Cost-effectiveness of electricity energy efficiency programs
By D. Revel. 2011
166 citations recorded by the source corpus.
View Paper: https://www.semanticscholar.org/paper/b921e6476a1bfddb13d11a4ac2728b429bd4afe5
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Citations in the corpus
- Nudging Energy Efficiency Behavior: The Role of Information Labels (2014, unknown): “, Ruderman, Levine, and McMahon (1987), Sutherland (1991), Jaffe and Stavins (1994), Metcalf (1994), Gillingham, Newell, and Palmer (2006, 2009), Tietenberg (2009), Newell (2010), Allcott and Greenstone (2012), Arimura et al. (2012), and Gillingham and Palmer (2012). 556 Journal of the Association o”
- Bridging the Energy Efficiency Gap: Policy Insights from Economic Theory and Empirical Evidence (2014, unknown): “However, Auffhammer, Blumstein, and Fowlie (2008) and Arimura et al. (2012) find that the differences between their estimates of cost effectiveness and those reported by utilities are not statistically significant.”
- The short-run and long-run effects of behavioral interventions: Experimental evidence from energy conservation (2014, unknown): “Using nationwide data, Arimura et al. (2011) estimate average cost effectiveness to be about 5.”
- Should Governments Invest More in Nudging? (2017, unknown): “…effect in coastal areas $3.70 per customer for rebates plus $1.39 per customer for administrative and marketing costs 3.41 kWh saved per $1 spenta Arimura et al. (2012) Utilities provided incentives and education to reduce energy usage during peak times and promote efficiency investments 0.9…”
- Neighbors, Knowledge, and Nuggets: Two Natural Field Experiments on the Role of Incentives on Energy Conservation (2013, unknown): “The partial derivatives in (6) and (7) capture the positive and negative effects of increases in benefits and costs (respectively) on household utility.”
- A credible approach for measuring inframarginal participation in energy efficiency programs (2014, background): “Thereisalsoasmallliteraturewhichaddressesadditionality indirectly by comparing realized aggregate savings at the utility level to engineering estimates (Loughran and Kulick, 2004; Auffhammer et al., 2008; Arimura et al., 2012).”
- Site Selection Bias in Program Evaluation (2015, unknown): “To implement this, I insert the estimated sample ATE τ̂D=1 and the α̂ parameters from Equation (2) estimated with X∗ only.”