Table 5: Intervention impact on toilet uptake (self-reported and observed by interviewers)

||(1)<br>Own toilet<br>HH report|(2)<br>Own toilet<br>Interviewer<br>observation|(3)<br>Functioning<br>toilet<br>HH report|(4)<br>Functioning<br>toilet<br>Interviewer<br>Observed<br>Toilet|
|---|---|---|---|---|
|SL|0.0863<sup>_∗∗_</sup>|0.0909<sup>_∗∗∗_</sup>|0.0925<sup>_∗∗∗_</sup>|0.0966<sup>_∗∗∗_</sup>|
||(0.0263)|(0.0250)|(0.0238)|(0.0236)|
|Cluster-robust p-value|[0.0011]|[0.0003]|[0.0001]|[0.0000]|
|Romano-Wolf p-value|[0.0020]|[0.0000]|[0.0000]|[0.0000]|
|Strata FE|Yes|Yes|Yes|Yes|
|Interviewer FE|Yes|Yes|Yes|Yes|
|Household covariates|Yes|Yes|Yes|Yes|
|Ratio sample clients/GP size|Yes|Yes|Yes|Yes|
|Control mean|0.452|0.413|0.398|0.372|
|N|2821|2821|2821|2821|

_Notes_ : SL equals sanitation loan arm. Standard errors clustered at the village level are shown in round parentheses. *, **, *** indicate significance at the 10, 5 and 1 percent level, referring to Romano-Wolf p-values. These are obtained from a step-down procedure to adjust for multiple hypothesis testing performing 1000 bootstrap replications as proposed by Romano and Wolf (2005). Covariates: Toilet ownership at baseline, indicator for presence of a child aged 0 - 2 at baseline, ratio of number of sampled clients to village size. HH stands for household. Functioning toilet is defined as toilet that is either in use (household report), or is not in use because of household preferences or a lack of water. Dependent variable in Column 4 is defined on household reports related to functioning of toilets observed by interviewers. Data source: household survey.

correlated variables into a set of linearly uncorrelated variables in a manner such that the largest principal components explain the largest possible variance among the original variables. The analysis yields one component for underground quality and two for overground quality. A detailed description of the approach we used for the construction of these composite measures is provided in Online AppendixD.<sup>44</sup> Table 6 displays the findings on these dimensions. The upper panel shows impacts on the overall sample and the lower panel shows impacts separately by whether or not the household had a toilet at baseline. The latter would reveal whether households with toilets at baseline upgraded them, or whether households building new toilets after baseline were building higher quality toilets as a result of the sanitation loan program. When we conduct inference using cluster-robust standard errors, the results suggest that the provision of sanitation loans led to an improvement in overground quality, potentially affecting different overground components for both new and existing toilets. However, these effects are not robust to adjustments for multiple hypothesis testing, as can be seen from the p-values calculated using the step-down procedure of Romano and Wolf [2005]. Moreover, the lower panel of the table shows that there were no differences, that are robust to multiple hypothesis testing, in the impacts on toilet quality by whether or not households had a toilet at baseline, prior to the start of the intervention. This evidence indicates once again that few of the sanitation loans were used for upgrade or repair of toilets, in line with households’ own reports of how they spent the sanitation loan.

Important for achieving the objective of improving health through improved sanitation is that newly constructed toilets are accompanied by a change in sanitation behaviour, in particular that toilets

> 44See Attanasio et al. [2018] for further details.

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