Decentralized Renewable Energy and Socioeconomic Disparities

Abstract

Decentralized renewable energy (DRE) has emerged as a key tool for global energy transition and emissions reduction. While DRE has the potential to democratize energy production, evidence suggests it may cause unequal benefit distribution across population groups. This study provides the first comprehensive empirical analysis of DRE distribution patterns across all Israeli municipalities, examining policy implications for equitable energy transitions. We analyzed 16,998 rooftop solar installations across 232 municipalities between 2017 and 2022, categorized as residential and commercial installations. Using regression analysis, we examined how geographic, socioeconomic, and demographic factors associate with installation adoption rates. Findings reveal divergent patterns between installation types. For residential installations, socioeconomic status emerged as the primary determinant, with adoption rates increasing linearly with municipal wealth. These disparities widened significantly over time, contradicting expectations that declining costs would democratize access. For commercial installations, the urban–rural divide proved dominant, with rural areas showing substantially higher adoption rates. Our analysis reveals important policy implications and recommendations for global DRE deployment, emphasizing the need to integrate equity considerations into renewable energy policy design to accelerate the transition to renewable energy while minimizing socioeconomic disparities.

1. Introduction

Decentralized deployment of renewable energy infrastructure is expected to play a key role in the global energy transition [1,2,3,4]. Unlike the traditional system of centralized electricity production—where energy is generated by a public authority in large-scale facilities such as national power plants—a decentralized system allows the public to actively participate in the process. This can be done by financing and owning small-scale generation units, producing power either for self-consumption or for generating additional income in the process [5].

Decentralized renewable energy (DRE) seems like a win-win system, beneficial to the planet as well as to users [6], but despite its numerous advantages, a growing body of research points to significant drawbacks of this policy, particularly with respect to distributive effects and the exacerbation of socioeconomic inequalities across diverse population groups [7,8]. Large-scale empirical evidence of how the benefits of solar energy are distributed across different socioeconomic groups remains limited, creating a critical knowledge gap for evidence-based policymaking. This study addresses this gap by providing comprehensive empirical analysis of solar adoption patterns in Israel.

This study focused on DRE in Israel, which constitutes a particularly intriguing international case study for examining the transition to DRE because of several unique characteristics. First, Israel is a developed economy, with abundant sunshine and significant solar resources [9] as well as high population density, according to the World Bank (2025) [10]. Second, Israeli policy is highly centralized, especially concerning land and planning with a high percentage of land under national ownership [11,12,13], which gives the government considerable influence on energy policy. Third, the country’s geographic composition enhances its potential for solar energy production: The Negev desert comprises 54% of Israel’s total land area (12,000 sq. km.), offering ideal conditions for large-scale solar installations. Lastly, Israel is at the forefront of the global energy industry in terms of entrepreneurship and startups [14,15].

To understand the relation between the distribution of DRE installations and socioeconomic disparities in Israel, we examined the distribution of rooftop solar PV installations across entire Israeli municipalities. We divided installations into two distinct categories, according to the definitions of the Israeli Electricity Authority (IEA): residential installations, typically installed on residential roofs by households, and commercial installations, installed on larger buildings and facilities by firms. Using a quantitative, cross-sectional approach, we analyzed how demographic, socioeconomic, and geographic characteristics are associated with the adoption rates of both installation types across Israeli municipalities. The study provides the first comprehensive empirical evidence of installation patterns across Israeli municipalities, filling a crucial gap in understanding renewable-energy policy outcomes.

Our findings reveal divergent patterns between residential and commercial rooftop installations. In the residential sector, results align with international evidence, showing that installations exhibit a rising monotonic relationship with socioeconomic status. However, we found that these gaps persist and even expand over time despite rising environmental awareness and significant declines in installation costs—contrary to what might have been expected. For commercial installations in Israel, the dominant factor is the urban–rural divide, even after controlling for installation potential. These findings reflect the country’s unique land policy and spatial–demographic structure. The divergent patterns suggest that private installations in lower income communities are inhibited by barriers, be they financial or other, that are in fact related to their socioeconomic status.

As countries worldwide accelerate their transition to DRE systems, the research findings have significant implications beyond Israel’s borders, demonstrating that without explicit equity considerations, renewable energy policies risk failing to achieve their generation potential as well as reinforcing existing socioeconomic inequalities rather than alleviating them.

The structure of the study is as follows: The next section (Section 2) presents the theoretical framework of the research and the relations between socioeconomic disparities and a renewable-energy policy in general and a decentralized renewable energy policy in particular. The third section presents Israel’s renewable energy market and policy and the developments in recent decades. The fourth section focuses on the research methodology and the unique datasets we used. The fifth and main section presents the research findings, and the last sections present the discussion and research conclusions.

1.1. DRE, Socioeconomic Disparities and Urban Policy

Decentralized renewable energy (DRE) has emerged as a central mechanism in the global transition toward sustainable energy systems [16]. Unlike traditional centralized power plants, DRE allows a diverse range of actors—including households, businesses, farmers, and public institutions—to generate electricity locally, most commonly through rooftop or land-based photovoltaic (PV) installations. These systems enable producers not only to consume the electricity they generate but also to sell excess supply to the grid, creating a more diversified, participatory, and resilient energy market [17,18].

