A Review of Willingness to Pay Studies for Climate Change Mitigation in the Energy Sector
Abstract
:1. Introduction
- What are the main methods applied for assessment of WTP for climate change mitigation across different countries?
- What are the main drivers of WTP for climate change mitigation in different countries?
- What kind of policy measures can be applied to increase WTP for climate change mitigation?
2. Methods
3. The Background for Assessment of Willingness to Pay for Climate Change Mitigation
4. Methods for Assessment of WTP for Climate Change Mitigation in Households
5. WTP Studies for Renewables in Households
6. WTP for Energy Efficiency Improvements in Households
7. Discussion of Results
8. Conclusions and Future Research
Author Contributions
Funding
Conflicts of Interest
References
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Study | Type of Analysis to Assess Respondents WTP | Target Segments | Target Renewable Source Technology/Electricity Services | State/Region | Model Estimating WTP | |
---|---|---|---|---|---|---|
1. | (Wood et al., 1995) [66] | CA | Residential, small and large commercial and industrial consumers | Different energy balances for electricity generation | Probit model | |
2. | (Hanley & Nevin, 1999) [73] | Direct contingent valuation | Remote community | Wind mills, small-scale hydro scheme and biomass development | None (stated WTP) | |
3. | (Roe et al., 2001) [75] | CA | Households | Residential electricity services | Linear model | |
Hedonic pricing | Households | Residential electricity services | Hedonic regression (linear ordinary least squares) | |||
4. | (Nomura & Akai, 2004) [52] | Direct contingent valuation | Residents from large cities (owners of telephone) | Electricity generated from photovoltaic and wind power systems | None (stated WTP) | |
5. | (Ek, 2005) [76] | CE | House owners | Hydro, biomass, solar and wind | Probit model | |
6. | (Borchers et al., 2007) [78] | CE | New Castle County, DE, USA | Different renewable energy programs | Non-linear probability model | |
7. | (Bergmann et al., 2008) [79] | CE | Rural and urban households | Hydro, on-shore and off-shore wind and biomass production | Logit model | |
8. | (Longo et al., 2008) [80] | CE | Residents of Bath | Hypothetical program that promotes RE production | Random utility model | |
9. | (Banfi et al., 2008) [61] | CE | House owners and apartment tenants | Air renewal (ventilation) systems for energy saving | Logit model | |
10. | (Bollino, 2009) [85] | CVM | Households | Electricity generated from RES | Probit model | |
11. | (Zografakis et al., 2010) [81] | CVM | Residents of Crete | RES project | Logistic regression | |
12. | (Scarpa & Willis, 2010) [86] | CE | Households | Solar photo-voltaic, micro-wind, solar thermal, heat pumps, biomass boiler and pellet stoves | Logit model | |
13. | (Claudy et al., 2011) [62] | CVM | Residents | Wood pellet boilers, small wind turbines, solar panels, solar water heaters | Probit model | |
14. | (Zorić & Hrovatin, 2012) [82] | CE | Residents | Electricity generated from RES | Tobit model | |
15. | (Aravena, Hutchinson & Longo, 2012) [87] | CVM | Residents | Electricity generated from RES | Discrete choice random utility model | |
16. | (Kosenius & Ollikainen, 2013) [72] | CE | Residents | Wind power, hydro power, energy from crops and wood | Logit model | |
17. | (Guo et al., 2014) [83] | CVM | Residents of Beijing | Electricity generated from RES | Logit model | |
