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Journal of Regulatory Economics

, Volume 41, Issue 1, pp 80–99 | Cite as

Pricing the use of capital-intensive infrastructure over time and efficient capacity expansion: illustrations for electric transmission investment

  • Richard E. SchulerEmail author
Original Article

Abstract

Traditional economic theory provides a conundrum for pricing large, lumpy infrastructure investments: very different short- and long-run pricing prescriptions. Unless the facility is congested, efficient short run prices should only cover operating costs (short-run marginal cost, SMC); any higher price designed to also recover capital costs would risk inefficient under-utilization. However, if the facility becomes crowded, capital costs should be included in the calculation of user-fees since that burgeoning demand is likely to cause the construction of more capacity, and users should be confronted with the cost-consequences of their decisions. Once additional capacity is completed, however, and if because of the large size of the addition the facility is no longer congested, then price should once again fall to SMC. The resulting jagged pattern of prices offers little assurance to investors of capital cost-recovery without a government guarantee, and it may lead to schizophrenic behavior by both customers and potential suppliers. Just because the physical investment is lumpy, should the price pattern also be dichotomous or can a smoother transition be employed? By integrating the use of congestion fees that are based upon the external costs imposed by one user on all others prior to the construction of added capacity, and then by using the same congestion charge to gauge the “willingness-to-pay” for new capacity and to set an “opportunity-cost”-based benchmark for capital cost recovery afterward, a smoother sequence of prices can evolve. The capital cost recovery portion of these prices, whose magnitude is based upon the congestion eliminated, is premised on a long-run, dynamic view of markets and the transitions they can facilitate, and these cost-recovery adders can be combined with “peak-load-pricing” and the “inverse-elasticity” rule, for example, to improve efficiency and fairness over both space and time. The resulting price patterns can provide compatible incentives for all parties, and they complement several existing electricity system planning processes in those regions where congestion rents are already assessed for the use of transmission. The net effect could be similar to a sequential “real-options” analysis of efficient capacity expansion.

Keywords

Infrastructure Dynamic pricing Transitions Investment Cost-recovery Congestion fees 

JEL Classification

L51 

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References

  1. Baumol W. J., Bradford D. F. (1970) Optimal departure from marginal cost. American Economic Review 60: 265–283Google Scholar
  2. Blumsack, S., Illic’, M., & Lave, L. B. (2007). Separability and independence of congestion and reliability: Theory and simulations. In Proceedings IEEE power engineering systems conference.Google Scholar
  3. Bower R. S. (1985) The capital recovery question: An overview. Resources and Energy 7(1): 7–42CrossRefGoogle Scholar
  4. Chang N. B., Schuler R. E., Shoemaker C. A. (1993) Environmental and economic optimization of an integrated solid waste management system. Journal of Resource Management and Technology 21: 87–100Google Scholar
  5. Chao H.-P. (1983) Peak load pricing and capacity planning with demand and supply uncertainty. The Bell Journal of Economics 14: 179–190CrossRefGoogle Scholar
  6. Crew M. A., Fernando C. S., Kleindorfer P. R. (1995) The theory of peak-load pricing: A survey. Journal of Regulatory Economics 8: 215–248CrossRefGoogle Scholar
  7. Manne, A. S. (eds) (1967) Investments for capacity expansion. MIT Press, Cambridge, MAGoogle Scholar
  8. Mount, T. D., Maneevitjit, S., & Lamadrid, A. (2010). How integrating wind power into an electric grid affects the economic value of transmission lines. Presented at Rutgers advanced workshop in regulation and competition, 29th eastern conference.Google Scholar
  9. Mount, T. D., Schuler, R. E., & Schulze, W. D. (2003). Markets for reliability and financial options in electricity: Theory to support the practice. In: Proceedings of Hawaii international conference on systems science (Vol. 36).Google Scholar
  10. Oren S., Smith S., Wilson R. (1985) Capacity pricing. Econometrica 53: 545–566CrossRefGoogle Scholar
  11. Ramsey F. P. (1927) A contribution to the theory of taxation. Economic Journal 37: 47–61CrossRefGoogle Scholar
  12. Schuler R. E. (1985) Alternative electric power plant financing and cost recovery methods: Introduction. Resources and Energy 7(1): 1–6CrossRefGoogle Scholar
  13. Schuler, R. E., Schulze, W. D., Mount, T. D., & Alvarado, F. (2009). Summary of the executive forum on planning, markets and investment in the electric supply industry. Power Systems Engineering Research Center Report 09-01.Google Scholar
  14. Vickrey W. (1963) Pricing of urban and suburban transport. American Economic Review Proceedings 53: 452–465Google Scholar
  15. Walters A. A. (1961) The theory and measurement of private and social costs of highway congestion. Econometrica 29: 691CrossRefGoogle Scholar
  16. Williamson O. E. (1966) Peak load pricing and optimal capacity under constraints. American Economic Review 56: 810–827Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.Cornell UniversityIthacaUSA

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