Implementing the energy transition: lessons from New Jersey’s residential solar industry

ABSTRACT A desire to shift from fossil fuels to non-carbon-emitting energy sources has become an imperative supported by national, state, and local policies. In the U.S., a diverse array of policies at multiple levels of government have helped the solar industry achieve exponential growth. These advancements, however, are mediated by local implementation processes, which might be expected to have a large impact in the context of U.S. federalism. This paper investigates the effects of two countervailing forces – policy incentives and implementation disincentives – on residential solar adoption in New Jersey. The New Jersey case study includes two complementary analyses designed to illuminate policy incentives and implementation disincentives, respectively. The first is an interrupted time-series analysis that evaluates the effects of federal and statewide renewable energy policies on residential photovoltaic (PV) growth. The second is a set of semi-structured in-depth interviews with solar industry experts, providing implementation insights from the solar industry and indirectly portraying residential customers’ experiences. Results confirm that market-based instruments at the state-level play a crucial role in increasing the relative financial advantage of these systems and, thus, the attraction of residential solar PV to adopters. In addition, the behaviours of future adopters and the valuation of this technology as an investment in the housing market will impact the spread of residential PV systems in the future. Unfortunately, case study findings also confirm that an absence of standardized solar application procedures and outdated interconnection standards is a significant drag on the adoption rate. This highlights a need for policymakers to place greater emphasis on local implementation pathways in solar policy design. Options to achieve this include more robust ex-ante coordination among state and local levels of government and with industry to standardize implementation processes. While U.S. federalism may at times be constraining, our results suggest that even minimal levels of ex-ante coordination can lead to implementation gains that will have a large impact on solar diffusion outcomes. Key policy insights: Federal and state-level financial incentives significantly impact the residential photovoltaic solar adoption rate. The absence of streamlined interconnection application procedures and outdated interconnection standards for the grid limit the residential PV adoption in New Jersey. Our findings underline the importance of paying equal attention to both policy design and to technical standards to underpin implementation processes, especially in the decentralized context of U.S. federalism.


Introduction
Several decades into the political effort to achieve a clean energy transition, there is now enough evidence to support critical thinking about how policy design and implementation are each affecting the trajectory of the energy sector.The impetus for policymaking has been strong, especially after the publication of the Third Assessment Report of the IPCC (2001).However, historians of technology argue that the transition to renewables will take longer than anticipated due to multiple implementation issues (Grubler, 2012;Smil, 2005Smil, , 2017)).
Total U.S. energy demand, most of which has been satisfied by fossil fuels, grew exponentially over many decades until it flattened during the second half of the 1990s, under the influence of technology advancements, saturation of end uses, and structural changes in economic activity (U.S. Energy Information Administration, 2022).U.S. greenhouse gas emissions have followed this trend, peaking in 2007 and declining slightly since then as the energy supply mix has shifted and efficiencies have improved (U.S. Environmental Protection Agency, 2022a).Residential and commercial buildings today account for 40 percent of total U.S. energy consumption, including end-use consumption and electrical system energy losses (U.S. Energy Information Administration, 2021).Consequently, reducing the energy consumption in buildings and integrating renewable energy production technologies into buildings is a fundamental objective of climate mitigation policies.
Solar photovoltaics has been the fastest-growing renewable electricity source in OECD countries since 1990 (International Energy Agency, 2020).The cost of installing photovoltaic solar systems has decreased significantly as the global solar industry has grown since the beginning of this century.National Renewable Energy Laboratory (2022) reported a 64% reduction in the cost benchmark for residential systems between 2010 and 2020.In addition to falling installation costs, the payback period for photovoltaic solar systems in the U.S. has decreased with federal market-based policies.Furthermore, most states have enacted additional financial and regulatory policies to support the solar energy transition, such as feed-in-tariffs, tax credits, pricing laws, production incentives, quota requirements for utility companies, and renewable energy certificate (REC) trading markets (DSIRE, 2021).