18. | (Bigerna & Polinori, 2014) [28] | CVM | Households | Electricity generated from RES | Logistic regression | |
19. | (Štreimikienė & Baležentis, 2014) [59] | Direct contingent valuation | Households | Electricity degenerated from | Non-parametric regression | |
20. | (Oberst & Madlener, 2014) [88] | CE | Households | Wind power, solar power, biomass | Logit model | |
21. | (Akcura, 2015) [84] | CVM | Households | Electricity generated from RES | Probit model | |
22. | (Chan, Oerlemans & Volschenk, 2015) [89] | CVM | Households | Electricity generated from RES | Tobit model | |
23. | (Dagher & Harajli, 2015) [90] | CVM | Residents | Electricity generated from RES | Tobit model | |
24. | (Grilli, Balest, Garegnani & Paletto, 2015) [91] | CVM | Residents | Hydro power, biomass | Tobit model | |
25. | (Yamamoto, 2015) [92] | Direct contingent valuation | Households with PV-systems adoption | Photovoltaic system | None (stated WTP) | |
26. | (Kwon et al, 2015) [93] | CVM | Residents | Renewable energy | Regression model | |
27. | (Morita & Managi, 2015) [94] | CA | Residents | Electricity generated from solar and wind power | Logit model | |
28. | (Sun, Yuan & Xu, 2015) [95] | CVM | Households | Smog mitigation | Probit model and interval regression | |
29. | (Vecchiato & Tempesta, 2015) [96] | CE | Residents of Veneto | Different renewable energy mixes | Logit model | |
30. | (Lee & Heo, 2016) [97] | CVM | Residents | Electricity generated from solar and wind power | Logistic regression |
Determinants | Health Effects | Environmental Effects | Political Views | Gender | Marital Status | Education | Age | Vacancies | Income | Equipment Use Restrictions | Price | Contract Terms | Race | Environmental Organization Affiliation | Geographical Place of Residence | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Study | ||||||||||||||||
(Wood et al., 1995) [66] | * | * | * | * | ||||||||||||
(Roe et al., 2001) [75] | * | * | * | * | * | * | * | * | * | * | ||||||
(Ek, 2005) [76] | * | * | * | * | ||||||||||||
(Borchers et al., 2007) [78] | * | * | * | |||||||||||||
(Bergmann et al., 2008) [79] | * | * | * | * | * | * | ||||||||||
(Longo et al., 2008) [80] | * | * | * | * | * | * | * | * | ||||||||
(Bollino, 2009) [85] | * | * | * | * | * | * | ||||||||||
(Claudy et al., 2011) [62] | * | * | * | |||||||||||||
(Zorić & Hrovatin, 2012) [82] | * | * | * | * | * | * | * | |||||||||
(Aravena et al., 2012) [87] | * | * | * | * | * | |||||||||||
(Kosenius & Ollikainen, 2013) [72] | * | * | * | * | * | * | ||||||||||
(Guo et al., 2014) [83] | * | * | * | * | * | |||||||||||
(Bigerna & Polinori, 2014) [28] | * | * | * | * | ||||||||||||
(Štreimikienė & Baležentis, 2014) [59] | * | * | * | * | * | |||||||||||
(Oberst & Madlener, 2014) [88] | * | * | * | * | * | * | ||||||||||
(Akcura, 2015) [84] | * | * | * | * | ||||||||||||
(Chan et al., 2015) [69] | * | * | * | * | ||||||||||||
(Dagher & Harajli, 2015) [90] | * | * | * | * | * | * | * | * | * | |||||||
(Grilli et al., 2015) [91] | * | * | * | * | * | |||||||||||
(Yamamoto, 2015) [92] | * | * | * | * | ||||||||||||
(Kwon et al., 2015) [93] | * | * | * | |||||||||||||
(Morita & Managi, 2015) [94] | * | * | * | * | ||||||||||||
(Sun et al., 2015) [95] | * | * | ||||||||||||||
(Vecchiato & Tempesta, 2015) [96] | * | * | * | |||||||||||||
(Lee & Heo, 2016) [97] | * | * | * | * |
