Latest Findings from Randomized Evaluations of Microfinance

Access to Finance
Forum
Reports by CGAP and Its Partners
No. 2, December 2011
Latest Findings from Randomized
Evaluations of Microfinance
Jonathan Bauchet, Cristobal Marshall, Laura Starita,
Jeanette Thomas, and Anna Yalouris
1

© 2011 Consultative Group to Assist the Poor/The World Bank
All rights reserved.
Consultative Group to Assist the Poor
1818 H Street, N.W.
Washington, DC 20433 USA
Internet: www.cgap.org
Email: cgap@worldbank.org
Telephone: +1 202 473 9594
Acknowledgments
Our thanks to the following people who reviewed and
gave helpful input on this paper: Lasse Brune, Erica Field,
Nathanael Goldberg, Dean Karlan, Asim Khwaja, Meng Lu,
David McKenzie, Jonathan Morduch, Jonathan Robinson,
and Dean Yang, and from CGAP’s publications committee
Tilman Ehrbeck, Alexia Latortue, Kate McKee, and
Richard Rosenberg.

1
Latest Findings from Randomized
Evaluations of Microfinance
In 2009, the results from two microcredit impact
studies in Hyderabad, India, and Manila, the
Philippines were released to mixed responses
(Banerjee, Duflo, Glennerster, and Kinnan 2010;
Karlan and Zinman 2011). Some media declared mi-crofinance
a failure (Bennett 2009). Many in the
microfinance community dismissed these random-ized
studies as too limited to be a true reflection of
the entire sector.1
These first randomized studies caused a sensa-tion
because they challenged the dominant impact
narrative for microcredit—a narrative that rests on
loans to capital-constrained microentrepreneurs
who earn a steep return on marginal capital and
thus can repay a relatively high interest rate and re-invest
to grow out of poverty—and the way in which
that narrative had been universalized in the popu-lar
imagination. In fact, the results were more nu-anced.
What the microcredit studies really showed
is that this model of microcredit works for some
populations—those who successfully grow busi-nesses—
but not for others.
Many now agree that the expectations for micro-credit
in the popular discourse were overblown.
For some, the pendulum had swung: far from a pan-acea
against poverty, some argued that microcredit
was actually doing harm. The evidence supports
neither extreme view. In fact, the results of the
studies aligned with and confirmed some of the evi-dence
from nonrandomized methods already in the
microfinance research literature that found modest
but neither revolutionary nor deleterious impacts
from credit. While the concept of capital that will
allow poor people to unleash small business oppor-tunities
remains valid for some poor clients, not ev-ery
borrower is a microentrepreneur—take-up rates
for credit products are often surprisingly low, and
not all economic activities that poor people engage
in yield high returns. Microcredit is not transform-ing
informal markets and generating significantly
higher incomes on average for enterprises. And yet
the industry has focused almost exclusively on the
rhetoric of entrepreneurship and has overlooked
the many important benefits to households that are
using loans to accelerate consumption, absorb
shocks, or make household investments, such as in-vestments
in durable goods, home improvements,
or education for their children.
Combined with other evidence, randomized
evaluations are contributing to an emerging body of
knowledge that is creating a new narrative around
how financial services for the poor really work. As
the results from new studies have been released,
the discussion has evolved, and randomized evalua-tions
are being used to examine when particular
products and designs work, for what segments of
people, and why.
Today researchers are using randomized tech-niques
to better understand the underlying finan-cial
services needs of poor clients and what impacts
are achieved when appropriate financial services
are offered. Building on evidence from earlier non-randomized
studies, researchers are increasingly
able to work with microfinance providers to apply
these techniques to product innovation and to
tweak product design. In this way, randomized
techniques can make a significant contribution to
the field by clarifying our understanding of precise-ly
how, and under what conditions, financial ser-vices
benefit poor people.2 (See Box 1.)
Poor households clearly have other financial
needs that go beyond working capital loans to mi-croentrepreneurs.
They use a variety of informal
and semi-formal mechanisms to cope with risk,
1. See, e.g., Helms (2010).
2. Naturally, not all settings are appropriate for randomized eval-uations.
This paper does not discuss such methodological
issues in detail, but it does share findings from settings where
randomized evaluations were feasible and illuminating.

2
Box 1
Frequently Asked Questions about Randomized Evaluations
Why are randomized trials considered the most
rigorous method of impact evaluation?
In the case of evaluating a microfinance program, if we simply
compare clients to nonclients we are comparing two differ-ent
types of people: those who choose to borrow or save,
and those who do not. The ones who choose to participate
likely have different business acumen, tolerance for risk, and
other characteristics, and studies have shown that they can
be wealthier than nonclients—even before joining a microfi-nance
program. By randomly assigning access to financial
services, randomized trials ensure that the only difference, on
average, between clients and nonclients is access to the
program. Therefore any difference between the groups can
be confidently attributed as the impact of the program.
Can results from randomized trials be generalized?
Randomized trials help to establish causality. But they do
this only for the particular context of the evaluation (i.e., what
we learn from Kenya may or may not apply to Vietnam).
This is a limitation of all types of evaluation, however. Ran-domized
trials are no more or less vulnerable than other
seize opportunities, manage the risks and incon-veniences
that come from having uneven cash
flows, and smooth household consumption. They
use credit or savings to pay school fees, they save
to invest in businesses, and they use health and
crop insurance, when available, to stave off risk.
While these uses of financial services are differ-ent
from the uses initially anticipated, they are
still valuable, and the ability to manage finances
is a fundamental part of everyday life for all peo-ple
(Collins, Morduch, Rutherford, and Ruthven
2009). The financial services needs of poor
households may require different product fea-tures,
and perhaps different payment and deliv-ery
structures, but when such needs are met
methods.
An increasing number of credible studies, using both
qualitative and quantitative techniques, are helping to build
a body of knowledge about how financial services work. But
it is not a specific number of studies that will allow researchers
to assert a theory to make predictions about what happens in
other places. The only way to generalize findings is to conduct
a series of careful replications to evaluate similar approaches in
different contexts until a clear pattern emerges.
Why do researchers measure results after only one
or two years? Microentrepreneurs need much more
time to establish their businesses or build up savings,
so we should perhaps not expect to see impact on
poverty within such a short timeframe.
This is a limitation of randomized evaluations, as well as some
other evaluation techniques. Most randomized evaluations of
microfinance programs measure results after two years or less,
in part, because practitioners are typically reluctant to refrain
from serving a control group for longer than a couple years.
However, follow-up studies may be employed to estimate
long-run effects, and where practical, researchers may go back
and resurvey households after a longer period.
Why are randomized trials so expensive?
Randomized evaluations are not more expensive than other
types of evaluations. The high cost from many impact evalua-tions
comes from collecting data, such as household surveys,
to measure household welfare, whether randomized or not.
Note: For a short history of randomized evaluations, see http://www.povertyactionlab.org/methodology/when/when-did-randomized-evaluations-begin
appropriately, the impact should nonetheless be
welfare-enhancing.
Recent evaluations are helping us understand
when access to the appropriate product is welfare-enhancing,
and when it is not. And the emerging
body of evidence is both promising and highly prac-tical,
allowing practitioners to think more creative-ly
about options that will help their clients. While
microcredit in the India study showed no discern-ible
impact on measures of health, education, and
female empowerment, it led to more businesses be-ing
created and enabled poor households with busi-nesses
to change their spending patterns. Further
randomized evaluations of other products have
been far more positive on welfare impacts. A study

3
conducted in Kenya shows that access to savings
accounts for female market vendors allows them to
keep higher levels of inventory and therefore have
higher incomes. Consumer credit was shown to
have significant welfare benefits for wage earners
in South Africa. A study conducted in Ghana pro-vides
evidence that rainfall insurance helps farmers
use more fertilizers and increase their cultivation
area, and results in fewer meals missed for the fam-ily.
(See Annex 1 for a summary of the research pa-pers
discussed in this paper.)
Perhaps one of the greatest contributions from
these first randomized evaluations of microcredit
will be to help reset expectations. Far from offering
the last word on the impact of microfinance, the ex-isting
evidence instead offers a foundation for
learning what works, for whom, and under what
circumstances so that products and delivery ap-proaches
can be better used and adjusted to meet
the needs of poor people.
This paper summarizes the latest research find-ings
from a new body of empirical evidence that
uses randomized evaluations, similar to those used
in medical trials, to compare how one group re-sponds
to access to specific new financial services
against how a comparable group fares without
those services. (See Box 2.) This paper goes back a
couple of years to the first studies that used this ap-proach,
and summarizes a series of research studies
presented at the October 2010 Microfinance Im-pact
and Innovation Conference in New York.
These studies evaluated product design for a range
of financial services, including credit, savings, and
insurance. The studies discussed here were under-taken
by research affiliates of Innovations for Pov-erty
Action (IPA), the Financial Access Initiative
(FAI), and the Abdul Latif Jameel Poverty Action
Lab (J-PAL) at the Massachusetts Institute of Tech-nology;
they are all randomized evaluations unless
otherwise specified.
Part 1 of this paper reviews the main results from
randomized evaluations that measure the impact of
microcredit and microsavings on business invest-ment
and creation, consumption, and household
well-being. Part 2 presents evidence from evalua-tions
of products and delivery design. Part 3 dis-cusses
the evidence on microinsurance products.