The global shift to renewable energy has generated extensive research on renewable energy and carbon emissions across various communities, sectors, and time [3,19,20,21]. Given its central role in advancing the energy transition, DRE has over the past decade become the focus of substantial multidisciplinary scholarship that examines the phenomenon from multiple perspectives. Scholars explore, among other themes, the technical feasibility of decentralized systems [17,18]; their economic viability and long-term sustainability [22]; changing patterns of public awareness [23]; political mobilization and civic activism [4]; the role of national governments and local authorities in shaping and regulating the transition [24,25,26]; as well as the barriers and constraints affecting adoption across sectors, regions, and diverse population group [1,27].

The scholarly literature highlights both the opportunities and the risks associated with decentralized renewable energy (DRE). On the one hand, DRE offers clear environmental and socioeconomic benefits. Globally, it reduces reliance on fossil fuels and contributes substantially to climate change mitigation [3]. Locally, it can lower electricity costs, provide households with supplementary income, and enhance energy autonomy [27]. Beyond providing individual benefits, DRE can stimulate rural development, foster technological innovation, and strengthen local economies by diversifying opportunities for investment and production across society [1,6]. Importantly, the decentralization and democratization of energy production create possibilities for greater community empowerment and citizen participation in shaping the energy transition [4,16,28].

On the other hand, the dispersion of DRE is deeply conditioned by existing inequalities. Access often depends on socioeconomic status, access to finance, property ownership, and institutional capacity [17]. Affluent households may be more likely to adopt solar technologies, benefit from subsidies, and realize long-term savings, whereas disadvantaged groups—including low-income households, renters, and residents of multi-family housing—face structural or financial barriers to participation [1,27]. Access to finance may be especially relevant because DRE requires large upfront investments even when the returns recover the costs over time. Evidence shows that while some populations bear disproportionate environmental and social burdens—such as health impacts or reduced landscape value—others are positioned to capitalize on new economic opportunities [29].

Empirical studies consistently reveal that DRE adoption correlates strongly with wealth, property ownership, and institutional access [30]. Higher-income groups not only adopt DRE at higher rates but also capture most subsidies and long-term savings, whereas lower-income populations—despite shouldering heavier energy burdens—are frequently excluded because of high upfront costs, limited financing options, or inadequate information [31,32]. Renters and residents of apartment buildings often lack both the legal and physical means to participate in DRE schemes. Furthermore, projects are frequently designed to maximize commercial profitability rather than community benefit, at times generating negative externalities such as environmental degradation or health risks [33]. Scholars warn of “energy privilege,” whereby advantaged groups disproportionately benefit while marginalized populations are systematically left behind [8,34,35,36]. Weak regulatory mechanisms, insufficient community-ownership models, and a lack of targeted public support exacerbate these inequalities, even when projects are introduced with progressive intent. Thus, the renewable energy transition has an inherent duality: It may widen existing inequalities, but it also holds the potential to restructure energy systems in ways that reduce social gaps [7,29,37].

1.2. Urban Policy in Advancing DRE

Public policy and urban policy play a pivotal role in advancing the adoption of renewable energy [38]. Policy frameworks ensure alignment with international climate agreements while internalizing external costs—both positive and negative—associated with energy production [21]. Because renewable energy projects require substantial upfront investment and often face significant uncertainty, public intervention is essential for ensuring the private profitability of DRE (e.g., through subsidies or purchase of generated power by utilities), mitigating risks and providing stable conditions for long-term development. Moreover, well-designed policies can maximize the socioeconomic benefits of renewable energy transitions, such as job creation, industrial growth, and economic diversification [17,34].

Although national governments have traditionally led the design of decentralized renewable energy (DRE) systems, the role of local governments and subnational actors has become increasingly central to implementation and innovation [39]. Over the past few decades, municipalities have emerged as key players in both national and international arenas, meriting greater scholarly and policy attention, particularly in environmental governance [40,41,42]. In some contexts, municipalities function primarily as implementing agencies of central government policy, while in others they exercise considerable autonomy, often advancing policies more progressive than those of national authorities [43,44,45].

This dynamic is especially relevant to solar DRE. Research has demonstrated that local government involvement is crucial to the successful adoption of solar technologies, particularly for residential systems installed on rooftops [24]. As the tier of government closest to citizens, municipalities can bridge the gap between policy design and practical implementation, encouraging household participation and fostering community-level innovation. For this reason, local authorities stand at the forefront of both the opportunities and challenges associated with the expansion of decentralized solar energy—a central focus of this study.

1.3. Renewable Energy in Israel: Historical Overview and Current Developments

Since its founding in 1948, Israel has pursued evolving strategies to secure its energy independence amid geopolitical isolation. Often described as an “energy island” because of limited integration with regional grids [46], Israel has prioritized domestic energy development and diversification, and the country’s energy policy has undergone significant transformations. In the 1950s–1960s, the energy policy emphasized conservation, R&D, and coal imports supplemented by limited domestic oil [47]. The 1973 oil crisis, triggered by the Arab embargo following the Yom Kippur War, exposed Israel’s vulnerability to fossil fuel dependency, prompting a shift toward diversification and domestic alternatives [48].

The year 1976 saw a turning point: Legislation mandated solar water heaters in new residential buildings, establishing Israel as a global leader in solar thermal technology [9]. During the 1970s–1980s, Israel expanded natural gas exploration and leveraged hydroelectric generation via the National Water Carrier [49]. The 1996 Electricity Sector Law initiated market liberalization, enabling independent power producers (IPPs) and incentivizing renewable energy deployment.

Natural gas discoveries in the early 2000s, particularly the Tamar and Leviathan fields, transformed Israel’s energy mix. By 2023, natural gas accounted for approximately 65–70% of electricity generation [50], supported by major infrastructure investment [51].