Attributes | Capital Cost | Installation Cost | Investment Risk | Maintenance Cost | Payback Period | Net Electricity Cost (or Monthly Electricity Bill) | Annual Energy Saving | Recommended by | CO2 Reduction (Contribution to Climate Protection) | Degree of Electricity Self-supply | Social Impacts (e.g., Create New Local Employment) | Contract Length | Air Pollution | Landscape Impact | Wildlife Impact | Annual Length of Electricity Shortages | Certification of Origin | Minimum Distance from Houses | Size of the Installed Device | Inconvenience of System | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Study | |||||||||||||||||||||
(Borchers et al., 2007) [78] | * | * | |||||||||||||||||||
(Bergmann et al., 2008) [79] | * | * | * | * | * | ||||||||||||||||
(Longo et al., 2008) [80] | * | * | * | * | |||||||||||||||||
(Scarpa & Willis, 2010) [86] | * | * | * | * | * | * | * | ||||||||||||||
(Kosenius & Ollikainen, 2013) [72] | * | * | * | * | |||||||||||||||||
(Oberst & Madlener, 2014) [88] | * | * | * | * | * | * | * | ||||||||||||||
(Vecchiato & Tempesta, 2015) [96] | * | * | * | * |
No. | Study | Type of Analysis to Assess Respondents WTP | Target Segments | Target of Assessment | State/Region | Model Estimating WTP |
---|---|---|---|---|---|---|
1. | Newell et al., 1999; [121] | CVA | Households | Energy appliances with energy labelling | Tobit model | |
2. | Silvia Banfi et al., 2008 [61] | CE | Resident | Energy-saving measures in residential buildings (Window, Facade, Ventilation, Price) | Fixed-effects logit model | |
3. | Peter Grosche and Colin Vance, 2009 [144] | Survey | Household | Financial support for Home renovations. (Free-riding) roof, facade, windows, heating-equipment | Logit model | |
4. | Alberto Longo et al., 2015 [80] | CVM; SP | Household | General public for climate change mitigation programmes | Probit model | |
5. | Reynolds et al. (2012) [126] | CVA | Residential | Fluorescent light bulbs | Tobit model | |
6. | Andreas Wiencke, 2013 [147] | CE | Corporations | Green buildings | Tobit model | |
7. | Agnieszka Zalejska-Jonsson, 2014 [141] | CE | Household | Green buildings | Quasi-experimental method | |
8. | Julia Blasch et al., 2017 [137] | CE | Household | Energy-efficient household appliances | Probit model; bivariate probit model | |
9. | Marco Ferreira et al., 2017 [142] | IEA EBC Annex 56 project and using the case-studies provided | Building renovation | The crossed-analysis | ||
10. | Anna Alberini et al., 2018 [22] | CAWI (Computer-assisted web interviewing) | Household | Policies seeking to reduce CO2 | Random utility model (RUM) | |
11. | Matthew Collins and John Curtis, 2018 [140] | CE | Household | Grants available for various energy efficiency measures (Free-riding) (roof/attic insulation, wall insulation, and solar collector installation) | McFadden’s random utility model | |
12. | Nan Liu et al., 2018 [138] | Transaction data of private residential property | Private rented housing sector (tenants) | WTP for energy efficiency in the private rented housing sector during economic recessions | Hedonic regression models | |
13. | Marko Matosovic and Željko Tomšic, 2018 [146] | Discrete choice model | Households | Energy efficiency measures among households | Multinomial and nested logit models | |
14. | Boris A. Portnov et al., 2018 [145] | CVM | Homebuyers | Price premium for green buildings | Multiple regression analysis | |
15. | Ben Chak-Man Leung, 2018 [143] | Pilot test | Public housing | Effectively greening the existing Buildings (GEB) |
