have been taken to indicate greater depth of outreach.<sup>11</sup> Because depth of outreach is at least as important as its breadth for most MFIs, we focus on those two variables in the analyses that follow.

Both the MICROSCOPE and ‘Country’ variables are measured at country level as described above. Because we have more observations than in the country-level penetration regressions we are also able to include a basic measure of banking sector development, _Bank Cred/GDP_ , in the MFI-level regressions. We also include regional dummy variables in the regressions since those have explained substantial variation in the outreach and financial performance of MFIs in other studies (see, e.g., Cull, Demirguc-Kunt, and Morduch, 2007). ‘MFI’ represents a set of variables summarizing an MFI’s characteristics including its size in terms of assets, organizational type (bank, rural bank, credit union, cooperative, non-bank financial institution, or NGO), and preferred lending methodology.<sup>12</sup> The lending methodology variables are not available for a substantial fraction of the MFIs in our sample. We therefore present models with and without those variables.

# (2) OUTREACHij = α + β1MICROSCOPEi + β2Countryi + β3MFIij + εij

The organizational type for each MFI is among the control variables under the ‘MFI’ umbrella in Equation 2. To derive more precise tests of how the business environment affects the financial performance of different types of MFIs, Equation 3 adds interactions between the Microscope and dummy variables describing organizational type to the set of explanatory variables. The coefficients on the simple organizational type dummy variables will therefore summarize the average depth of outreach for that type, while the coefficient on the interaction term (β2) summarizes how that average effect changes as the business environment for microfinance as summarized in the Microscope improves (or worsens).

# (3) OUTREACHij = α + β1MICROSCOPEi + β2MICROSCOPEi*Typej + β3Countryi + β4MFIij + εij

Results from regressions that use average loan size (as a share of per capita income) appear in Table 2. In Panel A, the overall Microscope score is used as the measure of the quality of the business environment for microfinance. As in the country-level penetration regressions,

> 11 See, for example, Cull, Demirguc-Kunt, and Morduch (2009).

> 12 Note that the revised Microscope carries a 2011 title, while the most recent MFI-level data from the MIX is for 2010. While this might seem problematic at first blush, the survey underlying the Microscope was conducted beginning in late 2010 and 2011, so the two sources of information are close to contemporaneous. Also, to the extent that survey responses tend to summarize the recent past rather than forecast future events, this is not a severe problem. Moreover, to the extent that there is persistence in both MFI financial performance over time and in the Microscope, the relationships that are uncovered are unlikely to be misleading. Certainly, measures such as portfolio quality are likely to exhibit such persistence because they tend to change relatively slowly over time. In any event, given the time-consuming nature of collecting, vetting, and processing the MFI-level information, the MIX data will always lag the Microscope by some interval.

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