16 consumption in the rainy season of 2013 (i.e. the average of water consumption between May and November 2013), by treatment status. We use the rainy season of 2013 as our measure of “preintervention” water consumption to ensure that seasonal factors, which have large effects on water use, are minimized. This ought to ensure that differences in pre- and post-intervention water consumption are not driven mainly by seasonality, which is possible if we were to use, e.g., the two months immediately prior to the intervention or the full prior year consumption data. **Figure 6** gives a graphical representation of this information.

Average water consumption in Treatment households declined by more than in Control households for each of the three Treatments, although the difference-in-differences is only significant for the Neighborhood Norms and Plan-Making interventions. In general, we can see that both control and treatment households’ average monthly water consumption in August-September 2014 was less than their average monthly water consumption in the corresponding season of the previous year. However, the decline in consumption is much larger for households in the Treatment group.

# **_Result 2: Neighborhood comparison reduces water use by between 3.5 percent and 5.6 percent of control group consumption, but city comparison has no significant effect on water consumption._**

**Table 3** presents our central regression results. We regress post-period water consumption on treatment status and control for baseline water consumption. Reading across the first row, we see that relative to the control group, the Neighborhood Comparison Treatment reduces water consumption by between 0.98 and 1.47 cubic meters per household, or between 3.7 percent and 5.6 percent of water consumption for the control group over the same period. In contrast, there is no evidence that the City Comparison reduced water consumption significantly in any specification.

As discussed earlier, we use baseline consumption measures from either only the rainy season of 2013, the rainy season of 2013 and the pre-intervention rainy season months of 2014, or the monthly consumption for 2013 as a whole. While the choice of control does affect the size of our coefficients, they are consistently negative and statistically significant.

# **_Result 3: Plan-making reduces water use by between 3.4 percent and 5.5 percent of control group water consumption._**

Reading across the third row of **Table 3** , we see that relative to the control group, the Plan-making treatment reduces water consumption by between 0.90 and 1.46 cubic meters per household, or between 3.4 percent and 5.5 percent of water consumption for the control group over the same period. As with the Neighborhood Comparison, the choice of baseline consumption measure affects the size of our coefficients, but not their sign or significance: they are consistently negative and statistically significant.

# **_Result 4: Pooled data confirms the effectiveness of neighborhood comparison and plan-making._**

**Table 4** pools the data for the months of August and September 2013 and 2014, giving us two postintervention and two pre-intervention observations on each household in the sample, and runs a classic difference-in-differences estimator. The coefficient of interest is now the post-intervention consumption