Preference heterogeneity for renewable energy technology

Abstract

This study explores heterogeneity in individual willingness to pay (WTP) for a public good using several different variants of the multinomial logit (MNL) model for stated choice data. These include a simple MNL model with interaction terms between respondent characteristics and attribute levels, a latent class model, a random parameter (mixed) logit model, and a hybrid random parameter-latent class model. The public good valued was an increase in renewable electricity generation. The models consistently show that preferences over renewable technologies are heterogeneous among respondents, but that the degree of heterogeneity differs for different renewable technologies. Specifically, preferences over solar power appear to be more heterogeneous across respondents than preferences for other renewable technologies. Comparing across models, the random parameter logit model and the hybrid random parameter-latent class model fit the choice data best and did the best job capturing preference heterogeneity.