Transcript Put Your Money Where Your Butt Is: A Commitment Savings

Financial Services to the Micro,
Small and Medium Enterprises
Dean Karlan
Yale University
Innovations for Poverty Action
stickK.com
Two Themes
• Apply Behavioral Economics to product design
• Find win-win evaluation strategies:
– Measure social impact
AND
– Improve operations
Behavioral Economics
Assumptions of Behavioral Economics
• Humans vs. Econs
• Bounded Rationality
– including bounded attention
• Bounded Willpower
• Bounded Self-interest
Escalator Lesson
• People are complicated. No one model
predicts a person’s behavior.
• Design matters
Suppose you received one of these letters:
What would be most important to you?
Direct Mail Lesson
• The “normal” things economists look at aren’t
always the drivers.
• Behavioral economics has expanded the
standard set of behavior drivers…
Behavioral Economics
• Theoretical behavioral economics:
– Tries to understand, develop models, etc. to
predict behavior better (and heterogeneity)
• Applied behavioral economics:
– Tries to figure out how to use behavioral
economics to make the world a better place
Nudges
Anyone who designs the environment in which
people make choices is a “choice architect”
– Menus
– Store layouts
– Organ donorship
– Retirement savings plans
– One last amusing one, and then banking
Urinal, Amsterdam Airport
Applications in Banking
• Commitment contracts
– Savings
• Reminds to save
– Increased savings by 6% in three country study!
• But also..
– Smoking
– Weight loss
Goals and Commitment
• Three “truths” for most if not everyone:
– You have set goals for yourself in the past.
– You have not achieved every one of those goals.
– You regret not having achieved some of them.
Commitment Contracts
• Make your vices more expensive
• Make your virtues cheaper
• The obvious:
– Savings
– Weight loss
– Smoking
– Exercise
Philippines: Savings
• “SEED” for the Green Bank of
Caraga in Mindanao
• Simplest “commitment:” no
withdrawals until goal amount or
date is reached
• No increase in interest rates for
illiquidity
• 28% opened an account
• 300% increase in savings for
those who opened an account
• Similar to “Christmas Clubs” in
the USA, popular in the past
Philippine: Smoking
“Committed Action to Reduce and End Smoking”
• Minimum deposit of 50 pesos ($1.25)
• CARES lock box to help clients save daily
• No access to the money in the account for 6
months
• No interest-bearing
• Weekly deposit collection service (the service
stops if the client fails to deposit for 3
consecutive weeks)
• Must pass a urine test within 1 week of the 6
month maturity date in order to gain access to
the money in the account
Philippine Smoking: Results
• 83 out of 781 (11%) individuals offered
CARES signed a contract.
• 29 of 83 passed at 6 months
• Of the 29 who passed at 6 months:
• 14 passed and 15 failed at 12 months
• Of the 54 who failed at 6 months:
• 7 passed and 47 failed at 12 months
• 30 percentage points more likely to stop
smoking
Mexico: Corporate Employee Wellness Program
• Contracts for employees
– Lose weight
– Stop smoking
– Read more
– Play more
– Complete tasks on time for work
• No financial incentives
• But psychological commitment
• And public visibility
Behavioral Economics: Conclusions
Humans are imperfect. We need all
need help.
We can improve choices without
restricting options.
Nudges can work.
Part II: Win-Win for Social Impact
• Many ways to improve programs
• Evaluation, done well
– Looks forward, Not backwards
– Is an investment, not a cost
– Helps improve profits, not merely prove impact
Outline
• Four specific projects to describe
– Reminders to save
– Small/medium enterprise mentoring/consulting
• Mexico
– Price: expanding access to credit
• South Africa and Mexico
– Credit scoring to measure impact of loans
• Philippines and South Africa
Reminders to Save:
Peru, Bolivia & Philippines
• Attention problem: Savings is “saliencedisadvantaged” relative to debt
• Do the poor save everything they can? Or does
attention to needs influence savings?
• Three country study
• Impact:
– Increase savings by 6% with monthly reminder
– Increased likelihood of reaching goal by 3
percentage points
Mentoring/Consulting Project
• Run by Mexican state government
• Firms apply for grants for consultants/mentors
from consulting firms in Puebla
• Limited supply of grants for eligible firms
– Thus randomization good for two reasons:
• 1) Helped solve political problem, by choosing
randomly no complaints of favoritism when allocating a
scarce resource
• 2) Provides powerful impact evaluation by independent
researchers to help strengthen future policy discussions
• Fairly small sample, 433 firms
Results
• After one year
• Monthly firm sales & profits up 78% and 110%
respectively
• Productivity increased
– Productivity defined as profits unexplained by
assets
Demand Elasticities
• Large-scale experiment in Mexico,
Compartamos Bank
• Randomized over branches spread throughout
entire country
• Incorporates general equilibrium effects
Price
•
•
•
•
Huge variance in rates around the world
Huge variance in depth of outreach
Significant debate, especially in high rate countries
Two sides to the calculation
– Costs
– Demand
• Most of the data/analysis/discussion is on costs
• For years, World Bank (CGAP) and others pushed to
raise rates, to get to sustainability
Compartamos experiment
• Randomization at branch level
• Data collected over 19 months
• Two “take-up” sets of data
– Specific face-to-face marketing
– Natural over time process, i.e., branch level
outcomes with normal marketing, growth, gossip
and general equilibrium effects
Experimental Design
•
•
•
“Crédito Mujer” village banking
loan product only for women
Bank branches grouped into 80
geographic clusters across Mexico
– Half assigned “high” rate
– Half assigned “low” rate
Difference of 10% (0.50% per month)
Branch Locations
“high” rate
“low” rate

Final sample included
132 branch offices in 80
geographic clusters across
Mexico
Results: More Clients
Total Number of Clients per cluster per month
6000
5000
4000
3000
2000
1000
0
Low Rate
High Rate
Total Clients
Results: Larger Loan Portfolio
Total Loan Amount per cluster per month (1000s, Pesos)
40000
35000
30000
25000
20000
15000
10000
5000
0
Low Rate
High Rate
Total Loan Amount
All together for Compartamos
• Compartamos is a for-profit
• Impact on society important
• Promise to investors of course is that helping
society can be profitable.
