Abstract
Combustion of fossil fuels is the major source of energy in the United States and around the world. The combustion causes emission of greenhouse gases and particle pollution, which leads to health hazards. As people become increasingly conscious of their carbon footprints, they may choose to reduce their energy consumption using a variety of energy-saving technologies. We design a context-rich incentivized decision-making experiment in a laboratory set-up. The decision scenario has been enriched with elements of a public good, risk, and intertemporal discounting. Each subject represents a household and decides how much to spend on energy-saving technologies that can reduce future energy costs and emissions. The reduction in emission decreases health risk and medical costs for an individual and everyone else in the group. Discounting is represented by the ability to save, with interest. Each subject plays three sections (baseline, a treatment, and a repeated baseline). Each section had 30 rounds. The treatment has a threshold public good feature of energy-savings. The emission tax level depends on the aggregate energy-savings. Subjects exhibit significant learning effect and tend to increase adoption rate of energy-saving technologies over time. The adoption rate significantly improves when subjects can reduce their emission tax obligations by decreasing their energy consumption. There is no evidence of significant change in behavior when subjects learn energy-saving choices made by other group members.
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Notes
Please visit https://www.eia.gov/energyexplained/us-energy-facts/ for U.S. energy facts.
We have consulted with a number of staff from Miami-Dade County who run different energy efficiency programs [e.g., Property Assessed Clean Energy (PACE) program] to encourage homeowners, businesses, and industries for installing energy-saving upgrades at the local level. We have also consulted with several faculties from universities who work on engineering and management aspects of energy efficiency. We have considered their inputs; however, the final decisions in the experimental design were made by us.
Subjects do not observe the decisions and/or the outcomes of other group members in Experiment 1. They may form expectations about other’s behavior based on how often they experience sickness events. Hence, there is negligible or no concern for within-session inter-subject collaboration.
Information available at: https://data.census.gov/cedsci/profile?g=0500000US12086
For detail report, please see: https://www.bls.gov/regions/southeast/news-release/consumerexpenditures_miami.htm
Please see the report: https://www.eia.gov/electricity/sales_revenue_price/pdf/table5a.pdf?kbid=118190
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Acknowledgements
We acknowledge support from the National Science Foundation (Award #1204762, #1832693) and Florida Division of Emergency Management (DEM). We are also thankful to subjects who participated in the experimental sessions, and to the conference attendees who provided comments at the North American Meetings of the Economic Science Association, Canadian Economics Association, and Western Economic Association. However, the opinions expressed here solely belong to us.
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Appendix
Appendix
1.1 (A) Medical emergency, allied expenses, and benefit from reduction in energy bill
Probability of Medical Emergency = P (Medical Emergency) = 0.60.
Probability of Negligible Medical Emergency.
= P (Negligible Medical Emergency/Medical Emergency)
= P (Negligible Medical Emergency) x P (Medical Emergency) = 0.50x0.60 = 0.3
Probability of Minor Medical Emergency.
= P (Minor Medical Emergency/Medical Emergency)
= P (Minor Medical Emergency) x P (Medical Emergency) = 0.47x0.60 = 0.282
Probability of Major Medical Emergency.
= P (Major Medical Emergency/Medical Emergency)
= P (Major Medical Emergency) x P (Medical Emergency) = 0.03x0.60 = 0.018
Average medical expense of ‘Negligible Medical Emergency’ = $0.
Average medical expense of ‘Minor Medical Emergency’ = $3000.
Average medical expense of ‘Major Medical Emergency’ = $35,000.
Expected medical expense of every subject.
= ($0 x 0.3 + $3000 x 0.282 + $35,000 x 0.018)/round
= $1476/round
Probability of medical emergency decreases by 1% for every $200 decrease in energy bill. Therefore, expected medical expense of every subject per round decreases by ($1476/60) = $24.6.
1.2 (B) Individual and group (8 subjects/session) benefit of short-term energy-saving choices
Private benefit of EEL (per round) = Reduction in energy bill + Reduction in expected medical expenses = $60 + (60/200) x $24.2 = $67.26
Group benefit of EEL (per round) = Reduction in energy bill + Reduction in group’s total expected medical expenses = $60 + (60/200) x 8 x $24.2 = $118.08
Private benefit of ECB (per round) = Reduction in energy bill + Reduction in expected medical expenses = $140 + (140/200) x $24.2 = $156.94
Group benefit of ECB (per round) = Reduction in energy bill + Reduction in group’s total expected medical expenses = $140 + (140/200) x 8 x $24.2 = $275.52.
1.3 (C) Discounted present value of private and group (8 subjects/session) benefit of long-term energy-saving choices
Discount Rate = d = 1/(1+Rate of Interest) = 1/1.03 =0.97
Discounted present value of private benefits of GHP = Discounted present value of reduction in energy bill + Discounted present value of reduction in expected medical expenses = \(\left(\frac{1-{d}^{30}}{1-d}\right)\){$200 + (200/200) x $24.2} = 20.19 x $224.2 = $4526.60.
Discounted present value of social benefit of GHP (per round) = Reduction in energy bill + Reduction in group’s total expected medical expenses = \(\left(\frac{1-{d}^{30}}{1-d}\right)\){$200 + (200/200) × 8 x $24.2} = 20.19 x $393.6 = $7,946.78.
Discounted present value of private benefits of RWT = Discounted present value of reduction in energy bill + Discounted present value of reduction in expected medical expenses = \(\left(\frac{1-{d}^{30}}{1-d}\right)\){$200 + (200/200) x $24.2} = 20.19 x $224.2 = $4526.60.
Discounted present value of social benefit of RWT (per round) = Reduction in energy bill + Reduction in group’s total expected medical expenses = \(\left(\frac{1-{d}^{30}}{1-d}\right)\){$200 + (200/200) × 8 x $24.2} = 20.19 x $393.6 = $7946.78.
Discounted present value of private benefits of RSES = Discounted present value of reduction in energy bill + Discounted present value of reduction in expected medical expenses = \(\left(\frac{1-{d}^{30}}{1-d}\right)\){$400 + (400/200) x $24.2} = 20.19 x $448.4 = $9053.20.
Discounted present value of social benefit of GHP (per round) = Reduction in energy bill + Reduction in group’s total expected medical expenses = \(\left(\frac{1-{d}^{30}}{1-d}\right)\){$400 + (400/200) × 8 x $24.2} = 20.19 x $787.2 = $15,893.57.
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Chatterjee, C., Halim, N. & Mozumder, P. Energy conservation and health risk reduction: an experimental investigation of punishing vs. rewarding incentives. Environ Econ Policy Stud 24, 551–570 (2022). https://doi.org/10.1007/s10018-021-00337-3
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DOI: https://doi.org/10.1007/s10018-021-00337-3