4
Evaluating the Impacts of Microcredit
and Microsavings3
Many poor families in the developing world
have limited access to formal financial
services, including credit, savings, and in-surance.
They instead rely on a variety of informal
credit relationships with moneylenders, relatives,
friends, or merchants. Poor people also use a num-ber
of informal savings devices—for example, they
may participate in rotating savings associations or
keep their savings at home. These options are not
ideal. They tend to be unreliable, and it can be hard
to protect savers from the demands of relatives and
friends.4 Traditionally, banks and other formal fi-nancial
service providers, such as insurance compa-nies,
have not considered the poor a viable market,
and penetration rates for formal financial services
in developing countries are extremely low.5
Increasing access to financial services holds the
promise to help reduce poverty and improve de-velopment
outcomes, by enabling the poor to
smooth consumption, start or expand a business,
cope with risk, and increase or diversify house-hold
income. Microcredit stands to benefit poor
individuals who lack collateral, steady employ-ment,
verifiable credit history, or other require-ments
necessary to gain access to formal credit. In
the past three decades, access to credit has ex-panded
dramatically. Now with nearly 200 million
borrowers, microcredit has been successful in
bringing formal financial services to the poor.6
Many believe it has done much more. By putting
money into the hands of poor families, and partic-ularly
poor women, they argue, microcredit has
the potential to increase households’ health and
education, empower women, and reduce poverty.
What does the evidence say?
Recent experimental evidence from three random-ized
impact evaluations suggests that while increas-ing
access to credit does not produce the kind of dra-matic
transformations conjured in the popular
imagination, with millions of poor people springing
out of poverty simply by taking out loans and apply-ing
them to their microbusinesses, it does appear
to have some important—though more modest—
outcomes for some people. These include creating
new businesses and tipping consumption away from
temptation goods, such as alcohol, tobacco, and
snacks, so that households can invest in their busi-nesses
or buy more durable goods. This suggests
that microloans help some households reprioritize
their expenditures and smooth consumption—a
valuable function for poor households that suffer
from irregular and unpredictable income streams.
The results of these randomized evaluations find
little, if any, evidence of impact on use of healthcare,7
education, or female empowerment within the
treatment period (Banerjee, Duflo, Glennerster, and
Kinnan 2010; Karlan and Zinman 2009; Crépon, De-voto,
Duflo, and Parienté 2011). The groups that ben-efited
most from increased access to credit tended to
be men with relatively high incomes, not those typi-cally
targeted by microfinance institutions (MFIs)
(i.e., poor female entrepreneurs). Significant welfare
benefits were found in a study that extended con-sumer
credit to wage earners who were considered
marginally creditworthy because it enabled them to
withstand shocks and keep their jobs.
One evaluation of the impact of access to formal
savings for businesses in Kenya found increased
3. “Impacts” in this context refers to the effect that access to fi-nance
has on the well-being of poor people, as indicated by
business income, household income, household consumption,
health, children’s schooling, and other measures.
4. Collins, Morduch, Rutherford, and Ruthven (2009) show that
poor people use a variety of informal mechanisms to manage
cash flow, cope with risk, and seize opportunities. They also
find that at almost every turn poor households are frustrated
by the poor quality—particularly the low reliability—of the in-struments
they use to manage their meager incomes.
5. See CGAP and the World Bank (2010, p. 4).
6. According to the Microcredit Summit, as of 31 December 2009,
3,589 microcredit institutions reported reaching 190,135,080
clients (Reed 2011, p. 5).
7. Microcredit did help families deal with health shocks, but it
did not lead to greater expenditure on healthcare or better
health outcomes for children.
Pa r t 1

5
Randomized Approaches to Measuring Impacta
To evaluate the impacts of microfinance, researchers use ran-domized
techniques to assess how the lives of people in a
program changed compared to how their lives would have
changed if the program had not existed. Simply comparing
clients with nonclients cannot account for the fact that those
who sign up are likely to have both observable and nonob-servable
characteristics that make them not comparable to
nonclients. Randomized assignment, whereby one group or
individual gains access to a particular service while another
group or individual does not, allows researchers to compare
two statistically equivalent groups.
Existing evaluations follow one of two approaches: ran-domizing
MFI branch placement in new areas, or randomiz-ing
loan approval for marginally creditworthy applicants.
Randomizing MFI branch placement
The approach used by Banerjee, Duflo, Glennerster, and Kinnan
(2010) in urban India and Crépon, Devoto, Duflo, and Pariente
(2011) in rural Morocco is to partner with an MFI and randomize
the placement of new branches offering services. From a pool
of areas identified by the MFI as being places where it would be
a. For more on randomized evaluation methodologies, see Bauchet and Morduch (2010) and Duflo, Glennerster, and Kremer (2008).
b. For a discussion of the advantages and disadvantages of this approach, see Karlan and Zinman (2011).
business investment and personal income growth
among women, suggesting that savings could be an
effective tool to help the poor accumulate funds for
investment or consumption.
Credit
Impact of Grameen-style group lending
in an urban setting
Starting in 2005, Banerjee, Duflo, Glennerster, and
Kinnan (2010) conducted the first randomized im-pact
evaluation of expanding access to credit in a
new urban market. Researchers partnered with
Spandana, one of the largest and fastest growing
MFIs in India, to identify 104 slums in Hyderabad as
places where Spandana would be interested in open-ing
new branches. Fifty-two communities were ran-domly
interested in opening a new branch, the MFI randomly selects
some areas for opening new branches. Areas not selected for the
opening of a new branch make up the comparison group.
Randomizing access at the margin
A second approach, used by Karlan and Zinman in South Africa
(2010) and the Philippines (2011), is to randomize access to
credit among clients that the lending institution has identified
as being marginally creditworthy. Applicants for loans are sort-ed
into groups based on a credit scoring mechanism that mea-sures
business capacity, personal financial resources, outside
financial resources, personal and business stability, and demo-graphic
characteristics. Those with high scores are automati-cally
approved, and those with low scores are automatically
rejected. From the group that falls in the middle and is scored
borderline creditworthy, applicants are randomly assigned a
loan. This allows researchers to compare outcomes for groups
who received a loan with those who were denied credit. It also
provides the lending institution with a way to judge what differ-ence
approving more risky loans might make to its business so
that it can fine-tune its approval threshold.b
selected for the opening of a new MFI branch
offering loans to self-formed groups of six to ten
women. The typical loan averaged Rs. 10,000
(US$200), for families where the average monthly
expenditure was Rs. 5,000 (US$100) for a family of
five (Banerjee, Duflo, Glennerster, and Kinnan 2010).
Twelve to 18 months after the introduction of an
MFI branch, a comprehensive household survey was
conducted in a random sample of eligible households
in both treatment and comparison areas. Demand for
the credit product was not high: take-up was 18.6 per-cent
among households in the treatment group, 8.3
percentage points higher than in comparison areas.
People with access to microcredit were more
likely to have started a business. The probability of
starting a business increased by 1.7 percentage
points relative to comparison areas, implying that
approximately one in five of the additional MFI
Box 2

6
loans in treatment areas was associated with the
opening of a new business. Beyond the impact on
new business creation, there was no significant ef-fect
on average business profits, monthly revenues,
inputs spending, or number of employees.
Access to credit did not change the amount house-holds
spent significantly, but researchers did find a
change in how households spent. Those with an ex-isting
business bought more durable goods for their
home and business. Households that did not start a
business consumed more nondurable goods. But
those who started a new business cut back on tempta-tion
goods (tobacco, alcohol, tea, betel leaves, gam-bling,
and food consumed outside the home) and in-vested
more—tightening their belts to make the most
of the new opportunity.8 This switch from temptation
goods to investment and durable consumption in the
groups with businesses is an encouraging finding.
No evidence was found to suggest that micro-credit
was empowering women, at least along mea-sured
dimensions, such as exercising greater control
over how the household spent its money. Research-ers
also found no evidence of improved indicators
for the use of healthcare services or education.9
While media reports interpreted the lack of pos-itive
results along measurable dimensions of health,
women’s empowerment, and education as signs
that microcredit was a failure,10 Banerjee and Duflo
say this study presented clear evidence that micro-credit
was working along the dimension it was sup-posed
to. The new businesses created and the shift
away from small “wasteful” expenditures implied
that access to loans enabled households to make
clear choices to reprioritize, invest, and make the
most of the new opportunity: “The main objective
of microfinance seemed to have been achieved. It
was not miraculous, but it was working” (Banerjee
and Duflo 2011, p. 171).
Impact of Grameen-style group lending
in a rural setting
In 2006 and 2007, Crépon, Devoto, Duflo, and Pari-ente
(2011) conducted the first randomized impact
evaluation of microcredit in a rural setting. While
there are some differences, the results show some
notable parallels with the Spandana study.
Al Amana, a Moroccan microcredit institution,
opened 60 new branches serving 81 rural districts
that had no previous access to formal financial ser-vices.
Taking advantage of this expansion, research-ers
selected two similar villages at the periphery of
each district and offered group loans of 1,000 to
15,000 DH (approximately US$124–1,855) to one
randomly selected village, while the other village
would be served two years later, after the outcomes
of both groups had been compared.
After two years, loan take-up was fairly low. Only
16 percent of people borrowed from Al Amana, and
many used loans to pay off existing debt. Similar to
the results found by Banerjee, Duflo, Glennerster,
and Kinnan (2010) in urban India, there was no in-crease
in consumption and no noticeable welfare
improvements. Researchers did not find any evi-dence
that access to credit helped absorb income
shocks. Fourteen percent of households experi-enced
health shocks, while 25 percent experienced
shocks to business,11 yet there was no evidence that
consumption decreased less for people with access
to microcredit, as we would expect to see if access
to credit helped families cope with financial shocks
(Crépon, Devoto, Duflo, and Parienté 2011, p. 16).
Contrary to what was found in India, the number
of new businesses did not increase in rural Morocco
as a result of the loans, even though there was a lot of
activity in the sample in terms of businesses starting
and finishing. For individuals with existing farming
activities, access to credit increased the volume of
activity: more employees were hired from outside
the household, and sales, expenses, and profits in-creased.
In the case of livestock activities, most of
the expansion can be explained by higher savings
(livestock accumulation). There were some minor
effects on sales but no effect on profits. Animal hus-bandry
also increased, and loans were used to diver-
8. Spending on temptation goods was reduced by Rs 9 per capi-ta
per month (Banerjee, Duflo, Glennerster, and Kinnan 2010,
p. 19).
9. Households in treatment areas spent no more on medical and
sanitation items (e.g., medicines, soap) than comparison house-holds,
and among households with children, households in
treatment areas were no less likely to report that a child had a
major illness in the past year. There was no significant increase
in levels of spending on school tuition, fees, and other educa-tion
expenses or on school enrollment of teenage children (Ba-nerjee,
Duflo, Glennerster, and Kinnan 2010).
10. See, e.g., Bennett (2009).
11. Esther Duflo presentation at Microfinance Impact and Inno-vation
Conference in New York, October 2010.

