Research in Micro Finance: Big Questions and How to Answer Them

1. Research in Micro Finance: Big Questions and How to Answer Them

2. Agenda • What is the goal of good research? • Why is research needed in microfinance? • What are some of the important questions? • How might we answer these questions? • What limits many common methods? • How can we measure causal impact, and why does causality matter? • How do we get good data? • How do we make research matter?

3. The Goal of Research • To define reality as accurately as possible • To create useful knowledge 3

4. Why Research in Microfinance is Needed • Despite major growth of microfinance, there are more poor people in India now than ever before • Still a young industry • We still don’t understand basic impacts, or relative value of different models • Many misconceptions about microfinance prevail 4

5. Important Questions in Microfinance • What are the basic impacts of credit? Savings? Insurance? • Who benefits from microfinance? • What are the returns to receiving capital? • Why don’t micro-businesses grow? • How do different products affect different people in different ways? (heterogeneous effects) • How are loans used for consumption, and is this good or bad? • How can the poor mitigate risk? • How do the poor think of fees and interest rates? 5

6. Common Research Methods • Focus groups and anecdotes of existing clients – good for understanding colorful information for how impacts happen, or information about a community (PRA’s) but not for understanding prevalence! • Finding groups for comparison • Comparing clients to non-clients • Comparing clients “before” and “after” • Comparing new clients to old clients 6

7. Common Research Methods (and their problems) • Focus groups and anecdotes of existing clients • (but drop-out rates are 20%+ - what about impacts on them? Are anecdotes reliable?) • Comparing clients to non-clients • (but clients are inherently different from non-clients) • Comparing clients “before” and “after” • (but other things may have happened in the meantime with greater effect) • Comparing new clients to old clients • (but early adopters are inherently different from later adopters) 7

8. Determining Causal Impact • Randomized control trial is the “gold standard” methodology • Develop a true “control” group: Randomizing access to a product, and compare outcomes among “treatment” to “control” • Just like those used in medical trials • Selection bias and attrition bias solved, assures internal validity 8

9. Getting good data • Data from organizations reporting on themselves is suspect (e.g. MIX Market) • If you want good data for original research, you have to get it yourself! (but it’s expensive!) • Primary data collection is very important for field experiments • Data collected is only as good as the sample selection, survey design, collection process, data entry, cleaning, and analysis – every step requires good planning and rigorous monitoring 9

10. Making research matter • Research should inform practice: provides evidence on what works, and what does not. • Research should inform policy: document and inform policy debates with empirical data and analysis • Research should facilitate a process where research questions emerge from the local policy context and policy and programmatic decisions are guided by research outcomes. • Good research on microfinance requires good relationships with practitioners! 10