How does electricity consumption behavior change with different energy sources? We seek to understand how consumers change their consumption behaviors when they begin to use renewable electricity via a community solar program. Previous research has found consumers distinguish the power sources of electricity and even change their consumption behavior. Recent studies found that consumers increase their total consumption after adopting rooftop solar panels (‘Solar Rebound'), though studies on community solar programs are absent. This study explores household-level consumption behavior after adopting solar electricity without panel installation. We use household-level monthly electricity consumption data in a large electric co-op in Georgia, ranging from 2015 to 2023, for both community solar subscribers and non-subscribers. We use staggered difference-in-differences, along with matching, to compare consumption changes before and after the subscription. Findings reveal that the consumption does not change after subscription, but subscribers’ monthly bills increase by about 3-4%, indicating they pay marginally more to make the grid greener. This study will broaden the understanding of consumer behavior by adding the analysis of prevalent but under-studied community solar electricity programs in the Southeast context. It will help utility planners understand the changing demand as a result of renewable energy adoption.

Prior studies focus on marginal price changes, which fail to capture behavior under large price changes. Using restricted household-level billing data from California’s two largest natural gas retailers with about 14 million observations, we analyze the effects of a 146% price hike by one retailer in January 2023. Following Burlig et al. (2020), we train machine learning models for each household to account for time-invariant household-level characteristics that could affect natural gas consumption. Unlike previous studies that overlook endogeneity, our analysis addresses this limitation by employing a control function approach following Brewer & Carlson (2024) to account for the endogeneity between household-level average natural gas prices and consumption. This methodological innovation ensures more accurate and reliable estimates, providing new insights into consumer behavior under price shocks. Using the trained model, we predict and demonstrate consumption behavior deviates under price surges. The estimates show that consumers further decrease about 3% of their monthly consumption during unexpected price shocks compared to regular price variations. We also investigate if behavior spillover happens and examine consumption changes of electricity that didn’t experience price fluctuation using monthly electricity consumption data. This study will also examine the heterogeneity of behavioral responses to price shock among households in income-qualified subsidy programs, which will provide the necessity of policy designs to consider various consumption responses to unexpected market shocks.

Research on the clean energy transition has examined partisan and ideological cleavages, as well as environmental attitudes and governmental trust. Few studies have examined how factual information about the energy sector relates to public support for different types of energy infrastructure. Using an original survey of 1342 residents of the US state of Georgia, regression analysis, and a survey experiment, we test whether energy knowledge is associated with support for renewable and fossil fuel energy infrastructure, and if political identities moderate this relationship. We find that respondents that have more factual information about energy are more likely to support solar panels, wind farms, transmission lines, and energy-efficient technologies–all key building blocks of the clean energy transition. Conversely, we observe a partisan wedge in energy knowledge for two fossil fuels: Greater energy knowledge corresponds with opposition to coal plants only among Democrats, and support for natural gas only among Republicans. However, the informational treatment in the survey experiment is null, which suggests that factual information alone may not change opinion. Altogether, our research shows that knowledge corresponds with greater support for innovation in the energy sector but that political values compete with facts in shaping views, particularly on fossil fuel infrastructure.

The marketplace of climate solutions has grown considerably. Three technologies, in particular, exhibit strong potential for disruptive change and advancement in the residential sector: electric vehicles (EVs), rooftop photovoltaics (RPVs), and efficient heating, ventilation, and air conditioning (HVAC) systems. Many scholars have studied the adoption of these; we address their co-adoption, i.e., the adoption of multiple technologies. Using a survey conducted in Georgia, we examine pro-environmental behavior, risk tolerance, and energy-related knowledge as social-psychological drivers for the co-adoption of RPVs, EVs, and efficient HVACs (including heat pumps). We conclude that some but not all of these drivers are relevant to the adoption and co-adoption of the three transformational climate solutions. Pro-environmental behaviors, for instance, appear to create conditions for “positive spillover,” propelling consumers toward adopting multiple climate solutions, whereas energy knowledge has no clear relationship with co-adoption. At the same time, the complexities of their influence are unique to different combinations of technologies – one notable example is the significance of risk tolerance when RPV is added to technology bundles. Our paper contributes to the literature by broadening the understanding of the adoption of bundled climate solutions.