Alongside gas development, Israel set national renewable-energy targets—10% by 2020 and 30% by 2030—accompanied by policy tools such as feed-in tariffs (FiTs) and, later, competitive bidding [52]. Nonetheless, progress has lagged. The 2020 target was met only in 2022, and interim goals remain unmet [53].

Because of land scarcity and grid limitations, Israel has prioritized decentralized solar energy, particularly rooftop photovoltaics (PV) and agro-voltaic systems [54]. However, uptake of rooftop PV has been limited—by late 2020, only 59% of allocated quotas were utilized—primarily because of regulatory barriers, insufficient incentives, and the technical complexity of installing panels on shared rooftops in high-density urban areas [14]. These constraints disproportionately affect lower-income, urban populations, limiting equitable access to solar energy [47,55,56].

Government scenarios project that rooftop and dual-use PV could supply up to 43% of the national electricity demand by 2030 [57], but realizing this potential requires addressing social and regulatory hurdles. For example, the regulation of dual-use solar installations on farmland remains contentious, linked to broader debates on historical land inequality [12,13,58,59].

By the end of 2022, Israel had installed 4.7 GW of renewable capacity, supplying just under 10% of total electricity demand, with solar PV contributing over 80% of renewable generation [53]. Annual growth has accelerated in recent years but remains insufficient to meet the 2030 target.

Despite underperformance in deployment, Israel is recognized as a global leader in clean energy innovation, supported by a dynamic startup ecosystem that drives technological advancement [14]. Yet rooftop solar adoption continues to reflect socioeconomic disparities. Although declining installation costs have reduced some barriers, households in multifamily urban dwellings remain largely excluded due to collective ownership structures and regulatory complexity [15]. National initiatives such as the National Solar Plan and programs promoting rooftop deployment on public and commercial buildings [60] have not been matched by a coordinated, multi-year implementation roadmap [61], undermining progress toward Israel’s carbon neutrality target for 2050 [57].

Socioeconomic inequalities in Israel are among the widest in the OECD and extend into the energy domain, where renewable technologies disproportionately benefit affluent households and urban centers [62,63]. Spatial divides between the center and periphery, along with the rural–urban distinction, further constrain disadvantaged municipalities from participating in the energy transition [64,65]. Recent studies caution that without explicit corrective measures, renewable energy expansion risks exacerbating these socioeconomic and spatial disparities [66,67,68]. However, despite the growing body of research on renewable energy and inequality, no comprehensive empirical study has yet examined solar installations across all Israeli municipalities in relation to standardized socioeconomic and demographic indicators—an important gap that the present research addresses.

2. Materials and Methods

This study examined patterns of rooftop solar photovoltaic (PV) installations across Israeli municipalities to understand how the distribution of these installations relates to existing socioeconomic disparities. We employed a cross-sectional research design with multiple layers of analysis that enabled us to systematically examine installation patterns and their relation with municipal characteristics. Specifically, we analyzed how spatial, socioeconomic, and demographic characteristics of municipalities associate with rooftop solar PV adoption rates, in residential and commercial installations. Municipalities served as the primary unit of analysis because they are the key actors implementing energy policy and promoting solar installations through permits and local incentives, such as implementation of decentralized energy. Israel’s small size and high population density make the municipal level particularly suitable for analyzing installation patterns and characteristics, and Israel’s Central Bureau of Statistics (CBS) systematically collects comprehensive demographic, socioeconomic, and spatial data at the municipal level.

We measured adoption through installed solar PV capacity in relation to its technical potential. The technical potential metric, assessed by Israel’s Ministry of Energy, represents each municipality’s estimated rooftop solar installation capacity based on available roof area, solar radiation levels, and technical constraints. Using potential as the denominator provides an accurate measure of actual utilization rates by controlling for physical infrastructure differences between municipalities. This normalization reveals the efficiency with which each municipality converts its available solar resources into actual installations, showing the percentage of solar realization in each municipality.

We examined four key characteristics of the municipalities: the first two commonly used in international literature to distinguish between municipalities and the latter two unique to Israel.

• Municipality’s socioeconomic cluster (Ranking is based on socioeconomic variables, such as mean per capita income (including pensions or benefits); residents’ motorization level; percentages of pupils eligible for matriculation, of students in higher education, and of job seekers; the dependency ratio and percentage of residents receiving an income subsidy [68] Israel’s CBS divided municipalities into 10 clusters (10 being the highest socioeconomic level), reflecting differences in economic development, education levels, and living standards.
• Geographic distribution—Israel is divided into six districts—North, Haifa, Tel Aviv, Center, Jerusalem, and South—a division that captures variations in solar radiation exposure, land availability, and economic development patterns.
• Urban/rural classification—In Israel, the majority of the population (92%) resides in urban areas, which occupy approximately 20% of the country’s land. In contrast, a minority of the population (approximately 8%) lives in rural areas that span over 80% of the national territory [69]. Moreover, the majority of the land in Israel (both urban and rural) is nationally owned and managed by the Israel Land Authority. This classification is particularly significant in Israel’s context also because rural communities historically receive more favorable land-use considerations than urban areas, reflecting long-standing national development land policy [12,13,58].
• Jewish/Arab population—Israel is the only country where the majority of the population is Jewish (73.75%). Arab citizens constitute 21.71% of the population, divided as follows: ~18.29% Muslim, 1.86% Christian, and 1.56% Druze [70]. The Arab population resides predominantly in ethnically separate localities, with the exception of four mixed cities: Tel Aviv–Jaffa, Lod, Ramla, and Acre. The remaining 4.54% of the population are either unaffiliated with any religion or belong to other religious groups. They are not perceived as a unit or category, they do not reside in defined geographic municipalities, and there are no dedicated statistical data available for them. Thus, the common classification in Israel is between municipalities with a Jewish majority and those with an Arab majority. Most Arab municipalities are located in Israel’s social and geographic periphery and are characterized by a low socioeconomic status, a pattern that shapes their social standing, fiscal resilience, and economic sustainability [71].

