1. What is the cash-transfer program? what is the conditional and unconditional cash transfer programs? Is there any difference? Where might UCT be particularly
ineffective?
2. According to the book, what are the main concerns or argument?
3. Is cash transfer program effective to poverty people? Which things can make more effective the cash transfer program? (If we pay more money can cash-transfer
program will more effective?)
You do not need to write introduction write one sentence of thesis statement and write three or four body paragraphs and less than four sentences of conclusion.
The most important thing is your ideas; please write correct answer with your ideas.
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ThecontentsoʢForeignAffairsarecopyrighted©2014CouncilonForeignRelations,Inc.Allrightsreserved.
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ChristopherBlattmanandPaulNiehaus
WhyGivingCash
HelpsAlleviatePoverty
ShowThem
theMoney
Volume93 Number3
MAY/JUNE2014
CHRISTOPHER BLATTMAN is Assistant Professor of Political Science and International
Affairs at Columbia University. Follow him on Twitter @cblatts.
PAUL NIEHAUS is Assistant Professor of Economics at the University of California, San
Diego, and Co-Founder of GiveDirectly. Follow him on Twitter @Give_Directly.
May/June 2014 117
Show Them the Money
Why Giving Cash Helps Alleviate Poverty
Christopher Blattman and Paul Niehaus
Every year, wealthy countries spend billions of dollars to help
the world’s poor, paying for cows, goats, seeds, beans, textbooks,
business training, microloans, and much more. Such aid
is designed to give poor people things they can’t afford or the tools
and skills to earn more. Much of this aid undoubtedly works. But
even when assistance programs accomplish things, they often do so in
a tremendously expensive and inefficient way. Part of this is due
to overhead, but overhead costs get far more attention than they
deserve. More worrisome is the actual price of procuring and giving
away goats, textbooks, sacks of beans, and the like.
Most development agencies either fail to track their costs precisely
or keep their accounting books confidential, but a number of candid
organizations have opened themselves up to scrutiny. Their experiences
suggest that delivering stuff to the poor is a lot more expensive
than one might expect.
Take cows. Many Western organizations give poor families livestock,
along with training in how to raise and profit from the animals.
Cows themselves usually cost no more than a few hundred dollars
each, but delivering them—targeting recipients, administering the
donations, transporting the animals—gets expensive. In West Bengal,
India, for example, the nonprofit Bandhan spends $331 to get $166
worth of local livestock and other assets to the poor, according to a
report by the rating agency Micro-Credit Ratings International. Yet
even this program sounds like a bargain compared to others. In
Rwanda, a study led by the economist Rosemary Rawlins found that
Christopher Blattman and Paul Niehaus
118 foreign affairs
the cost of donating a pregnant cow, with attendant training classes
and support services, through the charity Heifer International can
reach $3,000.
Such programs surely reduce poverty: having a cow is undoubtedly
better than not having one. But they also carry an opportunity cost,
since the money spent on procuring and delivering the cows or other
assets could instead go directly to the poor. Bandhan, for example,
could give twice as many households cash grants equal to the local
price of the livestock it now gives as it does actual livestock. And in
place of each cow it provides, Heifer could give $300—roughly half of
Rwanda’s per capita income—to ten poor families.
Does the benefit of an in-kind donation to one family really
outweigh the value of helping twice or even ten times as many
households? For a growing number of antipoverty programs, the
answer to that question appears to be no. New research suggests
that cash grants to the poor are as good as or better than many
traditional forms of aid when it comes to reducing poverty. The
process of transferring cash, moreover, is only getting cheaper, thanks
to the spread of technologies such as cell phones and satellite signals.
And simply asking whether a given program is doing more
good than it costs puts pressure on the aid sector to be more transparent
and accountable. It’s well past time, then, for donors to stop
thinking of unconditional cash payments as an oddball policy and
start seeing them for what they are: one of the most sensible tools
of poverty alleviation.
MONEY MATTERS
When it comes to deciding how to help the poor, the stakes couldn’t
be higher. Each year, U.S. households donate at least $15 billion
abroad. Their government gives $30 billion in foreign aid, and wealthy
states collectively give $150 billion in development aid. Yet the world’s
poorest people receive very little of that money in actual cash.
“Just give the poor cash” is an old refrain. What is new, however, is
a burgeoning body of experimental evidence, produced by groups
ranging from the nonprofit Innovations for Poverty Action to the
World Bank, on how the effect of cash grants compares to that of
in-kind donations. Recent studies have come to surprising conclusions,
finding that typically lauded approaches to reducing poverty, such as
educational and loan programs, are not so effective after all.
Show Them the Money
May/June 2014 119
One of the best examples is microloans, small, short-term loans to
poor entrepreneurs. By opening up credit to people who were too
poor to borrow from banks, the logic went, microfinance would give
the poor the jump-start they needed to escape their plight. Beginning
in the 1990s, the microcredit movement took the development world
by storm, leading to a Nobel Peace Prize for the Bangladesh-based
Grameen Bank in 2006.
Yet a belated series of randomized trials has called the success of
microloans into question. One example comes from the Indian nonprofit
Spandana. Beginning in 2005, the group made loans of about $250
to hundreds of women in Hyderabad, India, at relatively low interest
rates. The mit economist Abhijit
Banerjee and a number of collaborators
worked with Spandana to evaluate the
program’s performance over three years;
they found no effect on education, health,
poverty, or women’s empowerment. To
be sure, people certainly benefit from
access to credit; it helps them cope
with crises and buy expensive things such as new roofs or farm equipment
and pay for them over time. But as Banerjee concluded after
reviewing an additional two decades’ worth of data on such loans,
“there is no evidence of large sustained consumption or income gains
as a result of access to microcredit.”
Another popular approach to development aid has been business
and vocational training. There is little data on how much aid spending
goes to training, but as an example, the International Labor Organization’s
Start and Improve Your Business Program claims to have trained
more than 4.5 million people in over 100 countries since 1977. “Teach
a man to fish and you feed him for a lifetime,” the proverb goes. Yet
the results of teaching anything—be it fishing or farming or word
processing—have been patchy at best. In 2012, the economists David
McKenzie and Christopher Woodruff reviewed more than a dozen
randomized trials in developing countries and concluded that training
business owners had little lasting effect on their sales or profits.
No wonder people in developing countries, when given the choice,
don’t necessarily choose to invest in skills training. In another recent
study, one of us (Christopher Blattman) worked with the economists
Nathan Fiala and Sebastian Martinez to examine a government-run
Cash grants to the poor are
as good as many traditional
forms of aid when it comes
to reducing poverty.
