Renewable Energy and Territory: Perceptions of Wind and Solar Deployment in Spain

The experiment includes two information treatments delivered through short videos of less than two minutes. Treatment A provides information about the unequal territorial distribution of wind and solar facilities in Spain. It explains that renewable-energy installations are disproportionately located in rural and sparsely populated municipalities, where suitable land and renewable resources are available, while much of the electricity generated is consumed elsewhere, particularly in urban areas. The treatment emphasizes that local impacts, including landscape change and land use, are geographically concentrated in host communities, whereas the broader benefits of renewable energy, such as electricity generation and lower emissions, are shared more widely.

Treatment B provides the same information as Treatment A and additionally explains that hosting renewable-energy facilities can generate economic resources for local communities. In particular, it describes municipal revenues from taxes and other project-related payments, as well as compensation and benefit-sharing mechanisms through which part of the value generated by renewable-energy projects can be returned to host municipalities.

The control group receives no additional information on the territorial distribution or local economic consequences of renewable-energy deployment.

2026-09-04

2026-09-14

Willingness to accept a new wind or solar facility in the respondent’s municipality or in a nearby municipality. The outcome is elicited on an ordered five-point response scale and coded so that higher values indicate greater willingness to accept the facility. The main analysis uses the original response scale. We will additionally construct a binary version equal to one for responses indicating acceptance and zero for neutral or negative responses.

Secondary outcomes comprise four groups. First, posterior beliefs about the territorial concentration of wind and solar installations and beliefs about whether renewable-energy projects can generate additional revenues, compensation, or other resources for host municipalities. Second, perceived unfairness of the current territorial distribution of renewable-energy installations. Third, policy preferences, including perceived effectiveness and fairness of, and support for, a public green-infrastructure programme; support for additional public spending on renewable-energy deployment; an urban electricity-bill surcharge to compensate rural host municipalities; greater renewable-energy generation in urban areas; and procedural safeguards for communities affected by new installations. Fourth, political outcomes measuring respondents’ willingness to support three hypothetical party platforms proposing alternative approaches to renewable-energy deployment, local compensation, and territorial justice. Where the response scales permit a substantively meaningful distinction, we will also analyze pre-specified binary versions distinguishing favorable from neutral or unfavorable responses.

We conduct an online randomized information-provision experiment with approximately 2,000 respondents recruited from the Netquest online panel. Eligibility is restricted to Spanish nationals residing in Spain and aged 18–64. Sampling quotas are applied by gender, age, and region of residence. The design deliberately oversamples respondents living in municipalities with fewer than 5,000 inhabitants, targeting 750 such respondents (37.5% of the total sample).

Respondents are randomly assigned at the individual level, in approximately equal proportions within gender-by-age quota cells, to one of three experimental conditions. Rural residence is not used as a blocking variable. The Control group receives no additional information relevant to the territorial distribution of renewable energy. Treatment A receives a short information video describing the unequal territorial distribution of wind and solar facilities in Spain, emphasizing their concentration in rural and sparsely populated municipalities and the geographically concentrated local impacts of renewable-energy infrastructure. Treatment B receives the same information and additionally receives information about municipal revenues, project-related payments, compensation, and benefit-sharing mechanisms that may return resources to host communities.

All respondents complete the same pre-treatment questions before experimental assignment and the same post-treatment outcome modules after their assigned experimental condition. The main experimental comparisons are Treatment A versus Control, Treatment B versus Control, and Treatment B versus Treatment A.

Respondents are randomly assigned at the individual level, in approximately equal proportions, to one of three experimental conditions: Control, Treatment A, or Treatment B. Randomization is conducted within gender-by-age quota cells.

Individual respondent

No

N/A - treatment is randomized at the individual respondent level

2000 individual respondents

~667 in the Control group
~667 in Treatment A
~667 in Treatment B

For the main full-sample treatment-control contrasts, the design has a minimum detectable effect of approximately 0.10 standard deviations at 80% power and a 5% two-sided significance level. The calculation assumes a total sample of 2,000 respondents, approximately equal assignment across the three experimental arms, 750 rural respondents, and that pre-treatment covariates explain approximately 20% of the outcome variance. For comparison, the corresponding MDE is approximately 0.24 standard deviations within the rural subsample and 0.12 standard deviations for the nationally weighted estimand. The MDE for rural-by-treatment interactions is substantially larger, approximately 0.29 standard deviations.

Renewable Energy and Territory: Perceptions of Wind and Solar Deployment in Spain