This article considers the gap between policy design and implementation on renewable energy, which creates a range of common problems that are well documented in the literature studying policy processes in other fields.These issues include a lack of clear policy objectives, a multiplicity of actors, conflicting interests and priorities, and relative autonomy of implementing agencies (Gunn, 1978;Hanf & Scharpf, 1978;Pressman & Wildavsky, 1984;Sabatier & Mazmanian, 1979).The literature on fiscal federalism provides a framework to discuss the trade-off for allocating the responsibilities and resources between the different tiers of government (Grodzins, 1960;King, 1984;Oates, 1999).In general, central governments are well suited to enact policies to internalize spillovers between local jurisdictions, reap the benefits of scale, and pool risks.On the other hand, decentralized fiscal frameworks cater to local preferences and cost conditions by being closer to people and their local circumstances (Oates, 1999;OECD, 2013).How to build the capacity for implementing bold policies (Barrett, 2004), especially in the context of renewable energy policy under U.S. federalism (Karapin, 2020), remains an open question, and this is our focus.
In addition to the intricate trade-offs of federalism, environmental regulators largely rely on two types of instruments: command-and-control (CAC) regulations and market-based instruments (MBI) (Blackman et al., 2018).Historically, command-and-control regulations have dominated environmental policies in the U.S. As environmental policymaking became less centralized, market-based instruments received attention in some jurisdictions (Harrington & Morgenstern, 2007).Several empirical studies investigate the influence of decentralized market-based policies on the diffusion of residential solar systems in the U.S. (Bauner & Crago, 2015;Bollinger & Gillingham, 2019;Crago & Chernyakhovskiy, 2014).Nevertheless, we need to know the respective magnitudes of their impact to reliably compare these policy types and discuss how the responsibilities should be divided between different tiers of government.
Such renewable energy policies act as a catalyst to increase the relative advantage of solar systems.This is noted by the scholars who adopt the diffusion of innovation framework developed by Rogers (1962Rogers ( , 2003)), which explains how new ideas and technologies spread.Previous studies demonstrated the significance of relative financial, environmental, and social advantages perceived by residential households (Bauner & Crago, 2015;O'Shaughnessy et al., 2020;Pathania et al., 2017;Rai & Beck, 2015;Sommerfeld et al., 2017;Wolske et al., 2017).
Renewable energy policies are expected to underpin these relative advantages for households, and the total installed photovoltaic capacity is expected to more than triple over the next 10 years in the U.S. (Solar Energy Industries Association, 2021).The case of New Jersey presents an opportunity to investigate the impact of policy design and implementation pathways on residential solar.Over the years, New Jersey has moved from direct subsidies to MBIs to promote residential solar projects.This research addresses two complementary research questions: (1) What is the relative impact of federal and statewide renewable energy policies on residential solar growth in New Jersey?and (2) How are these policies implemented and how do they address barriers that homeowners experience?By using a mixed-method approach, this study aims to provide empirical evidence on the relative impact of renewable energy policies and provide implementation insights from the solar industry perspective.
This paper is structured as follows.The following section introduces our empirical approach for the quantitative and qualitative analyses.Section three presents the results of our study and our discussion.Finally, section four presents potential policy implications based on our findings and concludes the paper.

Methodology and data
We carried out this research in two stages in which we applied different research methods.First, we carried out an interrupted time-series (ITS) approach to evaluate the systemic effects of federal and statewide renewable energy policies in New Jersey.Next, we conducted semi-structured in-depth interviews with representatives of solar companies operating in New Jersey to glean valuable insights into both the solar industry perspective and residential customers' experiences as portrayed by the solar industry representatives.We followed a converged mixed-methods approach, in which we compiled quantitative and qualitative data separately, analyzed them, and drew relationships based on the findings (Creswell, 2014).A mixed-method research design allowed us to answer to what extent and how renewable energy policies impact the photovoltaic adoption process and to tease out tensions between policy design and implementation.We discuss the procedural details of the quantitative and qualitative methods next.

Interrupted time series (ITS) analysis
We conducted a time-series analysis to investigate which policies effectively promote photovoltaic solar systems to households in New Jersey.Time series analysis comprises a wide range of methods to extract meaningful statistics and characteristics of the data (Kabacoff, 2015).Typically, these methods use data points recorded over time to detect historical trends and predict future values based on observations.However, our goal in this study is not to make future predictions on residential photovoltaic solar installations but to explain historical trends for which we employed the robust ITS analysis method.
