Content uploaded by Suresh de Mel
Author content
All content in this area was uploaded by Suresh de Mel on Aug 14, 2014
Content may be subject to copyright.
DOI: 10.1126/science.1212973
, 962 (2012);335 Science et al.Suresh de Mel
Microenterprises in Sri Lanka
One-Time Transfers of Cash or Capital Have Long-Lasting Effects on
This copy is for your personal, non-commercial use only.
clicking here.colleagues, clients, or customers by , you can order high-quality copies for yourIf you wish to distribute this article to others
here.following the guidelines can be obtained byPermission to republish or repurpose articles or portions of articles
): June 16, 2012 www.sciencemag.org (this information is current as of
The following resources related to this article are available online at
http://www.sciencemag.org/content/335/6071/962.full.html
version of this article at: including high-resolution figures, can be found in the onlineUpdated information and services,
http://www.sciencemag.org/content/suppl/2012/02/22/335.6071.962.DC1.html
can be found at: Supporting Online Material
http://www.sciencemag.org/content/335/6071/962.full.html#ref-list-1
, 4 of which can be accessed free:cites 14 articlesThis article
http://www.sciencemag.org/cgi/collection/economics
Economics subject collections:This article appears in the following
registered trademark of AAAS. is aScience2012 by the American Association for the Advancement of Science; all rights reserved. The title CopyrightAmerican Association for the Advancement of Science, 1200 New York Avenue NW, Washington, DC 20005.
(print ISSN 0036-8075; online ISSN 1095-9203) is published weekly, except the last week in December, by theScience
on June 16, 2012www.sciencemag.orgDownloaded from
7. E. Mayr, Animal Species and Evolution (Harvard Univ.
Press, Cambridge, MA, 1963).
8. K. G. Ashton, M. C. Tracy, A. de Queiroz, Am. Nat. 156,
390 (2000).
9. M. Á. Rodríguez, M. Á. Olalla-Tárraga, B. A. Hawkins,
Glob. Ecol. Biogeogr. 17, 274 (2008).
10. J. L. Gardner, A. Peters, M. R. Kearney, L. Joseph,
R. Heinsohn, Trends Ecol. Evol. 26, 285 (2011).
11. B. K. McNab, Oecologia 164, 13 (2010).
12. V. Millien et al., Ecol. Lett. 9, 853 (2006).
13. F. A. Smith et al., Global Planet. Change 65, 122 (2009).
14. P. D. Gingerich, Univ. Mich. Pap. Paleontol. 28,1(1989).
15. W. C. Clyde, P. D. Gingerich, Geology 26, 1011 (1998).
16. Numerous authors have shown the use of “Hyracotherium”
to be invalid for North American equids. Thus, the species
“Hyracotherium”sandrae (PETM) and “H.”grangeri
(post-PETM) were assigned to the new genera Sifrhippus
Froelich 2002 and Arenahippus Froelich 2002, respectively.
We found, however, that characters used to separate
Sifrhippus from Arenahippus are highly variable and not
useful for generic identification. Thus, we refer both
species to Sifrhippus pending formal revision.
17. P. L. Koch, J. C. Zachos, P. D. Gingerich, Nature 358,
319 (1992).
18. F. A. Smith, S. L. Wing, K. H. Freeman, Earth Planet. Sci. Lett.
262, 50 (2007).
19. B. H. Passey et al., J. Archaeol. Sci. 32, 1459 (2005).
20. A. F. Diefendorf, K. E. Mueller, S. L. Wing, P. L. Koch,
K. H. Freeman, Proc. Natl. Acad. Sci. U.S.A. 107,
5738 (2010).
21. R.Secord,S.L.Wing,A.Chew,Paleobiology 34, 282 (2008).
22. P. D. Gingerich, Genetica 112–113, 127 (2001).
23. M. T. Clementz, P. A. Holroyd, P. L. Koch, Palaios 23,
574 (2008).
24. N. E. Levin, T. E. Cerling, B. H. Passey, J. M. Harris,
J. R. Ehleringer, Proc. Natl. Acad. Sci. U.S.A. 103, 11201
(2006).
25. J. D. Bryant, P. N. Froelich, Geochim. Cosmochim. Acta
59, 4523 (1995).
26. W. Dansgaard, Tellus 16, 436 (1964).
27. M. J. Kraus, S. Riggins, Palaeogeogr. Palaeoclimatol.
Palaeoecol. 245, 444 (2007).
28. P. D. Gingerich, Trends Ecol. Evol. 21, 246 (2006).
29. P. Stiling, T. Co rnelissen, Glob. Change Biol. 13, 1823 (2007).
30. C. E. Owensby, R. C. Cochran, L. M. Auen, in Carbon
Dioxide, Populations, and Communities, C. Koerner,
F. Bazzaz, Eds. (Academic Press, San Diego, CA, 1996),
pp. 363–371.
