Abstract
Building on the results from Chap. 4, this chapter analyzes how risk from the companies investigated is effected by the regulatory system shift in the Austrian electric power supply industry. For this purpose, the database used for this investigation and the hypotheses to be tested are presented in Sect. 5.1. In Sect. 5.2, the inference-statistical results are presented and interpreted for the structural break analysis. The results of the events study are presented an interpreted in Sect. 5.3.
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Notes
- 1.
International Securities Identification Number (ISIN).
- 2.
May it be noted for the segment report issued from EVN that the segmentation changed in the 2006 fiscal year, which is why segment results for the time period 2002–2005 and 2005–2008 are presented in this work. The 2005 fiscal year was adjusted in the 2006 fiscal year as a year of comparison for the new structure. To the extent the electricity network figures and the gas network figures for Verbund and EVN were reported separately, they are presented separately in the present work. The remaining areas (e.g. water, long-distance heating, electricity generation, etc) are summarized under “Sum other”.
- 3.
Verbund holds stake in Steweag-Steg GmbH (stakes: 34.57%) and in KELAG - Kärntner Elektrizitäts-Aktiengesellschaft (35.12%) during the entire period of the investigation 01/2003 to 06/2008. As of the 2005 fiscal year, Verbund also holds stake in Energie Klagenfurt GmbH (49%). The three stakes cited that Verbund holds are distribution operators.
Moreover, it should be assumed that introducing an incentive regulation is a signal of the shift of negotiating power between the regulatory agency and the price-regulated company, according to the reflections from Stigler/Peltzman and Binder, as outlined in Sect. 5.2 of this work. On the basis of the explanations in Sect. 3.3.3 in Chap. 3 of this work, it is assumed that the shift of negotiating power follows because of the strengthening of the regulatory agency’s position, which also influences the results from the individual cost audit as a part of the ROR regulatory system.
- 4.
By way of example, EVN AG made acquisitions in 2005 in Southeastern Europe; the 2005 Annual Report cites the following on this:: “With the acquisition of 67.0% of the shares to both southeastern Bulgarian electricity distribution companies ERP Plovdiv and ERP Stara Zagora, EVN has taken over the operative governance in both companies in January 2005. Overall, ERP Plovdiv and ERP Stara Zagora supply electricity to approximately 1.5 million end clients, and thus around 33% of the Bulgarian electricity customers. For this, both companies operate a medium and low-voltage network totaling 56,800 km. Electricity sales from both Bulgarian suppliers jointly came to around 6.597 GWh in 2004, of which ERP Plovdiv accounted for around 3.622 GWh and ERP Stara Zagora accounted for around 2.974 GWh. By taking over the majority of both companies, the EVN group thus practically tripled their previous client base in electricity and doubled their electricity sales to end clients”.cf. Annual Report EVN AG 2005, p. 58.
- 5.
Only the ownership structure as of 31 Dec. 2008 is cited in this work because the percentage of the free float changed only slightly over the entire time period of the investigation (01/2003–06/2008). Verbund reports free float percentage of 15.7% in the 2002 Annual Report. For EVN, the free float percentage at the end of the 2002/2003 fiscal year (the calendar year deviating from the fiscal year) was around 34%, which lowered to around 14% in October 2005 because Energie Baden Württemberg AG increased their percentage held up to that point, cf. (2005) Annual Report EVN AG, p. 32.
- 6.
- 7.
A lowering of the level of indebtedness tends to lead to a lower risk for investors. Since the investigations of this work involve increasing risk amounts, not considering this effect should contribute to an addition, if small, strengthening of potentially significant results. As to the interrelation between level of indebtedness and the beta factor, reference is made to Sect. 2.2.1.3.2 in Chap. 2 of this work.
- 8.
Price indices were used (from Laspeyres). Data from the Dow Jones Indices were taken from http://www.stoxx.com/ (14 Feb. 2009).
- 9.
Data was taken from:
http://www.indices.cc/static/cms/sites/indices/media/de/pdf/download/ultimo/2008/atx_2008.pdf (04 Mar. 2009).
- 10.
cf. http://www.stoxx.com/indices/types/benchmark.html (04 Mar. 2009).
- 11.
cf. http://www.stoxx.com/indices/types/benchmark.html (04 Mar. 2009).
- 12.
Data was taken from:
- 13.
- 14.
- 15.
When the results from the structural break analysis (Sects. 5.2.1–5.2.6) were verbally explained, the alpha probability of error (p) for the distortion of H0 at p < 0.1% were described as extremely significant. Events with 0.9% ≥ p ≥ 0.1% are described as highly significant and those with 5.0% ≥ p > 0.9% as significant. Defining p takes place in Sect. 5.2 on a two-sided basis. Events with 10.0% ≥ p > 5.0% are described as distinctive, in order to underscore the events that would be rated as significant at the 5% level with a one-sided significant test, but would have to be rated as not significant with a two-sided test.
- 16.
cf. Bortz (1999), p. 209 ff.
- 17.
Descriptions of the models implemented are cited in the respective cells.
- 18.
When the results from the event study (Sect. 6.3.2–6.3.5) were verbally explained, the alpha probability of error (p) for the distortion of H0 at p < 0.1% were described as extremely significant. Events with 0.9% ≥ p ≥ 0.1% are described as highly significant and those with 5.0% ≥ p > 0.9% as significant. Defining p takes place in Sect. 6.2 on a two-sided basis. Events with 10.0% ≥ p > 5.0% are described as distinctive, in order to underscore the events that would be rated as significant at the 5% level with a one-sided significant test, but would have to be rated as not significant with a two-sided test.
- 19.
The Association of Austrian Electricity Companies (shorthand: VEÖ; www.veoe.at ) is the lobbyist from electricity network operators, electricity generation and electricity business in Austria.
- 20.
AR = abnormal returns.
- 21.
Reference is made here to Table 5.44 of the current work, in which the model descriptions and the model specifications are cited.
References
Binder, J.J., Norton, P.W.: Regulation, profit variability and beta. J. Regul. Econ. 15, 249–265 (1999)
Bortz, J.: Statistik für Sozialwissenschaftler, 5th edn. Springer Verlag, Berlin, Heidelberg, New York, Barcelona, Hongkong, London, Mailand, Paris, Singapur (1999)
Buckland, R., Fraser, P.: Political and regulatory risk: beta sensitivity in U.K. Electricity distribution. J. Regul. Econ. 19, 5–25 (2001)
Grout, P.A., Zalewska, A.: The impact of regulation on market risk. J. Financ. Econ. 80, 149–184 (2006)
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Hierzenberger, M. (2010). The Primary Empirical Study. In: Price Regulation and Risk. Lecture Notes in Economics and Mathematical Systems, vol 641. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12047-3_5
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