Table 9: Intervention impact on toilet funding source

||(1)<br>Any source|(2)<br>Credit from<br>MFI|(3)<br>Credit from<br>MFI, SHG,<br>banks|(4)<br>Savings|(5)<br>Other sources|
|---|---|---|---|---|---|
|SL|0.0715<sup>_∗∗_</sup>|0.0380<sup>_∗∗∗_</sup>|0.0545<sup>_∗∗∗_</sup>|0.0731<sup>_∗∗∗_</sup>|0.0268|
||(0.0257)|(0.0109)|(0.0161)|(0.0231)|(0.0192)|
|Cluster-robust p-value|[0.0054]|[0.0005]|[0.0007]|[0.0016]|[0.1642]|
|Romano-Wolf p-value|[0.0110]|[0.0020]|[0.0020]|[0.0050]|[0.1818]|
|Strata FE|Yes|Yes|Yes|Yes|Yes|
|Interviewer FE|Yes|Yes|Yes|Yes|Yes|
|Household covariates|Yes|Yes|Yes|Yes|Yes|
|Ratio sample clients/GP size|Yes|Yes|Yes|Yes|Yes|
|Control mean|0.397|0.0438|0.0723|0.312|0.142|
|N|2821|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, OD for open defecation. Data source: household survey.

of the sanitation loan, leaving overall borrowing unchanged. Thus, this offers an opportunity to test for the relevance of the loan label: an increase in sanitation loan take-up, and in sanitation investments, coupled with substitution out of other investments and other loans, and no change in overall borrowing would be consistent with the loan label mattering. However, if overall borrowing increases, we will not be able to identify the importance of each feature by considering average impacts only. In this case, we would need to study impacts for specific sub-groups (e.g. those who were not credit constrained ex-ante) in order to identify the importance of each channel.

# **6.3.1 Overall borrowing**

We start by looking at overall borrowing of the client households. As part of the household survey, respondents were asked to report on loans taken since the baseline survey was conducted. As is common in surveys of this type, we collected information on total household borrowing by asking households about the three largest loans (above Rs 500) taken since the start of the experiment.<sup>47</sup> In addition to information such as loan size and outstanding balance, respondents were asked to report on the lending source, which we use to classify loans into two categories - formal and informal.<sup>48</sup> We further split formal borrowing into loans from MFIs and those from other formal sources. Results are presented in

> 47Furthermore, respondents are asked about the sum of all small loans taken in the month prior to the survey and the sources of this borrowing. We do not use this data in our analysis for the following reason: We only have this information for the month prior to the survey, rather than for the period since the start of the intervention, which is the relevant variable. It would not be possible to obtain an indicator for this without making extremely strong and implausible assumptions (e.g. that the borrowing in the past month is representative of the whole period). Moreover, it is very unlikely that households would be able to aggregate sufficient loans of this size ( _<_ 500 Rs.) to invest in a toilet. It is thus reasonable for us to focus our analysis on large loans.

> 48We classify as formal sources banks, MFIs, NGOs, cooperatives/savings funds, and Self Help Groups (SHGs). Informal sources are moneylenders, relatives , friend/acquaintance/private financiers, work, pawnshop and other local shops.

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