Table 7: Intervention impact on toilet usage

||(1)<br>Open <br>All HH<br>members|(2)<br> Defecation<br>Any HH<br>member|
|---|---|---|
|SL|-0.107<sup>_∗∗∗_</sup>|-0.104<sup>_∗∗∗_</sup>|
||(0.0245)|(0.0243)|
|Cluster-robust p-value|[0.0000]|[0.0000]|
|Romano-Wolf p-value|[0.0000]|[0.0000]|
|Strata FE|Yes|Yes|
|Interviewer FE|Yes|Yes|
|Household covariates|Yes|Yes|
|Ratio sample clients/GP size|Yes|Yes|
|Control mean|0.603|0.610|
|N|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, OD for open defecation. Data source: household survey.

uptake indicator with the treatment assignment. This exercise assumes that changes in toilet ownership induced by the intervention happen only through the loan uptake itself. A potential alternative channel includes salience (i.e. the pure offering of the loan product making clients more inclined to make this investment). However, we show below that knowledge about the benefits of sanitation have not changed due to the intervention, making this an unlikely channel.Table 8 confirms that 50% of sanitation loans were used to construct toilets that otherwise would not have been built.

An important question is whether the remaining 50% of sanitation loans were also used for sanitation, but simply displaced other sources of funding for toilets that households would have built anyways in the absence of the intervention, or whether they were used to finance other investments, or consumption expenditures. We address this question by analyzing reported funding sources for toilets constructed since sanitation loans were offered, impact estimates presented in Table 9. Two important conclusions can be drawn: For one, clients in treated villages are 4-5 percentage points more likely to report having financed their toilet with credit from a formal source. Column 2 shows a coefficient of 0.038 for reported MFI funding, and column 3 one of 0.055 pooling formal sources (MFI, banks and SHGs) together.<sup>45</sup> Given the female lending group structure of our implementing partner, some respondents (not always the clients themselves), might confuse the exact funding source, which is why we present both definitions. Importantly, while the range of estimated impacts is not exactly in line with the 9ppt impact on toilet uptake, it is close and supports that about 50% of sanitation loans result in newly constructed toilets.<sup>46</sup>

> 45Self-Help Groups in India are typically formal, as they are lending groups linked to banks.

> 46We note that reported funding sources are missing for some households that own a toilet at endline, wich we conservatively set to zero. Setting it for the ’Any source’ variable to one for missing households would give us, by construction,

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