120 foreign affairs
training program in Uganda. Rather than simply providing classes in
various trades, the initiative gave grants of around $7,000 to over
250 groups of 15–25 young adults (roughly $400 per group member)
in return for a simple business plan describing how they would use the
money to buy vocational training and tools. The groups were otherwise
free to spend the money without oversight. The majority of the
participants ended up using the funding to enter skilled trades such as
tailoring or metalworking. But they spent most of the money acquiring
the physical tools and materials they needed to start working, allocating
only around ten percent of the grants to training. That turned out to
be a wise investment decision: over four years, the participants’ incomes
rose by an average of roughly 40 percent.
None of this is to say that existing practices should be tossed aside.
But they can certainly be improved. With microfinance, for example,
finding ways of lending larger sums for longer periods at lower rates
would surely make many businesses more sustainable and profitable.
The key point, however, is that new data are challenging the conventional
wisdom that has long dictated how billions in development
dollars are spent. Simply having a plausible theory of change doesn’t
cut it anymore. These days, it’s about providing evidence of change—
especially change that justifies the price of bringing it about.
May/June 2014 121
DON’T HAVE A COW, MAN
Over the past few years, it has
become increasingly clear that
giving away money works
in a wide range of development
situations. Mexican
families, Ghanaian farmers,
Kenyan villagers, Malawian
schoolgirls, and war-affected
Ugandans—all have been
shown in randomized trials
to benefit from cash transfers.
Economists have studied
money transfers with conditions
and without conditions,
under supervision and not under
supervision, on large scales and
small scales, and against comparable loans. And by testing the effects of
handouts over unusually long periods of time—five years out in Sri Lanka,
four years out in Uganda—scholars have had access to far more detailed
data than is available for many other poverty-reduction strategies.
These findings are particularly important because many funders,
including governments, aid organizations, and development professionals,
still harbor significant reservations about cash transfers. They
raise a variety of familiar concerns: that men drink their cash away,
that the diligent but uneducated poor struggle to make sound decisions,
and that handouts make people ever more dependent on aid. So far,
however, the data contradict the most pessimistic of these worries.
Studies have shown that the world’s poorest people do not squander
cash transfers, even when there are no strings attached. An extreme
example comes from a recent experiment run by one of us (Blattman),
Julian Jamison, and Margaret Sheridan. In 2010–13, we gave unconditional
grants of $200 to some of the least disciplined men to be found:
drug addicts and petty criminals in the slums of Liberia. Bucking
expectations, these recipients did not waste the money, instead spending
the majority of the funds on basic necessities or starting their own
businesses. If these men didn’t throw away free money, who would?
That finding echoes similar results elsewhere. Study after study has
shown that recipients of cash grants invest the money or spend it on
Christopher Blattman and Paul Niehaus
122 foreign affairs
such basic items as food and better shelter. Poor people don’t always
make the best choices with their money, of course, but fears that they
consistently waste it are simply not borne out in the available data.
Nor is there evidence that unconditional cash transfers make
recipients lazy. Especially for poor people who have not fulfilled their
potential, such as small-business owners or underemployed youth
with little access to hard capital, cash
grants have frequently created wealth.
Using such donations, entrepreneurs
in Ghana and Sri Lanka have expanded
their businesses, displaced women in
Uganda have become traders and doubled
their earnings, and farmers in
Kenya have made home investments
with high returns. In most of these experiments, people increased their
future earning potential over the long term. In some cases, they did
not. But in every study, people worked at least as many hours in the
labor force as they had before receiving the cash transfers, if not more.
In some ways, the new research on cash transfers actually affirms
the wisdom of traditional approaches to development assistance. Poor
people in developing countries often use the cash given them to buy
the same things that aid organizations have traditionally provided—
livestock, tools, training, and so on. No one living on less than $2 a
day says no to a free cow, even if he is not cut out to be a dairy farmer.
But the advantage of cash is its flexibility. When people have cash in
hand, they tend to buy a wider variety of goods and services. Not
everyone, after all, wants a cow.
THE FUTURE OF GIVING
This abundance of data suggests that people are poor not because they
lack initiative but because they lack resources and opportunities—things
that, in many places, money can buy. Donors should thus ask themselves:
With each dollar we spend, are we doing more good than the
poor could do on their own with the same dollar?
In 2010–11, the Association of Volunteers in International Service,
a Catholic development organization, did just that, evaluating an
ongoing program in postwar northern Uganda in real time. To help
1,800 of the country’s poorest women become retailers and traders,
the program had been providing each woman with a grant of $150,
Fears that poor people
waste cash are simply
not borne out by the
available data.
Show Them the Money
May/June 2014 123
five days of business planning assistance and training, and follow-up
visits from aid workers who offered supervision and advice. Altogether,
the program cost nearly $700 for every impoverished woman it assisted.
The organization, working with a team of researchers that included one
of us (Blattman), decided to measure the impact of the program without
its most expensive service: the follow-up visits. We found that such
visits did increase the women’s profits yet cost more than twice the
amount of the cash grant itself. In other words, the follow-up was far
less effective per dollar than the grant and the training course.
One potential response would have been to cut the follow-up
service and give out larger cash grants. But in this case, the organization
plans to find a way to provide the extra services more cheaply.
This will prove a high bar to meet, but either way, the end result will
be that it gets more bang for its buck.
The Ugandan example illustrates another upside to cash transfers:
they can serve as the index funds of international development. An
index fund is a bundle of investments that is not actively managed,
reducing the costs for investors. Its value simply reflects the upward
and downward swings of the individual stocks that are included in the
bundle. Similarly, a cash transfer is a development project stripped of
any active management costs, and its performance tracks the success
or failure of the individual recipient. Cash transfers thus provide a
baseline for evaluating the active management performance of government
officials and development professionals. Unfortunately, the
sort of hard-nosed performance review seen in the Ugandan study—
let alone the courage and discipline required for any organization to
put its core competencies to the test—remains rare.
Still, the studies so far, plus basic economic reasoning, suggest three
predictions about how cash will perform relative to traditional aid
programs. First, money transfers will likely prove most valuable in
places where the population has been hit hard by unexpected crises—
countries or regions recovering from violent conflicts, natural disasters,
or extended periods of political uncertainty. Think of Southeast Asia
after a tsunami or the Middle East flooded with Syrian refugees,
where the returns on capital after a recovery period are likely to be
unusually high and the challenge of making smart investments without
localized knowledge unusually large.
Second, cash could also excel in places such as Ghana, Kenya, or
Uganda—reasonably stable, growing countries that happen to have
Christopher Blattman and Paul Niehaus
124 foreign affairs
few firms offering jobs and where most workers, by necessity, are selfemployed.