2.1. Data

The analysis was based on two data sources. The first database, from the IEA (The Israeli Electricity Authority (IEA) is the government regulatory body that sets electricity policy and tariffs, whereas the Israel Electric Corporation (IEC) is the state-owned utility company that generates and supplies electricity to consumers. https://www.iec.co.il/en/content/about/lobbies/lobby (accessed on 1 January 2025), contains detailed records of PV installations. The dataset encompasses 28,979 rooftop solar installations across 1214 localities (The term “localities” refers to any rural community (kibbutz or moshav) in Israel that does not have independent municipal status.) in Israel, tracking installations from 2010 through January 2022.

First, the IEA’s dataset underwent a cleaning and preparation process. We restricted the analysis to installations between 2017 and January 2022 because of substantial data gaps in earlier periods. Next, we excluded areas containing only industrial complexes, because the study focused on municipalities with resident populations. Municipalities in the Judea and Samaria area, and Bedouin dispersed communities, were omitted for lack of data. Second, based on the IEA’s definitions, we categorized two types of installations, by capacity (Another type of installations—competitive process installations (exceeding 630 kW DC)—were excluded from the analysis because they represent only 1% of installations and operate through competitive tenders in which producers bid for feed-in tariffs, unlike the tariff-based arrangements in our study where rates are pre-set by the Authority and open to all eligible participants.):

• Residential installations: (up to 18 kW DC) (DC (direct current) refers to the rated power output from solar panels, while AC (alternating current) refers to the inverter output that converts DC to usable power. DC ratings are approximately 20% higher than their AC output. For example, an 18 kW DC installation typically produces 15 kW AC power through its inverter.): primarily serving individual households, representing 48% of total installations.
• Commercial installations: (18 kW DC to 630 kW DC): serving businesses and public institutions, representing 51% of total installations.

We used the refined installation data to examine our dependent variable: installed capacity per potential.

The second database, for explanatory variables, included data from the CBS annual publication on municipalities. This dataset enabled us to measure and analyze the four key municipal characteristics discussed above: socioeconomic clusters, geographic distribution across districts, urban/rural classification, and demographic composition. This enabled us to examine how various municipal dimensions might be associated with solar adoption patterns across municipalities in Israel.

2.2. Research Stages

The research design consists of four sequential stages, each building upon the previous one, which together provide a comprehensive picture, as illustrated in Figure 1.

In the first stage, we aggregated installation data from the locality level to match the municipality-level data from the CBS. Then we merged the two data tables into a unified dataset at the municipality level. The final dataset includes 16,998 PV rooftop installations across 232 municipalities (of 256 municipalities in Israel. One municipality (Arava Tichona) was excluded from the commercial installations analysis because of its being a significant outlier. Municipalities in the Judea and Samaria area, and Bedouin dispersed communities, were omitted for lack of data.), totaling 1,176,811 kW DC of installed capacity (59% of the original data). This dataset comprises 8007 residential installations (125,306 kW DC) and 8991 commercial installations (1,051,505 kW DC).

In the second stage, we conducted descriptive statistics analysis to examine patterns of PV adoption across different municipal characteristics.

In the third stage, we employed regression analysis to examine how socioeconomic status is associated with PV adoption rates while controlling for other factors. We estimate the relation through several specifications that include various other demographic and geographic controls, in order to test the robustness of the result. We began with a simple regression model and sequentially added one predictor variable in each subsequent regression to examine the incremental contribution of each factor. This approach enabled us to assess the robustness of the relation between socioeconomic status and PV adoption while controlling for geographic, urbanization, and demographic factors. The main analysis was based on the full regression model, presented below:

$$Y_i={\beta }_0+\sum _{j=2}^{10}{\beta }_j{SE}_{i,j}+\sum _{k=1}^5{{\beta }_{k}DISTRICT}_{i,k}+{\beta }_u{URBAN/RURAL}_{i,u}+{\beta }_a{JEWS/ARABS}_{i,a}+{\epsilon }_i$$

The dependent variable $Y_i$ represents the installed capacity of solar PV per rooftop potential in each municipality i, measuring the efficiency of solar potential utilization as the ratio of actual installed capacity to estimated rooftop potential, ranging from 0 to 0.135. The key explanatory variable is socioeconomic status ${SE}_{i,j}$, with variables for clusters 2–10, using socioeconomic cluster 1 (lowest) as the reference category. ${DISTRICT}_{i,k}$ (Haifa, Jerusalem, Northern, Southern, and Tel Aviv) controls for the municipality’s geographic location, with Central District as the reference category. ${URBAN/RURAL}_{i,u}$ is a binary indicator distinguishing between urban and rural municipalities, with rural area as the reference category. ${JEWS/ARABS}_{i,a}$ indicates whether a municipality has a Jewish or Arab majority population, with Arab majority as the reference category. ${\epsilon }_i$ is the error term.

In the fourth stage, we performed the analysis separately by years in order to track the evolution of the relation between socioeconomic status and installation rate over time. This enabled us to identify whether socioeconomic and spatial disparities in solar PV adoption narrowed or widened during the study period.