In time series analysis, randomized controlled trials (RCTs) are considered the gold standard for evaluating the effectiveness of interventions and policies (Bernal et al., 2017;Kontopantelis et al., 2015;Nistal-Nuño, 2017).However, randomized controlled trials are not always possible, particularly for assessing policies targeted at the population level.In these instances, quasi-experimental research designs with adequate sample size can be used to evaluate the longitudinal effects of the policy interventions (Kontopantelis et al., 2015;Zhang et al., 2009).
ITS analysis is a robust method that accounts for potential confounders of longitudinal analysis and secular data trends (Nistal-Nuño, 2017;Wagner et al., 2002).This research design is favoured in instances where there are substantial and equally spaced repeated measurements before and after the intervention (Mascha & Sessler, 2019).Policy changes are considered as 'interventions' or 'interruptions' at a known point in time when using ITS analysis to evaluate the impact of policies.Our analysis uses robust ITS analysis that performs inference on differences in pre-intervention and post-intervention correlation.Typically, records are aggregated by time point in ITS analysis, which may help remove the effects of autocorrelation (Mascha & Sessler, 2019;Nistal-Nuño, 2017).Upon preliminary investigation of this effect, we decided to use months as our time unit and aggregated photovoltaic solar installations accordingly.Moreover, we used Durbin-Watson statistics (1950, 1951) to identify the autocorrelation in the model and the Prais-Winsten estimator (1954) to implement a generalized least-squares method to correct the data for first-order autocorrelation.
In addition to renewable energy policies, earlier iterations of our model controlled for macroeconomic conditions and energy prices by introducing variables such as GDP, electricity price, and interest rate.However, these additional variables we controlled for did not yield statistically significant results, nor did they improve our model's fit significantly.Thus, the final version of our ITS model presented in this paper does not include macroeconomic conditions and energy price indicators.
We calculated four variables included in our final model: Y t indicates monthly installations.A continuous variable, time, marks the elapsed number of months from the beginning of the observation period, January 2002.A dummy variable, intervention, indicates the pre-intervention period and post-intervention period.Finally, postslope is a continuous variable counting the number of months since the policy intervention.The following regression model is used to estimate the changes in level and trend after the policy interventions in New Jersey: In our model, b 0 estimates the monthly baseline installations at the beginning of the observed period (time 0); b 1 estimates the structural trend in the installations before the policy intervention and represents the underlying pre-intervention trend; b 2 estimates the level change in monthly installations after the intervention; and b 3 indicates the change in the slope after the policy intervention by using the interaction between the time and intervention.It should be noted that b 3 is the difference in slopes between the post-and pre-intervention periods and indicates the marginal impact of the policy intervention on the long-term trend.Lastly, the error term 1 t represents the random variability not explained by the model.
Residential installation data were obtained from New Jersey's Clean Energy Program (2020d), which included 121,990 residential photovoltaic solar installation records.The photovoltaic installation records dataset includes an adequate sample size between January 2002 and December 2019.Moreover, we gathered the details of federal and statewide renewable energy policies from New Jersey's Clean Energy Program (2020e), the New Jersey Energy Master Plan (New Jersey Board of Public Utilities, 2019), and DSIRE (2021).This analysis did not include some federal or statewide policies that became effective before January 2002 or after December 2019.On the other hand, major amendments to original renewable energy policies within this period were included.
In addition to temporal limitations due to the availability of residential solar installation records, certain methodological limitations of the ITS approach should be acknowledged in interpreting the findings.First, it is hard to draw causal inferences between the observed pattern and the intervention in the absence of the control group (Lagarde, 2012;Linden & Adams, 2011).Next, aggregating the records by monthly points does not allow controlling for individual-level covariates (Nistal-Nuño, 2017).Lastly, given the complexity of the compounding factors in the adoption process, concurrent changes at the time of the intervention will have a combined effect on the outcome that is impossible to filter in the ITS method.
Although the robust ITS model includes an error term to account for the variability not explained by the policy interventions, other explanatory factors relating to adopting photovoltaic solar systems should be considered to reach reliable policy implications.Thus, we employed a mixed-method approach that allowed us to triangulate our interpretations while increasing the contextual sensitivity of our analyses.This process added accuracy, completeness, and usefulness to the final narrative (Roller & Lavrakas, 2015).