Here, many of the poor are working below their potential
because they lack the capital, credit, or insurance products necessary
to grow their businesses. In the absence of financial services, which
can take decades to develop, cash can fill the gap.
Third, the forms of aid most likely to outperform cash will be those
that address collective problems, or what economists term “public
goods.” Consider health, for example. Say you were buying a vaccine
to reduce your child’s risk of getting sick. A big part of the social value
of this purchase would be reducing your neighbors’ risk of illness, too.
If you had little cash to spare, the vaccine might cost more than it was
worth to you but less than it was worth to the community at large. In
this case, an outside group would be better placed to tend to the
greater good by subsidizing the vaccine or even providing it for free.
A cash transfer wouldn’t solve the social problem if the recipient had
more pressing needs to spend the money on than the vaccine.
In many cases, however, Western officials and organizations are not
the best judges of what poor people in developing countries need to
make a better living; the poor people themselves are. One of us (Paul
Niehaus), working with fellow economists Karthik Muralidharan
and Sandip Sukhtankar, is currently conducting an unusual poll in
rural Bihar, India. We are giving poor citizens a choice between
two types of aid: the assistance provided by the government’s Public
Distribution System, a venerable program of subsidized food
delivery that consumes nearly one percent of India’s gdp, or cash
transfers, calibrated to cost the government the same amount per
family. Both forms of welfare have their advantages. Direct cash
transfers bypass corrupt officials and crafty middlemen, whereas
food transfers provide a more reliable form of insurance against
rising food prices. The results are not yet in, but the experiment
should provide a promising model for determining how to spend
aid dollars in the future.
Such exercises have their limitations, of course, but they also have
the advantage of linking smart policy with smart politics. Offering
citizens their choice of programs gives elected officials the kind of
insight they crave: raw data that describe what voters want and whether
or not the civil service is delivering it. Like cash transfers themselves,
such mechanisms can help make aid delivery more accountable to
the people the aid is intended to serve.
Show Them the Money
May/June 2014 125
CASHING IN
Despite everything that cash transfers can do, their future role in poverty
alleviation remains uncertain. The findings of small-scale experiments,
involving just a few thousand recipients, cannot reliably tell what might
happen when the same policies are rolled out to millions. One looming
question is whether money transfers are more or less feasible on a large
scale than traditional programs—whether, for example, corrupt officials
and armed groups could exploit such programs more easily.
But the evidence from countries that already use cash transfers on
a massive scale is promising. According to the United Kingdom’s
Department for International Development, governments in the developing
world already run cash-transfer programs that reach between
750 million and one billion people, whether by way of employment
programs in India, pension funds in South Africa, or welfare schemes
in Brazil. Many of these programs involve some kind of condition
that must be met before recipients get paid, such as getting a checkup
or a vaccine at a health clinic. But they all end in cash transfers.
The worst fears surrounding them—of fraud, corruption, and plain
ineffectiveness—have thus far not been realized.
New technologies have also made such programs easier to implement.
In India, one of us (Niehaus), along with Muralidharan and
Sukhtankar, recently worked with the government of the state of
Andhra Pradesh to measure the effects of replacing paper money
delivered through the mail to pensioners and workfare participants
with digital payments using biometric authentication. We found
that the new system both reduced theft and improved the speed and
reliability of the payments. Taking this approach further, the nonprofit
GiveDirectly (of which Niehaus is president) now delivers
unconditional cash payments to thousands of extremely poor households
in East Africa through accounts on their cell phones, all at a
cost of less than ten cents per dollar donated.
Another concern about rolling out cash transfers on a large scale
in developing economies is that an influx of money could lead to
disruptive inflation. Whether that fear will materialize remains unclear.
It will depend in large part on what the macroeconomic effects
of cash transfers are compared to—whether food aid, universal
education, or other goods and services. Any large-scale influx of
goods or currency has the potential to be disruptive, and so the real
question is whether giving cash is worse than giving something else.
Christopher Blattman and Paul Niehaus
126 foreign affairs
Economic theory and experience provide some reassurance.
Consider the hundreds of thousands of Syrian refugees now living
in Lebanon, where the United Nations and humanitarian agencies
are dispensing cash via atm cards as the main form of relief. In
such open economies, cash should have little effect on food prices
or supplies, and it could even stimulate local production. But when
it comes to goods that are slow to keep up with demand—electricity
or rental housing, for example—prices are rising and supplies are
dwindling. However troublesome the shortages, though, there are
few better or more efficient options for helping the refugees buy
basic necessities.
To be sure, cash is no panacea. Not every person will grow his or
her income or business with a grant; some recipients will use all the
money to pay for immediate needs. The effectiveness of cash-transfer
programs are only partly proven, and many unknowns and risks
remain. But the evidence is stacking up faster in favor of cash than
it is for a lot of the alternatives, and direct cash transfers deserve to
shed their reputation of being eccentric. Just as important, donors
and the public must hold charitable organizations accountable for
the wasteful expenses they regularly incur. The expansion of cashtransfer
programs themselves could do the most to bring such costs
into clearer focus. And when that happens, the global effort to end
poverty will have entered a new and better era.∂
Policy Research Working Paper 6886
Cash Transfers and Temptation Goods
A Review of Global Evidence
David K. Evans
Anna Popova
The World Bank
Africa Region
Office of the Chief Economist
May 2014
WPS6886 Public Disclosure Authorized Public Disclosure Authorized Public Disclosure Authorized Public Disclosure Authorized
Produced by the Research Support Team
Abstract
The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development
issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the
names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those
of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and
its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.
Policy Research Working Paper 6886
Cash transfers have been demonstrated to improve
education and health outcomes and alleviate poverty
in various contexts. However, policy makers and others
often express concern that poor households will use
transfers to buy alcohol, tobacco, or other “temptation
goods.” The income effect of transfers will increase
expenditures if alcohol and tobacco are normal goods,
but this may be offset by other effects, including the
substitution effect, the effect of social messaging about
the appropriate use of transfers, and the effect of shifting
dynamics in intra-household bargaining. The net
effect is ambiguous. This paper reviews 19 studies with
This paper is a product of the Office of the Chief Economist, Africa Region. It is part of a larger effort by the World
Bank to provide open access to its research and make a contribution to development policy discussions around the world.
Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted
at devans2@worldbank.org and apopova@worldbank.org.
quantitative evidence on the impact of cash transfers on
temptation goods, as well as 11 studies that surveyed the
number of respondents who reported they used transfers
for temptation goods. Almost without exception, studies
find either no significant impact or a significant negative
impact of transfers on temptation goods. In the only
(two, non-experimental) studies with positive significant
impacts, the magnitude is small. This result is supported
by data from Latin America, Africa, and Asia. A growing
number of studies from a range of contexts therefore
indicate that concerns about the use of cash transfers for
alcohol and tobacco consumption are unfounded.
Cash Transfers and Temptation Goods:
A Review of Global Evidence
David K. Evans
World Bank
Anna Popova
World Bank
Keywords: Cash Transfers, Temptation Goods, Impact Evaluation, Review, Consumption
JEL Codes: E20, I38, O12
Acknowledgments: The authors are very grateful for comments and guidance from Javier Baez, Chris
Blattman, Julio Elias, Francisco Ferreira, Mario Macis, and Norbert Schady. The findings, interpretations,
and conclusions are entirely those of the authors. Corresponding author: David Evans
(devans2@worldbank.org).
Motivation
Since the introduction of cash transfer programs, both conditional and unconditional, a major
concern has been that households will misuse the cash. In Nicaragua, a senior government
official expressed concern that “husbands were waiting for wives to return in order to take the
money and spend it on alcohol” (Moore 2009). Interviews with stakeholders in Kenya revealed
“widespread belief that cash transfers would either be abused or misdirected in alcohol
consumption and other non-essential forms of consumption” (Ikiara 2009). A broader survey
highlights that, “There is a widely held belief that cash given to poor people (especially to men)
will be squandered on alcohol and other non-essentials” (Devereux 2002). Governments and
aid agencies may worry that “men could control the cash provided and spend it on alcohol and
cigarettes, rather than food for hungry children” (Harvey 2005). These concerns may explain
why many countries prefer in-kind transfer programs, even though economic reasoning would
suggest that cash transfers are more efficient (Case and Deaton 1998): Households can more
easily meet their heterogeneous needs with liquid cash than with other, less liquid goods.
Alcohol and tobacco have been referred to as “temptation goods” (Dasso and Fernandez 2013),
a term used by Banerjee & Mullainathan (2010) to refer to “goods that generate positive utility
for the self that consumes them, but not for any previous self that anticipates that they will be
consumed in the future.” In an earlier literature, Musgrave (1959) used a related (but more
normatively charged) term, “demerit goods,” to refer to goods that were so demeritorious
(either to the consumer or to others) that the government may be correct in regulating their
use. That term is sometimes used in reference to alcohol and tobacco in cash transfer studies.
In this study, we use the term “temptation goods” principally to refer to alcohol and tobacco.
1
This study makes no normative assumption as to the value of alcohol and tobacco expenditures
but merely seeks to systematically characterize the literature on the impact of cash transfers on
these goods. Although alcohol and tobacco are the principal goods under consideration, some
studies report other items as part of the same category, from doughnuts (Aker 2013) to soft
drinks and Chinese food (Dasso and Fernandez 2013). The poor may wish to reduce spending
on these items, as evidenced by a survey in Hyderabad, India, that asked households if they
would like to eliminate any expenses in their budget: 28% of households identified at least one
item, and the top items (44% of those) that households wanted to cut were alcohol and
tobacco (Banerjee and Duflo 2007).
Most cash transfer programs are not focused on either increasing or decreasing consumption of
these goods specifically, and so most evaluations and the subsequent reviews have not been
1 Consumption of these goods may in some cases serve positive social purposes. For example, one study recounts
the anecdote of demobilized soldiers returning home in Mozambique and using some of their demobilization grant
on alcohol in the context of a village celebration to assist in their reintegration (Harvey 2005).
2
focused on these. Rather, reviews have focused on outcomes in schooling (Baird, et al. 2014,
Saavedra and García 2013), health (Leroy, Ruel and Verhofstadt 2009, Ranganathan and
Lagarde 2012), consumption (Fiszbein, et al. 2009), or a combination of these (IEG 2011). At the
same time, many individual evaluations of cash transfer programs have included analysis of the
impact on some set of temptation goods within their consumption analysis.
Across 44 estimates from 19 studies, we find that almost without exception, studies find either
no significant impact or a significant negative impact of transfers on expenditures on alcohol
and tobacco. This finding is similar whether the analysis includes experimental and quasiexperimental
designs or if it is restricted to randomized trials alone. Likewise, studies that have
tried to quantify the proportion of beneficiaries who spend transfers on temptation goods find
negligible effects. This result is consistent across the world, supported by data from Latin
America, Africa, and Asia. It is also consistent across conditional and unconditional cash transfer
programs. The evidence suggests that cash transfers are not used for alcohol and tobacco at
any significant levels.
Cash, Spending, and Consumption of Temptation Goods
If alcohol and tobacco are normal goods, then as incomes rise, consumption of these goods will
likewise rise (i.e., the income effect). Evidence from the United States suggests that alcohol is a
normal good, whereas tobacco is an inferior good (Decker and Schwartz 2000); evidence from
the United Kingdom suggests that alcohol expenditures rise with income, at least to a point
(Banks, Blundell and Lewbel 1997). Banerjee and Duflo (2006; 2007) show expenditures for
households living on under $1.08 per day and for households living on under $2.16 per day in
11 countries divided into urban and rural areas, resulting in 21 country-urban or country-rural
combinations, due to missing data on urban Guatemala (Table 1). Of these 21 combinations, 14
increased or maintained the same percentage of spending on alcohol and tobacco combined
when comparing $1.08 to $2.16 daily income, suggesting a likely increase in the total spending.
2
That number rises to 20 out of 21 if one includes settings with minor decreases in the
proportion, still consistent with increases in the total spending on these goods given the rise in
income. These numbers suggest that alcohol and tobacco, when examining regular income, are
normal goods.
Beyond the income effect, there are at least three reasons that cash transfer income may affect
spending on temptation goods differently from other income. First, conditional cash transfers in
particular may induce a substitution effect, increasing the value of schooling and health
2 These percentages are best for distinguishing luxury goods (for which the proportion of spending increases with
income) from necessity goods (for which the proportion falls), but they are suggestive of an increase in absolute
spending (i.e., normal goods).
3
investments relative to all other goods, which may shift households away from consumption of
temptation goods (Fiszbein, et al. 2009). The relative strength of the income and substitution
effects will vary across households depending on their baseline schooling and health
investments. Those beneficiary households that make sufficient investments in their children’s
education to satisfy the conditions of the program, before the program, will be less affected by
the substitution effect. On the other hand, those who – before the program – are investing in
education and health at levels below those required by program conditions will be more
affected by the substitution effect.
