Practical Implications

This section presents some thoughts and considerations about practical implications of the analysis. Whereas some practical implications were already touched upon in the previous section, the discussion here intends to demonstrate how designers of regulatory policies, affected companies and the energy industry as a whole may benefit from the insights in this thesis. However, it must be noted that the model insights have all been achieved through a very abstract analysis, and conclusions for reality or practical purposes must be drawn with a lot of caution. Hence, all implications illustrated in this section require more investigation.

In the specific model setup, overlapping investment is considered. In other words, ca- pacity adds up, and at the time of the second investment, the first investment has not been depreciated yet. It has been demonstrated that this very particular setup changes existing findings substantially. For instance, the use of the annuity depreciation rule does not lead to efficient investment while it does so in other similar models. The failure of the annuity depreciation in this particular setting points out that it is crucial to account for the exist- ing asset base when prices are determined, not just for new investment. In the German AReg, this is realized: when costs are determined as the basis for the revenue cap, all costs including depreciation from past investments must be incorporated.

The analysis further showed that the development of the capacity costs - i.e. whether investing becomes “cheaper” or not - is an important driver. It could be found that when capacity costs decrease, no investment can be induced in the first period. On the oppo- site, when capacity costs increase, no investment can be induced in the second period. An implication which can be drawn for practical purposes is simply that the development of capacity costs must be taken into consideration. When it is very likely that investing be- comes cheaper tomorrow, for instance because of economies of scale or economies of scope, then the companies particularly need incentives for investing today. When investing is ex- pected to become more expensive, then means must be implemented to shift investment from today into the future.

Another insight of the model was that in the second period, where scope in determining the regulated price evolves, the most intuitive way of dealing with this scope - i.e. using

a simple average of both possibilities - is not the best choice. The discussion showed that choosing the smaller one of the two candidates is the best option. Whereas this is again due to the specific model setup, the message which still can be taken away is that the simplest or most intuitive solution may not be the optimal one. Furthermore, the solution that a smaller price is in fact more beneficial for investment than a higher price is also surprising and leads to another insight: whereas one might think that a regulated company would always prefer to charge higher prices and that this consequently results in more investment, this is not true if a capacity constraint exists. Capacity constraint means that only the amount of capacity is provided that can be sold. This appears if demand for the product is limited. Hence, when designing a regulatory policy, the demand for the product must not be neglected.

Furthermore, it turned out that underinvestment cannot be avoided in the context of the model in chapter 4. Whereas this is of course again due to the very specific setup, for practical purposes it shows that there may be certain circumstances making it impossible to achieve the social welfare optimum. In this case, other instruments for inducing invest- ment must be developed. This could be a governmental subsidy, or any other mean like the investment budgets in the German AReg. If efficient investment is a prior concern - as it is in the context of the German energy turnaround - then a regulator cannot rely on the believe that the basic design of the regulation (for instance the AReg without the feature of investment budgets) will solve this issue. Even if such a specific investment inducing feature is introduced, it must be ensured that the actual design serves the original inten- tion. This issue for instance appeared in the approval process of the investment budgets, as illustrated before.

While it was not assessed analytically in the formal model, and while this clearly beyond the core scope of this thesis, insights concerning the regulator’s commitment still deserve being mentioned. The literature review of selected special issues in the context of regula- tion and investment in section 3.4 revealed another important message for the design of a regulatory policy. It was illustrated that the regulator’s commitment as well as the level of uncertainty can have a substantial impact on investment behavior. Consequently, the regulator should put a lot of emphasis on his credibility, and policies should be designed such that they cannot be significantly modified in an easy way. The possible change of a regulatory policy also directly affects the uncertainty about the future value of an invest- ment project. Hence, creating a stable and reliable regulatory environment should be a major concern for regulators.

4 Model on the Influence of Multi-period Investment on Optimal Regulatory Pricing

cannot actively influence the decisions of the regulator concerning the regulatory policy.206 One recommendation could be that when deciding upon a specific investment project, i.e. when determining that project’s NPV, it is risky for the company to assume that a particular regulated price will stay fixed over all regulation periods. To value this project in a sound fashion, it would be important for the company to be well informed about, and to analyze precisely how the investment will translate into the regulated price. In particular, it is crucial whether this investment will decrease or increase the regulated price. However, in most cases, the company is either not perfectly informed, the analysis is too complex, or it involves too many uncertainties. If this is the case, then investment projects should at least be valued in different scenarios.

Under the - admittedly implausible - assumption that first, full commitment of the reg- ulator is possible, and second that the company is perfectly informed about future devel- opment of capacity costs and future demand, then it is beneficial for the company to not invest today, but to postpone projects to the future, if capacity costs decrease. This is intu- itive because expressed differently, investment becomes cheaper in the future. However, this level of full information is beyond any realistic assumptions.