In-depth expert interviews
We conducted semi-structured interviews with experts from the solar industry to understand how renewable energy policies are implemented in New Jersey and their impact on incentivizing photovoltaic solar systems in residential buildings.In particular, we employed this method to elicit the viewpoints and experiences of key actors (Bailey, 1987;Chambliss & Schutt, 2016) on topics including how federal and statewide policies impact the solar industry, the adaptability of the solar industry to changes in these policies, and any evidence on how residential users perceive and respond to a dynamic solar policy environment and changing solar technology given structural informational asymmetries that may be unfavourable to residential users (Robinson et al., 2013).
To this end, C-level executives, managers, and other stakeholders from private solar companies in New Jersey were identified as the target audience for the semi-structured interviews.A list of photovoltaic solar system manufacturers, installers, and stakeholders in New Jersey was obtained from the Solar Energy Industries Association's (2019b) website.We conducted 16 in-depth interviews with solar industry experts.Each subject participated in a semi-structured interview once (see Supplementary Material) between June 1, 2020, and October 31, 2020.Each interview took between 30 and 45 minutes and was conducted remotely using Zoom.Interviews covered topics such as the impact of federal and statewide policies on the solar industry, social acceptance of residential PV systems, and barriers that potential adopters experience during the decision-making process.The recruitment process and data collection continued until the analysis achieved saturation, i.e. new insights ceased to be revealed by continued interviewing.
We followed content analysis methods that allowed us to systematically classify and maintain crucial data while reducing the volume of qualitative data to a manageable level (Roller & Lavrakas, 2015).Qualitative analysis began with absorbing the content, in which we examined each interview to gain an understanding of the complete content.The following steps involved developing unique codes and conducting preliminary coding.Procedurally, the examination of the data and developing codes were informed and partially directed by previous literature on the topic.For instance, the previously noted discussion on peer effects (Bollinger & Gillingham, 2012;Palm, 2017;Robinson et al., 2013), on permitting process and temporal lag (Busic-Sontic & Fuerst, 2018;O'Shaughnessy et al., 2020), and on social acceptance of solar systems (Rai et al., 2016;Schelly, 2014;Sommerfeld et al., 2017) informed us to address these issues in New Jersey during our interviews.We also reviewed primary source documents to triangulate the findings from the expert interviews and our interpretations.We used sources from public entities such as the New Jersey Board of Public Utilities (2020b, 2020e), the New Jersey Energy Master Plan (New Jersey Board of Public Utilities, 2019), and the New Jersey Legislature (2022) website.

The impact of renewable energy policies in New Jersey
We analyzed both federal and state policies that were implemented between January 2002 and December 2019.At the federal level, we analyzed one CAC regulation (with two policy amendments) and one MBI (with two policy amendments) (Table 1).At the state level, we analyzed four CAC regulations (with one policy amendment) and three MBIs (with three policy amendments) (Table 2).Figure 1 maps monthly installations and policy types between 2002 and 2019.New Jersey's new monthly installations increased after 2010 following a series of MBIs and CAC regulations.The Great Recession (Q4 2007to Q3 2009, per Hamilton, 2023) did not have a strong negative effect on monthly installations directly, but the event spurred the passage of the American Recovery and Reinvestment Act of 2009, which did have a significant positive influence.Tables 1 and 2 list the federal and statewide policies included in this analysis, present the results, and feature the estimated impact of policy interventions after 12 months.While this estimated value indicates the monthly number of added installations after the policy intervention, the trend change coefficient and p-value indicate the statistical significance and magnitude of the policy change between the post-and pre-intervention periods.