This study examines spatially dynamic diffusion processes of local policy adoption among municipal governments. Using city-level climate action plans (CAPs) adopted in the Southern California region during 2000-2018 as a study frame, our analysis unpacks spatial variations in the effects of geographic neighbors and regional leaders on local policy diffusion processes. We first argue that both factors will spur CAP diffusion among city governments. We then develop a novel hypothesis of a spatial moderating effect between these two influences. Specifically, we theorize that adjacent neighboring diffusion effects will be less prominent in the areas with nearby regional innovators, while neighboring effects will be more prominent in the absence of regional policy leadership. To examine this, we first use traditional event history and logistic regression analyses. We then investigate inter-city diffusion dynamics in greater detail with a novel geographically weighted regression (GWR) method that unravels regional variations in local diffusion effects. Our aggregate analysis finds that both geographic neighbors and regional leaders drive the diffusion of local CAP adoptions. The novel application of GWR further shows marked spatial variations within the region, suggesting that neighboring proximity-driven diffusion effects are muted by the influence of regional leaders. By spatially unpacking the effect of geographic proximity and regional leadership in policy diffusion, this study enhances our understanding of dynamic and varied diffusion processes.

This paper explores the willingness of consumers to pay for three key electrification technologies – electric vehicles (EVs), rooftop solar (RPV), and air source heat pumps (HPs), using a nuanced two-step model. The first step focuses on whether or not a consumer would consider purchasing a technology, paying particular attention to thresholds and constraints. For those who are willing to pay, the second step focuses on the minimum return-on-investment (ROI) that they require, based on gradations of supporting circumstances such as sustainable lifestyle and climate concern. The second step conjoins respondents' willingness to pay if their energy savings are sufficient and those who are willing to pay if a supportive policy were available. We use the two-step Heckman model to test the validity of our framework using data from an original survey of 1800 adults living in the state of Georgia, USA in 2021. While various enablers and constraints play significant roles in the first step as thresholds, the internal motivators highlighted in the theories of innovation diffusion and planned behavior dominate the minimum ROI. The most consistently significant predictors of being willing to pay for EVs, RPVs, and HPs are having knowledge about energy systems, being risk-tolerant, not being a Republican, living a highly sustainable lifestyle, and believing that there is a climate urgency. Additionally, technology-specific infrastructure constraints are impactful, such as heating with natural gas when considering a conversion to electric heat pumps. Several common predictors affect ROI across all three technologies (e.g., having a sustainable lifestyle and being younger). Common predictors can be used to effectively guide policy design and deployment programs, and may help to promote other electric devices.

Estimating the technical potential of carbon-abatement options involves straightforward calculations, while estimating the achievable potential is more challenging. We illustrate this by examining solar photovoltaics (PV). We estimate that a 92% gap exists between the achievable and technical potential for rooftop solar in Georgia and it is shrinking slowly, while in contrast the state’s solar farms are rapidly expanding. Closing the gap between the technically possible and achievable levels of solar PV requires an understanding of why some electricity providers promote utility-scale solar and not solar rooftop systems. Our financial analysis suggests that rooftop PV on buildings in Georgia could deliver substantial economic benefits to host customers, if utilities offered favorable net metering rates and if host customers, in turn, curtailed their consumption. Comparing the slow diffusion of rooftop solar in Georgia with California and Massachusetts that are rapidly solarizing, underscores the need to develop methodologies that account for utility business models, policy interventions, and behavioral factors. A sensitivity analysis of alternative net metering policies, rebound and curtailment behaviors, a stakeholder analysis, and an assessment of barriers and accelerants documents that these factors are as important as techno-economic drivers in explaining solar technology transitions. Given the numerous barriers to adoption by low- and moderate-income households, an equitable solar transition requires business models and policies that foster participation by all.