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Yardstick Competition to Elicit Private Information: An Empirical Analysis of the Japanese Gas Distribution Industry

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  • Ayako Suzuki

Abstract

This study examines the effect of yardstick regulation in Japan's gas distribution sector, especially focusing on its effect of reducing the adverse selection problem. The Japanese government has regulated the price of city gas supplies by a combination of fixed-price regulation and ex-ante yardstick regulation. The yardstick compares a firm's reported costs wit those of "similar" firms before the price is determined.Realizing that yardstick inspection will lead the industry to a full-information outcome if it works perfectly, we infer its effect from the difference between the current and the counterfactual full-information welfare levels. We estimate the cost function of retail gas distributors under the assumption of asymmetric information between the regulator and the distributor in the efficient level of labor. The estimation allows us to obtain informational parameters such as firms' efficiency levels and effort levels. Using the estimated cost structure and the firms' behavior inresponse to the regulatory incentive, along with the demand system and the behavior of the regulator, we calculate the current and the hypothetical full-information welfare levels, and examine whether the discrepancy of the current level from the full-information one has been significantly reduced since the introduction of yardstick regulation. Our results suggest that, on average, yardstick regulation reduces welfare discrepancy, implying it is somewhat effective in reducing firms' incentive to report higher costs. This effect, however, comes mainly from the very first inspection conducted in 1995. There seems to be a dynamic problem, similar to the Ratchet effect, because subsequent inspections cannot be effective for a firm that has learned the relative position of its own cost in the comparison group.

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Paper provided by Institute of Social and Economic Research, Osaka University in its series ISER Discussion Paper with number 0709.

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Date of creation: Mar 2008
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Handle: RePEc:dpr:wpaper:0709

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  1. Gagnepain, Philippe & Ivaldi, Marc, 1999. "Incentive Regulatory Policies: The Case of Public Transit Systems in France," IDEI Working Papers 84, Institut d'Économie Industrielle (IDEI), Toulouse.
  2. Damme, E.E.C. van & Potters, J.J.M. & Rockenbach, B. & Sadrieh, A., 2003. "Collusion under Yardstick Competition: An Experimental Study," Discussion Paper 2003-009, Tilburg University, Tilburg Law and Economic Center.
  3. Auriol, Emmanuelle & Laffont, Jean-Jacques, 1992. "Regulation by Duopoly," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 1(3), pages 507-33, Fall.
  4. Lewis, Tracy R & Sappington, David E M, 1988. "Regulating a Monopolist with Unknown Demand," American Economic Review, American Economic Association, vol. 78(5), pages 986-98, December.
  5. Mehdi Farsi & Massimo Filippini, 2003. "Regulation and Measuring Cost Efficiency with Panel Data Models: Application to Electricity Distribution Utilities," CEPE Working paper series 03-19, CEPE Center for Energy Policy and Economics, ETH Zurich.
  6. Laffont, Jean-Jacques & Tirole, Jean, 1986. "Using Cost Observation to Regulate Firms," Journal of Political Economy, University of Chicago Press, vol. 94(3), pages 614-41, June.
  7. Antonioli, B. & Filippini, M., 2001. "The use of a variable cost function in the regulation of the Italian water industry," Utilities Policy, Elsevier, vol. 10(3-4), pages 181-187.
  8. Vuong, Quang H, 1989. "Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses," Econometrica, Econometric Society, vol. 57(2), pages 307-33, March.
  9. Cornwell, Christopher & Schmidt, Peter & Sickles, Robin C., 1990. "Production frontiers with cross-sectional and time-series variation in efficiency levels," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 185-200.
  10. 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.
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