either other formal or informal sources and therefore conclude that the micro-credit intervention improved toilet uptake of subsidy ineligible households by removing overall credit constraints for sanitation.

Linking these results to the predictions laid out above, we are able to exclude the reduction in interest rate and a reduction of overall credit constraints as possible drivers for subsidy ineligible client households. If the reduction in interest rate was the main driver, then we would have expected to see a shift away from more expensive loans, of which one is the business loan offered by the MFI. However, we do not observe such a pattern. Instead, we see a reduction in take up of education loans from the MFI, which had a similar interest rate as the sanitation loan. If sanitation loans were able to reduce overall credit constraints, then we would have expected to see an increase in overall borrowing from micro-finance sources and/or from other formal or informal sources. However, we find no evidence of such a pattern.. Thus, given that subsidy ineligible households take the sanitation loans, increase their sanitation investments, but do not increase overall borrowing by substituting out of the education loan – which had a similar interest rate to the sanitation loan – we can conclude that the impacts on subsidy ineligible households can be explained by the labelling of the loan as a sanitation loan. This also explains the high loan-to-new toilet conversion rate that we observed in the previous section.

Importantly, however, note that the reduction in education loan uptake shows that the introduction of micro-credit was unable to remove overall credit constraints for subsidy ineligible households. If labelling indeed matters for subsidy ineligible households, then the fact that they took an education loan prior to the intervention signals their interest in taking such a consumption loan. If they were no longer credit constrained post-intervention then we would have expected overall borrowing to go up rather than seeing a shift away from education loans. In on-going research we are exploring possible reasons for why subsidy ineligible households appear to remain overall credit constraints in this context.

Our findings for subsidy eligible households are not as conclusive. While Table 10 reveals that the average subsidy eligible MF client household responded to the micro-credit intervention by significantly increasing its overall MFI borrowing, it did so without reducing its uptake of other types of loans (Table 11). This combination of findings does not allow us to identify whether these households decided to take up the sanitation loans in response to the favourable interest rate, and/or because the provision of additional credit relaxed constraints in obtaining sufficient credit to make other types of non-sanitation investments. In the next section we explore further the extent to which micro-credit relaxed credit constraints for subsidy eligible households.

# **5.3 Complementing subsidy support to subsidy eligibles**

The results in the previous sections reveal that, on average, a significant portion of subsidy eligible households took up the sanitation loans, and that these loans were taken in addition to their existing loan portfolio, resulting in an increase in their overall borrowing. And yet, on average, this loan uptake did not translate into a significant number of new toilets. In this section we move beyond average numbers and explore whether micro-credit was able to support particular sub-groups of subsidy eligible households in making sanitation investments, and how. Specifically, we consider the potential use of micro-credit as a means to bridge the time gap between toilet construction and actual subsidy disbursement; before survey over MFI loan amount as recorded in the credit bureau data. Note that here we inevitably assume that the respondent’s misreporting behavior is the same across different types of lending sources.

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