The short-run and long-run effects of behavioral interventions: Experimental evidence from energy conservation

By Hunt Allcott, Todd Rogers. 2014

1,269 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Management, Monitoring, Policy and Law, Pollution

View Paper: https://www.semanticscholar.org/paper/240b069944c920da5dc89015b94a6167d3effa85

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Citations in the corpus

Social Norms and Energy Conservation Beyond the US (2020, positive): “In this section, we test the sensitivity of our conclusion concerning two aspects where our calculations might be overly pessimistic: persistency in electricity savings beyond the treatment year (Allcott and Rogers 2014) and the consideration of a broader set of benefits and cost for welfare analysi”
Persistence (2014, positive): “Three long-term randomized experiments conducted by OPOWER (Allcott & Rogers, 2014) have identical experimental designs: Beginning around 2008, 234,000 total households were randomly assigned to one of three conditions.”
Social norms and pro-environmental behavior: A review of the evidence (2017, background): “Inenergystudies,forexample,theuseofdescriptive norms has been shown to have a boomerang effect for some individuals who learn that they outperform the norm (Allcott and Rogers, 2014; Schultz et al., 2007), a result that is not re ﬂ ected in the main effects re-ported in Table 2.”
High energy burden and low-income energy affordability: conclusions from a literature review (2020, background): “Well established concepts in behavioral and experimental economics on principal agent problems, information asymmetry, and bounded rationality inform this research (Simon 1976, Brown 2001, Gillingham et al 2009, Allcott and Rogers 2014).”
Consumers and their behavior: state of the art in behavioral science supporting use phase modeling in LCA and ecodesign (2016, background): “The average treatment effects of OPOWER’s conservation programs ranged from 1.4 to 3.3 % of baseline usage, with a mean reduction in energy consumption of 2.0 % (Allcott 2011; Allcott and Rogers 2014).”
Nudging out support for a carbon tax (2019, positive): “More generally, nudges promise positive impacts on a range of problems at lower costs than those associated with standard economic policies 8–15 .”
The Long-Run Dynamics of Electricity Demand: Evidence from Municipal Aggregation (2020, background): “Allcott and Rogers (2014) estimate that the energy reductions following random assignment of a home energy report are larger 7–12 months after the beginning of the program, relative to 1–6 months after.”
Should Governments Invest More in Nudging? (2017, neutral): “Allcott and Rogers (2014) directed readers to Allcott (2011) for simpler cost effectiveness calculations for the program.”
Neighbors, Knowledge, and Nuggets: Two Natural Field Experiments on the Role of Incentives on Energy Conservation (2013, neutral): “Once we control for these background variables in specification (5), the only variable that remains important is size of property.”
Tackling Climate Change with Machine Learning (2019, background): “Some works have also used agent-based models to better understand behavior from a climate economics perspective [617, 649, 650].”