31. S. G. B. Chester, J. I. Bloch, R. Secord, D. M. Boyer,
J. Mamm. Evol. 17, 227 (2010).
Acknowledgments: We thank T. Bown, P. Gingerich,
B. MacFadden, K. Rose, E. Sargis, and S. Strait for
helpful discussions and advice; J. Curtis, B. Tucker,
and A. Baczynski for help with isotope lab work;
J. Bourque and A. Hastings for specimen preparation; and
P. Koch and two anonymous reviewers for helpful comments.
Supported by NSF grants EAR-0640076 (J.I.B., J.K., R.S.),
EAR-0719941 (J.I.B.), EAR-0717892 (S.L.W.),
EAR-0718740 (M.J.K.), and EAR-0720268 (F.A.M.).
Data used in this paper are available in the SOM.
Supporting Online Material
www.sciencemag.org/cgi/content/full/335/6071/959/DC1
Materials and Methods
SOM Text
Figs. S1 to S4
Tables S1 to S9
References
12 September 2011; accepted 13 January 2012
10.1126/science.1213859
One-Time Transfers of Cash or Capital
Have Long-Lasting Effects on
Microenterprises in Sri Lanka
Suresh de Mel,
1
David McKenzie,
2
*Christopher Woodruff
3
Standard economic theory suggests that one-time business grants can have at most temporary effects,
and accordingly, policies to increase incomes of the self-employed in developing countries typically
rely on sustained engagement. In contrast, we found long-lasting impacts from one-time grants given
in a randomized experiment to subsistence firms. Five years after we gave $100 or $200 to 115 of 197
male and 100 of 190 female Sri Lankan microenterprise owners, we found 10-percentage-point-higher
enterprise survival rates, and $8-to-$12-per-month-higher profits for male-owned businesses that
received the grants. Female-owned businesses showed no long-term (or short-term) impacts. Our
follow-up investigation interviewed 94% of the original sample and collected survivorship data
from the remaining 6%, demonstrating that tracking long-term outcomes is both feasible and
worthwhile. The results suggest that one-off grants may have lasting impacts on some types of
subsistence firms, challenging the view that sustained engagement is always required.
Self-employment is one of the major sources
of income for the urban poor across the
world, with between 47 and 69% of poor
(per capita income less than $2 per day) house-
holds in urban areas in Indonesia, Pakistan, Peru,
and Nicaragua running a business (1), most often
without paid employees. Typical policies to im-
prove the incomes of these households and their
businesses are based on sustained provision of
services. Three such programs are (i) microfinance,
which is often based on the expectation of a succes-
sion of loans, and in many cases regular follow-up
meetings with clients in groups (2–4); (ii) condi-
tional cash transfer programs, which typically give
households regular transfers over a period of years
(5,6); and (iii) business training programs, which
are based on the idea that capital alone is not
enough—as in the ancient proverb “give a man a
fish and he eats for a day, teach a man to fish and
he can feed himself for life”—with some evidence
suggesting that training works best when accom-
panied by one-on-one follow-up visits (7).
But can just giving a fish feed a man for life?
That is, does the much simpler policy of giving a
one-time grant to small business owners have any
long-term effect? Traditional economic models
of firm investment such as the Ramsey model
predict that there is an efficient size for a busi-
ness, conditional on the owner’s ability level. Any
shock to capital in this model will have only
temporary effects, and the firm will quickly re-
turn to the steady state. In such a model, an extra
infusion of capital in the business can speed up
convergence to this steady-state efficient size but
cannot have any long-term effect (8).
In contrast, a one-off infusion of capital can
have a permanent impact on business invest-
ment if there are poverty traps or under-investment
caused by production nonconvexities (in which
the only profitable investments are lumpy ones,
such as buying a large machine, and where it may
be not be possible to operate a business if capital
falls below some threshold level) (9); if there are
self-control problems and time-inconsistent pref-
erences (for example, in which today an individ-
ual prefers that tomorrow he or she reinvests
profits in the business, but when tomorrow comes
prefers to spend the money) (8,10); or if there
are intra-household inefficiencies (for example,
owners may underinvest when they expect pro-
ceeds to be taken by a spouse or other family
members) (8,11). Knowing whether the tradi-
tional models or these alternatives best describe
1
Department of Economics, Universityof Peradeniya, Peradeniya
20400, Sri Lanka.
2
Development Research Group, The World
Bank, Washington, DC 20433, USA.
3
Department of Economics,
University of Warwick, Coventry CV4 7AL, UK.
*To whom correspondence should be addressed. E-mail:
dmckenzie@worldbank.org.
Table 1. Impact of the grants on business survival rates and reporting profits. Data are ordinary
least squares results of the impact of the grant on (i) whether the business was closed in 2010, as
measured in the June 2010 and December 2010 survey rounds and by observation and proxy
reports for firms not interviewed, and (ii) whether it reports profits in either survey round.
Robustness to excluding proxy reporting is shown in table S2. Sample size is 197 for male-owned
firms and 190 for female-owned firms. Huber-White SE are shown in parentheses. *, **, and ***
denote impact is significantly different from zero at the 10, 5, and 1% levels, respectively.
