The importance of regret minimization in the choice for renewable energy programmes: Evidence from a discrete choice experiment

Marco Boeri and Alberto Longo

Energy Economics, 2017, vol. 63, issue C, 253-260

Abstract: This study provides a methodologically rigorous attempt to disentangle the impact of various factors – unobserved heterogeneity, information and environmental attitudes – on the inclination of individuals to exhibit either a utility maximization or a regret minimization behaviour in a discrete choice experiment for renewable energy programmes described by four attributes: greenhouse gas emissions, power outages, employment in the energy sector, and electricity bill. We explore the ability of different models – multinomial logit, random parameters logit, and hybrid latent class – and of different choice paradigms – utility maximization and regret minimization – in explaining people's choices for renewable energy programmes. The “pure” random regret random parameters logit model explains the choices of our respondents better than other models, indicating that regret is an important choice paradigm, and that choices for renewable energy programmes are mostly driven by regret, rather than by rejoice. In particular, we find that our respondents' choices are driven more by changes in greenhouse gas emissions than by reductions in power outages. Finally, we find that changing the level of information to one attribute has no effect on choices, and that being a member of an environmental organization makes a respondent more likely to be associated with the utility maximization choice framework.

Keywords: Random Regret Minimization; Random Utility Maximization; Renewable energy; Greenhouse gas emissions; Discrete choice experiments (search for similar items in EconPapers)
JEL-codes: Q42 Q51 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (16)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:63:y:2017:i:c:p:253-260

DOI: 10.1016/j.eneco.2017.03.005

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