whether the credit supports those _eligible_ for the financial incentive provided by the government. To this end, we examine impact heterogeneity by subsidy eligibility status, thereby analysing whether impacts are concentrated amongst subsidy ineligible or subsidy eligible households, or both. Matching the household survey data to the SBM administrative records allows us to obtain households’ official subsidy eligibility status, which is determined by both its VG classification and its official record of SBM baseline toilet ownership. Restricting the matched sample to MF client households that did not have a toilet at survey baseline (since these are the households targeted by the micro-credit and subsidy interventions) we estimate the following equation: where _SLv_ takes the value of 1 if the household lives in GP _v_ that was randomly assigned to the treatment group, and 0 otherwise. Dichotomous variables _SubsidyEligibleiv_ and _SubsidyIneligibleiv_ denote whether or not household _i_ is officially classified as being a subsidy eligible household. _Xiv_ is a vector of household-level controls that helps to increase power and precision.<sup>17</sup> Vector _Xiv_ also includes a dummy for whether or not a manual check revealed some uncertainty about the reliability of a particular match between a survey data record and an SBM administrative data record (see Section 3). We also control for a set of strata dummies _θv_ for GP _v_ . Standard errors are clustered at the GP level.

We estimate equation 1 for four main outcomes of interest _Yiv_ :(i) sanitation loan uptake, (ii) toilet ownership, (iii) toilet usage and open defecation, and (iv) subsidy uptake. Sanitation loan uptake is measured as a dichotomous variable using administrative data from the MFI. Toilet ownership is measured based on interviewer verified reports on toilet ownership by the survey respondent (usually the household head). Specifically, this variable takes a value of 1 if the respondent reports that the household owns a toilet, and the interviewer sees it; and 0 otherwise. We complement this measure with toilet ownership status captured in the 2016 SBM snapshot and use toilet construction date reported during the survey endline survey to compare consistency between these two data sources. The third outcome of interest – sanitation behaviour – is particularly relevant for policy. We measure this through two variables: an indicator for whether the toilets reported by households are in use, and an indicator for open defecation (as reported by the survey respondent for different demographic groups in the household). Finally, the fourth outcome of interest – subsidy uptake – is measured using data on subsidy receipts recorded in the September 2016 SBM snapshot.<sup>18</sup>

> 17The included covariates are chosen to be those that most explain the variation in toilet ownership among control households, and include a dummy for whether or not the household has a child aged 3 or 4, toilet uptake status at baseline, interviewer fixed effects, and village size. The baseline survey sampling strategy over-sampled households with children aged less than 2 years, which is why we control for whether the household had a child aged 3-4 years at endline. We control for village size since the endline sample of clients was (inadvertently) selected in a manner that correlates with village size. To control for toilet ownership pre-introduction of the loan product, we use reconstructed baseline toilet ownership, using respondent’s endline report on the age of their toilet. We use reconstructed baseline toilet ownership instead of census data on toilet ownership because census was based on segmenting and therefore not available for all households in our sample. We nevertheless conduct robustness checks using actual baseline ownership data on the restricted panel sample and results remain qualitatively the same.

> 18The reason why we do not use subsidy receipt as reported in the household survey is because this was only asked of households that owned a toilet, whereas the SBM dataset records this for any household, irrespective of their toilet ownership

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