Males Females
Closed Reports profits Closed Reports profits
Treatment amount (in 10,000s of LKR) –0.109*** 0.0876** 0.0252 –0.0176
(0.0401) (0.0378) (0.0558) (0.0546)
Control group mean 0.29 0.77 0.26 0.77
24 FEBRUARY 2012 VOL 335 SCIENCE www.sciencemag.org962
REPORTS
on June 16, 2012www.sciencemag.orgDownloaded from
the world is crucial for designing policies to
help poor entrepreneurs as well as for charitable
giving decisions. However, to date there is no
long-term evidence on the effect of one-time
injections of capital into these small businesses.
Does it matter whether the “fish”is given to a
man or a woman? Microfinance has traditionally
focused on women, with the belief that their busi-
nesses are smaller and more credit-constrained
and thus in more need of access to capital (12).
For example, 96% of the clients of the Grameen
Bank, which is probably the most famous mi-
crofinance organization, are female. Grameen’s
founder, Nobel laureate Muhammad Yunus, has
famously argued that capital, not skills, is the con-
straint on these businesses, stating that “giving
the poor access to credit allows them to imme-
diately put into practice the skills they already
know”(13). Yet in many societies, women face
social constraints and additional demands on their
time from household responsibilities. These may
limit the types of business they operate, and thus
the ability of capital alone to generate expansion
of their subsistence-level enterprises.
In April 2005, we began a randomized ex-
periment among 408 microenterprises with no
paid employees in urban Sri Lanka, in which
grants of 10,000 or 20,000 Sri Lankan Rupees
(LKR) (approximately US$100 to $200 at the
time)weregiventojustoverhalfofthesefirms.
Half of those grants were given as cash, the other
half as in-kind purchases of equipment or ma-
terials for their business. In the short term (within
2.5 years of receiving the grants), we have found
that these grants led to relatively large increases
in business profits for male owners but no change
in business profits for female business owners
(11,14). Here, we report on the results of re-
interviewing the same firms in June and Decem-
ber 2010, between 4.5 and 5.5 years after the
one-time grants were given, enabling measure-
ment of the long-run impacts on business sur-
vival and profitability.
This Report’s main contribution is in pro-
viding evidence that one-off grants can have
longer-term effects on microenterprises. One
critique of randomized experiments in develop-
ment economics is that they tend to focus only
on short-term impacts (15,16). There are a few
recent studies that track long-term outcomes in
health and education (17–21); a further contri-
bution of this Report is being the first to track
outcomes over a longer period for firms. Track-
ing firms over longer periods is important in
order to be able to distinguish between the stan-
dard Ramsey model, in which any impacts of
additional capital are temporary, and other mod-
els of firm behavior in which effects may persist.
It also is important for measuring impacts on firm
survival that may take several years to material-
ize. Yet, there are questions about the incentives
of researchers to continue monitoring impacts
over longer periods, as well as the feasibility of
doing so because of sample attrition. This Report
illustrates that it is both feasible and beneficial to
track impact trajectories for a firm intervention
over longer periods of time.
Our baseline sample was obtained via a door-
to-door screening survey of households in se-
lected administrative units of urban areas in the
Kalutara, Galle, and Matara districts of Sri Lanka.
The target population was microenterprise owners
aged 20 to 65 who worked at least 30 hours per
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
0 1020304050607080
Real Monthly Profits in Sri Lankan Rupees
Months since Baseline Survey
Male Control Male Treatment
Female Control Female Treatment
Intervention
Window
Fig. 1. Mean monthly real profits by survey round for treatment and control firms by gender. Data are
from the 13 rounds of the Sri Lanka Microenterprise Survey. Intervention window shows the time period
during which the one-time grants were given. The data for males are also shown in fig. S3, with pointwise
95% confidence intervals.
Table 2. Test of equality of treatment and control means in sample of
firms that survive to report profits in 2010. Columns show means of base-
line or time-invariant variables by treatment status for the 161 male-owned
firms and 151 female-owned firms surviving to report profits in either or
both the June 2010 and December 2010 survey rounds. Pvalues are from
ttestsofequalityofmeans.AnFtest of joint orthogonality of these char-
acteristics to treatment status has a Pvalue of 0.410 for males and 0.211
for females.
Males Females
Control Treatment Pvalue Control Treatment Pvalue
Business characteristics
Age of business (years) 10.37 12.54 0.240 9.25 11.22 0.232
Real profits in month of March 2005 (LKR) 4748 4919 0.778 2883 2669 0.578
Real revenue in month of March 2005 (LKR) 16098 14554 0.583 8818 7455 0.453
Total invested capital stock excluding land and buildings March 2005 (LKR) 32231 30290 0.649 21038 21278 0.951
Firm is in trade sector 0.51 0.50 0.922 0.43 0.44 0.958
Hours in the business worked by the owner in March 2005 59.27 55.70 0.282 51.84 44.73 0.065
Owner characteristics
Age of owner 44.06 42.05 0.280 39.65 42.77 0.073
Years of education of owner 7.97 8.89 0.059 10.03 9.04 0.050
Number of digits recalled in digit-span recall test 5.91 5.97 0.778 5.73 5.71 0.915
Household asset index 0.18 0.07 0.656 0.77 0.33 0.053
Implied coefficient of relative risk aversion from lottery game 0.27 0.49 0.421 –0.29 –0.09 0.363
www.sciencemag.org SCIENCE VOL 335 24 FEBRUARY 2012 963
REPORTS
on June 16, 2012www.sciencemag.orgDownloaded from
week in their business, had no paid employees,
and had less than 100,000 LKR (~US$1000) in
capital, excluding land and buildings. These
criteria were intended to restrict our focus to the
types of subsistence microenterprises that are
most prevalent among the poor in developing
countries (22). The baseline interviews were carried
out in April 2005.
