Design of Renewable Support Schemes and Windfall Profits: A Monte Carlo Analysis for the Netherlands.

AuthorHulshof, Daan
  1. INTRODUCTION

    Many governments use subsidy schemes in order to increase the production of renewable electricity, and realize climate-policy objectives. Supporting renewable electricity with subsidy schemes involves sizable government expenditures. (1) For example, in the EU in 2017, governments spent [euro]78.4 billion, or 0.5% of GDP, on subsidies for renewable electricity (Taylor, 2020). These subsidies contributed to renewable electricity production of 1,003TWh or 30.4% of total electricity production (Eurostat, 2020c). Dividing total subsidy expenditures by total renewable-electricity production implies an average subsidy expenditure per kWh of [euro]7.8 ct. (2) Compared to the average electricity wholesale price in the EU over 2015-2019 of [euro]4.1 ct/kWh, this is very substantial (Eurostat, 2020b). The financial burden that subsidy payments put on society is also reflected in the considerable renewable-electricity-specific taxes and levies that typically fund these schemes. For instance, in 2019, the average EU household faced a renewable-energy related tax on electricity consumption of [euro]2.6 ct/kWh (Eurostat, 2020a).

    In light of the considerable expenditures associated with promoting renewable electricity, it is important to design subsidy schemes in a cost-efficient manner. From the perspective of the government budget, attaining cost-efficiency implies not only stimulating low-cost technologies but also not paying more than necessary for a certain project. This is particularly important as taxpayers or energy consumers typically fund the subsidy schemes, meaning that relatively generous schemes result in large welfare transfers from these groups to subsidized investors seeking to gain private benefits (see also Borenstein, 2017).

    This paper analyzes the degree to which subsidized renewable energy projects yield private benefits in excess of what is required for investors to be willing to undertake them. We refer to these "excessive" private benefits as windfall profits. Limiting windfall profits implies that the compensation for a project should not exceed the project's levelized-cost-of-electricity (LCOE). A key challenge for achieving this is that, due to information asymmetry between governments and investors, it is prohibitively costly to observe both the true LCOE and revenues of individual renewable electricity projects. This hinders tailoring the subsidy at the minimally required level for each project. As a consequence, most governments provide a uniform feed-in subsidy for renewable electricity or a specific technique (e.g. on-shore wind). This means that projects with favorable characteristics will be remunerated in excess of their LCOE and, as a consequence, earn windfall profits, putting a financial burden on those who finance the scheme. In turn, this implies a typical trade-off between effectiveness and cost-efficiency (from the perspective of the government budget): a lower subsidy level will improve cost-efficiency and limit windfall profits, but will reduce the policy's effectiveness in triggering investments.

    We empirically investigate to what extent the Dutch feed-in premium (FiP) scheme resulted in windfall profits. (3) Despite being a relative laggard in the European energy transition, (4) the Netherlands provides a relevant case to study as it has operated a FiP since 2003 and implemented a number of design adaptations specifically aimed at limiting windfall profits without reducing effectiveness. To learn from this experience, we investigate how windfall profits for on-shore wind projects have developed from 2003-2018. In addition, we analyze to what extent investors are able to seek out projects yielding the highest windfall profits, despite the scheme's adaptations.

    The contribution of this paper is that, compared with the previous literature which is mainly focused on the efficiency (e.g. Schmalensee, 2012; Borenstein, 2012) and effectiveness (e.g. Nicolini and Tavoni, 2017; Haas et al., 2011) of renewable-energy promotion schemes, it focuses on the distributional effects. Specifically, the paper provides quantitative insight regarding the effect on windfall profits of not sufficiently accounting for heterogeneity in project characteristics in the subsidy scheme design. In addition, we learn whether policymakers can account for this heterogeneity by increasing the scheme's level of detail, thereby reducing the opportunities for firms to realize windfall profits.