7
sify the types of animals raised, increasing the asset
value of the livestock. On the other hand, micro-credit
had no effect on nonagricultural businesses.
Those with an existing business at the start of the
study reduced consumption (presumably as they ex-panded
their business) and considerably increased
savings. But for those without prior business activi-ties,
consumption increased. These changes in con-sumption
patterns are similar to those of the Hyder-abad
study (Banerjee, Duflo, Glennerster, and Kinnan
2010). The findings suggest that microcredit is an
opportunity that different people will take advantage
of in different ways—whether because of disposition
or circumstances. More evidence could help us un-derstand
the factors that affect a person’s ability to
make good use of loans.
Impact of individual microcredit loans in
a peri-urban setting
Karlan and Zinman (2011) published the first ran-domized
impact study to evaluate access to individ-ual
microcredit loans in the Philippines. Research-ers
worked with First Macro Bank, a for-profit
lender offering small, short-term, uncollateralized
credit with fixed repayment schedules to microen-trepreneurs
on the outskirts of Manila. While the
study focused on microentrepreneurs, the average
income and education level of these customers is
somewhat higher than that of traditional micro-credit
borrowers.12 The bank used credit-scoring
software to rate applicants based on business capac-ity,
personal financial resources, outside financial
resources, and personal and business stability. Some
applicants scored well above the bank’s base re-quirements
and some scored well below, but there
was a marginal group that just barely failed to meet
the bank’s criteria for lending. For the study, a num-ber
of the 1,601 sample of marginally creditworthy
applicants were randomly approved for a loan of
around 10,000 pesos (US$220), equivalent to 37 per-cent
of the average borrower’s net monthly income
(Karlan and Zinman 2011).
Eleven to 22 months later, the researchers found
that even though they borrowed more, those given
access to credit did not increase investment in their
business and they reduced their overall number of
business activities and employees. Subjective well-being
slightly declined.
But access to credit helped borrowers cope with
risk, strengthened community ties, and increased
their access to informal credit. Karlan and Zinman
(2011) conclude that microcredit may work, “but
through channels different from those often hy-pothesized
by its proponents … and that start with
the household rather than with the business.” Ac-cess
to credit lowered the demand for other kinds of
risk mitigation tools, a similar result to a study Kar-lan
and Zinman (2010) conducted in South Africa,
where wage earners with access to consumer credit
were more able to absorb shocks, and therefore
more likely to keep their jobs.
Impact of consumer credit
Karlan and Zinman (2010) worked with a consum-er
finance company in South Africa in designing an
experiment to estimate the effects of expanding
consumer credit to low-income workers in South
Africa.13 The lender had operated for over 20 years
as one of the largest, most profitable consumer
lenders in South Africa, offering small loans at high
interest rates, frequently to low-income workers
who have no collateral and must make payments on
a fixed schedule. Just over half of the sample of 787
loan applicants who had narrowly failed to qualify
under the normal underwriting criteria was offered
standard loans of US$127 (equivalent to 40 percent
of the median borrower’s gross monthly income) at
a 200 percent annual percentage rate (APR).14
The results were quite striking. Expanding ac-cess
to credit increased borrower well-being. Six to
12 months after taking out the loan, incomes were
higher for applicants in the treatment group, and
applicants in the treatment group were more likely
to have kept their jobs than those in the comparison
group. Twenty-six percent of treated households
reported an improvement in food consumption.
Subjective measures of decision-making within the
household, community status, and overall optimism
were also higher. In addition, the creation of a cred-
12. Households in the study had incomes averaging 5,301 pesos/ it history increased the probability of future loan
month/household member (US$106/month/person, or
about US$3.50/day). The Manila borrowers were far above
the official Philippines poverty line of about 1,000 pesos/
month/person, and well above the Hyderabad slum dwellers
in the Banerjee, Duflo, Glennerster, and Kinnan (2010) study,
who earned about $20/month/person.
13. Income averaged about $300 a month.
14. APR describes the interest rate for a whole year (annualized).
In this case, effective APR is used (the fee plus compound in-terest
rate calculated across a year).

8
approval in the sample by 19 percent over a 15 to 27
month horizon. All these outcomes were measured
well after the loan had been taken out and repaid.
Savings15
To study the effects of savings constraints on the
poor, Dupas and Robinson (2011) worked in collab-oration
with the Bumala village bank in Kenya to
randomly provide small business owners with ac-cess
to savings accounts.
The accounts offered no interest on deposits and
included substantial withdrawal fees. There was
nonetheless high demand for these costly savings
strategies, which suggests that the available alter-natives
were worse.16
The potential savers were market vendors, bicy-cle
taxi drivers, and self-employed artisans who did
not already have a savings account, but were inter-ested
in opening one. The researchers had them
keep daily logbooks with detailed information on
business investments, expenditures, and health
shocks.17 From this information, Dupas and Robin-son
were able to examine the impact of the savings
accounts along a variety of dimensions.
Data from the bank showed that many women
used the accounts quite intensively. For example,
25 percent of women saved more than 1,000 K Sh
(US$14.28) in the accounts, a substantial amount
given daily income of about $2 per day. Some
women saved much more. These savings translat-ed
into other positive outcomes. Four to six
months after account opening, women in the
treatment group had 45 percent higher daily in-vestment
in their businesses than women in the
comparison group. These findings suggest that
women faced significant barriers to saving, and
those constraints were important for the business-es
they run. There was no measurable impact for
men in the study.
Several categories of expenditures were also
higher for women in the treatment group. Food ex-penditures
were 10–20 percent higher, suggesting
that income had increased. Daily private expendi-tures
were also 27–40 percent higher. This latter
result also suggests higher income, though another
possible explanation is that women were better
able to shield their income from others, thus spend-ing
a higher share of their income for themselves
and their children.
Savings accounts also seemed to make women
somewhat less vulnerable to health shocks, which
were particularly common in this sample. The log-books
showed that women without savings ac-counts
were forced to draw down their working
capital in response to illness. In contrast, female
savers did not have to reduce their business invest-ment
levels when dealing with a health shock, and
were better able to afford medical expenses for
more serious illness episodes.
The study suggests that the bank accounts of-fered
were effective in increasing savings by over-coming
pressure on market women to share their
cash with others. Putting money into formal ac-counts
seemed to reduce the risk of appropriation
by relatives, friends, and neighbors.18 However, the
sample size of this study was too small to be defini-tive,
so future work will be needed to explore how
robust this finding is.
Despite the lack of evidence for positive effects
on welfare from credit, the studies so far offer tanta-lizing
evidence that there could be important poten-tial
benefits for some poor households to be gained
by helping the poor reprioritize their expenditures.
Notably, the impact study for savings showed posi-tive
outcomes for female savers. While it is still too
early to reach any definitive conclusions, particu-larly
for savings where there is just one existing im-pact
study with a small sample size, the findings give
researchers cause to explore further, and more stud-ies
are underway to see if these findings hold up in
other contexts. The next generation of studies is ex-amining
product design to see how small changes
can improve outcomes for poor clients.
15. In Part 2 we consider the impact of savings accounts com-bined
with commitment devices that address the issue of self-control
among farmers.
16. From the whole sample only 8 percent of respondents re-fused
to open an account; 39 percent opened an account but
never made a deposit.
17. Dupas, Karlan, and Robinson are currently replicating this
study in four different settings: Chile, Malawi, Uganda, and
the Philippines.
18. We use the term “formal” for consistency with the original
research paper, but the savings accounts offered by Bumala
village bank would often be called “semi-formal” since
Bumala village bank is not regulated by the Central Bank of
Kenya. It is affiliated with K-Rep bank and has private de-posit
insurance.