The resulting sample consists of 408 micro-
enterprises, of which 197 are male-owned, 190
female-owned, and the remaining 21 jointly run
by husband and wife. We dropped the last group
given its small size and the important differences
in effects by gender, but show in table S1 pooled
results that include these jointly owned firms.
The sample then contains a diverse group of the
types of subsistence businesses typical in urban
areas in most developing countries: small grocery
stores, bicycle repairmen, food preparation (such
as string hoppers and lunch packets), sewing
clothing, and small-scale manufacture.
At baseline, in April 2005 the average male-
owned firm had monthly profits of 4,700 LKR
and a median capital stock, excluding land and
buildings of 25,000 LKR, and the average female-
owned firm had monthly profits of 2,800 LKR
and a median capital stock, excluding land and
buildings of 10,000 LKR. At an exchange rate of
US$1 = 100 LKR, monthly profits were thus in
the range of $1 to $2 per day for many firms. The
median owner was in his or her early 40s, had been
running the firm for 5 to 7 years, with male owners
having a median of 9 years and female owners a
median of 11 years schooling. Differences between
male and female owners in the types of businesses
they run and background of the owners are dis-
cussed in supporting online material (SOM) text 3.
In June 2010, we re-surveyed 348 of the
387 baseline firms (90%). In a second long-term
follow-up round in December 2010, we surveyed
356 firms (92%). Only 24 of the 387 (6.2%) male-
or female-owned firms could not be contacted in
either survey because of being deceased (two peo-
ple), migrating abroad (six people), migrating inter-
nally outside of the study areas (seven people),
refusals (three people), or being unable to be found
(six people). This high follow-up survey rate shows
the possibility of doing long-term follow-ups with
low attrition. Through physical observation and
discussions with neighbors, we were able to verify
whether the business had closed or not by the end
of 2010, even for those firm owners not interviewed.
We began by testing whether the one-time
grants affected the likelihood of a firm surviving
until the last round of our survey, and the related
question of whether the grants affected the pro-
portion of the original firms who reported profits
in either of the 2010 round of surveys (which re-
quires both the firms not to have closed and the
owners not to have refused to answer this ques-
tion). Profits were collected for existing firms,
and owners of firms that had closed were asked
for details of their profits before closure and any
current wage income. More detail on the mea-
surement of these quantities and the estimation
methodology are in the SOM text 4.
In addition to knowing whether the grants
affected survival, we wished to know whether
they affected the long-run profitability of the firm.
Mean monthly real profits by survey round, treat-
ment and control group status, and gender are
plotted in Fig. 1. Two patterns emerge. First, after
the intervention the male treatment group always
had higher mean profits than those of the male
control group, with the gap between the two not
noticeably growing or shrinking systematically
over time. Second, there was no such systematic
pattern for females, with treatment and control
groups typically having similar profits. The meth-
odology used to test whether these differences
are significant is presented in SOM text 4.
We examined whether one-off grants have
long-term effects by testing three hypotheses:
Hypothesis 1 was, “One-time grants have
no long-term effect on firm survival.”If a one-
time grant merely speeds convergence to a
firm’s optimal steady-state size as predicted by
neoclassical theory, any effect should be tempo-
rary, and we should see no effect on firm sur-
vival. Results testing this hypothesis are shown
in Table 1. We rejected the hypothesis for males:
A one-time grant of approximately $100 lowered
the likelihood of closure over the 5.75-year time
period by 10.9 percentage points and, as a result,
increased the likelihood the firm survived to re-
port profits in the 2010 surveys by 8.8 percentage
points. Given that 29% of the control firms close
down over this time period, these are sizeable
impacts, but as discussed in the SOM, they are
plausible given the size of the grants and the es-
timated monthly return on the grants. In contrast,
we cannot reject this hypothesis for females.
Table 3. Short- and Long-run impacts of grants on business profits. Data are
from the 13 survey rounds of the Sri Lanka Microenterprise Survey, from April
2005 through December 2010, and are for 197 male-owned and 190 female-
owned firms. The unbalanced panel is used so that firms do not appear in
survey waves in which they do not report profits. Truncated profits truncates
(caps) profits at the 99th percentile, reducing the influence of outliers. Log
real profits uses log of profits instead of levels as the dependent variable.
Total labor income is the sum of truncated profits and wage earnings. All
regressions include firm fixed effects and survey wave dummies. Huber-White
SEs are shown in parentheses, clustered at the firm level. *, **, and *** denote
impact is significantly different from zero at the 10, 5, and 1% levels,
respectively.