Second, while few cash transfer programs have explicit spending restrictions, they often come
with strong social messaging. For example, Ecuador’s unconditional cash transfer program
(Bono de Desarrollo Humano) was accompanied by an advertising campaign encouraging
households to invest in their children’s human capital (Schady and Rosero 2008). In Zimbabwe,
recipients of a cash transfer program were “instructed not to ‘waste’ the cash on drinks and
other unproductive items” (Román 2010). In Nicaragua, a task of the community coordinators
for the program was “promoting the use of cash transfers to buy goods and services which
improve the nutritional, educational and health status of beneficiary families” (Adato and
Roopnaraine 2004). Program officers often communicate to households that these resources
are intended to improve education or health outcomes. As a result, households may be more
likely to use the resources for expenditures related to education and health than on tempation
goods, a manifestation of what has been termed the flypaper effect (Inman 2008).
Finally, transfer income is often targeted at women, particularly in Latin America (Fiszbein, et al.
2009). This design choice is driven by the long-held idea that women are more likely to invest in
children than men. The actual evidence on this is mixed. On one hand, researchers found that
higher proportions of household income controlled by women led to greater food expenditures
in Côte d’Ivoire (Hoddinott and Haddad 1995), greater expenditures on food and children’s
goods in Mexico (Bobonis 2009), and to improved child health in Brazil (Thomas 1990). In
Macedonia, randomly assigning cash transfers to mothers (versus the household head)
significantly increased education expenditures as well as secondary school enrollment and
achievement, but only when parents’ perceived returns to education were high (Armand 2013).
On the other hand, two cash transfer programs that randomized whether the transfer was
given to the woman or the man found no sigificant differences in outcomes for children. The
outcome in the first study was health clinic visits for children in Burkina Faso (Akresh, de
Walque and Kazianga 2012) and in the second study it was school participation in Morocco
(Benhassine, et al. 2013).
If men are indeed more likely to purchase temptation goods (as was explicitly documented in
Côte d’Ivoire), then providing transfer income to women could reduce spending on those
4
goods, a household bargaining effect. The net effect – between the income effect, the
substitution effect, the flypaper effect, and the household bargaining effect – is unclear
theoretically: This paper seeks to characterize it empirically.
A large literature has examined the impact of cash transfers on consumption, with a few studies
explicitly contrasting transfer income with earned income. For example, Schady and Rosero
(2008) show that food expenditures were much higher for transfer recipients than nonrecipients
in the Ecuador program, even when controlling for per capita expenditures (i.e., the
income effect of cash transfers). This finding is contrary to Engel’s law, which states that “the
proportion of income spent on food declines as income rises” (Houthakker 1957) and which has
been empirically identified across many countries. In Nicaragua, Macours, Schady and Vakis
(2012) use a similar strategy and find that cash transfer recipients shifted the composition of
food expenditures to more expensive foods (i.e., more protein, fruits, and vegetables; fewer
staples), even though total food expenditures were not different from other households with
similar per capital expenditures. Case & Deaton (1998) demonstrate that pension income in
South Africa increased food consumption and may have reduced alcohol and tobacco
consumption, depending on the specification. These studies suggest that households may
indeed treat transfer income differently from earned income.
Methodology
In this section we describe the criteria used to define the universe of literature relevant to this
systematic review, as well as the search strategy employed to find papers conforming to these
criteria.
Scope of the review
First, we describe the scope of the review in terms of the types of interventions, studies, and
outcome variables of primary interest. We restrict our analysis to conditional cash transfers
(CCTs) and unconditional cash transfers (UCTs) implemented in low and middle-income
countries (as defined by the World Bank), with no other explicit population exclusion criteria.
Since both CCTs and UCTs generally target poor and vulnerable households (often including
school-aged children or pregnant women), the entire set of eligible interventions is largely
targeted at disadvantaged populations.
The review focuses on studies from 1997 to early 2014, which corresponds to the period
following the onset of PROGRESA/Oportunidades, allowing for a relatively comparable group of
cash transfer interventions, as in Baird et al. (2014). Eligible studies include both experimental
and quasi-experimental designs. We limit the review to papers that compare cash transfer
5
recipients to a group that receives no transfers. Specifically, in the systematic review we
consider the effects on consumption of all those goods which studies themselves identify as
“temptation”, “demerit”, or “anti-social” goods, or those which reflect “misuse” or “waste”. In
conducting the review we focus on the effects on alcohol and tobacco consumption, for
comparability purposes.
Consumption of temptation goods is measured in a number of ways across studies: notably,
expenditure, share of expenditure, and share of individuals consuming the temptation good in
the reference period. We include studies using all of these measures, although we focus on
expenditure as our primary outcome of interest.
We classify this universe of eligible studies into the following three categories:
i. Impact Estimates: Randomized-control trials or quasi-experimental studies that estimate
the impact of cash transfers on the consumption of temptation goods;
ii. Level Estimates: Studies that use surveys or focus groups to characterize the number of
beneficiaries or amount of transfers used to purchase temptation goods; and
iii. Qualitative Reports: Studies that discuss reports of the use of transfers to purchase
temptation goods, not necessarily by the interviewed household.
Search methods for the identification of studies
The remainder of this section describes how the literature was searched. The various phases of
the search process are also summarized in chronological order in Table 2, together with the
number of results they yielded. We restricted all searches to papers published since 1997. Our
primary electronic search was conducted using Google Scholar. 3 The initial search was
completed on January 20th, 2014; thus papers that were not yet available at that time are not
included in this review. We searched for papers that included both the term “cash transfers”,
and any one of the terms “alcohol”, “tobacco”, “cigarettes”, “temptation goods”, or “demerit
goods”. This search yielded a total of 4,290 articles. The titles and sources of these papers were
reviewed and the majority of papers discarded due to irrelevant subject areas, leaving 434
papers. These were then checked for duplicates and 23 were removed, leaving 411 papers.
These 411 papers were reviewed by reading their abstracts and conducting a word search
within each article for appearances of the key search terms listed above, so as to identify the
context within which they are referenced by the article. 179 papers were deemed irrelevant
and removed on the basis of this review process – typically because the terms of interest
3 The search produced results drawn from databases including Science Direct, the Social Science Research
Network, and the Wiley Online Library, as well as the databases of a number of international organizations –
notably the Overseas Development Institute, United Nations Development Programme, the United Nations
Children’s Fund, the World Bank, the International Initiative for Impact Evaluation (3ie), the World Food Program –
and universities.