9
Evaluations of Product Features—
Design Matters
As the headlines and bloglines buzz with dis-cussion
of whether or not microfinance—or
more precisely, microcredit—works, several
evaluations have started using randomized ap-proaches
to explore specific questions around
product design. What would be the impact of offer-ing
flexible repayment options, of allowing for grace
periods, or of replacing group liability with individ-ual
loans? This ongoing work reveals that small de-tails
matter, sometimes enormously.
This section reviews a series of recent studies
that isolate specific features or attributes of prod-ucts
to show how even small changes in their de-sign
can yield significantly different results. These
studies offer insights for how financial service pro-viders
can tweak or improve their products to ben-efit
poor and low-income clients. We begin with
some studies that have explored variations on tradi-tional
microcredit products and, indeed, challenge
some core tenets of the microcredit movement. We
then discuss the latest evidence on the effect of
commitment savings, reminders to save, and ac-count
“labeling.”
Microcredit Design—
Disrupting Tradition
Targeting women, group liability, and weekly re-payments
that start immediately have long been
considered defining attributes of a classic micro-credit
model that is particularly strong throughout
South Asia and in some other places. Some provid-ers
see them as keys to success in keeping default
rates close to zero.
Especially in the early days of the modern micro-credit
movement, each of these features was seen as
key to reducing the risk for the provider of uncollat-eralized
lending, allowing many MFIs to operate as
sustainable, even profitable, businesses. Group liabil-ity
ensures repayment by enlisting the benefits of
Pa r t
screening and peer monitoring. Women, it is be-lieved,
pay back their loans more reliably than men
(Armendariz and Morduch 2007). (Lending to wom-en
also supports the social mission of many MFIs,
since women are more likely than men to be poor,
and income in the hands of women is more often
spent to benefit the household and the children.)19
And weekly repayment that begins right after the
loan is given decreases credit risk by creating imme-diate
discipline and a pattern of repayment.
Simply put, the model works for MFIs. But does
it work for borrowers?
Increasing evidence suggests that some of these
key design features may be far from optimal and
may actually bring negative trade-offs. Some recent
studies look in turn at group liability, the effects of
lending to women, the importance of timing for en-suring
repayment, and emerging tools for lenders to
assess and monitor the credit worthiness of clients.
Collectively, these results provide insight into im-portant
product design options that may be used to
improve financial outcomes for poor clients.
Questioning group liability
Group liability has been at the center of the peer
pressure model, which assumes that borrowers will
choose members they know to be reliable. Yet there
are some very real disadvantages of group liability.
If an emergency leads a group borrower to default,
her social and community support system can un-ravel
with it.
Beginning in 2004, Giné and Karlan (2011) ran a
study with Green Bank in rural areas of the Philip-pines
to explore whether group liability was in fact
necessary for managing default risk. The study ex-amined
what happened when the bank switched its
existing group liability model to an individual liabil-ity
model, as well as when groups of new borrowers
started out with individual liability loans.
19. See Thomas (1990), Engle (1993), and Schultz (1990).
2

10
The results showed that the shift to individual
liability did not negatively affect loan repayment for
either group. The bank also saw an increase in out-reach,
as more customers, attracted by the individ-ual
liability option, sought loans from the bank. The
study was extended to new areas, in which groups
either formed initially as individuals or as groups.
Here, too, no difference in repayment was observed,
although the credit officers were more reluctant to
open up lending groups without individual liability.
Given how such results likely rely heavily on cul-tural
context and institutional incentives, these re-sults
should not be extrapolated without caution,
but they do provide cause for challenging the pre-sumption
that group liability is a key to successfully
lending to poor people.
Strengthening the case against group liability for
MFIs is the continued low demand for formal mi-crocredit.
As mentioned in the microcredit impact
studies described earlier, poor people are not
pounding down the doors of microlenders,20 de-spite
widespread, documented use among the poor
of informal loans from friends, neighbors, or mon-eylenders.
21 One possible reason why so few poor
people take out formal loans is that the group liabil-ity
model repels risk-adverse individuals who are
not willing to co-sign for their peers.22
Women, men, and returns to capital
MFIs’ focus on lending to women is partly a conse-quence
of commercial interest, given women’s
higher loan repayment rates. Development re-search
also suggests that women tend to put more
of their earnings back into the home or into services
for their children (health, education, etc.) than men
do.23 Serving women, therefore, is good for business
and good for fulfilling a social mission.
As mentioned, the vast majority of microcredit
programs nominally extend loans for the purpose of
starting or running a business. Business loans are
seen as addressing a critical need, since formal-sector
jobs are scarce in poor communities and
poor, unemployed women often do not have the
necessary capital available all at once to invest in in-ventory
or equipment to start a business or make
necessary investments for growth. Giving women
credit, cash, or business inputs theoretically re-lieves
capital constraints and helps them take busi-ness
opportunities.
In practice, however, access to capital does not
seem to be having as large an effect on increasing
women’s incomes as development experts had
thought. The three microcredit impact studies con-ducted
in India, the Philippines, and Morocco
showed that increasing the availability of credit had
no impact on the profits of women-owned busi-nesses
(Banerjee, Duflo, Glennerster, and Kinnan
2010; Karlan and Zinman 2011; Crépon, Devoto,
Duflo, and Parienté 2011).
A 2008 study by de Mel, McKenzie, and Woodruff
on returns to capital for businesses in Sri Lanka
found that the average real return to capital was 5.7
percent per month—substantially higher than the
market interest rate—and the returns varied with
measures of ability, household liquidity, and the gen-der
of the owner. In a follow-up study (2009) the
researchers show that women-owned businesses
earned no returns from either cash or in-kind grants,
compared to men in the study who earned high re-turns
from both. These results could have been en-tirely
explained by environment, however, given
that only 35 percent of women participate in the
work force in Sri Lanka and may choose low-return
sectors for their businesses (World Bank n.d.).
To test whether the results held in an environ-ment
with higher female participation, McKenzie
and Woodruff partnered with Fafchamps and
Quinn from the University of Oxford to study fe-male
and male entrepreneurs in Ghana, a country in
which 74 percent of women participate in the
workforce (World Bank n.d.). In Ghana, the re-searchers
gave either cash grants or grants of in-kind
inventory or equipment to different male and
female entrepreneurs, to see whether cash had a
different effect than in-kind capital, and whether
20. Loan take-up from MFIs was only 16 percent in rural Mo-rocco
(Crépon, Devoto, Duflo, and Parienté 2011) and 18.6
percent in urban India (Banerjee, Duflo, Glennerster, and
Kinnan 2010).
21. See Collins, Morduch, Rutherford, and Ruthven (2009).
22. Context may make a big difference to the effects of the group
lending approach, and not all of the literature points in the
same direction. For example, a World Bank study (Carpela,
Cole, Shapiro, and Zia 2010) exploits a natural experiment
and shows benefits of group lending.
23. See, e.g., Engle (1991).

11
women responded differently than men.24 They
did, on both counts.
Cash grants to female entrepreneurs in Ghana
produced no return on capital, just as in Sri Lanka.
Yet in Ghana, the in-kind gifts of inventory or
equipment showed a significant average return for
women. The researchers found that when given
cash, women invested less of the gift in the busi-ness,
splitting pieces off for household purchases
or other expenses. They also found an important
nuance: the high returns from in-kind gifts came
entirely from the women who had larger, higher
profit businesses at the outset. Women with below-average
profits (around $1 a day) saw no benefit in
terms of profit from either form of grant. Male
business owners, on the other hand, saw significant
returns to capital from both the in-kind grants and
the cash grants.
These findings from Ghana are certainly more
encouraging for female microentrepreneurs than
the earlier findings from Sri Lanka. But even in
Ghana, it was only the larger female-owned busi-nesses
that benefited in terms of profit. Women
from the general population are not always, nor, in-deed,
more likely to be, able to convert capital into
profits, and men tend to be more successful overall.
These results suggest opportunities to adjust to
whom MFIs lend and how they structure their
products. MFIs may have a greater impact on the
women they serve if they can filter their applicant
pool to identify and target high performers. It is rel-evant
not only for knowing which clients can excel,
but also for the MFIs’ ability to offer more flexible
products. Knowing what the client is likely to earn
can allow lenders to adjust the risk profile—and the
interest rate. It even may allow institutions to add
microequity to their product portfolio, assuming
they can find effective ways to accurately monitor
business performance. It may also be time for mi-crofinance
providers to redesign their loan prod-ucts
to acknowledge what many already know—
that loans are often used for nonbusiness purposes.25
The role of timing—delaying repayment
Growing a business, no matter the size, often re-quires
entrepreneurs to make investments and then
wait for those investments to mature. Yet the inflex-ible
nature of the typical microcredit programs, in-volving
weekly, or monthly, repayments that begin
the first week or month after the loan is given, may
not provide the necessary time for investments to
show a yield. Many loan recipients, in fact, set aside
part of the loan from the beginning to ensure they
can make the first two or more payments. So clients
are not investing the full bulk of the funds, and they
may be avoiding investments that require a longer
period to yield returns.
When Field, Pande, Papp, and Rigol (2011)
looked at small business loan design in the United
States, they saw that business loans build in a grace
period of a few months between when the funds are
given and when the borrower has to begin paying
the loan back. Between 13 percent and 15 percent of
U.S. business borrowers default, compared to be-tween
2 percent and 5 percent of microcredit bor-rowers
in developing countries, a significant in-crease
in default risk for the lender. Yet the key
question—does increased repayment flexibility cor-relate
with increased profit and still allow the lend-er
to manage default risks adequately—is important
enough from the development perspective to war-rant
examination.
In West Bengal, India, the researchers (2011)
compared the outcomes of two groups of micro-credit
borrowers with the Village Welfare Society.
One group received a traditional group microcredit
product with semi-weekly payments that started
immediately after receipt of the loan, and the sec-ond
group was awarded a two-month grace period
before repayment began.
24. Fafchamps, McKenzie, Quinn, and Woodruff (2011) offer
grants instead of loans because many banks require that their
clients already be business owners or have an idea for a start-up
that the banks deem worthy; likewise, entrepreneurs who
take loans may be more willing to take risks. Both factors po-tentially
create a study population that is more savvy or more
likely to be successful than the average population, so they
work with existing entrepreneurs and provide them with
grants as a technique for preventing bias.
25. As noted, in practice poor clients are not only using loans to
invest in businesses, but also as a means to manage their
household cash flow, for emergencies, and to smooth con-sumption.
While theory of impact is quite different, the use
of microcredit or savings for consumption smoothing may
nonetheless be important for the overall well-being of
clients.