2.3. Obstacles and Challenges

The study faced several challenges. First, we encountered data timeline limitations. Although installation data exist prior to 2017, they were collected retrospectively and lacked consistency in reporting methods. Therefore, we focused the analysis on data from 2017 to 2022, ensuring higher reliability and completeness of our dataset. Second, the absence of an independent dataset from the IEA to cross-reference against the Israel Electric Corporation (IEC) data, coupled with inconsistent terminology between the two organizations, complicated our verification efforts. We addressed this through a data cleaning process, implementing rigorous verification procedures to ensure data accuracy and consistency.

Third, the spatial scale of analysis posed an additional methodological challenge. Whereas installation data were available at the locality level, the data from the CBS were at the municipality level. We resolved this by aggregating installation data to match the CBS level, allowing for consistent cross-analysis of socioeconomic and demographic variables with installation patterns. Moreover, our dataset included only legally registered installations connected to the electricity grid through proper channels, potentially missing informal or undocumented installations that exist outside official records. Finally, endogeneity concerns must be acknowledged. The causal direction clearly suggests that the municipality characteristics influenced PV installation rates, as it is unlikely that solar panel installations affected municipal socioeconomic, demographic, or geographic status. With regard to other issues of endogeneity, omitted variables such as solar radiation could correlate with the explanatory variables in the model. However, normalizing our dependent variable by installation potential helped us address this concern, as the potential metric already incorporated solar radiation levels and other physical constraints at the municipal level. This suggested an opportunity for future research incorporating additional variables while recognizing that our current approach partly controlled for key physical factors.

Perhaps most importantly, it is important to recognize that our estimates reflect correlations, rather than causal relations. The association between socioeconomic status and installation rate is monotonic and robust, but it does not necessarily imply that installations are lower in municipalities with lower socioeconomic status because of that status. It is impossible to rule out the possibility that there are confounding factors that are correlated with socioeconomic status that are reducing installations. The analysis also does not allow us to pinpoint the mechanism which is driving the relation, for example, whether it is related to financial barriers or lack of awareness or agency. We note, however, that conducting the analysis separately for residential and commercial installations helps to separate factors that are related to the socioeconomic composition of the residential population in each municipality from technical or geographical factors that would also affect commercial installations.

We acknowledge the challenges faced throughout the study. However, we are confident that the robustness of the dataset and the methodological steps we have taken provide confidence in the findings’ reliability.

3. Results

The findings highlighted significant disparities in solar PV adoption across three dimensions: spatial, geographic, and socioeconomic. Although these disparities manifested differently in residential and commercial installations, collectively they suggest that Israel’s decentralized solar energy policy faces substantial challenges.

Table 1. Descriptive Statistics of Key Variables and Dataset Composition.

Variable	Mean (Std. Dev.)
Capacity per Potential for Residential installations	0.0110 (0.0161)
Capacity per Potential for Commercial installations	0.0638 (0.0660)
Dataset Composition
Category	Value
Total number of installations	16,998
Number of Residential Installations	8007
Number of Commercial Installations	8991
Time Range	2017–January 2022
Number of Municipalities	232
Percentage of Municipalities with Jews population majority	63.5%
Percentage of Municipalities with Arab population majority	36.5%
Urban Authorities	50
Rural Authorities	182
Socio-economic clusters	1–10

and

Table 2. Distribution of Solar PV Installations by Key Characteristics.

Category	Residential Installations Mean kW/Potential (S.D)	Commercial Installations Mean kW/Potential (S.D)
District
Southern	0.017 (0.025)	0.099 (0.073)
Northern	0.010 (0.017)	0.064 (0.071)
Central	0.012 (0.010)	0.059 (0.055)
Haifa	0.008 (0.009)	0.047 (0.051)
Jerusalem	0.006 (0.004)	0.046 (0.063)
Tel Aviv	0.004 (0.003)	0.024 (0.038)
Urban/Rural
Rural Areas	0.016 (0.013)	0.134 (0.065)
Urban Areas	0.010 (0.017)	0.045 (0.053)
Socioeconomic Cluster (ranges)
Low (1–3)	0.0001–0.004 (0.0002–0.008)	0.026–0.032 (0.025–0.048)
Medium (4–7)	0.005–0.015 (0.006–0.016)	0.042–0.099 (0.049–0.073)
High (8–10)	0.016–0.035 (0.014–0.033)	0.026–0.057 (0.023–0.058)
Population
Jewish Majority	0.016 (0.013)	0.088 (0.068)
Arab Majority	0.003 (0.017)	0.023 (0.034)

present the data composition, four key characteristics, and their descriptive statistics, providing an overview of the dataset used for analysis.

The geographic distribution of solar PV rooftop installations across Israel revealed significant disparities. Descriptive statistics showed that whereas the Northern District led in absolute numbers, accounting for approximately one-third of both installations and total capacity (see Appendix A), the Southern District showed remarkably higher rates when we examined capacity normalized by potential (Table 2; Figure 2). In contrast, the most populated districts, Tel Aviv and Jerusalem, consistently showed the lowest installation rates, with capacities per potential roughly one-quarter of those in the Southern District in both residential and commercial categories.

These geographic patterns were confirmed by the regression results (

Table 3. Regression result for residential installations.

