全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

Directional Distance Functions and Rate-of-Return Regulation

DOI: 10.1155/2012/731497

Full-Text   Cite this paper   Add to My Lib

Abstract:

This paper is concerned with formulating directional distance functions assuming that firms operate subject to rate-of-return regulation. To this end, we consider two different contexts. First, we assume that input prices are known, which allows us to extend the rate of return regulated version of Farrell efficiency. Secondly, we assume that input prices are unknown, showing then that a specific reference direction arises as a natural choice for measuring efficiency with directional distance functions. 1. Introduction All over the world, most countries deal with the problem of monopoly by means of regulation. This type of solution is widespread in the case of natural monopolies: water, natural gas, and electric companies. These companies are not allowed to charge any price they want to. Instead, government agencies regulate their output prices. One form of regulation is that of rate-of-return regulation. After the firm subtracts its operating expenses from gross revenues, the remaining net revenue should be just sufficient to compensate the firm for its investment in plant and equipment. In particular, the regulator authorizes the output price which, if anticipated future market conditions are realized, results in the firm earning a rate of return equal to the predetermined allowed level upon which the output price has been estimated. At a subsequent stage, if the obtained firm rate of return is less than the allowed level, the firm can request an increase in the output price. It is well known that one disadvantage of rate-of-return regulation is that it may encourage inefficiency because the regulated firms have no incentive to decrease costs. For this reason, assessing the performance of regulated companies with respect to technical inefficiency is an important issue for government agencies. Measuring inefficiency of firms subject to rate-of-return regulation has been yet studied previously in the literature (see [1–4]). In particular, F?re and Logan [4] introduced and explored a regulated version of Farrell efficiency. Nevertheless, there are other alternatives to measure technical inefficiency in production theory. As Portela et al. [5] argue, on some markets it is not possible or is not desired to modify equiproportionately inputs or outputs. A well-known drawback of Farrell efficiency is the arbitrariness in imposing targets on the efficient frontier preserving the mix within inputs or within outputs, when really the firm’s very reason to change its input and output levels is often the desire to change the mix (see [6]). If so, an efficiency

References

[1]  H. Averch and L. L. Hohnson, “Behavior of the firm under regulatory constraint,” American Economic Review, vol. 52, pp. 1052–1069, 1962.
[2]  W. J. Baumol and A. K. Klevorick, “Input choices and rate-of-return regulation: an overview of the discussion,” The Rand Journal of Economics, vol. 1, pp. 162–190, 1970.
[3]  R. F?re and J. Logan, “The rate of return regulated firm: cost and production duality,” The Bell Journal of Economics, vol. 14, no. 2, pp. 405–414, 1983.
[4]  R. F?re and J. Logan, “The rate of return regulated version of farrell efficiency,” International Journal of Production Economics, vol. 27, pp. 161–165, 1992.
[5]  M. C. A. S. Portela, P. C. Borges, and E. Thanassoulis, “Finding closest targets in non-oriented DEA models: the case of convex and non-convex technologies,” Journal of Productivity Analysis, vol. 19, pp. 251–269, 2003.
[6]  R. G. Chambers and T. Mitchell, “Homotheticity and non-radial changes,” Journal of Productivity Analysis, vol. 15, no. 1, pp. 31–39, 2001.
[7]  R. G. Chambers, Y. Chung, and R. F?re, “Benefit and distance functions,” Journal of Economic Theory, vol. 70, pp. 407–419, 1996.
[8]  R. G. Chambers, Y. Chung, and R. F?re, “Profit, directional distance functions, and Nerlovian efficiency,” Journal of Optimization Theory and Applications, vol. 98, no. 2, pp. 351–364, 1998.
[9]  G. Granderson, “Externalities, efficiency, regulation, and productivity growth in the U.S. Electric utility industry,” Journal of Productivity Analysis, vol. 26, pp. 269–287, 2006.
[10]  Y. H. Chung, R. F?re, and S. Grosskopf, “Productivity and undesirable outputs: a directional distance function approach,” Journal of Environmental Management, vol. 51, pp. 229–240, 1997.
[11]  R. F?re and D. Primont, Multi-Output Production and Duality: Theory and Applications, Kluwer Academic, 1995.
[12]  R. W. Shephard, Cost and Production Functions, Princeton University Press, Princeton, NJ, USA, 1953.
[13]  M. Farrell, “The masurement of productive efficiency,” Journal of the Royal Statistical Society A, vol. 120, pp. 253–281, 1957.
[14]  D. McFadden, “Cost, revenue and profit functions,” in Production Economics: A Dual Approach to Theory and Application, M. Fuss and D. McFadden, Eds., vol. 1, pp. 1–110, North Holland, Amsterdam, The Netherlands, 1978.
[15]  R. F?re, S. Grosskopf, D.-W. Noh, and W. Weber, “Characteristics of a polluting technology: theory and practice,” Journal of Econometrics, vol. 126, no. 2, pp. 469–492, 2005.
[16]  A. Charnes, W. W. Cooper, and E. Rhodes, “Measuring the efficiency of decision making units,” European Journal of Operational Research, vol. 2, no. 6, pp. 429–444, 1978.
[17]  W. Briec and J. B. Lesourd, “Metric distance function and profit: some duality results,” Journal of Optimization Theory and Applications, vol. 101, no. 1, pp. 15–33, 1999.
[18]  R. G. Chambers and R. F?re, Technical Efficiency Measurement: The Choice of Direction. V North American Productivity Workshop, Stern School of Business, New York University, New York, NY, USA, 2008.
[19]  M. Nerlove, Estimation and Identification of Cobb-Douglas Production Functions, Rand McNally Company, Chicago, Ill, USA, 1965.
[20]  R. Weron, Modeling and Forecasting Electricity Loads and Prices, John Wiley & Sons, Chichester, UK, 2006.
[21]  R. F?re and S. Grosskopf, “Theory and applications of directional distance functions,” Journal of Productivity Analysis, vol. 13, pp. 93–103, 2000.

Full-Text

Contact Us

[email protected]

QQ:3279437679

WhatsApp +8615387084133