Males Females
Monthly
real profits (LKR)
Truncated real
profits (LKR)
Log
real profits
Total labor
income (LKR)
Monthly
real profits (LKR)
Truncated
real profits (LKR)
Log
real profits
Total
labor income (LKR)
Amount ×
first year
since grant
648.2**
(285.6)
685.3**
(272.5)
0.142***
(0.0486)
799.7***
(278.9)
94.79
(265.1)
107.0
(249.1)
0.0500
(0.0639)
66.18
(254.0)
Amount ×
second year
since grant
625.3
(406.4)
576.4
(384.3)
0.0927
(0.0563)
768.3*
(391.6)
206.5
(450.3)
54.30
(371.8)
0.0288
(0.0785)
27.90
(376.3)
Amount ×
third year
since grant
749.6*
(411.5)
703.8*
(392.8)
0.114*
(0.0634)
867.9**
(405.7)
3.994
(432.3)
–51.73
(391.3)
–0.0659
(0.105)
–36.33
(398.9)
Amount ×
five to six years
since grant
1218*
(622.3)
789.3
(499.6)
0.136**
(0.0637)
875.8*
(506.5)
–284.9
(450.8)
–258.9
(396.1)
–0.0914
(0.101)
–148.7
(447.6)
Mean for
control group
6864 6806 8.55 6455 3855 3724 7.77 3587
Pvalue
for testing
constant effect
over time
0.816 0.965 0.629 0.991 0.489 0.651 0.241 0.914
Observations 2212 2212 2201 2329 2148 2148 2140 2233
24 FEBRUARY 2012 VOL 335 SCIENCE www.sciencemag.org964
REPORTS
on June 16, 2012www.sciencemag.orgDownloaded from
The point estimate is actually positive (suggesting
slightly more firms who received the grant closed)
but small and statistically insignificant. These re-
sults are shown to be robust to concerns about
survey attrition in SOM text 5.
Hypothesis 2 was, “One-time grants don’taf-
fect which firms survive.”If the grants only prop
up failing firms, we should see the characteristics
of survivors in the treatment group differ sub-
stantially from those in the control group. As
shown in Table 2, this is not the case for either
male or female firms. Despite the lower failure
rate, surviving male-owned treatment firms have
similar initial profitability, revenues, and capital
stock, and operate in similar sectors, to the sur-
viving male-owned control firms. The only dif-
ference appears in owner education, which is
higher in the surviving treated firms. However,
an Ftest of joint orthogonality of these char-
acteristics to treatment status fails to show any
relationship between treatment and character-
istics of surviving firms. Among females, there
were more marginally apparent differences in
owner characteristics, but again we cannot reject
overall balance. As further shown in SOM text 5,
the entire distributions of baseline profits are sim-
ilar for surviving treatment and control, so that
the grants are not differentially affecting smaller
or larger firms within our sample.
Hypothesis 3 was, “One-off grants have at
most temporary effects on business profitability.”
Traditional economic models predict that any
impact on profits should be short-lived, merely
speeding up the transition to an equilibrium
steady-state. The results of estimating the treat-
ment effect on profits are reported in Table 3.
Consistent with Fig. 1, we found the one-time
grants had lasting impacts on firm profitability
for males but no impact in either the short or the
long run for females. For males, a 10,000 LKR
grant increased monthly profits by 600 to 1200
LKR, a 6 to 12% monthly real return. This per-
sists throughout the time period and does not
narrow dramatically (as would be the case with
a temporary effect) or increase dramatically (as
would be the case if returns compounded). This
effect is robust, and strengthened, when we look
at labor income and include the labor income
for those businesses which have closed, and are
shown in SOM text 5 to be robust to any selec-
tive attrition.
Conditional cash transfers in health and edu-
cation typically tie payments to irreversible ac-
tions, such as children attending school or getting
vaccinated. It is thus no surprise to find lasting
impacts of such programs. In contrast, half of
our grants were unconditional cash, and even the
conditional grants typically took the form of in-
ventories or raw materials that could easily have
been taken out of the business if desired. Tra-
ditional economic theory would predict that such
one-time grants would have at most temporary
effects. However, we found enduring effects for
male-owned microenterprises, with respect to both
business survival and business profitability. This
raises two questions: Why do we see these ef-
fects, and why don’t female-owned microenter-
prises also benefit?
Economic theory suggests at least three cat-
egories of reasons why a one-time grant may
have lasting effects. The first is that the extra
funding provided by the grants may have played
an insurance role, providing liquidity-constrained
firms with the ability to keep the business open
when faced with a temporary shock to the busi-
ness that might otherwise force them to close
down. As shown in SOM text 5, the main reason
for business closure in our firms was business
failure. However, the data also show that impacts
are not much greater for poorer owners or firms
with initially lower profitability within our sam-
ple. Because shocks are an important reason for
business failure, smoothing against shocks may
still help explain the lasting impacts if the fre-
quency of shocks that cause businesses to fail are
independent of business size within our sample.
