هزینه سرمایه سهام برای انرژی های تجدید پذیر در بازارهای نوظهور
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|13949||2012||10 صفحه PDF||سفارش دهید||7715 کلمه|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Energy Policy, Volume 40, January 2012, Pages 49–58
The appropriate cost of capital for a renewable energy project depends upon an accurate measure of investment risk. Employing the conceptual framework of a commonly accepted asset pricing model, we analyze the risk faced by renewable energy investors in large emerging markets. We find that firms in Brazil, China and India expose multinational investors to the same risk as investing in emerging markets generally. The risk to domestic investors in those same firms ranges from substantially below-average to above-average, depending upon the country. The results are robust across several model versions and statistical techniques. With an eye toward government efforts to encourage the deployment of renewable energy in developing countries, we establish a range of estimates for the required return on equity capital in this fast-growing and politically important economic sector.
Recent studies have forecasted more than $10 trillion of investment in the renewable energy sector over the next 20 years, much of it in developing countries (IEA, 2009). Because most renewable energy technologies are not cost-competitive in the current economic system, fiscal incentives have been implemented in nearly all large energy-consuming countries to encourage investment in the sector. A coordinated effort to support RE projects in the developing countries of Asia, Africa and Latin America will likely lead to rapid expansion of public funding programs and new economic support mechanisms (UNEP, 2009). Much of the funding for these programs will be drawn from the developed countries of Europe, North America and Asia. Rapidly growing subsidies to the private sector have raised questions about the effectiveness of current investment incentives. The Clean Development Mechanism, an initiative of the UN Framework Convention on Climate Change and one of the primary ways in which developed countries subsidize renewable energy projects beyond their own borders, has proven to be a lightning rod for this debate. More than 1,670,000 CDM carbon credits are expected to be issued to renewable energy project developers in developing countries though 2012 (UNFCCC, 2009), comprising a wealth transfer of some $20 billion.2 Concerns have been raised that the CDM approval process is too lenient, allowing firms to earn supra-normal profits from projects that would have occurred anyway (Harvey, 2007 and Wara and Victor, 2008). Others contend that the CDM has become too restrictive (Harvard Project on International Climate Agreements, 2009) with its most serious flaw being a failure to attract sufficient levels of private sector capital (Economist, 2007). To obtain CDM subsidy, a firm must demonstrate that it would not have implemented the project without financial support. The evaluation of “investment additionality” by CDM regulators relies upon a comparison of investment alternatives and/or internal rate of return (IRR) benchmarking (UNFCCC, 2008), with individual firms proposing a benchmark cost of capital for each project requesting subsidy. Projects having a rate of return without CDM subsidy less than their self-reported benchmark cost of capital should be approved while those with a rate of return without CDM subsidy greater than the benchmark may be rejected (UNFCCC, 2008). In the same vein as observed by Lewis (1996) about marketable permit and emissions tax programs generally, CDM regulators must balance the cost of making a type-one error (in this case, rejecting a deserving project) against the cost of making a type-two error (approving a project that would have occurred without extra support). The regulator’s view on required rate of return is a basic building block of all renewable energy investment policies. It is particularly important in the CDM. But while economists have long debated the efficiency of subsidies on climate change policy objectives, very little consideration has been made in the academic literature to the firm cost of capital and its critical role in determining investment patterns in climate-friendly industries. Without a clear view on industry cost of capital, it is exceedingly difficult for national and supra-national regulatory agencies to deliver the right amount of fiscal support to the right projects. The result of over-leniency may be, as has been the case in up to 60% of past environmental investment subsidy programs, that firms receive windfall profits at taxpayer expense (Arguedas and van Soest, 2009). Conversely, regulatory overshoot could deny fiscal support to projects that would not otherwise attract private sector investment, thereby exacerbating carbon lock-in (Unruh and Carrillo-Hermosilla, 2006). By directly comparing various models for estimating the cost of equity capital, our aim with this paper is to guide regulators, researchers and corporate managers who evaluate funding decisions within the industry. While the literature concerning industry-generic costs of capital is extensive in both its theoretical and empirical contributions, studies on climate change mitigation have tended to side-step difficult questions about the cost of capital in greenhouse gas-reducing industries. An authoritative report by Stern (2006), for example, used a social cost of capital3 to estimate the present value of future investment required to meet pollution reduction targets. Perhaps due to its relatively short track record as a stand-alone industry, there are very few studies in the academic literature concerning the cost of capital of clean energy firms, a key economic sector in the effort to slow human-induced global warming. When touching upon environmental issues more broadly, studies on cost of capital have observed a reduction in the cost of corporate funding due to environmental risk management practices (Feldman et al., 1997 and Sharfman and Fernando, 2008) but have not investigated investment hurdle rates in new industries gaining strength from rising ecological pressures. The limited number of references to internal rates of return for renewable energy companies have either lacked solid grounding in financial theory (Dunlop, 2006), been focused on companies in well established European markets (Muñoz et al., 2009), or are proprietary to investment banks and consultancies. On the issue of market risk, a key component of the cost of capital estimation, a recent study by Henriques and Sadorsky (2008) found that renewable energy companies have market beta values close to 2. Employing an empirical research design and using multiple asset pricing models, we take up the challenge of estimating the expected return on equity for renewable energy investors in emerging markets. We focus on the most complicated element of the cost of equity calculation, the market risk factor. The models considered in our study include the single-factor CAPM (Sharpe, 1964 and Lintner, 1965) and the downside beta CAPM (Estrada, 2000) as well as their “global” and “local” variants. A visual summary of the analysis is shown in Fig. 1.
