Bollinger, Bryan
[VerfasserIn]
;
Burkhardt, Jesse
[Sonstige Person, Familie und Körperschaft];
Gillingham, Kenneth
[Sonstige Person, Familie und Körperschaft]National Bureau of Economic Research
Erschienen:
Cambridge, Mass: National Bureau of Economic Research, July 2018
Erschienen in:NBER working paper series ; no. w24812
Umfang:
1 Online-Ressource
Sprache:
Englisch
DOI:
10.3386/w24812
Identifikator:
Reproduktionsnotiz:
Hardcopy version available to institutional subscribers
Entstehung:
Anmerkungen:
Mode of access: World Wide Web
System requirements: Adobe [Acrobat] Reader required for PDF files
Beschreibung:
Social interactions are widely understood to influence consumer decisions in many choice settings. This paper identifies causal peer effects in water conservation during the growing season, utilizing variation from consumer migration. We use machine learning to classify high-resolution remote sensing images to provide evidence that conversion to dry landscaping underpins the peer effects in water consumption. We also provide evidence that without a price signal, peer effects are muted, demonstrating a complementarity between information transmission and prices. These results inform water use policy in many areas of the world threatened by recurring drought conditions