Knowledge is (Less) Power: Experimental Evidence from Residential Energy Use

By Katrina Jessoe, D. Rapson. 2014

616 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Renewable Energy, Sustainability and the Environment

View Paper: https://www.semanticscholar.org/paper/b022429aa16aef401b2445ba08ae87e98ccebd14

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Citations in the corpus

The Impact of Management Practices on Employee Productivity: A Field Experiment with Airline Captains (2019, background): “…fuel use since it is anecdotally very difficult for captains to map their behaviors to their fuel use on a given flight (as experimentally demonstrated in the context of residential energy use; e.g., see Jessoe and Rapson, 2014), and behavioral inputs are more readily accessible than outputs.”
Internal and external barriers to energy efficiency: which role for policy interventions? (2019, background): “However, Jessoe and Rapson (2014) and Lynham et al. (2016) conclude that in-home-displays while help consumers improve the decision-making process in case of high prices, they are less likely to make prices more salient.”
The value of familiarity: Effects of knowledge and objective signals on willingness to pay for a public good (2014, background): “…decision making (Schotter 2003, Eil and Rao 2011, Grossman and Owens 2012).8 To this end, there is a growing literature highlighting how economic agents alter their behavior when they have better information (Duflo and Saez 2003, Jensen 2007, Bhargava and Manoli 2013, and Jessoe and Rapson 2014).”
A Review and Taxonomy of Choice Architecture Techniques (2016, background): “More direct feedback on behavior can have various forms, including smart electricity meters displaying energy consumption (Jessoe & Rapson, 2014) and segmentation cues, such as including a red potato chip for every five chips, allowing an individual to track the amount of food already consumed…”
Common correlated effects estimation of heterogeneous dynamic panel quantile regression models (2020, positive): “Thus, it appears that substantial peak load reductions can in fact be achieved from TOU pricing (Jessoe and Rapson (2014), Ito (2014)).”
The dynamics of behavior change: Evidence from energy conservation (2016, background): “Consumers, however, receive infrequent information about the monetary costs of electricity (Gilbert and Graff Zivin, 2014; Jessoe and Rapson 2012; Ito 2014).”
Rank And Response: A Field Experiment On Peer Information And Water Use Behavior (2017, background): “Research in psychology and behavioral economics has consistently demonstrated that our social surroundings a ect our behavior and that we are in uenced by how we compare to our peers (Schultz et al., 2007; Grisevicius et al., 2008; Beshears et al., 2014; Fehr and Gintis, 2007).”
Mean–field moral hazard for optimal energy demand response management (2019, background): “Faruqui and Sergici [19] investigate "the evidence from the 15 most recent pilots, experiments and full–scale implementations of dynamic pricing of electricity" (see also the related contributions of Abrahamse, Steg, Vlek and Rothengatter [1], Herter [24], Newsham and Bowker [35], Wolak [42], or Jes”
The Long-Run Dynamics of Electricity Demand: Evidence from Municipal Aggregation (2020, background): “4A growing literature investigates the impact of real-time pricing (e.g., Wolak, 2011; Allcott, 2011; Jessoe and Rapson, 2014).”
The role of information for energy efficiency in the residential sector (2015, positive): “For example, Jessoe and Rapson (2014) observed in a field experiment that the effect of a price changewas higher in households that received real-time information (through a smart meter) than it was in the control group.”
Green Innovation and Finance in Asia (2020, neutral): “As such, effective energy conservation strategies for this sector rely on price (Ayres et al., 2013; Jessoe and Rapson, 2014; Jessoe and Rapson, 2015) and non-price (Allcott, 2011; Asensio and Delmas, 2015) policy interventions.”