	Total kW per Potential
Socio-economic cluster #2	0.0094 (0.0062)
Socio-economic cluster #3	0.0092 (0.0057)
Socio-economic cluster #4	0.0092 (0.0062)
Socio-economic cluster #5	0.0162 ** (0.0062)
Socio-economic cluster #6	0.0167 * (0.0068)
Socio-economic cluster #7	0.0206 ** (0.0066)
Socio-economic cluster #8	0.0262 *** (0.0070)
Socio-economic cluster #9	0.0384 *** (0.0073)
Socio-economic cluster #10	0.0417 *** (0.0084)
Haifa District	0.0041 (0.0032)
Jerusalem District	0.0034 (0.0060)
Northern District	0.0108 *** (0.0027)
Southern District	0.0158 *** (0.0033)
Tel Aviv District	−0.0121 ** (0.0043)
Urban Area	0.0040 (0.0025)
Majority group–Jewish	0.0057 . (0.0030)
Observations	232
${\mathrm{R}}^2$	0.3687
$\mathrm{Adjusted} {\mathrm{R}}^2$	0.3217

The asterisks denote statistical significance as follows: *** p < 0.001, ** p < 0.01, * p < 0.05, . p < 0.1, with coefficients lacking symbols being non-significant at p ≥ 0.1.

and

Table 4. Regression result for commercial installations.

	Total kW per Potential
Socio-economic cluster #2	−0.0062 (0.0217)
Socio-economic cluster #3	0.0033 (0.0199)
Socio-economic cluster #4	−0.0025 (0.0218)
Socio-economic cluster #5	0.0309 (0.0215)
Socio-economic cluster #6	−0.0076 (0.0237)
Socio-economic cluster #7	−0.0018 (0.0232)
Socio-economic cluster #8	−0.0274 (0.0245)
Socio-economic cluster #9	−0.0271 (0.0254)
Socio-economic cluster #10	−0.0560 . (0.0291)
Haifa District	−0.0058 (0.0113)
Jerusalem District	−0.0107 (0.0209)
Northern District	0.0250 ** (0.0094)
Southern District	0.0287 * (0.0117)
Tel Aviv District	−0.0325 * (0.0150)
Urban Area	−0.0597 *** (0.0088)
Majority group–Jewish	0.0658 *** (0.0104)
Observations	231
${\mathrm{R}}^2$	0.5454
$\mathrm{Adjusted} {\mathrm{R}}^2$	0.5114

The asterisks denote statistical significance as follows: *** p < 0.001, ** p < 0.01, * p < 0.05, . p < 0.1, with coefficients lacking symbols being non-significant at p ≥ 0.1.

). Both residential and commercial installations showed significantly higher adoption rates in the full model: in the Southern District (β = 0.0158, p < 0.001 for residential; β = 0.0287, p < 0.05 for commercial) and Northern District (β = 0.0108, p < 0.001 for residential; β = 0.0250, p < 0.01 for commercial), compared to the Central District. Although the districts of Jerusalem and Haifa initially showed lower adoption rates, these effects become non-significant in the full model, suggesting that their apparent disadvantage is better explained by other structural factors, particularly the urban–rural divide. However, Tel Aviv District maintained a significant negative effect in both installation types (β = −0.0121, p < 0.01 for residential; β = −0.0325, p < 0.05 for commercial), indicating that even after controlling for all other factors, Tel Aviv showed consistently lower adoption rates across both sectors.

The Southern District’s dominance aligns with geographic and climatic advantages: The district experiences the highest solar radiation levels in Israel and benefits from abundant land availability. However, the Northern District’s strong performance in both absolute numbers and regression coefficients is particularly noteworthy, as it receives comparatively less solar radiation. This unexpected finding suggests that factors beyond solar resource availability, such as local policy implementation, agricultural sector engagement, or regional economic initiatives, may influence adoption patterns.

Upon examination of demographic disparities, the descriptive statistics analysis showed disparities in solar PV adoption rates across Israel’s municipalities. Jewish-majority areas showed higher capacity per potential in residential installations (0.016 vs. 0.003 kW/potential) and in commercial installations (0.088 vs. 0.023 kW/potential) compared to Arab-majority areas. This apparent disparity was further highlighted by the distribution of municipalities with zero installations: Among municipalities with no residential installations, 38 out of 39 were Arab-majority areas, while for commercial installations, 22 out of 31 municipalities with zero adoption were Arab-majority areas (see Appendix B for a complete list).

These descriptive differences were further confirmed and clarified in the regression analysis. When other factors were controlled for in the full model, the demographic composition showed different levels of significance for the two installation types (residential: β = 0.0057, p < 0.10; commercial: β = 0.0658, p < 0.001). For residential installations, demographic composition showed a marginally significant effect, suggesting a modest but measurable advantage for Jewish-majority municipalities. This effect appears to be correlated with lower socioeconomic clusters (2–4), which lose significance when demographic variables are added, indicating overlap between socioeconomic and demographic factors in lower-income areas. For commercial installations, the demographic dimension was highly significant even after we controlled for all other factors, indicating a substantial effect.

Regarding structural inequalities, our analysis showed that urban–rural differences and socioeconomic status emerged as the most significant predictors of solar PV adoption, though their effects varied notably between residential and commercial installations. We began by examining the urban–rural divide. The descriptive statistics indicated a significant urban–rural divide in adoption rates (Table 2). Rural areas showed significantly higher installation rates across both sectors, with approximately three times the capacity per potential in commercial installations (0.134 vs. 0.045 kW/potential) and 1.6 times the capacity per potential in residential installations (0.016 vs. 0.010 kW/potential) compared to urban areas.

These patterns were further reinforced by additional spatial analysis mapping capacity per household, which illustrated the substantial difference between commercial and residential installations, with commercial installations showing markedly higher capacity levels per household (darker shading) (Figure 3).