Determinants | Health Effects | Environmental Effects | Political Views | Gender | Marital Status | Education | Age | Vacancies | Income | Equipment Use Restrictions | Price | Contract Terms | Environmental Organization Affiliation | Geographical Place of Residence | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Study | |||||||||||||||
Silvia Banfi et al., 2008 [61] | * | * | * | * | |||||||||||
Peter Grosche and Colin Vance, 2009 [144] | * | ||||||||||||||
Alberto Longo et al., 2011 [80] | * | * | * | * | |||||||||||
Yue et al. (2013) [125] | * | * | * | * | |||||||||||
Hori et al. (2013) [127] | * | * | * | * | * | * | * | * | * | ||||||
Andreas Wiencke, 2013 [147] | * | * | |||||||||||||
Agnieszka Zalejska-Jonsson, 2014 [141] | * | * | * | * | |||||||||||
Julia Blasch et al., 2017 [137] | * | * | * | * | |||||||||||
Marco Ferreira et al., 2017 [142] | * | * | |||||||||||||
Anna Alberini et al., 2018 [22] | * | * | * | * | |||||||||||
Matthew Collins and John Curtis, 2018 [140] | * | * | |||||||||||||
Nan Liu et al., 2018 [138] | * | ||||||||||||||
Marko Matosovic and Željko Tomšic, 2018 [146] | * | * | * | * | |||||||||||
Boris A. Portnov et al., 2018 [145] | * | * | * | * | * | * | * | * | * | ||||||
Ben Chak-Man Leung, 2018 [143] | * | * |
Attributes | Capital Cost | Installation Cost | Investment Risk | Maintenance Cost | Payback Period | Annual Energy Saving | CO2 Reduction (Contribution to Climate Protection) | Social Impacts (e.g., Create New Local Employment) | Air Pollution | Inconvenience of System | Financial Incentives/Grants | |
---|---|---|---|---|---|---|---|---|---|---|---|---|
Study | ||||||||||||
Silvia Banfi et al., 2008 [61] | * | * | * | |||||||||
Peter Grosche and Colin Vance, 2009 [144] | * | * | * | * | ||||||||
Alberto Longo et al., 2011 [80] | * | |||||||||||
Hori et al. (2013) [127] | * | * | * | |||||||||
Andreas Wiencke, 2013 [147] | * | * | * | |||||||||
Agnieszka Zalejska-Jonsson, 2014 [141] | * | * | * | |||||||||
Julia Blasch et al., 2017 [137] | * | * | * | |||||||||
Marco Ferreira et al., 2017 [142] | * | * | * | |||||||||
Anna Alberini et al., 2018 [22] | * | * | * | |||||||||
Matthew Collins and John Curtis, 2018 [120] | * | * | * | |||||||||
Nan Liu et al., 2018 [138] | * | |||||||||||
Marko Matosovic and Željko Tomšic, 2018 [146] | * | * | * | |||||||||
Boris A. Portnov et al., 2018 [145] | * | * | * | * | ||||||||
Ben Chak-Man Leung, 2018 [143] | * | * | * | * | * |
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Streimikiene, D.; Balezentis, T.; Alisauskaite-Seskiene, I.; Stankuniene, G.; Simanaviciene, Z. A Review of Willingness to Pay Studies for Climate Change Mitigation in the Energy Sector. Energies 2019, 12, 1481. https://doi.org/10.3390/en12081481
Streimikiene D, Balezentis T, Alisauskaite-Seskiene I, Stankuniene G, Simanaviciene Z. A Review of Willingness to Pay Studies for Climate Change Mitigation in the Energy Sector. Energies. 2019; 12(8):1481. https://doi.org/10.3390/en12081481
Chicago/Turabian StyleStreimikiene, Dalia, Tomas Balezentis, Ilona Alisauskaite-Seskiene, Gintare Stankuniene, and Zaneta Simanaviciene. 2019. "A Review of Willingness to Pay Studies for Climate Change Mitigation in the Energy Sector" Energies 12, no. 8: 1481. https://doi.org/10.3390/en12081481
APA StyleStreimikiene, D., Balezentis, T., Alisauskaite-Seskiene, I., Stankuniene, G., & Simanaviciene, Z. (2019). A Review of Willingness to Pay Studies for Climate Change Mitigation in the Energy Sector. Energies, 12(8), 1481. https://doi.org/10.3390/en12081481