A second potential explanation offered by
theory is that the grants allowed liquidity-
constrained firm-owners to make lumpy invest-
ment with high returns and that, in the absence
of the grant, firm owners would not be able to
save enough to make these investments them-
selves, getting stuck in a poverty trap (9). How-
ever, the majority of the grants were invested in
inventories, materials, and other working capital
rather than in lumpy equipment. The owners in-
creased profits by selling larger quantities and a
wider variety of products rather than dramatically
changing their production technologies. Coupled
with a lack of evidence for production poverty
traps in other urban environments (23,24), this
suggests production non-convexities are also
not the main reason for the long-lasting effects.
The real returns to capital for these male firm-
owners are around 11% per month (11). Faced
with these returns, why does not the control group
reinvest small amounts at a time, compound-
ing and growing their profits to catch up to the
treatment group? Recent behavioral theories of
decision-making (8,10,25) are a third category
of explanation and, in our view, offer the greatest
potential for explaining why one-time grants have
long-term effects. These theories also may help
explain the differences in outcomes for males
and females. For example, if firm owners lack
self-control or have time-inconsistent preferences,
they will keep putting off investment opportu-
nities that are profitable in the long term. Because
this leads to less capital invested in the firm, this
may also make them more vulnerable to shocks.
However, this raises the question of why this
same behavior does not lead to an immediate de-
capitalization of the grants once they are received.
Some friction in removing capital from the firm
must be present. This could either be physical
friction (it takes several days to liquidate stock,
and this is enough to overcome immediate temp-
tation) or mental accounting friction (once capital
enters the business, it is treated differently from
capital in the household).
Two factors seem to explain the lack of effect
for female-owned microenterprises. First, much
of the treatment does not get invested in the busi-
ness but gets diverted to household uses. Second,
a combination of household inefficiencies (11)
and women working in industries with low ef-
ficient scale (26) means that the money these
womendoinvestintheirbusinesshaslowreturns.
Capital alone thus does not appear to be enough to
grow subsistence-level female-owned firms. On-
going work is exploring the extent to which com-
plementary interventions such as business training
can help, or whether the other duties such as
household production and child care constrain the
extent to which women wish to grow their firms.
Overall, these results show that it is both fea-
sible and of interest to track the outcomes of a
microenterprise intervention over a substantial
period of time, and that a one-off grant can have
a lasting influence. Sometimes, giving a fish may
be enough. As with any experiment, there are
limits to the extent to how much one can gener-
alize to other settings, but there is at least evi-
dence from Ghana and Mexico that male-owned
microenterprises have substantial short-term gains
from one-time grants (8,27). Replicating these
long-run results across a number of other set-
tings therefore offers the potential to provide a
basis for rethinking theories of microenterprise
growth and the policy actions that can be used to
aid subsistence entrepreneurs.
References and Notes
1. A. V. Banerjee, E. Duflo, J. Econ. Perspect. 21, 141 (2007).
2. B. Armendáriz, J. Morduch, The Economics of Microfinance
(MIT Press, Cambridge, MA, 2007).
3. D. Karlan, J. Zinman, Science 332, 1278 (2011).
4. A. Banerjee, E. Duflo, R. Glennester, C. Kinnan, “The miracle
of microfinance? Evidence from a randomized evaluation”,
BREAD Working Paper no. 278, 2010; available at:
http://ipl.econ.duke.edu/bread/abstract.php?paper=278.
5. J. Hanlon, A. Barrientos, D. Hulme, Just Give Money
to the Poor: The Development Revolution from the
Global South (Kumarian Press, West Hartford, CT, 2011).
6. A. Fiszbein, N. Schady, “Conditional Cash Transfers:
Reducing Present and Future Poverty,”World Bank Policy
Research Report (World Bank, Washington, DC, 2009).
7. M. Valdivia, “Training or technical assistance? A field
experiment to learn what works to increase managerial
capital for female microentrepreneurs”;availableat
http://siteresources.worldbank.org/INTGENDER/Resources/
336003-1303333954789/final_report_bustraining_BM_
march31.pdf, 2011.
8. M. Fafchamps, D. McKenzie, S. Quinn, C. Woodruff,
“When is capital enough to get female microenterprises
growing? Evidence from a randomized experiment in
Ghana,”World Bank Policy Research Working Paper
no. 5706 (World Bank, Washington, DC, 2011);
available at http://go.worldbank.org/84EOCSG1I0.
9. A. Banerjee, A. Newman, J. Polit. Econ. 101, 274 (1993).
10. A. Banerjee, S. Mullainathan, “Climbing out of poverty:
Long term decisions under income stress”(Centre for
Economic Policy Research, London, 2007); available at
www.cepr.org/meets/wkcn/7/770/papers/Banerjee.pdf.
11. S. de Mel, D. McKenzie, C. Woodruff, Amer. Econ. J.
Appl. Econ. 1, 1 (2009).
12. Socio-economic and Gender Analysis Programme, “Aguide
to gender sensitive microfinance”(Food and Agriculture
Organization of the United Nations, 2002); available at
http://www.fao.org/docrep/012/ak208e/ak208e00.pdf.
