Studying Microfinance & its Impacts (or Lack Thereof): What Next?

1. Studying Microfinance & its Impacts (or Lack Thereof):What Next? Jonathan Zinman Federal Reserve Bank of NY* Microfinance Mini-Conference NYU April 28th, 2005 * Views expressed are those of the authors and do not necessarily represent those of the Federal Reserve System or the Federal Reserve Bank of New York.

2. Overview of Talk • Quick intro to “market field experiments” • The billion (trillion?) dollar question…. IMPACTS? • Related, underlying mechanisms • Methodology Issues re: field experiments • Interplay with other methodologies • Interplay between theory, practice, empirical tests

3. Opening Credits:Market Field Experiments • Most of themes, projects discussed here stem from joint work with Dean Karlan (Princeton/Yale) • What we’ve been doing: • Designing “market field experiments” to address key questions • Including some deep theoretical ones that get to the very fundamentals of consumer choice and market transactions • Finding financial institutions willing to implement randomized-control designs as part of their day-to-day operations • Working with institutions to implement experimental protocols subject to operational constraints • This type of partnership between academics and firms is novel, especially in a market setting

4. What Do We Know About Microfinance Impacts? • Very little scientific evidence about the “Promise” (Morduch) of beneficial impacts on individuals, markets, society • Theory and practice far ahead of convincing empirical evidence

5. Measuring Impacts: Key Issues • Better, “cleaner” methodologies that can isolate causality are key • Example: Karlan-Zinman (ongoing) working with lenders in Manila and South Africa to randomly assign credit to marginal applicants • Define and measure impacts broadly • KZ follow-up surveys collect data on health and mental health (e.g., stress levels), school attendance, and employment status • Focus on the marginal borrower • I.e., at least as important to contemplate expansions of MFI activity as it is to justify existing activity • Benchmark any impacts against alternative (social) investments • I.e., can’t ignore opportunity cost of allocating resources to microfinance

6. Mechanisms Underlying Impacts (or lack thereof) • Theme: too little evidence on the micro decisions and markets that determine whether microfinance, properly designed will have positive impacts • Field experiments can help generate evidence

7. Mechanism #1: Household/consumer choice How do (poor) households make (financial) decisions? Examples of key questions (& related current research): • Response to incentives? • (KZ on information asymmetries) • Response to intertemporal tradeoffs • (DMM; KZ on price and term elasticities of demand for microcredit) • Importance, or lack thereof, of “behavioral” or “psychological” factors, bounded rationality; i.e., do folks make the “right” decision? • Dehejia talk today? • BKMSZ: powerful, but not totally predictable, effect of non-price cues, frames, and suggestions on credit demand

8. Mechanism #2: How do financial markets work, or not? • Lots of theory (e.g., on adverse selection and moral hazard) • Lots of practice • Little clean evidence on specific failures • Even best (more macro) work on the finance-growth nexus is very reduced-form: • Looks at symptoms of financial frictions rather than diagnosing specific problems • Particularly true of information asymmetries • Chiappori and Salanie (2000 survey article) • Nobel Committee citation for 2001 Prize

9. Mechanism #2: New evidence on specific market failures • Adverse selection and moral hazard among primary theoretical, anecdotal motivations for microfinance • Little evidence on their real-world import • Not for lack of effort, just a thorny methodological problem • KZ 2005 designs a rich market field experiment to disentangle • 3 dimensions of interest rate variation • Finds evidence of both problems

10. Interplay Between Field Experiments & Other Methodologies • Field Experiments not a panacea, but complement to other methodologies: • Strengths: • Clean evidence derived from “gold standard” methodology of behavioral sciences • Large stakes • Natural setting • Weaknesses: • Expensive • Less control than, e.g., lab • External Validity

11. Example of Methodology Interplay in Karlan-Zinman work • Playing “games” (lab techniques) to see if we can replicate key findings from market experiment on information asymms • Market experiment on info problems built in a test/comparison to standard (non-experimental) econometric approaches

12. Interplay Between Field Experiments, Theory, and Practice • New evidence is generating challenges for theorists, practitioners. Some examples: • Relationships between credit, savings, and insurance • Gender pattern in KZ on information asymmetries: women selecting, and men behaving, badly? • Optimal mechanism program/design (with more evidence on impacts, decisions, markets) • Optimal program marketing • New “behavioral” findings • Use methodology for high-freq. calibration relatively cheap • Field experiments can be used to evaluate existing programs

13. Take-Aways • Humility and hope • We know little in a scientific sense, but we’re learning a lot • Market field experiments can help answer key unresolved questions • Cooperation between researchers and practitioners absolutely critical • Field experimentation can then feed back into other, complementary methodologies • And then into program/product design and marketing

15. What Have we Learned from Interest Rate Randomizations? Re: Question #1 (Decision-Making) • Intertemporal tradeoffs: these borrowers are price-elastic on average, but: • Demand curves are relatively flat (contra recent evidence from US showing price elasticities > |1| • Elasticity is decreasing in income • Female borrowers are more elastic than males • They are more elastic with respect term (a la Attanasio, Goldberg & Kyriadzidou 2004) • See KZ 2005 on Demand Curves and Credit Constraints (new draft soon)

16. What Have we Learned from Interest Rate Randomizations? Re: Question 2. How financial markets work: • Evidence that both adverse selection and moral hazard matter: • But surprising pattern by gender: only female borrowers exhibit adverse selection, only male borrowers moral hazard • Not necessarily gender per se • Effects are large where present • 20% of defaults • Effects are consistent with “relationships” mitigating information problems • But: functional form (power) issues