006. "Interpreting and Testing the Scaling Property in Models where Inefficiency Depends on Firm Characteristics," Journal of Productivity Analysis, Springer, vol. 25(3), pages 201-212, June.
    42. Abreu, Dilip & Pearce, David & Stacchetti, Ennio, 1986. "Optimal cartel equilibria with imperfect monitoring," Journal of Economic Theory, Elsevier, vol. 39(1), pages 251-269, June.
    43. Severin Borenstein & James B. Bushnell & Frank A. Wolak, 2002. "Measuring Market Inefficiencies in California's Restructured Wholesale Electricity Market," American Economic Review, American Economic Association, vol. 92(5), pages 1376-1405, December.
    44. Christopher F. Parmeter & Hung-Jen Wang & Subal C. Kumbhakar, 2017. "Nonparametric estimation of the determinants of inefficiency," Journal of Productivity Analysis, Springer, vol. 47(3), pages 205-221, June.
    45. Steven Puller, 2009. "Estimation of competitive conduct when firms are efficiently colluding: addressing the Corts critique," Applied Economics Letters, Taylor & Francis Journals, vol. 16(15), pages 1497-1500.
    46. Severin Borenstein, 2002. "The Trouble With Electricity Markets: Understanding California's Restructuring Disaster," Journal of Economic Perspectives, American Economic Association, vol. 16(1), pages 191-211, Winter.
    47. Roberto Rigobon, 2003. "Identification Through Heteroskedasticity," The Review of Economics and Statistics, MIT Press, vol. 85(4), pages 777-792, November.
    48. Bresnahan, Timothy F., 1989. "Empirical studies of industries with market power," Handbook of Industrial Organization, in: R. Schmalensee & R. Willig (ed.), Handbook of Industrial Organization, edition 1, volume 2, chapter 17, pages 1011-1057, Elsevier.
    49. Karen Clay & Werner Troesken, 2003. "Further Tests of Static Oligopoly Models: Whiskey, 1882–1898," Journal of Industrial Economics, Wiley Blackwell, vol. 51(2), pages 151-166, June.
    50. Woo, Chi-Keung & Olson, Arne & Horowitz, Ira & Luk, Stephen, 2006. "Bi-directional causality in California's electricity and natural-gas markets," Energy Policy, Elsevier, vol. 34(15), pages 2060-2070, October.
    51. Porter, Robert H., 1983. "Optimal cartel trigger price strategies," Journal of Economic Theory, Elsevier, vol. 29(2), pages 313-338, April.
    52. Frank A. Wolak, 2003. "Measuring Unilateral Market Power in Wholesale Electricity Markets: The California Market, 1998–2000," American Economic Review, American Economic Association, vol. 93(2), pages 425-430, May.
    53. Corts, Kenneth S., 1998. "Conduct parameters and the measurement of market power," Journal of Econometrics, Elsevier, vol. 88(2), pages 227-250, November.
    54. Koetter, Michael & Poghosyan, Tigran, 2009. "The identification of technology regimes in banking: Implications for the market power-fragility nexus," Journal of Banking & Finance, Elsevier, vol. 33(8), pages 1413-1422, August.
    55. Jun–ichi Itaya & Makoto Okamura, 2003. "Conjectural Variations and Voluntary Public Good Provision in a Repeated Game Setting," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 5(1), pages 51-66, January.
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    Cited by:

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    3. Meryem Duygun & Jiaqi Hao & Anders Isaksson & Robin C. Sickles, 2017. "World Productivity Growth: A Model Averaging Approach," Pacific Economic Review, Wiley Blackwell, vol. 22(4), pages 587-619, October.
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    5. 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.
    6. 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.
    7. Kutlu, Levent & Tran, Kien C. & Tsionas, Mike G., 2019. "A time-varying true individual effects model with endogenous regressors," Journal of Econometrics, Elsevier, vol. 211(2), pages 539-559.
    8. 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).
    9. Dibyendu Maiti & Chiranjib Neogi, 2020. "Endogeneity Corrected Stochastic Frontier with Market Imperfections," Working papers 313, Centre for Development Economics, Delhi School of Economics.
    10. Garcia, Devin & Kutlu, Levent & Sickles, Robert C., 2018. "Market Structures in Production Economics," Working Papers 18-007, Rice University, Department of Economics.
    11. Sapio, Alessandro & Spagnolo, Nicola, 2016. "Price regimes in an energy island: Tacit collusion vs. cost and network explanations," Energy Economics, Elsevier, vol. 55(C), pages 157-172.

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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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