13. M. Yunus, Banker to the Poor: Micro-Lending and the Battle
Against World Poverty (Public Affairs, New York, 1999).
www.sciencemag.org SCIENCE VOL 335 24 FEBRUARY 2012 965
REPORTS
on June 16, 2012www.sciencemag.orgDownloaded from
14. S. de Mel, D. McKenzie, C. Woodruff, Q. J. Econ. 123,
1329 (2008).
15. M. Ravallion, Economists Voice 6, 1 (2009).
16. M. Woolcock, J. Develop. Effective. 1, 1 (2009).
17. S. Baird, J. Haomry Hicks, M. Kremer, E. Miguel,
“Worms at work: Long-run impacts of child-health
gains”(Poverty Action Lab, 2011); available at
http://www.povertyactionlab.org/publication/worms-
work-long-run-impacts-child-health-gains.
18. SOM.1. summarizes the tracking of (17) and other health
and education papers.
19. O. Ozier, “The impact of secondary schooling in Kenya: a
regression discontinuity analysis”(2011); available at
http://economics.ozier.com/owen/papers/
ozier_JMP_20110117.pdf.
20. W. Friedman, M. Kremer, E. Miguel, R. Thornton,
“Education as Liberation?”NBER Working Papers 16939,
2011; available at www.nber.org/papers/w16939.
21. R. Jensen, Q. J. Econ. 125, 515 (2010).
22. SOM text 2 provides greater detail on the sampling
methodology.
23. D. McKenzie, C. Woodruff, Econ. Dev. Cult. Change 55,
3 (2006).
24. M. Lokshin, M. Ravallion, Stud. Nonlinear Dynam.
Econometrics 8, 1 (2004).
25. E. Duflo, M. Kremer, J. Robinson, Am. Econ. Rev. 101,
2350 (2011).
26. M. S. Emran, A. K. M. M. Morshed, J. Stiglitz,
“Microfinance and Missing Markets”(Mimeo, George
Washington University, Washington, DC, 2007); available at
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1001309.
27. D. McKenzie, C. Woodruff, World Bank Econ. Rev. 22,
457 (2008).
Acknowledgments: We thank M. Groh for excellent research
assistance and two anonymous reviewers and the editors
for helpful comments. Financial support from NSF grants
SES-0523167 and SES-0617424, the World Bank’s Gender
Action Plan, and the World Bank’s Research Support Budget
is gratefully acknowledged. The data are available at
http://www2.warwick.ac.uk/fac/soc/economics/staff/academic/
woodruff/data, and replication files are provided in
the SOM.
Supporting Online Material
www.sciencemag.org/cgi/content/full/335/6071/962/DC1
SOM Text
Figs. S1 to S3
Tables S1 to S5
References (28–32)
22 August 2011; accepted 26 January 2012
10.1126/science.1212973
Evolutionarily Assembled
cis-Regulatory Module at a
Human Ciliopathy Locus
Jeong Ho Lee,
1
Jennifer L. Silhavy,
1
Ji Eun Lee,
1
Lihadh Al-Gazali,
2
Sophie Thomas,
3
Erica E. Davis,
4
Stephanie L. Bielas,
1
Kiley J. Hill,
1
Miriam Iannicelli,
6
Francesco Brancati,
6
Stacey B. Gabriel,
7
Carsten Russ,
7
Clare V. Logan,
8
Saghira Malik Sharif,
8
Christopher P. Bennett,
8
Masumi Abe,
9
Friedhelm Hildebrandt,
10
Bill H. Diplas,
11
Tania Attié-Bitach,
3
Nicholas Katsanis,
4,5
Anna Rajab,
12
Roshan Koul,
13
Laszlo Sztriha,
14
Elizabeth R. Waters,
15
Susan Ferro-Novick,
16
C. Geoffrey Woods,
17
Colin A. Johnson,
8
Enza Maria Valente,
6
Maha S. Zaki,
18
Joseph G. Gleeson
1
*
Neighboring genes are often coordinately expressed within cis-regulatory modules, but evidence that
nonparalogous genes share functions in mammals is lacking. Here, we report that mutation of either
TMEM138 or TMEM216 causes a phenotypically indistinguishable human ciliopathy, Joubert syndrome.
Despite a lack of sequence homology, the genes are aligned in a head-to-tail configuration and joined by
chromosomal rearrangement at the amphibian-to-reptile evolutionary transition. Expression of the two
genes is mediated by a conserved regulatory element in the noncoding intergenic region. Coordinated
expression is important for their interdependent cellular role in vesicular transport to primary cilia.
Hence, during vertebrate evolution of genes involved in ciliogenesis, nonparalogous genes were arranged
to a functional gene cluster with shared regulatory elements.
Cis-regulatory modules (CRMs) provide
binding sites for transcription factors that
regulate the expression of neighboring
genes (1). Relatively little is known about the
evolution of these regulatory elements, such as
how CRMs arise or how the regulated genes
cofunction, other than the rare instance such as
Hox gene clusters evolved by gene duplication
and the addition of regulatory elements to reg-
ulate body patterning (2).