As for the energy industry as a whole, several starting points can be identified for an explanation why the expansion of the power grid in Germany progresses slowly. As dis- cussed earlier, grid operators might expect decreasing capacity costs and thus postpone certain investment projects. Furthermore, uncertainty about several factors, for instance about future demand or about the regulatory environment, might be investment draw- backs as well. While the following is not an insight of the analytical model, the conceptual discussion of the AReg in chapter 2 revealed that certain elements of the AReg need some revision. The shortcomings in the design of the investment budgets were recently resolved, but other features such as the allowed rate of return and the time lag resulting from the early photoyears still deserve improvement.

In summary, even if the developed model in this thesis is very abstract and analyzes a very specific setting, it is still possible to draw important conclusions for the design of regulatory policies in general. Of course, these insights are neither new or particularly surprising, and many of them have been accounted for in the design of the AReg. Still, they are again justified by the model findings, and their importance has another theoretical foundation.

5.1 Summary

In order to come to the final conclusion, insights and findings of the thesis are summarized briefly and put in relation to the research questions of this thesis.

In chapter 1 the following research questions were posed:

(1) How does the German incentive regulation (AReg) affect investment in the power grid?

(2) What effect does the actual price determination have on the affected company’s invest- ment decision when overlapping investments over multiple periods are considered in a cost-based price-cap regulation environment? What is the optimal price from the regulator’s perspective?

Chapter 2 illustrated the background for the thesis: the electricity industry itself, as well as necessary investments in the power grid and the regulation of the grid. The chap- ter showed that while the expansion of renewable energies results in a need for massive investments in the grid, price regulation is known to cause distortions in investment be- havior. The currently effective regulatory regime in Germany, the Anreizregulierung, was described in detail and its known effects on investment were shown. Hence, the concep- tual discussion of the AReg along with a thorough review of existing literature provides the answer to research question (1).

Without a doubt, the AReg was designed carefully. While its primary objective is to set incentives for cost reductions and efficiency improvements, it also includes elements which foster investment. The most important elements are the investment budgets that apply to particular investment projects and that are separated from the revenue cap. Fur- thermore, a quality element is included in the AReg. However, there are also weaknesses in the design of the policy: some elements have room for improvement to avoid negative

5 Final Conclusion

effects on investment behavior. Three commonly discussed major aspects are investment budgets, cost of equity, and a time lag issue. Investment budgets now are approved based on planned instead of realized costs. Second, according to several experts, the approved cost of equity is too low to guarantee an adequate return to the grid operating company. Third, apart from investment budgets, all relevant costs for the revenue cap are only calcu- lated in the photoyear. As a result, it can take up to seven years until costs become effective for the revenue cap. This long time lag between realization of costs and their effectiveness is considered another problem. These insights were all illustrated in detail in chapter 2.

Chapter 3 comprised on the one hand an extensive literature review of regulation and in- vestment. It discussed empirical, theoretical and analytical research, structured by method- ology. The focus was put on the influence of incentive regulation on investment, as op- posed to other forms of regulation such as rate-of-return regulation. The review proved that there is an essential connection between regulation and the investment behavior of the affected company. In most cases, incentive regulation discourages infrastructure in- vestment. Solutions suggested in the literature to overcome this problem were discussed. In total, the literature review created the framework for the developed model in the fol- lowing chapter.

On the other hand, the general literature review was enhanced by a discussion of se- lected issues in the context of regulation and investment. These issues were the level of information and regulator’s commitment, uncertainty, choice of cost basis and alternative pricing approaches. These topics were discussed extensively as they are recurring issues in the relevant literature and hence of particular importance. As the analysis of these topics in the formal analytical model was beyond the scope of this thesis, they were still accounted for by the academic discussion in section 3.4.

The analytical model developed in chapter 4 answered the second set of research ques- tions. Using a cost-based price-cap regulation environment, an analysis was conducted of the effect of the actual price determination on the affected company’s investment decision, when overlapping investments over multiple periods are considered. The main finding is that, when productive capacity is accumulated in the second considered period, an aver- age price must not be implemented, but the smaller option must be chosen. This choice minimizes the underinvestment problem and hence it is optimal from the regulator’s per- spective. Any other price determination causes more underinvestment and is worse, as a result. However, the predominant remaining problem is that in the specific considered model setup, with decreasing capacity costs and all parameters known to the company from the very beginning, it is impossible to induce any investment in the first period. This

effect is accredited to the decreasing capacity costs. Ultimately, the optimal price determi- nation under the specific circumstances was proven. Still the optimal capacity from the social welfare perspective cannot be achieved in this particular model setup.

In the end of chapter 4, first model limitations were discussed extensively. Second, a con- ceptual discussion of the model results completed the analytical investigation by concep- tually addressing important issues. Finally, practical implications concerning the design of the actual regulatory policy were identified in section 4.5.3.