The regression analysis revealed contrasting patterns for the urban–rural divide across installation types. For commercial installations, the urban–rural effect remained highly significant (β = −0.0597, p < 0.001), with rural areas maintaining a substantial advantage even after all other factors were controlled for. This means that moving from a rural to an urban municipality leads to a 5.97% decrease in commercial solar potential.

This commercial advantage aligned with Israel’s land distribution—approximately 80% agricultural land and only 20% urban—providing rural areas with substantially greater opportunities for large-scale commercial solar development. However, for residential installations, the urban–rural effect became non-significant (β = 0.0040, p > 0.10), indicating that whereas rural areas showed higher descriptive adoption rates, this advantage was primarily explained by socioeconomic composition rather than structural factors.

To understand these findings, it is crucial to examine Israel’s unique land policy context and the fundamental distinction between urban and rural lands. Rural communities benefit from greater land availability and a different land policy than that of the urban sector, encouraging them to team up with entrepreneurs to establish large-scale commercial projects [12,13,58]. These structural advantages manifest in several specific ways that facilitate solar PV adoption. Rural areas benefit from greater roof availability per household and simpler building ownership structures, reducing bureaucratic barriers to installation. Additionally, rural communities’ established experience in managing land resources and agricultural infrastructure probably lowers barriers to adopting new technologies like solar PV systems. The combination of favorable policy conditions and practical advantages helps explain the disproportionate adoption rates we observed in rural areas.

Examining solar PV adoption across socioeconomic clusters revealed distinct patterns that varied notably between residential and commercial installations. Descriptive statistics showed that residential installations displayed a clear positive correlation with socioeconomic status, with high-ranking clusters showing much higher capacity rates than low-ranking clusters (Table 2). For commercial installations, however, the pattern differed, with middle-ranking clusters showing the highest adoption rates, suggesting that commercial adoption was influenced by factors beyond socioeconomic status, as presented in Figure 4.

These patterns were further illuminated by the regression results. For residential installations, the relationship between socioeconomic status and adoption rates remained monotonic, robust and significant even after we controlled for all other factors, showing a clear pattern in which higher socioeconomic clusters consistently had higher adoption rates (Figure 5). This finding aligns with previous research in the field that has consistently demonstrated a strong relationship between socioeconomic status and solar panel adoption [29,30,35].

Residential installations indicate a clear upward trend: Wealthier municipalities consistently achieve higher solar adoption rates. The coefficient for cluster 10 is 0.042 and is highly statistically significant (p < 0.001), meaning that moving from cluster 1 to cluster 10 while holding all other characteristics constant leads to a 4.2% increase in residential solar potential utilization.

In contrast, commercial installations displayed a more complex pattern with no clear overall trend. Whereas initial models showed strong effects for middle-to-high socioeconomic clusters (particularly clusters 5–9), suggesting that these municipalities were more attractive to commercial solar investors, these effects became non-significant in the full model, suggesting that commercial adoption was more strongly influenced by geographic factors than by socioeconomic status.

To expand the analysis, we conducted additional year-by-year regressions, enabling us to examine the evolution of installation patterns throughout the study period. The year-by-year regression analysis yielded a significant insight not captured in the aggregated data (Figure 6).

In the full model for residential installations, the most affluent municipalities (cluster 10) showed a small but significant advantage over the poorest municipalities (cluster 1) in 2017. By 2021, this socioeconomic advantage increased dramatically by more than 17-fold, indicating that wealthy municipalities gained substantially more residential solar installations relative to poor municipalities over this four-year period. Similar, upward trends appeared across all higher socioeconomic clusters, with clusters 6–10 showing the strongest growth. Though only a few clusters showed significant growth in 2017, by 2021 nearly all higher clusters (5–10) showed highly significant effects (p < 0.01 or p < 0.001; Appendix C, Figure 6). Overall, these results indicate that socioeconomic disparities in residential installations widened substantially over time, with higher-status municipalities capturing a growing share of the benefits.

For commercial installations, the socioeconomic variable was not statistically significant in the year-by-year analysis, as shown in Figure 6. However, it was found that the urban–rural coefficient became increasingly dominant over time, growing substantially in magnitude from −0.0055 (p < 0.05) in 2017 to −0.0247 (p < 0.001) in 2021, indicating a dramatic strengthening of rural areas’ advantage (Figure 7). This pattern suggests that over time, structural spatial factors have become the primary determinant of commercial adoption.

To summarize, the findings indicated that socioeconomic status drives residential installation patterns, with disparities between socioeconomic clusters widening significantly over time. For commercial installations, the urban–rural divide remained the dominant factor, even after we controlled for other factors. Additionally, demographic composition emerged as a significant predictor for commercial installations, indicating that Jewish-majority municipalities maintained substantial advantages in accessing commercial solar development opportunities.

4. Discussion

Israel must transition to renewable energy to meet its long-term climate goals. Given the country’s abundant sunlight, solar power is an obvious choice: DRE has become a central pillar of Israel’s climate strategy [53], enabling households and businesses to become electricity producers and aligning with global trends toward decentralization and local empowerment. But although DRE offers the potential for broad social and economic benefits, it may fail to meet its potential because of socioeconomic barriers, and also risks exacerbating existing socioeconomic disparities [6,7,8].

This study examined rooftop solar photovoltaic (PV) adoption across Israeli municipalities to assess whether installation patterns reflect underlying socioeconomic inequalities. The findings show that PV benefits are not distributed equitably. Systematic disparities emerged in both residential and commercial sectors, though their drivers differed, raising important questions about the distributive implications of current policies.

