Growing literature points to the effectiveness of leveraging social interactions and nudges to spur adoption of prosocial behaviors. This study investigates a large-scale behavioral intervention ...designed to actively leverage social learning and peer interactions to encourage adoption of residential solar photovoltaic systems. Municipalities choose a solar installer offering group pricing and undertake an informational campaign driven by volunteer ambassadors. We find a causal treatment effect of 37 installations per municipality from the campaigns and no evidence of harvesting or persistence. The intervention also lowers installation prices. Randomized controlled trials based on the intervention show that selection into the program is important, whereas group pricing is not. Our results suggest that the program provided economies of scale and lowered consumer acquisition costs, leading to low-cost emission reductions.
This paper was accepted by Matthew Shum, marketing.
This study examines how messaging approaches in a prosocial intervention can influence not only the effectiveness of the intervention but also, contagion afterward. Our investigation focuses on ...leveraging two motivations for solar adoption: self-interest and prosocial. Using data from a natural field experiment in 29 municipalities containing 684,000 people, we find that selfinterest messaging is twice as effective in inducing solar adoption both during and after the intervention. Adoptions under self-interest messaging have 10% higher net present value, but prosocial messaging increases the likelihood that adopters recommend solar to their friends and neighbors. Income moderates the effectiveness of self-interest messaging, performing much better in high-income communities than low- and moderate-income communities. There was no significant difference across income groups for prosocial messaging. These results provide guidance to policy makers aiming to encourage prosocial behavior across all income groups.
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This study examines how electric utilities and regulators can encourage residential consumers to conserve electricity during the hottest summer days and shift electricity load from the day to ...off-peak, nighttime hours. We analyze a two-year field experiment involving 280 Texas households that explores approaches to conservation and load-shifting to enable emission reductions and reduce generation costs. Our critical peak pricing intervention reduces electricity consumption by 14% on the peak hours of the hottest days, leading to greenhouse gas emission reductions of about 16%. A key contribution of this study is the use of high-frequency appliance-level data. We show that 74% of the critical peak response is from reducing air conditioning. In a complementary nighttime pilot program, consumers respond strongly to lower prices by programming the timing of electric vehicle charging. Our work highlights how automation can influence the consumer tradeoffs relating to effort costs, discomfort, monetary incentives, and warm glow.
This paper was accepted by Rajesh Chandy, Special Section of
Management Science
on Business and Climate Change.
Supplemental Material:
The data and online appendices are available at
https://doi.org/10.1287/mnsc.2020.02074
.
Kenneth Gillingham is an Associate Professor of Economics at Yale University, with a primary appointment in the School of Forestry & Environmental Studies. In 2015 to 2016, he served as the Senior ...Economist for Energy and the Environment at the White House Council of Economic Advisers. His research interests cover energy and environmental economics, industrial organization, technological change, and energy modeling. He held a Fulbright to New Zealand and has worked for Resources for the Future and Pacific Northwest National Laboratory. He received a PhD and two MS degrees from Stanford University and an AB from Dartmouth College.
Christopher Knittel is the George P. Shultz Professor of Applied Economics in the Sloan School of Management at the Massachusetts Institute of Technology (MIT). He is also the Director of MIT’s Center for Energy and Environmental Policy Research, which serves as the hub for social science research on energy and the environmental since the late 1970s. Professor Knittel is also the Co-Director of the MIT Energy Initiative’s Electric Power System Low Carbon Energy Center and a co-director of The E2e Project, a research initiative between MIT, UC Berkeley, and the University of Chicago to undertake rigorous evaluation of energy efficiency investments.
Jing Li holds the inaugural William Barton Rogers Career Development Chair of Energy Economics at the MIT Sloan School of Management. From 2017–2018, Jing Li was a Postdoctoral Associate of the MIT Energy Initiative. Jing’s research interests lie in energy economics and industrial organization, focusing on development and adoption of new technologies. Her most recent work examines compatibility and investment in electric vehicle recharging networks in the United States and cost pass-through in the E85 retail market. Jing received double BSc degrees in Mathematics and Economics from MIT in 2011 and her PhD in Economics from Harvard in 2017.
Marten Ovaere is a Postdoctoral Associate in the School of Forestry & Environmental Studies of Yale University. His research interests lie in energy and environmental economics, with a focus on electricity markets, carbon pricing, and renewable energy. Marten holds a MSc in Economics, a MSc in Energy Engineering, and a PhD in Economics from KU Leuven.
Mar Reguant is an Associate Professor in Economics at Northwestern University. She received her PhD from MIT in 2011. Her research uses high-frequency data to study the impact of auction design and environmental regulation on electricity markets and energy-intensive industries. She has numerous awards, including a Sloan Research Fellowship in 2016, the Sabadell Prize for Economic Research in 2017, a Presidential Early Career Award for Scientists and Engineers award in 2019, and the European Association of Environmental and Resource Economists Award for Researchers in Environmental Economics under the Age of Forty in 2019.
The short-run effects of Covid-19 in reducing CO2 and local air pollutant emissions can easily be outweighed by the long-run effects on innovation. In the short-run, CO2 emissions have declined by 15%, and declines in local air pollutants have saved 200 lives per month. However, there could be a deep impact on innovation in clean energy, leading to an additional 2,500 MMT CO2 cumulatively and 40 deaths per month on average to 2035. But the policy response to Covid-19 is crucial.