نتیجه گیری انگلیسی
Although estimating the cost of capital is a notoriously challenging task for corporate managers, the price of inaccuracy is paid privately (by the firm). When cost of capital benchmarks are used by regulators to help determine investment subsidies, the task becomes crucial to the public's interest in economic fairness and efficiency. It is surprising therefore, that core elements of investment theory have not been widely analyzed in previous studies of leading environmental investment programs. The current regulatory approach of the Clean Development Mechanism (CDM), which relies upon firms to justify their own minimum rate of return as part of the subsidy award process, seems particularly overdue for deeper scrutiny. Using the CDM as a specific example of the need for greater clarity about private sector hurdle rates, we examined the key methodological challenges in determining the cost of equity capital for renewable energy companies in Brazil, China and India. Our most important contribution is the estimation of market risk for multinational and domestic investors. The outputs from many different model versions provided a stable set of results. The RE industry in these countries poses average risk for US multinational investors. From a domestic investor’s perspective, the industry poses lower than average market risk in Brazil, average market risk in China and higher than average risk in India. Our work provides a series of insights to both investors and regulators. The beta coefficients, gained from data regressions on a unique sample of renewable energy firms, should be useful to managers who set risk-adjusted return hurdle rates for investments in emerging markets. Our finding that the industry presents average market risk to international investors may be particularly valuable to firms considering expansion overseas. We also found that local versions of the CAPM provide more accurate estimations of market risk in these countries. It may be prudent, therefore, for investors to estimate the cost of equity capital for themselves and their competitors on a national market basis. Finally, our analysis has generated additional evidence that the downside beta CAPM may be a better model for explaining historical returns to investors in emerging markets. For regulators, we evaluated competing models for estimating a firm’s required rate of return and highlighted the inherent difficulties in using these models for adjudication of investment subsidy awards. These challenges include checks on model fitness, discretion regarding key model input assumptions (for example, equity risk premium and the risk free rate) and monitoring of data consistency. Our finding that a portfolio of renewable energy firms in emerging markets has near-average market risk stands in contrast to previous work (Henriques and Sadorsky, 2008) that estimated market betas twice as large as those set out in this paper. While employing similar statistical techniques to those used in our research, the historical return data used by those authors were drawn from a commercial index (WilderHill Clean Energy) comprised of renewable energy technology companies in the United States. In contrast, our sample is predominantly weighted towards renewable energy project investment companies and those located in emerging markets. Managers must, therefore, discriminate between these types of companies in making their assessments of market risk. Our study is not without limitations. While the sample used for global CAPM comprises 60 companies, the local CAPM uses smaller sample sizes, which may have influenced the results. Additionally, due to the relative immaturity of the renewable industry, the time series had to be limited to 3 years. Scholars may wish to re-visit our methodological approach with a longer time series. Finally, our findings have generated new questions regarding the characteristics of national renewable energy markets and the market risk of firms in those industries. Further exploration of these issues poses a promising line of future research. We believe that clarity about how firms establish the cost of capital for project investments will improve renewable energy investment policymaking. As noted by Lewis (1996), information asymmetry poses a tremendous challenge to efficient environmental policy outcomes. Our study comprises a step towards reducing adverse selection in policymaking (Sheriff, 2009), which results from regulators’ inability to access private information held by firms. The Clean Development Mechanism may eventually be replaced with a system of more direct financial support to national governments or may be overhauled to take a more uniform approach to sector subsidies (Aldy and Stavins, 2008). With reform, fundamental questions will continue to persist about appropriate levels of subsidy to climate-friendly industries. Objective consideration of market risk and its role in setting the cost of equity for the private sector should be a primary consideration in re-designing the system.