Finally, Panel E indicates that the _Formation of Non-Regulated Microfinance Institutions_ is positively associated with the share of lending to women, but only for NGOs and NBFIs. For all of the Microscope components in Table 5, this is the strongest indication that the type of MFI and its interaction with the regulatory environment matter for lending to women. Again, it appears that less formal MFIs are better able to deepen their outreach to underserved market segments in environments where they are freer to enter and operate.

# **_b. Financial Performance_**

The standard measures of financial performance include profitability (ROA and ROE) and measures of financial and operational self-sufficiency that are computed by the MIX. The MIX’s financial self-sufficiency (FSS) index adjusts for inflation and the subsidies that MFIs receive such as donated equity and concessional loans, and thus provides a fairer basis for comparing the financial performance of MFIs with different funding structures. We therefore rely on that measure in the regressions that follow, though results are often similar when we use other measures. Measures of loan portfolio quality also serve as the dependent variable in some regressions (also available in the MIX data). The FSS index and the share of the loan portfolio that is 30 days past due simply replace the outreach indicators in Equations 2 and 3.

Table 6 shows results from regressions that use the FSS index as the dependent variable. Unlike for the outreach measures, there are no strong relationships between the Microscope and its subcomponents and the FSS index in the non-IV models. However, there is a significant positive relationship in the IV models between FSS and the Microscope for the overall score (Panel A), the RFP sub-index (Panel B), and the RFDT subcomponent (Panel D).<sup>16</sup> We find it difficult to argue that better developed, more formal regulatory and supervisory practices _cause_ MFIs to become more profitable. Rather, the results suggest that strong financial performance for MFIs tends to be a part of business environments that also feature advanced regulation and supervision.

The models with interactions between the Microscope and organizational type also cast doubt on the notion that better developed regulatory structures improve the financial performance of MFIs (see Table 7). Instead, the significant positive coefficient for formal microbanks and credit unions/cooperatives indicates that those types tend to have better financial performance than other types. The significant negative coefficient on the interactions between that group and the Microscope variables (seen in models in all panels in Table 7) indicate that that as the regulatory and supervisory framework develops, the financial performance of those MFIs declines somewhat. Presumably these are the MFIs likely to face the most stringent forms of supervision and so it is plausible that complying with the costs of prudential supervision

> 16  There are also positive relationships between FSS and the formation/operation of non-regulated microcredit institutions for the IV models in Panel E. However, the test statistics indicate that our instruments are not highly relevant in those models. We therefore do not ascribe much meaning to those significant coefficients.

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