While total solar PV capacity in Hungary was only 1 MW in 2010, this figure had grown to 7551 MW by 2024 as a result of the favorable settlement system, subsidies, and the uncertainty caused by the Russo-Ukrainian war. At that time, more than 6.4% of households were already prosumers. In our study, we focus on Hungarian districts, examining the spatial patterns of household-scale solar PV systems and the main drivers of technology adoption in 2024. We use the Theil T index to examine spatial heterogeneity and the Moran’s I statistic to test for spatial dependence. Spatial autocorrelation is further explored using maps based on Local Moran’s I and Local Geary statistics. Finally, a spatial error model is applied to identify the factors influencing the share of household-scale solar PV systems per 100 households. Our results show that the spatial error variable has the largest effect, with household education, the age and size of the building stock, population growth, and built-up area also having significant effects. This confirms the need for a spatially sensitive policy approach and for incorporating space and spatial relations in energy economic studies.
Tóth et al. (Wed,) studied this question.