12
The grace period group members invested 6 per-cent
more of their loans in their businesses than
borrowers who received no grace period, and two
years after the loans were given, those grace period
borrowers saw 30 percent higher average profits.
Household income was also higher on average for
the grace period borrowers.
However, the average result masks significant
variation within the grace period group. The 25
percent average profit increase came about because
some of the women did extremely well with the de-layed
payment loans. Unfortunately, big wins for
some were matched by big losses for others—9 per-cent
of the individuals in the grace period group ul-timately
defaulted on their loans, compared with a
2 percent default rate among individuals with the
standard weekly repayment structure.
In 2008, the Village Welfare Society participated
in a study measuring the effects of weekly versus
monthly meetings on loan repayment (conducted
by Feigenberg with Field and Pande). When the re-searchers
found that the monthly meetings did
not affect repayment, the bank switched to month-ly
meetings, as the operational savings were sub-stantial.
These results again suggest significant opportu-nities
for both high-functioning borrowers and the
institutions that serve them. Banks could commer-cialize
business loans with a two-month grace pe-riod
for all borrowers who want it by increasing the
interest rate on those loans sufficiently to make up
the losses from default. It is not clear how much
such high rates would affect demand.
Another, more nuanced, approach is to identify
who the high-potential borrowers are before set-ting
product terms. Such individualized service of-fers
the possibility of creating a targeted product—
whether loan or microequity—built around that
person’s potential earnings, and tailoring loan
amount, term, and price accordingly.
The role of the borrower—client screening
as a product design tool
Financial service providers would be well-served
by any technique or tool that would allow them to
predict in advance who the high performers might
be. Banerjee, Duflo, Glennerster, and Kinnan (2010)
delved into their microcredit impact data from Hy-derabad
to identify some shared characteristics
among those individuals in their sample who were
more likely to start a business, but they have not
tested whether that information predicts successful
use of a loan when used as a selection tool.
Creating that selection tool is a high priority for
Khwaja, of Harvard’s Kennedy School. Khwaja’s
work focuses on the developing world’s small
firms—enterprises that have outgrown microcredit,
but that still lack the collateral and the size to easily
secure financing from a mainstream bank. These
businesses typically find it very difficult to grow
past the micro level for lack of investment capital.
This absence of small, formal firms is known as
the “missing middle,” and it is a problem, not only for
the high-potential poor who have the ability to grow
but lack the necessary capital, but also for poor en-trepreneurs
who have trouble increasing their in-come
from self-employment. High-potential micro-entrepreneurs
need financing, and the banks that
fund them need an inexpensive and reliable way to
sift through a pool of candidates and pull out those
with the highest potential for success.
The challenge is not insignificant. The banks and
venture capital firms that typically provide business
financing screen ideas for their business value and
the entrepreneur’s ability to pay back by delving
into credit or business histories or conducting an
in-depth evaluation of the business idea. These op-tions
are not viable with microfirms, however, be-cause
of their small size and smaller predicted re-turns.
For small firms, banks really need to know
about the ideas, skills, and trustworthiness of the
individual borrower.
Khwaja focused on the potential of automated
psychographic evaluation tools for measuring an
entrepreneur’s ability and honesty. The psycho-graphic
test is based on tools used by human re-source
departments in developed countries. These
tests are prevalent in other contexts, they are diffi-cult
to game, and the results tend to correlate with
entrepreneurial success.
To test their appropriateness for funding high-potential
microbusinesses, Khwaja has conducted a
number of tests around the world to see if the psy-chographic
tools work to identify high potential en-trepreneurs
with good ideas, strong business ability,
and honest character. Khwaja and his colleagues

13
developed a 30–40 minute computerized psycho-graphic
test to measure the test taker’s intelligence;
implicit, practical business skills; and psychology or
character (Is he honest? How does she view the
world, etc.?). To date, more than 2,000 entrepre-neurs
in seven countries have taken the test. They
have had different levels of experience, and they
have sought loans of varying sizes (from $2,000 to
$150,000). Khwaja’s pilot data show that the test
meets or exceeds the predictive ability of credit
scoring models used in developed countries, and it
effectively predicts financial success for micro or
small business entrepreneurs who do not have fi-nancial
histories.
The test is also uncovering some nonintuitive in-dicators
of business failure. For example, test takers
who scored higher for intelligence actually achieve
lower profits; honesty also correlates with lower
than average profits—in both cases, these effects
were stronger for women than men. The indicators
of success seem more obvious. Individuals with
strong drive do much better, and those with busi-ness
skills do moderately better than the average.
Making the borrower do the work
Khwaja’s approach puts the onus on the lender to
extract and evaluate that information and use it to
make a lending decision. Giné, Goldberg, and Yang
take a different approach.
Giné, Goldberg, and Yang (2011) evaluated the
impact of improving the lending institution’s abil-ity
to withhold credit from past defaulters and re-ward
good borrowers with expanded credit on
borrower behavior. Their study focuses on paprika
farmers in rural Malawi, where group liability and
frequent repayments are impractical, since crop
failure usually affects everyone in a region, and
farm income from this cash crop arrives all at
once. Likewise, there is no central identification
system in Malawi, so borrowers who default have
little problem accessing future loans, either by us-ing
a different name or seeking financing some-where
else. Together, these factors make it diffi-cult
for the lender to use loan access as an incentive
to encourage repayment—the customer knows de-fault
will likely have little consequence.
The researchers sought to improve the lender’s
ability to identify borrowers through the use of bio-metric
identifiers. Applicants in the study answered
questions about their business, their past borrow-ing
experiences, and their households, and they
were given a presentation on the importance of
maintaining a clean credit history to ensure future
access to credit. Some of the borrowers then had
their thumbprint recorded and were given a further
demonstration of how the print would be used to
identify them in the future.
Data collected at the beginning of the study were
used to identify borrowers predicted to be high-risk,
based on their probability of business success
and likelihood of repayment. As a result of the fin-gerprinting
intervention, borrowers predicted to be
least likely to repay showed a significant change in
behavior. Fingerprinted borrowers in this group
took smaller loans when they knew they could be
identified and were more likely to repay their loans
on time as well as eventually, compared to equiva-lent
borrowers in the comparison group.
Fingerprinted borrowers in the high-risk group
also allocated more of their land to the production of
paprika (the crop that the in-kind loan was intended
to finance) and invested more inputs, such as fertil-izer,
in the paprika crop. In addition to improving the
repayment performance of high-risk borrowers, be-ing
in the fingerprinting system may have further
benefits for well-performing borrowers if their good
credit histories can be stored and used to access bet-ter
borrowing conditions from other institutions.
Savings Design
As early as 1999, Rutherford showed that poor peo-ple
are active money managers: they look for ways
to “save up” (to create a usefully large sum of money
by storing it somewhere) or to “save down” (taking
a loan and repaying it later out of future savings).
Given that the poor do save, why don’t they use
those savings to finance business investments?
Experts agree it might be hard for poor individ-uals
with variable income to get together enough
money to start a business, but running a business
theoretically should not require further outside
funding, given that many microenterprises earn
high returns. Ananth, Karlan, and Mullainathan
(2007) conducted a survey that showed it would

14
not take much for vegetable market sellers in In-dia—
who usually finance the purchase of daily in-ventory
with loans from the moneylender—to save
a very small amount from the business every day,
equivalent to the amount needed to buy a cup of
tea. Within 28 days, those market sellers would
have saved the same amount that they borrow ev-ery
day. At this point, they would no longer need
cash from the moneylender and could instead use
savings for inventory purchases, thus saving even
more because they don’t have to pay the money-lender’s
high interest rates (Ananth, Karlan, and
Mullainathan 2007). Yet the vegetable vendors do
not do it. Ananth, Karlan, and Mullainathan tried a
number of different techniques to nudge the mar-ket
sellers to use savings for their businesses. For
instance, they tried giving vendors a “top up” grant
that restored savings after an emergency. They also
offered “financial literacy” training that taught the
vendors about the compounding effects of in-creased
savings and decreased interest rate pay-ments,
under the theory that the vendors did not
fully understand how much the moneylender was
costing them. Yet nothing seemed to change the
typical practice of frequent borrowing from the
moneylender.
Psychology offers a number of theories for why
people do not save enough for productive invest-ments,
despite having the apparent means to do so.
One theory suggests that some individuals simply
value the present more, and therefore prefer spend-ing
available funds immediately rather than saving
them. The future is unknown, so they don’t see
much use in considering it. Another possibility is
that people want to save, but self-control issues
make it difficult for them to resist the temptation to
use extra cash today rather than save it for tomor-row.
Limited attention can also explain the lack of
savings as people fail to foresee the need for cash in
the future. Last, there is the reality that not-quite-as-poor
individuals may receive a lot of pressure from
friends and family members to share any (relative)
windfalls or help on a day-to-day basis pay for re-curring
or emergency expenses, which eat away at
savings. Innovations in savings product design
therefore aim to help savers overcome one or more
of these challenges.
Commitment savings
Commitment savings accounts are one of the prime
innovations that have come out of recent efforts to
help poor people save. Commitment savings ac-counts
require the saver to deposit a certain amount
of money in a bank account and relinquish access to
the cash for a period of time—usually until a certain
date or until a certain dollar amount has accumulat-ed.
Such lack of access is valuable as a way of protect-ing
the cash both from the impulses of the savers
themselves, and from the hands of family and neigh-bors.
Ashraf, Karlan, and Yin (2006) conducted a
study on commitment savings accounts in the Philip-pines
that show they are effective at increasing sav-ings,
especially for people with self-control issues.
More recent studies have examined how a com-mitment
savings product helps farmers to adopt the
use of fertilizer and invest more in their crops. As
shown in randomized evaluations, farmers can earn
much stronger yields from their crops when they
take small steps, such as using fertilizer at specific
points during the growing season. Duflo, Kremer,
and Robinson (2008) show that, among maize farm-ers
in western Kenya, the annualized return to ½
teaspoon of fertilizer at top dressing (when the maize
plant is knee high) was almost 70 percent per year.
Despite this evidence, few farmers consistently
use fertilizer, largely because they earn all their in-come
for the year at harvest and do not have suffi-cient
funds left over to buy it at planting. In a fol-low-
up study, Duflo, Kremer, and Robinson (2010)
show how a simple commitment product can in-crease
fertilizer use. A field officer visited farmers
immediately after harvest and offered them an
opportunity to buy a voucher for fertilizer, at the
regular price, but with free delivery. The results
showed that free delivery early in the season in-creases
fertilizer use by 47–70 percent.
To benchmark this effect, a second treatment
group was made the same offer of free delivery later
in the season, while a third was offered a 50 percent
subsidy later in the season. If farmers are complete-ly
rational, then the effect of free delivery later in
the season should be the same as earlier, and the ef-fect
of the subsidy should be greater. However, the
effect of the commitment device was greater than
offering free delivery, even with a 50 percent subsi-dy
on fertilizer, later in the season.

