English
Social scientists rely heavily on self-reported data. But can respondents be trusted to report the truth? In this paper, the authors compared survey self reports with administrative data and found that nearly 50% of recent borrowers did not report their high-interest consumer loans. Under-reporting appeared to be correlated with several characteristics, in particular gender. Relying strictly on self-reported data may lead to biased inference, and the authors outline some methodological implications for identifying impacts of credit access on borrower behavior and outcomes. Matching female surveyors to female respondents appears to be one low-cost mitigation strategy. The best strategy, however, is to avoid reliance on self-reported data by using lenders’ administrative data or the credit bureau, when feasible.
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Brief
Date:
November 01, 2007
English
We compare survey self-reports with administrative data and find that  50% of recent borrowers do not report their high-interest loans. Under-reporting appears to be correlated with several of interest, in particular gender: 62% of women, when interviewed by men, under-report whereas 42% of women interviewed by women under-report. On the other hand, 40% of men under-report, irrespective of the gender of the interviewer. As such relying strictly on self-reported data may lead to biased inference, and we outline some methodological implications for identifying impacts of credit access on borrower behavior and outcomes. Matching female surveyors to female respondents appears to be a low-cost mitigating strategy, but clearly the best strategy is to make sure one has administrative data from a lender to measure actual borrowing history. 
 
Research brief also available here.
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Published Paper
Date:
November 01, 2007

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