6
appeared either in passing, or in a context other than that of cash transfers – leaving 232
papers. In addition to the Google Scholar search, we added 7 studies from our own knowledge
as well as those recommended by other researchers. We investigated the bibliographies of
relevant papers and systematic reviews of cash transfers uncovered through the previous steps
and manually searched a number of databases to find relevant papers mentioned, yielding
another 12 papers, bringing the total to 251 papers.
4
These papers were then examined more closely, and studies were removed that did not fall into
any of the three categories described earlier (impact estimates, level estimates, and qualitative
reports). This left 42 papers. The countries represented by these papers by impact estimates
and level estimates, from all over the world, are illustrated in Figure 1.
Several of these papers report multiple estimates: For example, estimates are reported using
two different estimators (e.g., treatment-on-the-treated versus intent-to-treat, or matching
versus instrumental variables) or in multiple time periods (e.g., the first tranche of transfers
versus the second tranche). In order to capture the full range of possible impacts, we include all
these estimates. We do not include estimates on sub-populations (e.g., female-headed
households only) except when that is the only format in which results are reported in the
original studies, because papers are very inconsistent in the sub-populations for which they
report outcomes, and because relatively few do so.
Results
First, we discuss the evidence from estimates of program impacts on spending on alcohol and
tobacco. Second, we discuss evidence from studies that surveyed the number of respondents
who reported using transfers to purchase temptation goods.
Impact Estimates
Nineteen studies from 10 countries around the world (in Latin America, Africa, and Asia) report
impacts of cash transfers on the level or proportion of expenditures on alcohol or tobacco, or
the probability of consumption or abuse of these goods. These studies and the reported
impacts are listed in Tables 3 and 4. The 19 studies include 44 impact estimates. To simplify, we
group these estimates into four categories:
4 Of the 19 papers which were added manually, 4 contained relevant impact estimates and made it to our final
sample of literature. Two of these (Dasso and Fernandez 2013 and Evans et al. 2014) were unpublished mimeos at
the time of the original search and were therefore not picked up by our algorithm. Another study (Gilligan and Roy
2013) was not picked up because it does not include any of our search terms; specifically, it refers to estimates of
consumption of “beer” only. The other study (The Kenya CT-OVC Evaluation Team 2010) was an in-depth internal
evaluation report underlying a policy note identified using our algorithm. The remaining 15 papers in this group – a
number of which were systematic reviews of cash transfers and social policies – contained relevant background
material on cash transfers but no evidence on their effect on the consumption of temptation goods.
7
(1) negative and significant,
(2) negative or zero and insignificant,
(3) positive and insignificant, and
(4) positive and significant.
Across all 44 estimates (from the 19 studies), there are 12 estimates which are negative and
significant, 24 which are negative and insignificant, 6 which are positive and insignificant, and 2
which are positive and significant (Table 5 Panel A). In other words, 82% of estimates are
negative, and just 5% of estimates are significant and positive (Table 6 and Figure 2). One of
those two positive results is an unconditional cash transfer program in Indonesia: in the first
disbursement, the impact was slightly negative and highly significant, whereas in the second
disbursement, the impact was slightly positive and mildly significant. The size of the coefficient
is almost identical to that for expenditures on prepared food. The other positive result, from
Peru’s Juntos program, is from a paper that uses two different methods, matching and
instrumental variables, and finds opposite results from the two estimates on alcohol
consumption: a moderately significant negative impact from the matching estimate and a
weakly significant positive impact from the instrumental variables estimate. Estimates on other
outcomes are mostly consistent across the two estimation methods. Thus, in both cases of
positive significant results, the impacts are weakly significant and are not consistent across
estimates within the same study. Furthermore, the effect sizes are very small: one is less than a
penny, whereas the other is 21 cents. Even if those estimates accurately reflect changes in
expenditures, the changes are trivial.
If we instead consider only the 17 estimates from 8 randomized-control trials, we find 1
estimate which is negative and significant, 13 that are negative and insignificant, 3 that are
positive and insignificant, and zero that are positive and significant (Table 5 Panel C). In other
words, 82% are negative, and none are positive and significant (Table 6).
Four studies explore the impacts on alternate measures of temptation goods. Two of them,
rather than estimating the impact of transfers on expenditure levels or proportions, estimate
the impact of the program on the share of individuals who consume any of the temptation
good (i.e., who smoke or who drink). They both examine this impact for adolescents in Mexico,
in the context of the Oportunidades transfer program. One paper examines the impact using
2004 data and an instrumental variables strategy. It separates the impact of program
participation from the impact of total cumulative transfers, with community awareness of the
program as an instrument for household participation in the program, and potential transfers
(based on household demographics) as an instrument for actual transfers (Galárraga and
Gertler 2009). The net effect is reported for smoking for men (a reduction from 30% of men
smoking to 16%) and for alcohol consumption for women (a reduction from 22% of women
8
drinking to 13%). The other paper, using data from 1998 and 2000 and a propensity score
matching approach, finds a reduction in adolescents that have had alcoholic drinks (12%
reduction in rural areas, 2% in urban areas) and in those that have smoked (14% in rural areas,
4% in urban areas) (Gutiérrez, et al. 2004). A third study, from Uganda, uses a randomized
design to estimate the impact of cash transfers provided through early childhood development
centers on the number of days that children (aged 1 to 7 years) drank beer in the week
preceding the survey (Gilligan and Roy 2013)5
. They find an insignificant reduction of 20% in the
frequency of consumption.
Finally, a randomized evaluation estimates the impact of Oportunidades on the probability of
alcohol abuse, and finds that beneficiaries of the program are significantly less likely to have a
habitual drinker present in the household than non-beneficiaries (Angelucci 2008). These
studies add to the evidence that the net effect of cash is likely to be either insignificant or
negative. The distribution of results is very similar if one includes only estimates on expenditure
levels and not on the proportion of income spent or these other outcomes (Table 5 and Figure
2).
There are several potential sources of heterogeneity in the impact of cash transfers on
temptation goods, including program design (e.g., conditional versus unconditional cash
transfers), geographic variation, or variation in how long households have been receiving the
transfers. However, with so few significant effects, it is difficult to identify heterogeneity. We
have 31 estimates from conditional cash transfer programs and 11 estimates from
unconditional cash transfer programs.6 Table 7 shows the distribution of estimates (from
negative and significant to positive and significant) for the two groups; we observe essentially
the same pattern, with 84% and 73% of estimates being negative for conditional cash transfer
programs and unconditional cash transfer programs, respectively. The proportions are almost
identical when we consider estimates from randomized trials only.