Our findings reveal that the CAC regulation on interconnection standards (Federal Energy Regulatory Commission's Order No. 792) had the most significant impact on residential photovoltaic solar installations, with an estimated about 206 added monthly installations in New Jersey.This policy became effective in 2013 and regulated pre-application and screening processes, as well as allowing energy storage systems to qualify for interconnection.Next, the American Recovery and Reinvestment Act of 2009 is estimated to have increased monthly installations by about 129 in New Jersey.The positive impact of this MBI was also highlighted during the interviews for creating new jobs, investing in the energy sector, providing stability to the economy, and removing the $2,000 cap for the residential renewable energy tax credit for residential photovoltaic systems.Our findings on state-level policies reveal that MBIs on Solar Renewable Energy Certificates (SRECs) yielded the most statistically significant trend change in residential photovoltaic solar installations.Previously, New Jersey pioneered online transactions of SRECs with the launch of their programme in June 2004 (DSIRE, 2019).Interviewed industry experts revealed that the high trade value of the SRECs at the beginning of New Jersey's market-based programme attracted many investors.The price of the SRECs was mainly determined by their market availability, and the ceiling value was determined by the New Jersey Board of Public Utilities.Three amendments to the SRECs Registration Program increased the lifetime of the certificates, extending the time period for participants to accrue and trade their certificates (DSIRE, 2019).Senate Bill No. 1925 had the highest positive impact among these amendments, with an estimated increase of about 280 monthly installations in New Jersey.Due to data availability and time limitations of our analysis, more recent Transition Incentive (TI) (New Jersey Board of Public Utilities, 2020a) and Successor Solar Incentive (SuSI) Programs in New Jersey were not included in this analysis.Nevertheless, it should be noted that one of the main changes of the active SuSI Program is the longer qualifying life and the fixed trade value of Renewable Energy Certificates (RECs) (New Jersey Board of Public Utilities, 2020h, 2021).
Following these MBIs, Solar Energy Option Requirement for Residential Developments is the next most statistically significant state-level policy.This CAC regulation requires developers to offer solar energy systems in new residential developments with 25 or more units, and it is estimated to have increased monthly installations by about 115 in New Jersey in the period since implementation -2009-2019.
Although most of the evaluated New Jersey-statewide policies have a statistically significant positive impact, MBIs yield higher added monthly installation estimates.One reason for this could be outdated CAC regulations on interconnection standards in New Jersey.The solar industry experts argue that residential interconnection applications are denied because electric utility companies shut off substations to new applicants when a certain limit is reached.Follow-up questions with the interview participants revealed that this problem is related to the backfeeding 1 of the substations.A report prepared by Rutgers University (2019) highlights the necessity to update interconnection standards in the state to include high penetration of local circuits and enable substations to backfeed renewable power, as is a routine practice in other states.For instance, the State of Massachusetts' recent Clean Energy and Climate Plan (Commonwealth of Massachusetts, 2022) includes strategies to integrate ever-increasing solar and storage resources into the grid and modernize the infrastructure to allow bi-directional electricity distribution.It should also be noted that utilities are not the ultimate authority on modernizing the grid infrastructure in New Jersey; the grid is operated by PJM, an inter-state regional transmission organization.New Jersey Board of Public Utilities leads a participatory process, including stakeholder meetings, deliberations, and consultations to prepare recommendations for the PJM interconnection process.Their recent straw proposal on the design of the competitive solar incentive programme highlighted delay issues associated with interconnection processes (New Jersey Board of Public Utilities, 2022).

Social acceptance of photovoltaic solar systems
We asked interviewed industry experts a series of questions on the interaction between themselves and their customers to better understand homeowners' motivations and limitations.Almost all interviewed experts underlined that economic benefits and saving money are the main motivations for residential users to install photovoltaic solar systems.One participant said, 'We did a lot of focus groups before we started the company.Obviously, we've dealt with a lot of clients and what it comes down to is, if it's going to save me money, I want to do it'.The political polarization of individuals on environmental issues in the U.S. (Greenberg & Schneider, 2019;Schelly, 2014) and how it would impact households' decision to adopt solar panels (Graziano, 2019;Mildenberger et al., 2019) have been previously discussed in the literature.Our interviews reveal the dominance of financial gains to households as the most significant consideration, framing the decision to install solar panels as an economical choice rather than a political preference for households.
1 Backfeeding refers to reversing the real power flow on the portion of the distribution circuit between the substation and the PV systems' points of interconnection when PV generation exceeds the demand.
Environmental concerns also appear to play a role in household decisions, though to a considerably lesser extent.Almost all expert interviewees explained that environmental benefits are prioritized by a very small percentage of their customers and are mostly considered 'nice to have' secondary benefits.One expert added, '[People] want to save money.But, if in the process of saving money, they can help the environment, they're all for it.But that's not the primary motivation'.
