repayment and overdue amounts are documented. This allows us to generate both loan-specific data and aggregated data for each of the loan officers from 2006 to 2010.

As described above, we use average loan size to reflect the depth of outreach to poorer borrowers.<sup>12</sup> From the CFPA Microfinance central database, we rely on the size of each loan as a dependent variable in the loan-level regression analysis and the average size of the loans disbursed in each year by each loan officer from 2006 to 2010 for the loan-officer-level regression analysis.

Our second data source is derived from a questionnaire that was administered to all of the CFPA loan officers. CFPA Microfinance’s inventory database provides information for 383 loan officers who extended loans at some point during the period 2006-2010. We first sent a questionnaire and an instruction letter through courier to each loan officer.<sup>13</sup> We then conducted telephone interviews with each loan officer during which we reviewed with them the entire questionnaire and the instruction letter. In several sections of the survey each loan officer was asked for personal information (e.g., age, gender, education, and career background prior to working at CFPA microfinance). Loan officers then sent completed questionnaires back to us through e-mail or courier. In the end, we received completed questionnaires from 379 loan officers.

Third, we rely on a county-level per capita income variable taken from the best secondary sources available to reflect economic conditions near the branches where loan officers are located. Specifically, we surveyed the _Yearbook of Rural Social and Economic Statistics_ and collected data on the annual income per capita among the rural population from 2006 to 2010.<sup>14</sup>

> 12 We acknowledge that there are limitations in using changes in loan size to measure mission drift. Non-poor borrowers may still be attracted by small loans when larger loans are expected in the future, as part of dynamic repayment incentives (Christen, 2000; Hishigsuren, 2004). Non-poor borrowers can also take a multiplicity of small loans from different lenders (McIntosh & Wydick, 2005). Direct measures such as transaction costs in accessing loans and the wealth status of borrowers and non-borrowers are potentially better suited to reflect targeting. However, these measures are prohibitively costly to collect in most empirical studies and thus loan size remains widely used.

> 13 We very much thank CFPA microfinance for providing contact information for the loan officers. Under our confidentiality agreement with CFPA, the anonymity of loan officers is preserved in the presentation of results and the discussion throughout the paper.

> 14 While it is not possible for us to verify the accuracy of that data, we note that measurement error in the income variable reduces the likelihood that we find a significant coefficient for it. In point of fact, the per capita income variable is highly significant in the regressions that follow. In addition, our standard errors allow for clustering at the county level and we derive similar results when county level fixed effects replace loan officer fixed effects in

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