Likewise, if we separate the studies in Latin America from those in Asia and in Africa, there are
no clear differences, albeit with slightly greater heterogeneity in Latin America (Table 8). We
find that 79% of estimates in Latin America are negative, compared to 88% of estimates from
other regions. There is also no evidence of differences related to the length of time people have
been receiving transfers. The time during which beneficiaries have been receiving transfers is –
on average – 1.9 years, and ranges from 6 months to 5.5 years, with no clear relationship
5 In the Karamoja sub-region of Uganda, where this program was implemented, it is common to make a local
homebrewed weak beer from sorghum and for both adults and young children to consume this, as well as the beer
residue (Gilligan and Roy 2013). 6 For this comparison of conditional and unconditional transfer programs, we exclude the 2 estimates from the
evaluation of The Kenya Cash Transfer Program for Orphans and Vulnerable Children, which imposed conditions in
3 of the 7 districts in which it was implemented.
9
between the duration of treatment and the program effects on consumption of alcohol and
tobacco.
Level Estimates
Other studies, while not estimating the impact of transfers on consumption of or expenditures
on temptation goods, have sought to quantify how many beneficiaries use transfers for
temptation goods, or how much of the transfers has been spent on temptation goods; these
studies rely either on surveys or focus groups. We identified 11 such studies, representing
programs in 8 countries: 6 in Africa, 1 in Asia, and 1 in the Middle East (Table 9). Four of the
studies identified a proportion of beneficiaries or households that spent some or all of the
transfer on temptation goods. The median proportion was 1.2%, a tiny fraction of households.
Even in the one outlier, Lesotho’s Cash & Food Transfers Pilot Project, where about 6% of
beneficiaries admitted to spending some of their transfer on alcohol and cigarettes, the study
quotes a recipient as saying that it happens “only in rare and discreet cases.” Two more studies,
from Malawi and Zimbabwe, identify the proportion of transfers spent on temptation goods: In
both cases, the proportion is under 0.5%. The remaining studies simply report that they found
no evidence that households were purchasing temptation goods, except one case that reports a
“marginal increase.”
This evidence is significantly less convincing than the impact estimates, which look at total
expenditures rather than transfer expenditures alone, as transfer and other income are
fungible. A household could, for example, use the transfer income entirely for education
investments but at the same time decrease spending on education from regular income by ten
percent. Then they could use that ten percent of regular income for temptation goods. In the
respondent’s view, none of the transfer income would have been used for temptation goods,
although clearly the transfer is what enabled the increased expenditures. Despite this caveat,
these level estimates are consistent with the finding of insignificant quantities being spent on
alcohol and tobacco that was already observed in the more reliable estimates on overall
expenditures.
Discussion
In this section we discuss some of the implications and challenges related to this analysis. One
principal concern when studying the consumption of goods such as alcohol and tobacco,
especially in the context of a program where beneficiaries are encouraged not to use the
resources on those goods, is that beneficiaries will report low expenditures on those goods
10
because they want to minimize the risk of expulsion from the program or other potential
negative consequences. This is known as “social desirability bias.” There is some evidence from
undergraduate students in the United States that self-reports of alcohol consumption can be
biased downward (David, Thake and Vilhena 2010). In developing contexts, this is much less
explored for alcohol and tobacco consumption. (For sexual behaviors, it has been explored
extensively.7
) However, we do not expect this to be a major problem here, for the following
reasons. First, the impact estimates presented here are usually based on detailed expenditure
surveys that ask a household respondent how much the household spends on each of a long list
of items. Alcohol and tobacco are not singled out. For the estimates of what proportion of
households spent any resources on temptation goods, alcohol and tobacco may be singled out,
which could explain why several studies found zero reports of any spending on temptation
goods. However, those estimates merely provide supportive evidence to the more robust
impact estimates.
Second, transfer income is not asked about separately, so households would have to recall the
amount of their overall income spent on temptation goods before the program and report a
similar amount later. The simplest solution for households seeking to appease an interviewer
would be to report zero or extremely low expenditures on alcohol and tobacco. This is
especially true since household surveys are administered infrequently and so recalling previous
reports may be difficult. In that case, we would expect to see a much starker pattern of
significant negative impacts. On the contrary, we observe just 24% of all impacts on
expenditures to be negative and significant, and 9% for randomized-control trials. The far more
common result is an insignificant difference: the outcome in all eleven randomized trials (Figure
2 Panel D). This does not look like systematic social desirability bias.
An additional concern could be that these studies were not sufficiently statistically powered to
capture consumption impacts at all, whether on temptation goods or other categories of
consumables. For this, we focus on the 6 positive and insignificant estimates in more detail.
These 6 estimates come from 5 studies (each from different countries around the world), most
of which report the estimated impact of cash transfers for total expenditure on temptation
goods; Maluccio and Flores (2005) also present an estimate of the impact on the proportion of
expenditures. For each of these studies, we examine whether the studies had sufficient
statistical power to identify significant impacts on overall consumption using the same
7 This issue has been studied more extensively for sexual behavior in developing countries, and the evidence has
been inconsistent: In Malawi and Kenya, for example, young women were more likely to report ever having had
sex in a face-to-face interview, whereas they were likely to report more total partners in an audio computerassisted
self-interview (Mensch, et al. 2008). In Zimbabwe, respondents also reported fewer partners in face-toface
interviews (Gregson, et al. 2002). A study in Tanzania found female adolescents were more honest about
sexual infection in face-to-face interviews, whereas males were less honest (Plummer, et al. 2004). A fuller list of
relevant references is available in Handa et al. (2014).
11
estimation methodology (Table 10). We observe that in every case, the studies finding positive
and insignificant estimates for temptation goods at the same time produce significant (positive)
estimates for the impact on overall consumption. Because identifying impacts on individual
consumption items or categories requires greater statistical power than identifying effects on
total consumption, we also look at whether these studies find significant impacts on individual
consumption items other than temptation goods (also in Table 10). We find that every study
finding positive and insignificant estimates for temptation goods produces significant estimates
for at least 20 percent of the disaggregated consumption items. This suggests that the
insignificance of these temptation good estimates does not derive from a lack of statistical
power. Rather, there is simply no quantitative evidence that beneficiaries use their transfers on
alcohol and tobacco.
An alternative comparison to the one central to this study is the relative impact of cash
transfers versus in-kind food transfers. In the course of our search, we identified three studies –
all randomized trials – that quantitatively estimate this relative impact: one in Mexico (Cunha
2012), one in Uganda (Gilligan and Roy 2013), and one in Yemen (Schwab, Margolies and
Hoddinott 2013). The Mexico study finds (insignificantly) increased expenditures on alcohol
among cash recipient households relative to food recipient households. The Uganda study,
focusing on children age 1-7, finds that children of cash transfer recipients are (insignificantly)
less likely to consume sorghum beer. The Yemen study estimates (insignificantly) higher
expenditures on tobacco and khat for cash transfer recipients. In none of the cases is there a
significant difference between the impact of cash and in-kind transfers on expenditures on
temptation goods. The first two studies also include a pure comparison group and are included
in the analysis above (and in Tables 3 and 4).
