Peer Effects in Water Conservation: Evidence from Consumer Migration

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.