On the flip side, homeowners appear to experience some limitations during their decision-making process.The most frequently mentioned limitation during the interviews was aesthetic concerns.One participant elaborated, 'One of the biggest challenges is curb appeal, and a lot of customers don't want the panels on the front of their house.They prefer to have it in the back of the house'.Solar industry experts argued that New Jersey's behind-the-meter system size limitations 2 and aesthetic concerns lead to sub-optimal placement of solar panels in New Jersey.
Industry expert interviewees also reported that homeowners usually inquire about the impact of photovoltaic solar panel installation on the sales value of their property.Connected to aesthetic values, homeowners are concerned that sales value would decline after the installation.Solar industry experts provided anecdotal evidence that solar system ownership options (e.g.outright ownership and third-party ownership) could positively or negatively impact the property's sales value.For instance, owning the system could increase sales value since future owners would enjoy the benefits and avoid most upfront costs (Klise & Johnson, 2014).On the other hand, long-term lease commitments could create obstacles during the sale and potentially decrease the property's sales value.Nevertheless, more definitive research on the magnitude of the impact of residential solar installations on sales value in New Jersey is needed.
Financial limitations were also mentioned as a significant reason for project cancellations whenever homeowners could not secure the funds or had low credit scores.In the U.S., the solar industry developed third-party ownership models, such as power purchasing agreements (PPA) or leasing arrangements, to address such limitations (U.S. Environmental Protection Agency, 2022b).Our expert interviewees discussed the advantages and disadvantages of different ownership options.In the outright ownership option, the homeowner pays the upfront cost and buys the system.The homeowner receives the federal tax credit, renewable energy certificate, and net metering benefits in this model.In the third-party ownership option, the homeowner pays little or no up-front cost by signing a power purchasing agreement (PPA) 3 or leasing agreement. 4In this ownership model, the third-party system owner (e.g.solar company) receives tax incentives and renewable energy certificate benefits (New Jersey Board of Public Utilities, 2020f).
Regardless of the ownership models they offered, all companies we interviewed utilize active peer effects and interpersonal communication channels through word-of-mouth marketing campaigns to promote their solar system products.Some solar industry experts elaborated that they find about 90% of their new customers through referral programmes.Moreover, experts mentioned that referral programmes lead to a higher sales closing ratio than other marketing strategies, confirming the importance of interpersonal communication highlighted in the diffusion of innovations literature (Rogers, 1962;2003).These findings of our interviews have parallels with previous empirical studies examining the information flows between residential homeowners (Bollinger & Gillingham, 2012;Graziano et al., 2019;Rai et al., 2016).To a lesser extent, expert interviewees also mentioned passive peer effects (e.g.seeing the solar panels while driving by).One participant said, 'There's a farm market that we installed solar on, and people asked the owner about it, and they told the people we installed it'.Overall, the solar industry experts we interviewed argued that active peer effects and interpersonal communication are more influential than passive effects, consistent with the previous empirical research on the impact of active peer effects in solar adoption (Noll et al., 2014;Palm, 2017).
Another strategy of the solar industry is to educate the public on solar energy.As discussed in the literature, educating the public involves informing individuals about incentive programmes, financial savings, environmental benefits, solar hardware, costs, and risks (Brugger & Henry, 2019;Rai et al., 2016).Our expert interviews 2 In New Jersey, the generating capacity of residential solar PV systems cannot exceed the customer's annual electric consumption (New Jersey Board of Public Utilities, 2020g).

3
In power purchasing agreements, the household obliges to buy electricity from the third-party at a set per-kilowatt-hour rate, which is lower than the utility rates, for a certain period.
revealed that companies also use public awareness activities to leverage the interpersonal communication channels of their potential customers.Moreover, the experts claimed that some companies in the solar industry are spreading misinformation, looking for transactional sales, and setting incorrect expectations about solar energy.The experts we interviewed consider public awareness activities and combating misinformation as another campaign to increase their market share in the long term.
Expert interviewees agreed that, on average, homeowners are more knowledgeable about solar energy compared to a decade ago.Some participants claimed that solar companies play an essential role in reaching out to new homeowners with door-to-door and phone marketing.One participant explained, 'If you're a homeowner [in New Jersey] who lived in a house for two or three years, you've had people come up to your door and knock and explain how this all works'.These findings highlight the critical information gatekeeper role of solar companies.Our findings show that the main motivations and limitations are centred around the financial returns of photovoltaic solar panels.Unlike many other technologies studied from the diffusion of innovations perspective, the adoption of photovoltaic solar systems in residential buildings presents an exceptional case due to a high financial threshold for purchasing the new technology (e.g.owning a house, having enough savings, or accessing bank credits for the up-front costs).