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Emissions from ships in and surrounding ports are a major contributor to urban air pollution in coastal and inland riverside cities. Connecting docked ships to onshore grid electricity and using ...electric tugboats are two approaches to reduce pollution damages. This paper examines the effects of the widespread adoption of electrification in waterborne shipping. Our study is novel in the use of an equilibrium model of the U.S. energy system to capture the effects of increasing electricity generation to electrify waterborne shipping both with and without a carbon pricing policy. We examine three scenarios, Electrifying in ports, Electrifying in Emission Control Areas, and Electrifying all U.S. vessel fuels, as well as an electrification scenario under carbon pricing, allowing electrification of waterborne shipping to contribute to deeper decarbonization. We find that electrification results in slight carbon emission reductions in early projected years and that the reductions increase as the electric grid evolves out to 2050. We also show that an ambitious scenario of electrifying all U.S. vessel fuels results in up to 65% net reduction in air pollution as we approach 2050, even after accounting for the pollution increase from grid generation. Our baseline results indicate that intensive waterborne shipping electrification can provide considerable social benefits that exceed the costs, especially as the electric grid decarbonizes.
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Residential energy demand can be greatly influenced by the types of housing structures that households live in, but few studies have assessed changes in the composition of housing stocks as a ...strategy for reducing residential energy demand or greenhouse gas (GHG) emissions. In this paper we examine the effects of three sequenced federal policies on the share of new housing construction by type in the U.S., and estimate the cumulative influence of those policies on the composition of the 2015 housing stock. In a counterfactual 2015 housing stock without the policy effects, 14 million housing units exist as multifamily rather than single-family, equal to 14.1% of urban housing. Accompanied by floor area reductions of 0–50%, the switch from single- to multifamily housing reduces energy demand by 27–47% per household, and total urban residential energy by 4.6–8.3%. This paper is the first to link federal policies to housing outcomes by type and estimate associated effects on residential energy and GHG emissions. Removing policy barriers and disincentives to multifamily housing can unlock a large potential for reducing residential energy demand and GHG emissions in the coming decades.
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Abstract
Annual greenhouse gas (GHG) emissions from residential energy use in the United States peaked in 2005 at 1.26 Gt CO
2-eq
yr
−1
, and have since decreased at an average annual rate of 2% yr
...−1
to 0.96 Gt CO
2-eq
yr
−1
in 2019. In this article we decompose changes in US residential energy supply and GHG emissions over the period 1990–2015 into relevant drivers for four end-use categories. The chosen drivers encompass changing demographics, housing characteristics, energy end-use intensities, and generation efficiency and GHG intensity of electricity. Reductions in household size, growth in heated floor area per house, and increased access to space cooling are the main drivers of increases in energy and GHG emissions after population growth. Growing shares of newer homes, and reductions in intensity of energy use per capita, household, or floor area have produced moderate primary energy and GHG emission reductions, but improved generation efficiency and decarbonization of electricity supply have brought about far bigger primary energy and GHG emission reductions. Continued decline of residential emissions from electrification of residential energy and decarbonization of electricity supply can be expected, but not fast enough to limit climate change to 1.5 °C warming. US residential final energy demand will therefore need to decline in absolute terms to meet such a target. However, without changes in the age distribution, type mix, or average size of housing, improvements in energy efficiency are unlikely to outweigh growth in the number of households from population growth and further household size reductions.
We conduct a systematic and interdisciplinary review of empirical literature assessing evidence on induced innovation in energy and related technologies. We explore links between demand-drivers (both ...market-wide and targeted); indicators of innovation (principally, patents); and outcomes (cost reduction, efficiency, and multi-sector/macro consequences). We build on existing reviews in different fields and assess over 200 papers containing original data analysis. Papers linking drivers to patents, and indicators of cumulative capacity to cost reductions (experience curves), dominate the literature. The former does not directly link patents to outcomes; the latter does not directly test for the causal impact of on cost reductions. Diverse other literatures provide additional evidence concerning the links between deployment, innovation activities, and outcomes. We derive three main conclusions. (a) Demand-pull forces enhance patenting; econometric studies find positive impacts in industry, electricity and transport sectors in all but a few specific cases. This applies to all drivers—general energy prices, carbon prices, and targeted interventions that build markets. (b) Technology costs decline with cumulative investment for almost every technology studied across all time periods, when controlled for other factors. Numerous lines of evidence point to dominant causality from at-scale deployment (prior to self-sustaining diffusion) to cost reduction in this relationship. (c) Overall innovation is cumulative, multi-faceted, and self-reinforcing in its direction (path-dependent). We conclude with brief observations on implications for modelling and policy. In interpreting these results, we suggest distinguishing the economics of active deployment, from more passive diffusion processes, and draw the following implications. There is a role for policy diversity and experimentation, with evaluation of potential gains from innovation in the broadest sense. Consequently, endogenising innovation in large-scale models is important for deriving policy-relevant conclusions. Finally, seeking to relate quantitative economic evaluation to the qualitative socio-technical transitions literatures could be a fruitful area for future research.
Car owners underestimate total vehicle costs. Giving consumers this information could encourage the switch to cleaner transport and reduce emissions.
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10.
Peer Effects in Residential Water Conservation Bollinger, Bryan; Burkhardt, Jesse; Gillingham, Kenneth T.
American economic journal. Economic policy,
08/2020, Volume:
12, Issue:
3
Journal Article
Peer reviewed
Open access
Social interactions are widely understood to influence consumer decisions in many choice settings. This paper identifies causal peer effects in residential water conservation during the summer using ...variation from movers. We classify high-resolution remote sensing images to provide evidence that conversions of green landscaping to dry landscaping are a primary determinant of the reductions in water consumption. We also find suggestive evidence that without a price signal, peer effects are muted, indicating a possible complementarity between information and prices. These results inform water use policy in many areas of the world threatened by recurring drought conditions.
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