    Analyzing the degree of windfall profits requires accounting for heterogeneity in project characteristics. We realize this by adding stochasticity in the key wind-project variables to the existing scheme's deterministic calculation of the required subsidy level, based on the characteristics of a reference project. Specifically, for the years 2003, 2009 and 2018, we estimate the distribution of the required subsidy of potential on-shore wind projects using Monte Carlo simulations in an investment model with stochastic inputs, reflecting the variability in the characteristics of on-shore wind projects (e.g. full-load hours). We then compare the estimated distributions with the actually granted subsidy. Potential projects here means that the analyzed group of projects, as reflected in the observed spread in the stochastic inputs, pertains to practically all available projects, stretching beyond the group of actually installed turbines. Specifically, we consider the spread in wind circumstances of practically all locations in the Netherlands. The selected years coincide with the three phases of the Dutch scheme between 2003-2018 (the MEP, SDE and SDE+), which had distinct characteristics. In addition, for 2018, the paper estimates the distribution of the required subsidy of actual projects. We compare these estimates with the results for potential projects to evaluate how successful investors are in seeking out the most profitable projects.

    We find that the windfall profits have decreased considerably in the period 2003-2018. Both the number of potential projects earning windfall profits (from 81% to 68%) as well as the average windfall profit per kWh (from [euro]2.4 ct/kWh in 2003 to [euro]0.9 ct/kWh in 2018) have decreased significantly. This decrease is the result of differentiating between projects as well as tighter assumptions on a project's cost by the scheme. Nevertheless, windfall profits remain present to a substantia! extent and have as a percentage of the granted subsidy remained unchanged (31% in 2003 vs. 32% in 2018). Moreover, in actual practice, investors are highly successful in seeking out the investments that yield the highest windfall profits.

    The remainder of this paper is organized as follows. Section 2 discusses the related literature. Section 3 summarizes the characteristics the Dutch subsidy scheme. Section 4 and 5 discuss the method and data, respectively. Section 6 provides the results and discussion. Section 7 concludes.

  2. RELATED LITERATURE

    There exists an extensive literature on the optimal design of climate policy, which is largely focused on the efficiency of policy measures and somewhat less on the distributional effects. This section reviews a number of key lessons from the literature. For a more broad discussion on the various policy options and their design, see for instance Meyer (2003), Haas et al. (2011), Green and Yatchew (2012), Gerlagh and Van der Zwaan (2006) and Schmalensee (2012). (5)

    With climate change being a classical market failure in the form of a negative externality from C[O.sub.2] emissions, the two optimal policy responses, or first-best solutions, according to the economic literature are (e.g. Stavins, 2011): a carbon tax conform Pigou (1920), or an emission-rights trading scheme conform Coase (1960). When adequately designed, these policies result in exact internalization of the external costs associated with emitting C[O.sub.2] (e.g. producing/consuming electricity with fossil fuels) and, as a result, maximum productive efficiency. Other, typically less efficient, available policy tools that may contribute to decarbonization target the electricity sector more directly, such as feed-in subsidies for renewables, a renewable portfolio standards (RPS) and command-and-control measures. These policy tools are sometimes referred to as second-best climate policies, given that they typically do not result in exact internalization of the external costs of fossil-fueled generation, and therefore not in maximum productive efficiency (e.g. Borenstein, 2012; Schmalensee. 2012). A major reason for this is that second-best policies usually focus on a particular reduction option (e.g. renewable electricity) while other, potentially less costly, reduction options may be available.

    Despite being regarded as sub-optimal by most economists, second-best policies have become highly popular for addressing emissions in the electricity sector. This is particularly true for subsidies. In 2018, out of 135 countries with some form of regulatory policy for renewable electricity in place. 111 operated a feed-in subsidy (REN21, 2020). In support of their effectiveness, there is empirical evidence that subsidies result in increased investment in renewable electricity (Bolkesj et al., 2014; Nicolini and Tavoni, 2017; Dijkgraaf et al., 2018). Regarding the popularity of second-best policies, Lyon and Yin (2010) empirically investigate the motivation of U.S. states to implement an RPS and find that the main drivers appear to be political ideology and private interests.

    In the literature on policy support for renewable electricity, subsidies have also been extensively compared to an RPS (e.g Schmalensee, 2012; Haas et al., 2011). The key difference is that, with subsidies one fixes the price/support and let the market determine the quantity of renewable electricity, whereas with an RPS one fixes the market quantity and let the market determine the price/support through trade in...

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