Adoption of green electricity policies: Investigating the role of environmental attitudes via big data-driven search-queries. (March 2016)
- Record Type:
- Journal Article
- Title:
- Adoption of green electricity policies: Investigating the role of environmental attitudes via big data-driven search-queries. (March 2016)
- Main Title:
- Adoption of green electricity policies: Investigating the role of environmental attitudes via big data-driven search-queries
- Authors:
- Lee, Donghyun
Kim, Minki
Lee, Jungyoun - Abstract:
- Abstract: Despite the rising influence of public opinion on government energy policy formulation and implementation, the roles of pro and/or anti-environmental attitudes among residents have not been empirically examined. To quantify time-varying environmental attitudes among local residents, we exploit geo-specific Google search-query data derived from Internet-based "big data" and verify through ordinary least squares regression outcomes regarding environmental behavior. For the purpose of drawing policy implications, we revisit decisions by state governments of the United States to adopt three well-known green electricity policies: renewable energy portfolio, net metering rules, and public benefit funds. As some states have not yet adopted some (or any) of these policies, unlike previous studies, we handle the issue by examining right-censored data and applying a duration-based econometric method called the accelerated failure time model. We found state residents' environmental attitudes to have statistically significant roles, after controlling for other traditional time-varying policy adoption factors. Interestingly, the extent to which anti-environmental attitudes affect a state's policy adoption differs across green energy policies, and knowing this can help a local government formulate better-tailored environmental policy. In particular, researchers can use our method of incorporating citizens' environmental attitudes to discuss relevant issues in the field of energyAbstract: Despite the rising influence of public opinion on government energy policy formulation and implementation, the roles of pro and/or anti-environmental attitudes among residents have not been empirically examined. To quantify time-varying environmental attitudes among local residents, we exploit geo-specific Google search-query data derived from Internet-based "big data" and verify through ordinary least squares regression outcomes regarding environmental behavior. For the purpose of drawing policy implications, we revisit decisions by state governments of the United States to adopt three well-known green electricity policies: renewable energy portfolio, net metering rules, and public benefit funds. As some states have not yet adopted some (or any) of these policies, unlike previous studies, we handle the issue by examining right-censored data and applying a duration-based econometric method called the accelerated failure time model. We found state residents' environmental attitudes to have statistically significant roles, after controlling for other traditional time-varying policy adoption factors. Interestingly, the extent to which anti-environmental attitudes affect a state's policy adoption differs across green energy policies, and knowing this can help a local government formulate better-tailored environmental policy. In particular, researchers can use our method of incorporating citizens' environmental attitudes to discuss relevant issues in the field of energy policy. … (more)
- Is Part Of:
- Energy policy. Volume 90(2016)
- Journal:
- Energy policy
- Issue:
- Volume 90(2016)
- Issue Display:
- Volume 90, Issue 2016 (2016)
- Year:
- 2016
- Volume:
- 90
- Issue:
- 2016
- Issue Sort Value:
- 2016-0090-2016-0000
- Page Start:
- 187
- Page End:
- 201
- Publication Date:
- 2016-03
- Subjects:
- Green electricity policy -- Citizens' environmental attitude -- Accelerated failure time model -- Google search-query
Energy policy -- Periodicals
Politique énergétique -- Périodiques
Electronic journals
333.79 - Journal URLs:
- http://www.sciencedirect.com/science/journal/03014215 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.enpol.2015.12.021 ↗
- Languages:
- English
- ISSNs:
- 0301-4215
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3747.720000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 2609.xml