Community solar is showing a rapid growth trajectory across the nation. It is expected to increase by 700% to meet the Department of Energy’s goal of providing enough community solar to power five million homes by 2025. Federal and state governments programs committed to clean and solar energy are driving the expansional use of community solar energy in the U.S. Regardless of technical or policy challenges, the consumer demand for solar energy –and community solar in particular, is steadily growing. To measure consumers’ demand and attitudes toward community solar we, at Zpryme, conducted a public survey.

The results of the survey were recently released in our infographic on public attitudes towards community solar. Solar energy in general is viewed with skepticism. Nearly 27% of respondents are neutral and 40% don’t trust solar energy as a reliable source to power their homes. This is understandable, as solar energy is a great source of clean and affordable energy, yet its availability is subject to weather conditions and sun exposure. However, those results raise question about how different age groups view solar energy. Because while the majority of the population does not use solar power at all, most of those who do use solar power own or lease their solar power. So there is hypothetically a strong relationship between home ownership and a positive view of solar energy as a reliable source of energy. Essentially, the question here is whether or not there is a relationship between age, income, home ownership and trust in solar energy?

Here, I take a deeper dive into the data from our above mentioned infographic to test how the above mentioned variables (age, income, and home ownership) affect the perception of solar energy. To test the relationship of income, age and home ownership I ran a generalized linear regression model. The variable trust measures the respondent’s trust in solar energy as a source to power their home on a scale of 1-5 where 1 is the lowest level of trust and 5 is the highest.

The results show that trust in solar energy increases, on average, by 0.95 units when the respondent own their home. In other words, people who own their homes are more likely to positively view solar energy and trust it as a reliable source of energy. When I control for income, trust in solar energy as a source of energy to power a household positively changes, on average, by 0.85 units when the respondent is a home owner. In this case, income does not have a significant impact on the relationship between trust in solar energy and home ownership. On the other hand, there is also a significant relationship between income and trust in solar energy. Specifically when a person’s income is $20,000/year or less their trust in solar energy is decreased by, on average, 1.43 units. Interestingly, when the respondent’s annual income is $100,000 or more, trust is solar energy also decreases, on average, by 0.73 units. When a respondent’s income falls within the range $35,000 – $49,999 their trust in solar energy decreases, on average, by 0.26. When income is between $50,000 – $74,000 trust in solar energy drops, on average, by only 0.09 units, whereas if the annual income is between $75,000 – $99,999 trust, on average, drops even further to -1.05 units.

In the second model I test the relationship between trust in solar energy and age. The results show that trust in solar energy increases for people between the ages of 25-34 by 0.53 units, on average, and that trust only increases, on average, by 0.34 units when the respondent is between 35-44 years old, 0.77 units when the respondent is between the ages 45-54, 0.57 units when respondent is between 55-64 years old, and 0.47 units at age 65+.

The results confirm a relationship between home ownership and positive attitudes toward solar energy and a relationship between annual income and perceptions on solar energy, though only home ownership and an income of <$20,000 showed statistical significance. Additionally, the results do not show a statistically significant relationship between age and trust in solar energy.

While the data is not without limitations, as the sample size is relatively small and the data, including age is collected and recorded as categorical variables as opposed to continuous variables, which may have affected the outcome of the analysis, the results show that it is worth exploring the effects of age, income, and home ownership on trust in solar energy with more robust data and accurate measures of age and income. And while most of the results of the regression analysis are statistically insignificant, the results offer practically significant insights into different factors that might affect public perception of solar energy that could potentially guide policy and educational efforts on the subject.