Residential solar permitting process and soft costs
Our expert interviews reveal that the solar permitting, registration, and inspection processes account for a substantial amount of soft and indirect costs (e.g.labour, marketing, taxes, and permitting fees) that are reflected in a project's total cost.The soft costs account for about two-thirds of the cost of typical residential solar installations in the U.S. (Solar Energy Industries Association, 2019a).Furthermore, the share of the soft costs in solar projects increased over the years despite the decreasing hardware costs (Fu et al., 2018).By elaborating on inadequate CAC regulations in New Jersey, solar industry experts addressed specific instances, such as inefficient workflow during permitting and consequent monetary business risks distributed across all customers.
Installation of photovoltaic solar systems in residential buildings starts with the initial communication between the homeowners and the solar company.The size and other design specifications of the solar system are determined at this stage.Next, the solar company files registration and permit applications to three main authorities: the State of New Jersey, the electric utility company, and the local municipality.The project is registered to New Jersey's Clean Energy Program to receive renewable energy certificates (RECs) benefits.An interconnection application is concurrently filed with the electric utility provider.The third application involves obtaining the required permits from the municipality, which includes submitting technical drawings and project details and examining the proposed project's compliance with the electric and building codes (New Jersey Board of Public Utilities, 2020f).The solar industry experts criticized onerous and inconsistent application required forms, fees, and waiting times across 565 municipalities in New Jersey.One expert elaborated, 'Usually getting the permits with the town is the real stumbling block.Every time it is different.There's absolutely no uniformity in New Jersey', and another expert said, 'Even in the same town, from project to project, they don't require the same things.If we could just get a standard set, basically a checklist, and it could be used throughout the entire state, [the permitting process] would move a lot faster'.
Some municipalities in New Jersey also require a zoning permit for residential installations, while most do not require it for roof-mounted systems.In New Jersey, local municipalities are required to review the proposed construction and return the permit application within 20 business days.However, the solar industry experts argued that different departments reviewing the permit could take 20 business days for each aspect of the permit (e.g.electric, building), depending on the municipal structure.Overall, the registration and permitting stage takes two to eight weeks before the installation can start.
Upon completing the registration and permitting process, the mounting system and the solar panels are installed.The installation typically takes one to two days.However, some municipalities in New Jersey require an additional inspection for the railing system before the solar panels are placed, which extends the installation period up to a week.
The completion of the project is filed with the same three agencies.However, these applications cannot be carried out simultaneously.The final inspections begin with a scheduled site visit with an inspector from the local municipality.Most expert interviewees raised concerns regarding the divergent inspection practices in municipalities across New Jersey.One expert said, 'A difference [between municipalities] mostly comes in terms of inspection.Some [inspectors] will just take a look at your system and make sure it looks safe.Others will want to open up everything and dig into every single wire to make sure it's attached the way it should be'.Once the inspection is approved, the local municipality issues a Certificate of Approval (COA) that typically takes two to three weeks.Some municipalities require solar companies to fill out a form to request the certificate, while others accept a verbal or in-person request.The solar industry experts also argued that the process to receive this certificate is not uniform across municipalities in New Jersey, nor is it automated.
Next, the solar company submits the Certificate of Approval (COA) and other documents that detail the final project specifications to the electric utility company.Within about two to three weeks, the electric utility company sends a representative to change the meter from a standard meter to a net meter and to turn the system on (New Jersey Board of Public Utilities, 2020f).Homeowners start receiving benefits at this point.
The final application is filed with New Jersey's Clean Energy Program and includes all previous approvals and documents (New Jersey Board of Public Utilities, 2020c).The experts reported that this final approval generally takes one to two weeks.A quality control process requires 10% of the installations to be randomly selected and inspected by state inspectors (New Jersey Board of Public Utilities, 2020c).This final application takes one to two weeks if the inspection is waived and three to four weeks if an inspection is scheduled.
