Solar Bait: How U.S. States Attract Solar Investments from Large Corporations.

AuthorCohen, Jed J.

    Motivated by environmental quality concerns, energy independence, and employment generation prospects, many states have adopted solar-friendly policies and subsidy programs to increase solar adoption and incentivize companies to add solar photovoltaic (PV) units to their facilities (Shrimali and Jenner, 2013; Jenner, et al. 2012; Ohler 2015). The stakes in this game of attraction are high, with large economic investments hanging in the balance. Nonresidential solar installations, including commercial buildings, with substantial untapped potential (Bird, Gognon and Heeter, 2016), represent a tangible investment in a state's economy and have the potential to create jobs (Wei et al. 2010). Nevertheless, thus far, only a small fraction of the total solar potential of corporate properties has been realized. Even Walmart, an avid corporate solar adopter, generates solar power at only 7% of its facilities. High initial cost has generally been argued to be the primary barrier for adoption (Shrimeli and Jenner, 2013).

    The Solar Energy Industries Association (SEIA) "Solar Means Business" Reports compile data on solar generation installations for major commercial solar adopters in the U.S. These are private companies that invest in solar generation capacity in the U.S. The SEIA data account for nearly 1,000 MW of solar capacity installed by corporations through 2015. The data cover an estimated 16% of non-residential and non-utility scale solar installations (SEIA, 2016). Assuming no sample-selection bias, this figure suggests that the total capacity installed by commercial entities through 2015 is approximately 6,250 MW , or enough to power the equivalent of 1 million homes per year. The SEIA finds that major corporations installed more solar capacity in 2016 than they did in 2015, and that 2013 was the year in which the most commercial solar was installed so far. The report suggests that the reduction in commercial solar installations from 2013 levels is due to "difficulties in obtaining financing for smaller commercial entities and state level policy instability" (SEIA, 2016). Commercial solar installations are concentrated on the East and West Coasts, near population centers, and are placed on all types of corporate buildings, from retail to manufacturing centers. Figure 1 provides an overview of aggregate solar installation capacities through 2015 on commercial properties across the United States. The figure indicates that the amount of solar capacity installed varies across states, both in terms of total installed capacity and population weighted capacity, which suggests that state level factors are important in determining where companies install solar. For instance, West Virginia and Pennsylvania have similar solar insolation. Yet, the SEIA data show zero solar installations on commercial properties in West Virginia, but 25 Pennsylvania installations totaling 15,964 kW. The variability of PV installed capacity on commercial properties across US begs the question: why do firms choose to install solar in some states and not others?

    The objective of this paper is to shed light on this question through exploratory empirical analyses. Specifically, we are interested in state level environments that may encourage companies to install solar PV units on their properties. We use the SEIA dataset to examine the PV installation decisions of firms that have revealed a propensity to invest in solar energy generation. The goal of this study is to understand the state-level drivers of solar installation decisions.

    All firms in our dataset have invested in at least one solar generation facility in at least one state. Therefore, the scope of the analysis in this study is limited to the firms who have shown interest in solar power and have revealed their willingness to invest in solar PV on the properties in the US. We construct and estimate various statistical models that relate the decision to install solar across states and years to state level characteristics and state policy variables.

    Prior studies have examined the effects of various policies, incentive programs, and other factors on residential adoption of solar technology. Crago and Chernyakovskiy (2016) use county level data from thirteen northeastern states in the US to examine the effects of demographic characteristics and incentive policies on residential solar adoption. They find that financial incentives are important determinants of solar adoption rates. Rebates, solar resources, and electricity prices, which affect return on investment in solar PV are found to be significant. Financial incentive programs are also found to be important predictors of residential solar adoption nationally (Matisoff and Johnson, 2017; Kwan, 2012) and in California (Hughes and Podolefsky, 2005). In addition to return on investment, Bauner and Crago (2015) show that policies which reduce uncertainties in returns from solar PV installations are effective in encouraging household adoption of solar energy. Borenstein (2017) shows that income is a significant determinant of solar PV adoption in California. However, he observes that income disparity between households with and without PV systems has been declining since 2011. Still, he shows that wealthier households with greater energy use enjoy greater benefits from PV installation given the increasing block rate electricity pricing, net metering and third-party ownership policies in CA.

    In addition to incentive policies, Crago and Chernyakovskiy (2016) also find that pro-environmental preferences, measured in terms of hybrid or electric vehicle sales, are important predictors of residential solar installation. Moreover, prior rates of solar PV installations have a positive effect on residential solar adoption implying positive effects from familiarity with solar technology and peer adoption. Evidence of a positive peer adoption effect is also presented in Graziano and Gillingham (2015). Using spatially detailed data on residential solar PV installations in Connecticut the authors find significant clustering of new PV panels. Observing decreasing diffusion with distance the authors argue that a spatial neighborhood effect is an important predictor of residential solar adoption.

    Beyond residential solar adoption Sarzynski et al. (2012) examine state level solar capacity from 1997 to 2009 in the US and observe that financial incentive programs and state renewable energy portfolio standards, with accompanying solar carve outs, have a positive relation with state level capacity of solar energy installations. Dijkgraaf et al. (2018) examines whether Feed-in Tariffs (FIT) increase annual capacity of cumulative solar power in OECD member countries during 1990-2011. This study shows that well designed FITs can have a significant effect on solar PV adoption. In general, support for renewable energy has been shown to be affected by unemployment, electricity market concentration, and solar resources (Jenner et al. 2012; Ohler, 2015).

    We build on prior literature by examining the factors that predict state level installation of solar power by commercial entities in the US. The literature on installation of solar on commercial properties is sparse relative to the literature on residential adoption. Although

    some of the drivers of solar PV installation can be expected to be common for residential and commercial customers, the motivations for installation can differ in terms of return on investment and public relations strategy. Rooftops of commercial properties can be promising sites for the expansion of solar energy generation.

    Commercial solar energy adoption can be viewed in terms of two non-exclusive purposes. One is to install solar panels on commercial properties for the sake of direct financial benefits of installation in the form of energy cost savings and subsidies. The other purpose may be to install solar PV systems as part of public relations strategy aimed at enhancing a firm's social responsibility image.

    From the former camp, Bazen and Brown (2009) analyze the feasibility of installing solar panels on poultry farms in Tennessee. They compare the costs of an installation to the benefits of reduced power expenditure and any financial incentive programs that are in place. They find that in 2009 the net present value of investing in solar generation was negative, however if the price of solar fell by around 10%, then investing in solar became a financially feasible proposition. Current PV installation prices are nearly 50% lower (1) than the 2009 prices that Bazen et al. (2009) used in their analysis, suggesting that the net present value of installing solar on Tennessee poultry farms would now be positive at the 2009 price of electricity. Borchers et al. (2014) is the only work to explicitly consider the effects of state level policies on the adoption of non-residential solar. The authors model the decision of farms to adopt renewable energy generation, either solar or wind, as a function of state level variables including incentive policies, and farm characteristics. They find that the impact of state level policies on the farm's adoption decision is limited, although net-metering and interconnection policies do have a small positive effect on the probability that a farm invests in renewable energy generation. A case-study from NREL (National Renewable Energy Laboratory) compares the solar financing decisions of two major commercial solar installers, IKEA and Staples (Feldman and Margolis, 2014). The report shows that depending on a firm's cash flow outlook and internal discount rates their preference in regard to owning their solar installation or using its power via a power purchase agreement (PPA) will vary. The report suggests that the existence of state policies that allow for PPAs might be an important factor affecting solar uptake rates. Beckman and Xiarchos (2013) draw attention to the importance of...

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