ABSTRACT
Japan experienced a surge in renewable power plant construction since adopting the Feed-in Tariff policy in 2012. But why did some municipalities choose to adopt more renewables than others? Do technical resources explain the difference, or might socioeconomics, social capital, and local policy also serve as motivations, resources, or obstacles? Using zero-inflated negative binomial and Conway Maxwell Poisson regression, the effects of technical and social variables on renewables siting for all municipalities in Japan are modeled, and compared with survey results from a sample of 56. Municipalities with high unemployment and cheap land are especially likely to host solar, wind, and biomass and have greater energy system redundancy. Those with stronger bonding social ties are more likely to host wind, contrary to predictions, and cities that invested early in reducing greenhouse gas emissions are more likely to deploy solar.
Disclosure statement
No potential conflict of interest was reported by the author.
Notes
1. Municipalities, including cities (shi), urban wards (ku), towns (chō), and villages (son) are examined. The terms ‘municipality’ and ‘city’ are here used interchangeably.
2. See my R code in the data repository, which tests other model types.
3. The multiple imputation process and all models can be replicated using the seed code in my R code and the supplementary data package. Rural, poorer towns tended to lack residential land prices, financial strength index, and emissions data, perhaps because governments lack resources to collect it annually. The imputation process drew on variation in data on population, income per capita, unemployment, and area to generate appropriate values for missing data given this pattern (King et al, Citation2001: 57).