15
Based on that knowledge, Brune, Giné, Goldberg,
and Yang (2011) estimated the impacts of facilitat-ing
access to a savings account coupled with a com-mitment
device as a mechanism to encourage sav-ings
among cash crop farmers in Malawi. The
evaluation allowed farmers to put funds into a spe-cial
account where withdrawals were restricted for
defined periods. The idea was to help farmers to
buy inputs by better dealing with self-control prob-lems
and cash demands from their social network.
In the study, farmers in the treatment group were
randomly assigned to receive assistance in either
opening an ordinary savings account or opening an
ordinary account with a commitment device.
The results of the evaluation showed the com-mitment
treatment had a large positive effect on the
amounts of deposits and withdrawals made imme-diately
before the planting season. On average, the
net effect on deposits (savings balance) was positive
although not statistically significant. Along with in-creasing
savings previous to the planting seasons,
the commitment device also had positive effects in
terms of a number of outcomes of interest. Farmers
in this treatment group had a 26 percent increase in
agricultural input use, 22 percent increase in value
of crop output in subsequent harvest, and 17 per-cent
increase in household total expenditure re-ported
in the past 30 days. Farmers who had access
to only the ordinary account showed lower or non-significant
impacts in terms of those same out-comes,
suggesting the commitment device played
an important role for these results.
Commitment savings accounts seem to help this
community of farmers less by increasing their self-control
than by shielding funds from an individual’s
social network (for better or worse).26 The study
data show that actual amounts saved in the ac-counts
were very low, ruling out that it helped indi-viduals
with self-control problems by restricting
their options to spend. Additionally, study partici-pants
who were identified as having self-control
problems experienced no different effects from the
commitment savings than their peers. Instead, the
commitment savings accounts had a higher impact
for wealthier households, a subgroup that may be
under more pressure to share. The existence of the
commitment device may have allowed farmers to
credibly claim that money was inaccessible.
Reminders to save—making tomorrow
real today
Beyond commitment savings, there are other inno-vations
in savings product design that try to combat
the tendency to spend, rather than save, limited re-sources,
by making the future seem more real and
relevant. These design innovations try to call the
saver’s attention to her long-term goals, based on the
theory that people get distracted by the everyday
and need help remembering, and properly prioritiz-ing,
the future. For example, a number of efforts to
promote savings accounts ask the savers what goals
they have for their savings, and then find ways to
regularly remind them of that goal. One program
had savers bring a representative photograph of
their goal—the new bicycle she wanted, for example,
or the new cook stove. The bank then created puz-zles
with the pictures and gave the saver a piece of
the puzzle every time she made a deposit (Karlan,
McConnell, Mullainathan, and Zinman 2011).
Four recent studies have examined the effects of
two different approaches to making the present
more salient to savers: one approach is to use re-minders,
the other is to offer “labeled” accounts.
The studies on savings reminders took place in
Peru, Bolivia, and the Philippines, where savers
were sent either letters (in Peru) or SMS text mes-sages
(in Bolivia and the Philippines) reminding
them to save. Karlan, McConnell, Mullainathan,
and Zinman (2011) varied the messages to test the
effects of different wording. Some savers received
generic messages that said simply that they should
save; others received messages that referenced a
specific purchase that the saver said she wanted to
make with her savings.
The studies found that reminders increased av-erage
savings balances overall by 6 percent, but this
impact increased substantially, to 16 percent, for the
Peruvian savers when the reminder referred to a
purchase goal. In the environments where SMS
text reminders were employed and automatically
executed, the cost of employing reminders to save
26. Note that this important finding points to a tension between
individual well-being and that of the community. It could be
that the introduction of commitment savings devices work
well for those who take them up but could also harm mem-bers
of their social network.

16
is very low, making text reminders a highly cost-effective
way to increase savings.
Account labeling offered an even greater return
for study participants in eastern Ghana.27 People
have long used the technique of “labeling” to allo-cate
funds for different purposes, and such labeling
can be highly effective at protecting the funds allo-cated
for, say, the rent from being siphoned for oth-er
purposes. Some use mental tallying to allocate
the funds; others literally place different amounts
in different jars or envelopes. With this approach in
mind, existing clients of the Mumuadu Rural Bank
in eastern Ghana were asked about their savings
goals; some were given the opportunity to open
separate, parallel savings accounts labeled “educa-tion,”
“business,” “housing,” or some other category.
The study found that savers eligible to open parallel
accounts saved 31 percent more on average than
those in the comparison group, with the greatest ef-fect
seen for the education label.
The strong effects of commitment savings, text
reminders, and account labeling show that small
design changes can help poor people save more, and
in some cases, to leverage those savings for positive
income-generating purposes.
Financial Product Plus: Improving
Results with Improved Skills
Many MFIs use the weekly or monthly repayment
meetings they hold with their clients as an opportu-nity
to teach some other relevant skill. No discus-sion
of financial product design would be complete
without commenting on these add-ons as a func-tion
of product design.
Add-on services—sometimes referred to as “mi-crofinance
plus”—vary significantly in their focus
and goals. Some of these programs provide useful
secondary skills, such as health education, with the
goal of helping customers avoid or lessen the im-pacts
of disruptive events on income and savings.
Others aim to equip customers with business or
financial management skills that they can use to
improve income generation.
A lack of financial literacy and basic accounting
skills offers one hypothesis for why the poor as a
whole do not experience significant income gains
when given access to formal credit—perhaps they
do not have the skills to compare the likely returns
of different investments and account for them ac-cordingly.
Yet there is little concrete evidence on
the effects of business or financial management
skills training on poor entrepreneurs. Karlan and
Valdivia (2011) found positive impacts of a business
training program for microcredit borrowers in a
study they conducted in Peru. Yet a paper by Cole
and Shastry (2009) on U.S. participation in savings
and investment markets showed that the education
level and cognitive ability of the participant corre-lated
with positive gains, but that financial literacy
training had no effect.
With the jury still out on the value of providing
financial and business training, Drexler, Fischer,
and Schoar (2011) tested whether financial literacy
training can improve business outcomes for small
businesses in the Dominican Republic. The re-searchers
tested the effect of two different sets of
content: one focused on traditional, principles-based
accounting rules taught in the curriculum of-fered
by organizations, such as Freedom from Hun-ger
and BRAC; the other taught simple accounting
rules of thumb, which essentially amounted to in-structing
the business owners to keep personal and
business accounts separate.
The researchers found that the business owners
who received the rules-of-thumb training applied
sound accounting principles more often than their
peers. For example, they were more likely to keep
their business and personal cash and accounts sep-arate,
they were more likely to keep records, they
were more likely to calculate their revenues, and
they were less likely to make mistakes when report-ing
any of their results. Those who received the
rules-of-thumb curriculum also earned more reve-nue
than their peers, especially during “bad” weeks.
Though the researchers are careful not to extend
their findings outside the specific group studied,
the results seen from rules-of-thumb education in
this one study suggest that less may well be more
when it comes to training poor business owners in
27. S tudy by Karlan, Osei-Akoto, Osei, and Udry (forthcoming). sound financial practices.