For commercial installations, the urban–rural divide was the strongest predictor of adoption, reflecting structural inequalities embedded in Israel’s land regime. Roughly 80% of land is classified as rural and only 20% as urban [11]. Rural communities, which historically received land at little or no cost, now generate revenue from agriculture and solar resources [13,58]. Access to large land reserves—rather than to industrial zones in urban areas—remains the critical differentiator. These inequalities have been reinforced over time: The year-by-year analysis revealed an increasingly dominant urban–rural gap by 2021. This raises significant questions about distributive justice in renewable energy revenues, which lie beyond the scope of this article but warrant further research.

For residential installations, the findings are equally striking. Consistent with global patterns, socioeconomic status is monotonically related to adoption rates: Higher socioeconomic clusters exhibit substantially higher PV uptake. This relationship is not explained by differences in rooftop potential but reflects difficulties in achieving each municipality’s own technical potential. Even after controlling for geographic and demographic variables, the link between socioeconomic status and adoption remains robust, indicating structural barriers to equitable access. Moreover, CBS data show no correlation between the prevalence of single-family homes and municipal socioeconomic status [72], further underscoring the conclusion that disparities cannot be attributed to housing stock alone. Year-by-year analysis confirms that socioeconomic gaps in residential adoption widened markedly between 2017 and 2021, intensifying rather than narrowing as costs declined.

These findings are particularly noteworthy given Israel’s strong promotion of decentralized energy, increased public discourse on inequality, and declining installation costs. One might have expected solar adoption to become more inclusive over time; Instead, the opposite trend emerged, with affluent communities continuing to benefit disproportionately. Previous research has highlighted multiple factors contributing to such disparities, including information asymmetries, lack of awareness, limited administrative capacity, and the need for substantial upfront capital [15].

A spatial perspective adds nuance: Whereas descriptive statistics initially suggested rural advantages in residential adoption, regression analyses revealed these differences to be largely socioeconomic in nature rather than structural. Still, the persistent descriptive gaps between urban and rural adoption highlight practical obstacles that demand policy attention [2,15,55].

Finally, demographic composition emerged as a cross-cutting factor. In residential adoption, demographic variables explained part of the disadvantage among lower socioeconomic clusters, which are often Arab-majority areas. In commercial adoption, demographic effects were even more pronounced: Rural areas with Jewish-majority populations benefited disproportionately from solar installations. Together, these patterns illustrate how Israel’s spatial, socioeconomic, and demographic structures intersect to shape the distributive outcomes of the renewable energy transition.

5. Conclusions and Policy Recommendations

This study provides the first comprehensive empirical analysis of rooftop solar PV installation patterns across Israeli municipalities, addressing a critical gap in the understanding of DRE policy outcomes. Our findings demonstrate systematic disparities in adoption that differ between residential and commercial installations, shaped by the interplay of socioeconomic, spatial, and demographic factors. These patterns show that market-driven renewable energy adoption, even when supported by government policies, does not automatically meet its technical potential for generation or help generate equitable outcomes. Instead, since PV installation is financially profitable in the long run, existing inequalities are often reproduced and even intensified. The broader implication is clear: Achieving both environmental and social objectives in the energy transition requires explicit attention to equity and the overcoming of socioeconomic barriers to installation, rather than the assumption that equal utilization of the economic opportunity and the resulting distribution of the economic benefits will automatically emerge as a by-product of efficiency-driven policies.

Several limitations should be acknowledged. First, the analysis focuses on the period 2017–2022, constrained by data availability and consistency and possibly omitting longer-term dynamics. Second, the study examines only legally registered installations connected to the official grid, potentially excluding informal or unregistered systems. Third, although our potential metric accounts for physical constraints, additional factors—such as local policy variations, social networks, and community initiatives—may influence adoption patterns but are not captured here. Finally, the Israeli case is shaped by unique land ownership structures and policy frameworks, which may limit direct comparability to other national contexts, although the underlying socioeconomic dynamics are relevant for DRE transitions more broadly.

The policy implications of our findings are significant. For residential installations, the persistence and widening of socioeconomic disparities indicate that current mechanisms such as feed-in tariffs are insufficient to ensure broad demand. Additional policies are needed to address barriers such as access to financing, administrative complexity, or information gaps. Moreover, the prevalence of rental housing and multi-unit buildings in lower-income areas creates structural obstacles that individual incentives cannot overcome. These findings call for direct and targeted interventions that might include tailored finance, subsidies or tariffs for low-income households, financial literacy and awareness programs, regulatory reforms to facilitate installations in multi-family housing, and community-based solar initiatives that pool resources and decision-making power. Israel’s history of cooperative and community-based resource management provides a strong foundation for collective approaches that could democratize access to renewable energy.

For commercial installations, the dominance of rural areas reflects deeper structural inequalities in land distribution and access. Though this pattern may appear economically rational, it raises social and distributional concerns, because many rural communities historically received land at highly subsidized rates and now benefit disproportionately from solar revenues. However, technological advances are reducing barriers to high-capacity solar deployment in urban areas. Policy intervention here should focus less on direct subsidies and more on enabling conditions: fostering partnerships between municipalities and private firms, streamlining regulatory frameworks, and learning from international cases where urban commercial installations have flourished.

In sum, this study establishes the empirical foundation for integrating social equity into renewable energy policy design. Different installation types require differentiated strategies—direct interventions to overcome structural barriers in the residential sector and facilitative measures to unlock urban potential in the commercial sector. As countries worldwide accelerate DRE transitions, incorporating equity into policy design is essential to ensure that climate goals are achieved in ways that distribute benefits fairly across all segments of society.