Working Paper: NBER ID: w24812
Authors: Bryan Bollinger; Jesse Burkhardt; Kenneth Gillingham
Abstract: 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.
Keywords: peer effects; water conservation; consumer migration; dry landscaping
JEL Codes: L95; Q25; R23
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Economic incentives (M52) | Influence of peer effects (C92) |
| Presence of price signal for water (Q21) | Strength of peer effects (C92) |
| Peer behavior (C92) | Water conservation behaviors (Q25) |
| Fraction of peer group households reducing their water consumption (D12) | Probability of focal household reducing its water consumption (D19) |
| Peer group water consumption changes (Q25) | Focal household water consumption decisions (D10) |