17
Poor people face an enormous amount of risk
in their lives. A major effort is currently un-derway
to expand access to insurance prod-ucts
that improve upon traditional risk-sharing
arrangements and informal insurance networks to
help poor households deal with weather shocks
and irregular income from agriculture. In theory,
microinsurance—insurance targeted to the poor
through low premiums and/or low coverage lim-its—
should be in strong demand to act as a safety
net for poor families whose crops may fail, whose
livestock may die, and who may suffer from the ef-fects
of bad weather and health shocks. This section
introduces some encouraging research results on in-novations
in microinsurance. Recent findings sug-gest
that microinsurance has positive impacts on
poor households, but persistent low rates of take-up,
even for effective products, show that product
design matters tremendously.
Design matters
The difficulty in designing good insurance products
partly comes from problems of information asym-metry—
when one party to a contract holds more
information than the other. For one thing, people
who are insulated against risk may behave differ-ently
than they would have if they were fully ex-posed
to the risk (what insurers call moral haz-ard).
Second, higher risk individuals may be more
likely to buy more insurance, which would not
matter as long as the insurer could charge that in-dividual
higher premiums to cover the risk. But if
the insurance company is unable to identify the
higher risk individuals, it responds by increasing
the premium for everyone. Both these information
asymmetries can push up premiums and contribute
to low take-up of products.
No perfect design solution has been found to
eliminate issues of asymmetric information, but
some types of risk should be easier to insure than
others. Rainfall insurance stands out among these
3
(Karlan and Morduch 2009; Banerjee and Duflo
2011). Rainfall insurance pays a set amount when
rainfall, as measured by a local weather station, is
lower or higher than established thresholds. Be-cause
rainfall is not under the control of insurance
clients, their behavior does not influence the possi-bility
of a payout (moral hazard is eliminated).
Rainfall insurance is also simpler and cheaper to
administer than many other types of insurance; be-cause
rainfall is a public event, insured households
do not need to file claims, and insurance companies
do not need to spend time and resources verifying
the validity of claims.28
Rainfall microinsurance holds promise to help
households reduce their exposure to risk, and may
modify farmers’ incentives to invest in riskier but
more profitable crops or varieties. But take-up rates
remain puzzlingly low.
Impact of rainfall microinsurance on
household decision-making
Giné, Menand, Townsend, and Vickery (2010) mea-sured
two different types of possible impacts of
rainfall microinsurance in Andhra Pradesh, India:
how well does having insurance help farmers cope
with an agricultural shock (in their case, a drought),
and how does having access to insurance affect
household decision-making, even in the absence of
a claim? Preliminary results indicate that insurance
does not increase the use of inputs or change the
allocation of land, although having access to rainfall
insurance does cause farmers to shift toward more
risky, rain-sensitive crops, which typically provide
higher profit.
In an ongoing project in Ghana, Karlan, Osei-
Akoto, Osei, and Udry (forthcoming) focus on how
Microinsurance and Household
Decision-Making
Pa r t
28. One potential drawback in the design of rainfall insurance is
the possibility of a gap between the amount of rainfall mea-sured
at the weather station and the actual losses suffered by
clients at their precise location, particularly if the two are far
from each other.

18
rainfall insurance helps rural households improve
their farm decision-making, in particular whether
microinsurance can help lower the risks of agricul-ture
production and counter farmers’ risk aversion.
The study couples rainfall insurance with cash
grants in four randomly selected groups of farmers:
in one group, farmers receive both insurance and
subsidy, another group receives insurance only, an-other
group receives capital only, and a final group
receives neither capital nor insurance, serving as a
comparison group.
Providing insurance and capital together (i.e.,
subsidizing the purchase) produced the most im-pact.
Farmers in the insurance and capital group
increased their spending on farm chemical inputs
by 47 percent, increased their cultivation area by 22
percent, and were less likely to have members of
their household miss meals than the comparison
group. Farmers in the insurance-only group
changed some of their farming decisions, but to a
lower extent than farmers in the insurance and cap-ital
group. This suggests that reducing risk is bene-ficial
by itself, but much greater impact may come
by looking at poor households’ financial needs in a
more comprehensive way.
Challenges in promoting microinsurance
products
Why, if having insurance has such potentially large
impacts, are take-up rates among poor farmers so
low?29 Cole et al. (2011) report take-up rates for a
rainfall insurance product in India between 23 and
29 percent, even though the households cited
droughts as the most significant risk they face.
About 40 percent of households in the Karlan,
Osei-Akoto, Osei, and Udry Ghana project bought
a rainfall insurance product at the actuarially fair
price (the price that covers average payouts, but
not the costs of administering the product).
In a 1994 study in rural Thailand, Townsend
showed that households use informal insurance
mechanisms to maintain a certain level of con-sumption
even when income fluctuates. Other re-search,
however, indicates that these informal
mechanisms do not cover all risks. Duflo and Udry
(2004), for example, showed that husbands and
wives fail to insure each other perfectly when a lack
of rainfall affects the yield of crops grown exclu-sively
by one or the other. In a survey in Andhra
Pradesh (Cole et al. 2011), 89 percent of households
reported that drought is the most significant risk
they face. Asked why they do not purchase insur-ance,
less than 25 percent of the surveyed house-holds
(and as low as 3 percent in one sample) indi-cated
that they did not need it.
Cole et al. presents the best evidence to date to
explain why take-up rates remain so low. Re-searchers
measured take-up of a microinsurance
product that protects farmers in Andhra Pradesh,
India, against too little or too much rainfall. The
researchers assigned a sample of potential clients
to receive various offers and information about the
product. Each offer or information set was de-signed
to isolate one possible cause of low take-up:
the price of the policy, the availability of cash in
the household to purchase the policy, the under-standing
of rainfall measurements by the potential
client, the level of trust of the potential client to-ward
the insurance scheme or the insurance mar-keting
agent, and the framing of the information
describing the insurance.
As expected, the price of the insurance policy is
a strong determinant of whether households buy
the product. Take-up increased by 10.4 percent on
average (from an overall average of 24–29 percent)
when the premium decreased by 10 percent. Price,
however, is not the only determinant of demand. In
Cole et al.’s survey, “lack of available funds” was the
most commonly cited reason for not purchasing in-surance.
Potential clients may also lack information about
and understanding of how formal insurance works.
However, Cole et al. show that receiving additional
information about the product did not cause an in-crease
in take-up.
Finally, lack of trust in the insurance provider
may be another reason why poor households do not
buy policies. To measure whether trust is indeed a
significant driver of take-up, Cole et al. evaluated
takeup of the insurance product when the market-ing
team was accompanied on their visits to house-holds
by an individual from Basix, a nongovern-
29. See also Karlan, McConnell, Mullainathan, and Zinman (2010). mental organization that the farmers know well,

19
versus when the team went out on its own. The re-searchers
found that households that were visited
by a marketer accompanied by a member of Basix
were 10 percentage points more likely to purchase a
policy, suggesting that trust is a significant issue.
While far from providing a complete picture,
these studies together do provide a more nuanced
and precise set of information on how to better de-sign,
price, and market microinsurance products so
that the supply of products for poor clients can
meet the real need in a cost-effective manner.
Conclusion
While still based on a relatively small number of
studies, the work of researchers and participating
microfinance providers is bringing new knowledge
about how clients use capital, what helps them to
save, and what constraints they face that prevent
them from benefiting more from financial access.
The overall message from this body of work is that
poor people face various limits, and their ability to
capitalize on opportunities varies greatly. One of
the next steps is to find simple ways to identify
those differences and cater to them with the right
products delivered with the right design.
Details matter. Purpose does as well—not all bor-rowers
want to grow a business. The variable results
seen can be as much a function of borrower intent as
borrower ability. A one-size-fits-all product will not
bring benefit to the borrowers or profit to the provid-ers.
Instead, the microfinance industry needs to con-tinue
to mature in ways that allow it to view poor
customers as individuals. Some of those individuals
will leverage financial services to smooth consump-tion;
some to manage risk; some to make investments
they have the skill and resources to profit from; some
will do all of the above. With a view of serving all of
these needs, microfinance providers may evolve a
new generation of improved services and products
that reliably and flexibly help poor people.

Annex 1
Researchers Location Financial Service Intervention Abhijit Banerjee, Esther Duflo, India microcredit Researchers evaluate the impact of access to credit by randomizing Rachel Glennerster, and the placement of new Spandana MFI branches in Hyderabad, India. Cynthia Kinnan (2010) Lasse Brune, Xavier Giné, Malawi microsavings Researchers evaluate whether commitment devices can reduce self- Jessica Goldberg, and control problems and cash demands from social networks. Farmers Dean Yang (2011) were randomly assigned to receive either assistance to open an ordinary savings account, or to open an ordinary account with a commitment device. Shawn Cole, Xavier Giné, India microinsurance Researchers investigate the importance of price and nonprice Jeremy Tobacman, Petia determinants in the demand for rainfall insurance by randomly Topalova, Robert Townsend, varying the price of the insurance policy, randomly assigning certain and James Vickery (2011) households’ positive liquidity shocks, or randomly assigning endorse-ments
20
by a trusted agent. Other experiments test the role of financial
literacy, product framing, and other behavioral biases.
Bruno Crépon, Florencia Devoto, Morocco microcredit Researchers evaluate the impact of access to credit in a rural setting Esther Duflo, and William by randomizing the placement of new Al Amana MFI branches in Pariente (2011) Morocco. Alejandro Drexler, Greg Fischer, Dominican financial literacy/ Researchers evaluate the impact of financial literacy training on and Antoinette Schoar (2011) Republic business training business outcomes for small enterprises in the Dominican Republic. Two methods of financial literacy training are tested: (1) classic accounting principles, and (2) simple accounting “rules of thumb.”
Esther Duflo, Michael Kremer, Kenya return to capital/ Researchers measure the rates of return for different quantities of and Jonathan Robinson (2008) inputs fertilizer used on crops in Kenya. Esther Duflo, Michael Kremer, Kenya commitment device Researchers evaluate an intervention to test whether providing and Jonathan Robinson (2010) mechanisms to save harvest income for future fertilizer purchases could be effective in increasing fertilizer use among farmers. Pascaline Dupas and Kenya microsavings Researchers investigate the importance of savings constraints for Jonathan Robinson (2011) microenterprise development by randomly providing small business owners in Kenya with access to savings accounts. Erica Field, Rohini Pande, India microcredit Researchers investigate how the term structure of debt influences John Papp, and Natalie entrepreneurship among the poor. Borrowers were randomly assigned Rigol (2010) either the classic microfinance contract with repayment beginning immediately after loan disbursement or a contract that provides a two- month grace period prior to repayment. Xavier Giné, Jessica Goldberg, Malawi microcredit Researchers evaluate the impact of an improved personal identification and Dean Yang (2011) system on loan repayment. Randomly selected borrowers who applied for loans for agricultural inputs in rural Malawi had fingerprints collected as a part of the loan application process.