The registration, permitting, and inspection stages vary broadly based on the property's municipality and electric utility provider.The solar industry experts argued that the timeline between signing the contract with the solar company and turning the system on after the electric utility company's final approval would take six to eight weeks in a streamlined permitting and approval process.However, they added that it takes up to four months due to delays in different steps.In addition to longer processing times directly impacting the soft costs, one expert elaborated on how insufficient CAC regulations in New Jersey are associated with the risks that businesses are taking, 'Some customers, the longer they wait, the more they might change their mind [and] decide they don't want to go through with it.The faster you get [the installation] done, the lower the risk of that happening'.Solar companies distribute added soft costs and costs related to these business risks across their customers.
Overall, more than half of the expert interviewees criticized the lack of standardization of the application process, permit fees, and inspections as a central issue regarding the installation process in New Jersey.These process challenges and practices were said to significantly increase transaction costs and decrease workflow efficiency.Most interviewed experts referred to California's streamlined permitting and inspection process model as a good practice and argued that the municipal permitting and inspection processes in New Jersey should be standardized by revised CAC regulations.Previous empirical research illustrates the potential cost and time benefits of California's streamlined local permitting procedures for residential installations (Hsu, 2018;Wiser & Dong, 2013).Specifically, Wiser and Dong (2013) argue that developing state-wide technical and procedural requirements, creating clear guidelines on permitting procedures, and using standardized online application forms would minimize local variations and provide benefits not only to solar installers and their customers but also to city permitting departments.

Conclusions
This study investigates the impact of renewable energy policies on residential solar installations in New Jersey by using ITS analysis and providing implementation insights from solar industry experts.At the federal level, the findings of our ITS analysis reveal that the CAC regulation on pre-application and screening processes had the most statistically significant impact on residential PV solar installations in New Jersey.Beyond the policies evaluated in our ITS analysis, conducting interviews with the solar industry experts provided practical insights and allowed us to identify missing policies at the state level.For instance, expert interviewees elaborated on how implementing a CAC regulation to streamline permitting and inspection processes could reduce soft costs that are currently distributed across customers by the solar companies.We argue that enacting policies to improve collaborations between solar developers, utilities, and local governments and prioritizing one-stop-shop approaches for new customers would require low costs and potentially lead to soft and indirect cost reductions for small-scale residential projects.
Statewide policies evaluated in our ITS analysis yielded comparatively better results than federal policies and explained a higher variability in installation trends.This can be described by state governments' ability to account for local preferences and cost conditions by being closer to local market conditions.For instance, successive MBI amendments to the Solar Renewable Energy Certificates (SRECs) led to the most statistically significant change in New Jersey.We argue that both the regulatory function of CAC policies and incentives through MBI should be brought into play to promote residential solar.Historical evidence suggests a correlation between the falling installation costs and the adoption rate for this technology, and our study highlights how these two types of policiesdirectly and indirectlyhelp reduce installation costs.
The case of New Jersey highlights a need for policymakers to place greater emphasis on local implementation pathways and processes in solar policy design under U.S. federalism.Aspects of the New Jersey experience may not translate directly to other jurisdictions because State constitutions vary in the degree of autonomy granted to localities, but strategies of standardization and soft-cost reduction should be transferable.Because residential solar energy deployment depends on incentivizing market transactions, the total costincluding regulatory soft costsbecomes a determinant of successful diffusion.Local bureaucratic discretion and variation are throttling the advancement of the solar industry.This is not about removing regulatory barriers but rather about standardizing processes so that market forces can work more effectively.In the case of residential solar systems, the purpose of federal and state policy and local planning is to create thriving markets for decentralized and clean energy production.
Aside from the policy-related issues, the future of residential solar in New Jersey will be further impacted by the ever-growing number of adopters of this technology and their behaviours.Our qualitative findings confirm the importance of interpersonal communications and peer effects in New Jersey, parallel with the findings of other scholars in other states.As motivations for households in the Northeast region increase with higher utility bills and extreme weather events, active peer effects will be vital in determining the adoption rate of residential solar systems.
Considering the dominance of financial benefits on households' motivations to install photovoltaic solar systems, more research is needed to better understand the impact of residential solar projects, specifically on property sales values.For instance, empirical research could be carried out to model the long-term costs and benefits of different ownership models.Such research would provide empirical data on the magnitude of economic benefits to decision-makers and potential residential solar adopters, including an evaluation of how solar installations affect the real estate market value of housing.