• Revenues increased by about 11%
• Costs did too
• Net impact on profits: up about 3%
– Statistically same as before
Measuring Social Impact
with Credit Scoring
• Credit scoring
– Difficult for SME sector
– Even more difficult for nicroentrepeneurs
– Much to be learned about optimal system
• How to balance hard and soft information
• How to build incentives for long term client loyalty
• How to maintain safe banking principles
Experiments to measure impact
• Impact studies of microcredit have been done
– and done and done and done…
– Questions linger regarding identification
• Basic selection problems:
– Who chooses to borrow?
• Entrepreneurial spirit? Resourceful individuals?
– Who do MFI’s agree to lend to?
– Program placement: MFI’s target growing areas
Microcredit Randomized Trials
• Now we are beginning to see a wave of them
– South Africa: urban/peri-urban, for-profit, individual lending, formal sector
employed individuals (Karlan and Zinman, 2008)
– Philippines: urban Manila, for-profit, individual lending (Karlan and Zinman,
2009)
– India: Spandana, urban Hyderabad, for-profit, group lending (Banerjee, Duflo,
Glennerster and Kinnan, 2009)
– Peru: Arariwa, rural, village banking, non-profit (Karlan and Zinman, 2010?)
– Mexico: Compartamos, peri-urban/urban, village banking, for-profit
(Angelucci, Conley, Karlan and Zinman, 2011?)
– Morocco: Al-Amana, rural, village banking, non-profit (Crepon, Duflo and
Pariente, 2010?)
– Philippines: FICO and First Valley (getting under way, 2012?)
– Bosnia: for-profit, individual liability, urban and rural (Augsburg, de Haas,
Hamgart and Meghir, 2011?)
– Mongolia: group liability, rural, Attanasio et al
Simple but critical test
• One theory: markets are actually complete.
• High prices for informal credit
– Incomplete credit markets?
– Or higher price for better service?
• Will increased loans  higher debt or change
in debt composition?
• If so, prima facie evidence for credit
constraints
Basic Methodology
1. Lender randomizes marginal loan applicants:
1 – 30
Auto reject
31 – 45
Randomly
46 – 59
Randomly
approve 60%
approve 85%
60 – 100
Auto approve
100-point credit scorecard based on applicant’s:
• Business capacity
• Personal financial resources
• Outside financial resources
• Personal and business stability
• Demographic characteristics
Basic Methodology
2. Follow-up with household survey that measures:
•
•
•
•
Borrowing, broadly defined
Business income, expenses, and profits
Investments, broadly defined
Psychological and political outlook
Surveyors completed 1,114 of 1,601 in sample for
70% response rate.
Number of days between treatment and follow-up:
Mean
Median
Standard Dev.
411
378
76
Why did the bank do this?
Weekly credit committees: slow, costly, subject
to inconsistencies of subjective scoring.
Computerized credit scoring fast (loan decision in
1 hour!) and quantitatively-based.
Future scorecard revision requires data points on
“below the line” applicants.
Market Settings
Small-business Microloan market in Philippines:
•
•
•
•
•
•
•
For-profit rural bank
Regulated but no viable credit bureau
Unsecured
Individual liability
High-risk
Short-term (13 weeks), fixed repayments
Expensive by many international
standards (63% APR)
Results
• Loan use increases: 9.6% more likely to have a
loan
– Evidence of market failure being solved
Impacts
• Key results:
– Profits go up for men, but not women (consistent with
de Mel et al capital drop experiment in Sri Lanka)
– Cut back in firm investments and cutback in formal
insurance
– Increased education for families of male borrowers
– Increased access to informal credit
– Increased trust in community
– Increased stress (consistent finding in South Africa)
South Africa
• Similar study
• Consumer lending
• Found increase in employment after getting a
loan
• Net impact: 8 percentage point reduction in
poverty headcount ratio
Further research
• What are patterns of impact?
• When should credit be increased?
• Who should lenders (and their funders) target?
• Replication needed to further answer these
questions. No one study can satisfy the policy
questions being posed.
– Need varying competitive settings
– Need varying cultural and economic conditions.
Five ideas
• SME
– Give a choice to a microentrepreneur
• Job
Or
• Microenterprise
– What will she choose?
– What are constraints? Managerial capital? Finance? Both together?
• Credit scoring
• Electronic/mobile banking  linkages to savings accounts
• Savings
– Behavioral Economics applications
• Integration of health into banking
– CARES
Thank you!
[email protected]
http://karlan.yale.edu
http://www.poverty-action.org
http://www.stickK.com