household income) is more likely the explanation for the educational effects of access to plant water.<sup>40</sup>

# **Household Income and Treatment Effect**

Does the treatment effect depend on household income? The answer to this question might shed light on the distributional impact of the water treatment program.<sup>41</sup> To answer the question, we divide the sample into two groups according to their baseline household incomes, each accounting for half of the income distribution. Table 8 shows the regression results for each outcome and for each income group. Overall, the coefficients for the high income group are reasonably close to those for the low income group in magnitudes and all of the coefficients are statistically significant at the one percent level. For example, the effect of plant water on grades of education completed is 0.984 for the poor vs. 1.043 for the rich. Although here the impacts are slightly stronger for the rich than the poor, this pattern diminishes—we find similar effects across groups--when we run regressions for three income groups. Our results thus suggest that water treatment in rural areas benefited the poor and the rich similarly.

# **Time of Exposure and Treatment Effects**

40 Note that the coefficients of the optimal water access are significant in regressions with outcomes of grades of education completed and the probability of graduating from a middle school, while not with the outcome of graduating from a high school. This finding fits the institution of China’s educational system. Rural students usually commute from home to schools when they are in primary or middle schools since the distances to those schools are not far (The average distance to a primary school and a middle school are 0.57 kms and 2.03 kms, respectively). In this case children can benefit from the availability of water in their premises since their time to fetch water can be saved. In contrast, a high school is normally located far away and our data shows that the average distance to a high school is 8.5 kms. Rural students in high schools are not able to travel between home and schools every day. They either live with relatives or rent a place close to schools. Quite often high schools also provide accommodation for their students as well. Those students do not do household chores such as fetching water. This observation explains why better access to water does not have a statistically significant impact on the children’s probability of graduating from a high school.

Our finding that optimal water access improves education is also consistent with Maimaitwe and Siebert (2009), who use CHNS data to finds that poor _access_ to water hurt girls’ education, but not boys (age between 6 and 19), which also imply a positive average effect of water _access_ on education. Their definition of optimal water access however differs from ours; they exclude but we and Manygo (2008) include “in-yard well” in the optimal water access category. Our results are thus not strictly comparable.

41 Galiani et al. (2005) and Kosec (2014), for instance, both find that private sector participation in water supply tends to benefit the poor more than the rest.

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