Peer Effects in Residential Water Conservation: Evidence from Migration

The raw water consumption data set contains 2,599,862 observations and 308,529 households. Often the utility will make billing adjustments by manually changing a household’s water consumption in a particular month to either credit or charge an account. Hence, negative and extremely large consumption values are either errors or billing adjustments and do not reflect actual consumption. Accordingly, we drop annual consumption below the 1st percentile of consumption and above the 99th percentile of consumption, as these are very likely to be outliers that do not reflect actual consumption. For our main specification, we also drop houses that were sold anytime during the current summer months, the current non-summer months, or the lagged summer months (196,925 observations). We also do not have sales price information for all peer groups. For example, if no houses were sold within the peer group for a particular time period. This drop an additional (589,383 observations). Finally, including household-level fixed effects leads to 27,997 singleton observations. The remaining data set, after dropping parcels that had a transaction in the last year, has 1,535,545 observations and 260,307 households. The raw fitted landscaping data set contains 544,882 observations and 74,112 households. Again, we drop observations below the 1st percentile of consumption and above the 99th percentile of consumption for similar reasons as above. The remaining data set contains 540,451 observations and 72,007 households. Finally, including household-level fixed effects leads to 7,313 singleton observations, resulting in a final data set of 531,650 observations and 71,477 households.