Simulating the impacts of climate change, prices and population on California’s residential electricity consumption

By M. Auffhammer, Anin Aroonruengsawat. 2011

186 citations recorded by the source corpus.

Subfields: Building and Construction, Pollution, Renewable Energy, Sustainability and the Environment

View Paper: https://www.semanticscholar.org/paper/552755d4b71cbdb665752cbc77ee45c40866a00a

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In Building and Construction

In Pollution

In Renewable Energy, Sustainability and the Environment

Citations in the corpus

Measuring climatic impacts on energy consumption: A review of the empirical literature (2014, background): “Auffhammer et al. (2013) provide a detailed discussion of climate models and their use in the social sciences.”
Valuing the Global Mortality Consequences of Climate Change Accounting for Adaptation Costs and Benefits (2019, unknown): “…of one or the other of these two factors for mediating climate impacts in crosssection (e.g. Mendelsohn, Nordhaus, and Shaw, 1994; Kahn, 2005; Auffhammer and Aroonruengsawat, 2011; Hsiang, Meng, and Cane, 2011; Graff Zivin and Neidell, 2014; Moore and Lobell, 2014; Davis and Gertler, 2015;…”
Durable goods and long-run electricity demand: : Evidence from air conditioner purchase behavior (2014, methodology): “Appliance price weakly influences the purchase decision, but not intensity-of-use thereafter.”
Air conditioning and electricity expenditure: The role of climate in temperate countries (2020, methodology): “Deschênes and Greenstone (2011) and Auffhammer and Aroonruengsawat (2011) also adopt the panel data approach.”
What Do We Learn from the Weather? The New Climate-Economy Literature (2014, background): “Partly for this reason, Deschênes and Greenstone (2011) and Auffhammer and Aroonruengsawat (2012) find that the net effect of warming over the 21 century is likely to increase energy demand substantially, ceteris paribus, with these studies estimating 11% and 3% demand increases respectively.”
Using Weather Data and Climate Model Output in Economic Analyses of Climate Change (2013, unknown): “…the response function is nonlinear in weather/climate, as has been shown to be the case in agriculture (e.g., Schlenker and Roberts 2009) and electricity demand (e.g., Auffhammer and Aroonruengsawat 2011, 2012), then this bias may be amplified or offset depending on the nature of the nonlinearity.”
Temperature and temperament: Evidence from Twitter (2020, methodology): “The adaptive exercise follows Auffhammer and Aroonruengsawat (2011) and uses the regionally-specific damage functions estimated in Figure 4 to project changes due to adaptation.”