21
Main Findings Paper
No discernible impact on measures of health, education, and female empowerment. The Miracle of Microfinance? Evidence from a
More businesses were created. While some households increased nondurable Randomized Evaluation
consumption, others reduced expenditure on temptation goods, such as alcohol,
tobacco, tea, and snacks, and instead invested in their businesses, or bought more
durable goods.
The commitment treatment had a large positive effect on the amounts of deposits and Commitments to Save: A Field Experiment in
withdrawals made immediately prior to the planting season and a positive effect on Rural Malawi
agricultural input use, leading to a 22 percent increase in the value of the crop output,
and a 17 percent increase in total household expenditure. Farmers who had access only
to the ordinary account showed lower or nonsignificant impacts on the same outcomes.
Insurance did not increase the use of inputs or change allocation of land, but having Barriers to Household Risk Management: Evidence
access to rainfall insurance did cause farmers to shift toward more risky, rain-sensitive from India
crops, which typically provide higher profit.
No discernible impact on measures of health, education, and female empowerment. Impact of Microcredit in Rural Areas of Morocco:
For individuals with existing farming activities, access to credit increased the volume Evidence from a Randomized Evaluation
of activity. Microcredit had no impact on nonagricultural businesses. Those with an
existing business at the start of the study reduced consumption and considerably
increased savings. But for those without prior business activities, consumption increased.
Business owners who received the rules-of-thumb training applied sound accounting Keeping It Simple: Financial Literacy and Rules of
principles more than their peers. Those who received the rules-of-thumb training also Thumb
earned more revenues than their peers, especially during “bad” weeks.
Farmers earn much stronger yields by using fertilizer at specific points during the How High are Rates of Return to Fertilizer?
growing season. The annualized return to half a teaspoon of fertilizer at top dressing Evidence from Field Experiments in Kenya
(when the maize plant is knee high) was almost 70 percent per year.
The commitment device offering an opportunity to buy a voucher for fertilizer but with Nudging Farmers to Use Fertilizer: Theory and
free delivery early in the season increased fertilizer use by 47 to 70 percent. The effect Experimental Evidence from Kenya
of the commitment device early in the season was greater than other offers, such as free
delivery later in the season, and a 50 percent subsidy also offered later in the season.
Access to formal savings accounts for market stallholders led to increased business Savings Constraints and Microenterprise
investment and personal income growth. Four to six months after account opening, Development: Evidence from a Field Experiment in
women in the treatment group had a 4.5 percent higher daily investment in their Kenya
businesses than women in the comparison group. There was was no measurable impact
for men in the study. Several categories of expenditures were higher for women in the
treatment group. Savings accounts also seemed to make women somewhat less
vulnerable to health shocks.
The grace period group members invested 6 percent more of their loans in their Term Structure of Debt and Entrepreneurial Behavior:
businesses than borrowers who received no grace period, and two years after the loans Experimental Evidence from Microfinance
were given, they had 30 percent higher average profits. Household income was also
higher. However, the average result masks significant variation within the grace period
group: some of the women did really well, while others suffered losses. Nineteen percent
of the individuals in the grace period group ultimately defaulted on their loans compared
with 2 percent default for the individuals with the standard repayment structure.
As a result of the fingerprinting intervention, borrowers predicted to be least likely to Credit Market Consequences of Improved Personal
repay showed a significant change in behavior. Fingerprinted borrowers in this group Identification: Field Experimental Evidence from
took smaller loans when they knew they could be identified, and were more likely to Malawi
repay their loans on time as well as eventually, compared to equivalent borrowers in
the comparison group.

Annex 1, continued
Researchers Location Financial Service Intervention Xavier Giné, Lev Menand, India microinsurance Researchers summarize results of previous research on rainfall Robert Townsend, and James insurance markets in India, which provides evidence that price, Vickery (2010) liquidity constraints, and trust all present significant barriers to increased take-up. Xavier Giné and Philippines microcredit Researchers investigate whether group liability is in fact necessary Dean Karlan (2011) for managing default risk. In one treatment, existing group-lending clients of the Green Bank of Caraga were randomly converted to an individual liability model. In a second treatment, new borrowers
22
started out with individual liability loans.
Dean Karlan, Edward Kutsoati, Ghana microsavings Researchers evaluated the impact of a new type of “labeled” savings Margaret McConnell, Margaret account that was intended to help clients save by focusing their attention McMillan, and Christopher on their savings goals. Existing clients of the Mumuada Rural Bank Udry (forthcoming) in Eastern Ghana were asked about their savings goals, and some
were given the opportunity to open separate, parallel savings
accounts labeled “education,” “business,” “housing,” or some other
category.
Dean Karlan, Margaret Peru, Bolivia, microsavings Researchers measure the effectiveness of sending savings reminders McConnell, Sendhil Philippines in the form of letters (in Peru) or SMS text messages (in Bolivia and Mullainathan, and Jonathan the Philippines) to clients holding programmed savings accounts. Zinman (2011)
Dean Karlan, Isaac Osei-Akoto, Ghana microinsurance Researchers investigate the role of risk in constraining farmer Robert Osei, and Chris Udry investment and technology adoption choices, and to evaluate its (forthcoming) importance relative to constraints on credit, by coupling rainfall insurance with cash grants. Dean Karlan and Peru financial literacy/ Researchers evaluate the marginal impact of adding business Martin Valdivia (2011) business training training to a group lending program in Peru. Dean Karlan and South Africa microcredit Researchers estimate the effects of expanding access to expensive Jonathan Zinman (2010) consumer credit in South Africa by randomizing loan approval for clients identified by the cooperating lender as being marginally creditworthy.
Dean Karlan and Philippines microcredit Researchers evaluate the impact of increasing access to credit in the Jonathan Zinman (2011) Philippines by randomizing loan approval for clients identified as marginally creditworthy. Suresh de Mel, Sri Lanka return to capital/inputs To evaluate whether there are high returns to capital for micro- David McKenzie, and enterprises, researchers randomize the provision of cash and equipment Christopher Woodruff (2008) grants to small firms in Sri Lanka, and measure the increase in profits arising from exogenous (positive) shock to capital stock.
Marcel Fafchamps, Ghana return to capital/inputs Researchers evaluate the differential effects of providing either cash David McKenzie, grants or in-kind grants of inventory or equipment on both male and Christopher Woodruff, female entrepreneurs. and Simon Quinn (2011)

23
Main Findings Paper
Preliminary results indicate that insurance does not increase the use of inputs or Microinsurance: A Case Study of the Indian
change the allocation of land, although having access to rainfall insurance does Rainfall Index Insurance Market
cause farmers to shift toward more risky, rain-sensitive crops, which typically provide
higher profit.
The shift to individual liability did not negatively affect loan repayment for either group. Group versus Individual Liability: Short and Long-
The bank also saw an increase in outreach, as more customers, attracted by the Term Evidence from Philippine Microcredit Lending
individual liability option, sought loans from the bank. Groups
Savers eligible to open parallel accounts saved 31 percent more on average than
those in the comparison group, with the greatest effect seen for the accounts labelled
“Education.”
Reminders increased average savings balances overall by 6 percent. This impact Getting to the Top of Mind: How Reminders Increase
increased substantially, to 16 percent, for the Peruvian savers when the reminder Saving
referred to a purchase goal.
Farmers who receive both insurance and capital (i.e., subsidizing the purchase) Examining Underinvestment in Agriculture:
increased their spending on farm chemical inputs by 47 percent, increased their Measuring Returns to Capital and Insurance
cultivation area by 22 percent, and were less likely to have members of their household
miss meals than the comparison group. Farmers who received insurance changed only
some of their farming decisions, but to a lower extent than those who had the
capital also.
The results found positive impacts from business training. Teaching Entrepreneurship: Impact of Business
Training on Microfinance Clients and Institutions
Expanding access to credit increased borrower well-being: incomes increased, food Expanding Credit Access: Using Randomized Supply
consumption went up, and measures of decision-making within the household Decisions to Estimate the Impacts
went up, alongside community status and overall optimism.
Net borrowing increased in the treatment group relative to the comparison. However, Microcredit in Theory and Practice: Using
the number of business activities and employees in the treatment group decreased Randomized Credit Scoring for Impact Evaluation
relative to the comparison, and subjective well-being declined slightly. However,
microloans increased ability to cope with risk, strengthened community ties, and
increased access to informal credit.
The average real return to capital was 5.7 percent per month—substantially higher than Returns to Capital in Microenterprises: Evidence from
the market interest rate. Returns varied with measures of ability, household liquidity, a Field Experiment
and the gender of the owner (men fared better than women).
Cash grants to women entrepreneurs produced no return on capital, whereas in-kind When Is Capital Enough to Get Female Enterprises
gifts of inventory or equipment to women showed a significant average return. When Growing? Evidence from a Randomized Experiment
given cash, women invested less of the gift in the business, splitting off pieces for in Ghana
household purchases or other expenses. The high returns from in-kind gifts came
entirely from the women who had larger, higher profit businesses at the outset.
Women with below-average profits (around $1 a day) saw no benefit in terms of
profit from either form of grant. Men-owned businesses, on the other hand, saw
signficant returns from both the in-kind grants and the cash grants.

24
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Latest Findings from Randomized Evaluations of Microfinance

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