| At present 37 U.S. states have passed Renewable Portfolio Standards (RPS) or have a legislative driven goal that supports investment in renewable energy (RE) technologies. Previous research has identified economic, governmental, ideological and infrastructural characteristics as key predictors of policy adoption and renewable energy deployment efforts (Carley, 2009; Davis & Davis, 2009; Bohn & Lant, 2009; Lyon & Yin, 2010). To date, only a few studies have investigated the target levels of renewable portfolio standards. Carley & Miller (2012) found that policies of differing stringencies were motivated by systematically different factors that included governmental ideology. The purpose of this dissertation is to replicate and expand upon earlier models that predicted RPS adoption and RE deployment efforts by adding regulatory, infrastructural and spatial characteristics to predict RPS target levels. Hypotheses were tested using three alternative measurements of RPS target level strength to determine to what extent a combination of explanatory variables explain variation in policy target levels. Multivariate linear regression and global spatial autocorrelation results indicated that multiple state internal determinants influenced RPS target level including average electricity price, state government ideology and to a lesser extent actual RE potential capacity. In addition, some diffusion effects were found to exist that indicated that states are setting their RPS target levels lower than their neighboring states and a local geo-spatial clustering effect was observed in the target levels for a grouping of northeastern states. |
