Abstract
This chapter discusses elementary properties of allowed depreciation and return on the asset base for a regulated company under two regulatory models, the traditional rate-of-return model and the more recent LRIC model. Under the former model, any method of computing depreciation and return on the asset base is, in principle, fair to the regulated company and its customers. Under the latter model, only the real annuity method is fair.
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- 1.
The example is a stylized description of regulation of electricity distribution in Sweden. It is perhaps somewhat unusual in that the regulation is ex post, that is, the regulator reviews the tariffs after they have been applied. According to Jamasb and Pollitt (2007, p. 5), ex ante regulation is the preferred regime by the majority of regulators. On ex post regulation, see Agrell and Bogetoft (2002). Cf. also Agrell et al. (2005) and EBL Kompetanse AS (2004) on different Scandinavian regulatory regimes in electricity distribution.
- 2.
For instance, in the regulated area of mobile telephony interconnection, around 1999 the Swedish incumbent Telia incurred marketing costs for attracting new subscribers (subsidized handsets). The regulator Post & Telestyrelsen (The Swedish Post and Telecom Agency) did not include this cost item in the allowed cost. (Incumbent is a term sometimes used in the regulation literature to designate a newly privatized, previously state-owned monopoly. Telia merged in 2003 with the Finnish incumbent Sonera to form TeliaSonera.)
- 3.
These three parts of the allowed total cost can be usefully distinguished in regulatory practice in Sweden that the author is familiar with (electricity distribution and mobile telephony interconnection). The three parts also correspond to the ‘building block’ approach that is mentioned in Davis (2006, pp. 105–106).
- 4.
In corporate finance, it is not recommended to evaluate, for instance, an investment project by discounting pre-tax cash flows at a pre-tax WACC. In particular, setting the pre-tax WACC to the after-tax WACC divided by ‘one minus the tax rate’ is no more than an unreliable rule of thumb (as is well known). However, in a regulatory situation, it is not inconsistent to use a pre-tax WACC to calculate a pre-tax allowed return on the asset base, assuming that the regulatory depreciation schedule is equal to the depreciation schedule that is accepted by the tax authority (so that is the assumption made here). See Davis (2006, especially Proposition 1 on p. 112).
- 5.
Also for simplicity, working capital is disregarded (this could, e.g. be interpreted to mean that working capital assets are exactly balanced by trade credit).
- 6.
The asset base need not be identical to the accounting book value in the company’s own books. If so, the asset base is a different accounting book value, constructed by the regulator. Of course, the regulatory process is simplified if the regulator accepts the company’s book value as the asset base.
- 7.
This chapter’s contrasting of rate-of-return and LRIC seems somewhat original. Other papers have usually compared the rate-of-return model to a different alternative, the price cap model (for instance, Beesley and Littlechild 1989; Liston 1993; Joskow 2006; Armstrong and :̧def :̧def Sappington 2007, pp. 1606–1640).
- 8.
To show that the asset base under the real annuity method is strictly larger than the asset base under the nominal annuity method is actually somewhat technical. Similarly, to show that the asset base under the real annuity method is strictly larger than the asset base under the real linear method is also somewhat technical. (Proofs can be obtained from the author on request.)
- 9.
- 10.
It is not suggested here that LRIC is the only competitor to the rate-of-return model (cf. footnote 7 above). For instance, Biglaiser and Riordan (2000, p. 759) give the following succinct sketch of the development of regulation of telecommunications in the United States: “… rate-of-return regulation has prevailed … for much of the century. Beginning in the 1980s, price-cap regulation gradually became ascendant. Now … there are emerging new forms of wholesale price regulation based on long-run marginal cost concepts.” The new forms that these authors refer to apparently include LRIC. Also as suggested by this quote, LRIC has been mainly applied in telecommunications. The Swedish Network Performance Assessment Model (NPAM; cf. Sperlingsson 2003; Gammelgård 2004; Jamasb and Pollitt 2007) that is used in the regulation of electricity distribution is mentioned in the following section as an example of LRIC. The reason is that it appears to be somewhat similar from a structural point of view to LRIC models in telecommunications. It is perhaps more accurate to label NPAM as an engineering cost model. Incidentally, a recent Swedish official inquiry recommends a phase-out of the current regulatory model for electricity distribution including NPAM (SOU 2007 :99, in particular pp. 159 and 285). Instead, some variant of rate-of-return regulation is proposed. Cf. also Yard (2008).
- 11.
Needless to say, the LRIC regulatory model is not only concerned with allowed depreciation and return on the asset base. There is also the allowed cash cost for operations and maintenance. Under LRIC, this cost refers to a (fictitious) situation where the company in every year uses a simulated, newly acquired state-of-the-art network. This cost can therefore also be considered as simulated. It could be quite different from the actual operations and maintenance cost that the company is incurring in connection with its currently existing network. As before, however, operations and maintenance cost is not considered in this chapter.
- 12.
On Telia, cf. footnote 2 above.
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Acknowledgements
The author is indebted to the referees and Henrik Andersson (Stockholm School of Economics) for comments. The author is also indebted to Försäkringsbolaget Pensionsgaranti for economic support.
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Jennergren, L.P. (2010). On Depreciation and Return on the Asset Base in a Regulated Company Under the Rate-of-Return and LRIC Regulatory Models. In: Bjørndal, E., Bjørndal, M., Pardalos, P., Rönnqvist, M. (eds) Energy, Natural Resources and Environmental Economics. Energy Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12067-1_19
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