Joubert syndrome (JBTS) is the most com-
mon neurodevelopmental disorder among the
ciliopathy spectrum, which is thought to en-
compass disorders of structure or function of
cellular primary (nonmotile) cilia (3). Affected
JBTS patients show hypotonia, ataxia, abnor-
mal eye movement, and a distinct mid-hindbrain
malformation presenting the “molar tooth”sign
on brain magnetic resonance images (MTI) (fig.
S1A) (4). Mounting evidence suggests that pri-
mary cilia as cellular antennae sense a wide
variety of signals, including Shh signaling, and
play a crucial role in vertebrate development (5).
Recently, we reported deleterious mutations
of the transmembrane protein (TMEM)216 gene,
linking to the JBTS2 locus on chromosome 11,
in about half of the 10 JBTS2-linked families
(Fig. 1A) (6–8). However, the remaining half
of the JBTS2 families (verified by the pathogno-
monic MTI) were phenotypically indistinguish-
able (displaying optic coloboma, retinal dysplasia,
nephronophthisis, and occasional occipital en-
cephalocele) but were negative for mutations in
TMEM216 (fig. S1, A and B, and table S1).
Furthermore, fibroblasts from these latter pa-
tients contained intact TMEM216 mRNA and
protein expression (fig. S2, A and B), thereby
suggesting another JBTS causative gene at the
JBTS2 locus.
We thus performed resequencing of all known
and predicted exonic and promoter genetic ele-
ments within the minimal 17-Mb candidate in-
terval defined by TMEM216 mutation-negative
families (9). From these data, we identified four
missense mutations and one splicing homozygous
deleterious mutation in evolutionarily conserved
residues of the nearby TMEM138 gene of unknown
function, thus accounting for all JBTS2-linked
families (Fig. 1A, fig. S2C, and table S1). All mu-
tations segregated according to a single recessive
disease mode and were not present in 400 eth-
nically matched chromosomes. Among missense
mutations in transmembrane domains, TMEM138
p.H96R led to unstable protein when transfected
into heterologous cells (fig. S2D), suggesting loss
of function as the disease mechanism.
Although both TMEM genes encode trans-
membrane proteins (Fig. 1A), neither the genes
nor the proteins demonstrated sequence homol-
ogy or shared any functional domains. Phylo-
genetic analysis showed that they represented
two distinct protein families, which have evolved
separately from invertebrates (figs. S4 and S5),
excluding a gene-duplication event. In all higher
1
Neurogenetics Laboratory, Howard Hughes Medical In-
stitute (HHMI), Department of Neurosciences, University of
California, San Diego, CA, USA.
2
Departments of Pediatrics,
Faculty of Medicine and Health Sciences, United Arab Emirates
University, Al Ain, United Arab Emirates.
3
Département de
Génétique, INSERM U781, Hôpital Necker-Enfants Malades,
Université Paris Descartes, Paris, France.
4
Center for Human
Disease Modeling, Duke University Medical Center, Durham,
NC, USA.
5
Department of Cell Biology and Pediatrics, Duke
University Medical Center, Durham, NC, USA.
6
Istituto di
Ricovero e Cura a Carattere Scientifico Casa Sollievo della
Sofferenza, Mendel Laboratory, San Giovanni Rotondo, Italy.
7
Broad Institute of Harvard and Massachusetts Institute of
Technology, Cambridge, MA, USA.
8
Department of Clinical
Genetics, Yorkshire Regional Genetics Service, St. James’s
University Hospital, Beckett, UK.
9
Transcriptome Research
Center, National Institute of Radiological Sciences, Chiba-shi,
Japan.
10
HHMI, Department of Pediatrics, University of
Michigan, Ann Arbor, MI, USA.
11
McKusick-Nathans Insti-
tute of Genetic Medicine, Johns Hopkins University School
ofMedicine,Baltimore,MD,USA.
12
Genetic Unit, Directorate
General of Health Affairs, Ministry of Health, Muscat, Sultanate
of Oman.
13
Department of Child Health (Neurology), Sultan
Qaboos University Hospital, College of Medicine and Health
Sciences, Muscat, Oman.
14
Department of Pediatrics, Division B,
University of Szeged, Szeged, Hungary.
15
Biology Department,
San Diego State University, San Diego, CA, USA.
16
Department
of Cellular and Molecular Medicine, HHMI, University of
Californiaat San Diego (UCSD), La Jolla,CA, USA.
17
Section of
Ophthalmology and Neurosciences, Wellcome Trust Brenner
Building, Leeds Institute of Molecular Medicine, St James’s
University Hospital, Leeds, UK.
18
Clinical Genetics Department,
Human Genetics and Genome Research Division, National
Research Centre, Dokki, Giza, Egypt.
*To whom correspondence should be addressed. E-mail:
jogleeson@ucsd.edu
24 FEBRUARY 2012 VOL 335 SCIENCE www.sciencemag.org966
REPORTS
on June 16, 2012www.sciencemag.orgDownloaded from