Qualitative Results
While the impact estimates suggest zero average effect, and the level estimates suggest only
tiny fractions of beneficiaries using transfer resources to purchase temptation goods,
qualitative reports sometimes tell a different story. Consider the following examples:
• In Malawi, researchers reported from focus groups that “In our village, there were
certain men who wasted their money even though they had families and children” and
“We heard of four men who received their rations on a Thursday. They all went to a
nearby popular drinking bar” (Devereux, Mvula and Solomon 2006).
• In Bolivia, “Of the 35 subjects interviewed, 20 admitted they knew people who misspent
the cash transfers.” However, “Many mentioned the media as their main source of
information regarding any misspending” (Vaughan 2010).
12
• In Kenya, “Cases of misuse of funds were reported in the two sites: according to key
informants, in some cases, male recipients have used some of the cash to buy alcohol,
although this is relatively rare (only three cases reported, with the majority of the cash
being used for consumption and investment)” (Onyango-Ouma and Samuel 2012).
• In Swaziland, a focus group participant reported that “Men don’t return home on paydays;
some have found other women to spend the money with” (Devereux and Jere,
2008).
• In Uganda, participants and informants observed that “Some beneficiaries – especially
men – have used the cash transfer in over-drinking alcohol” and “Some older men
especially drink all the money” (Bukuluki and Watson 2012).
How do we reconcile these anecdotes with the extremely insignificant or even negative effects
we observed earlier? First, the results previously discussed do not indicate that no single
beneficiary uses his or her transfer on alcohol. For example, the Malawi anecdote above comes
from a study that measured the proportion of transfers that were spent on alcohol; the
proportion was 0.1%. So although interviewees had “heard of four men” or knew “certain men”,
these numbers seem very small. What the quantitative results earlier claim is that, on average,
there is no positive impact of transfers on alcohol expenditures.
Second, most of these reports are not with reference to one’s own household, but rather to
other individuals who respondents may know who spend the money on alcohol and tobacco.
However, multiple respondents may well know the same person in the community who has a
reputation for high levels of alcohol or tobacco consumption. These anecdotes can be subject
to “saliency bias”, in which individuals pay attention to highly noticeable factors and dramatic
events: A village drunkard stands out and is likely to come up disproportionately in discussions.
An alternative possibility is that the respondents in household surveys are unaware of how
their household resources are spent. For example, if a husband takes household resources and
spends them on alcohol without the wife’s knowledge and the wife is the survey respondent,
then such spending might show up in qualitative reports from other households but be missing
in the impact estimates. However, it seems unlikely both that (1) the surveys consistently
interview the non-drinking member of the household, and (2) this member is consistently
ignorant of these expenditures, particularly in low-income households with limited liquid
income.
These results underline the importance of complementing qualitative reports with quantitative
data and are reconcilable with the earlier quantitative finding that, on average, there is no
increase in the consumption of temptation goods.
13
Conclusion
We have investigated evidence from around the developing world, including Latin America,
Africa, and Asia. There is clear evidence that transfers are not consistently used for alcohol or
tobacco in any of these environments. This is particularly true when relying on the randomized
trials. For all studies, the only evidence for a positive, significant effect is inconsistent across
estimates within the studies themselves; and in those cases, the size of the impact is trivial.
Thus, it seems that the flypaper effect and the effect of women controlling more resources (the
household bargaining effect) likely compensate for the income effect, leading to no significant
net change in alcohol and tobacco consumption. We see no difference between conditional and
unconditional cash transfer programs, so this does not seem to be a function of conditions. We
also observe no difference depending on the region of the transfer program.
These results provide strong evidence that concerns that transfers will be used on alcohol and
tobacco are unfounded. We do have estimates from Peru that beneficiaries are more likely to
purchase a roasted chicken at a restaurant or some chocolates soon after receiving their
transfer (Dasso and Fernandez 2013), but hopefully even the most puritanical policymaker
would not begrudge the poor a piece of chocolate.
14
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Farrington, John, and Rachel Slater. 2009. “Lump Sum Cash Transfers in Developmental and PostEmergency
Contexts: How Well Have They Performed?” London.
Fiszbein, Ariel, and Norbert R. Schady. 2009. Conditional Cash Transfers: Reducing Present and Future
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Galárraga, Omar, and Paul J. Gertler. 2009. “Conditional Cash & Adolescent Risk Behaviors: Evidence
from Urban Mexico.”
Gangopadhyay, Shubhashis, Robert Lensink, and Bhupesh Yadav. 2013. “Cash or Food Security Through
the Public Distribution System? Evidence from a Randomized Controlled Trial in Delhi, India.”
Evidence from a ….
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Gitter, SR. 2006. “Women and Targeted Cash Transfers in Nicaragua.” Aae.wisc.edu.
17
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18
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20
Tables
Table 1: Consumption of Alcohol and Tobacco as a Share of Total Consumption
Household living on less than…
$1 per
day
$2 per
day
Ratio
($2/$1)
Rural Côte d’Ivoire 2.7% 2.2% 81.5%
Guatemala 0.4% 0.5% 125.0%
India – UP/Bihar 3.1% 3.0% 96.8%
Indonesia 6.0% 6.8% 113.3%
Mexico 8.1% 6.5% 80.2%
Nicaragua 0.1% 0.6% 600.0%
Pakistan 3.1% 2.9% 93.5%
Papua New Guinea 4.1% 5.1% 124.4%
Peru 1.0% 1.3% 130.0%
South Africa 2.5% 3.4% 136.0%
Timor-Leste 0.0% 0.0% 100.0%
Urban Côte d’Ivoire 3.5% 3.3% 94.3%
India – Hyderabad 2.5% 2.7% 108.0%
Indonesia 5.5% 6.3% 114.5%
Mexico 3.6% 4.2% 116.7%
Nicaragua 1.0% 0.7% 70.0%
Pakistan 3.0% 2.9% 96.7%
Papua New Guinea 0.6% 4.4% 733.3%
Peru 0.2% 0.8% 400.0%
South Africa 5.0% 5.1% 102.0%
Timor-Leste 0.0% 0.0% 100.0%
Note: Adapted from Banerjee & Duflo (2006).
21
Table 2: Steps used to select papers in the systematic review
Review
Phase Procedures Used
Number of
Papers
1 Google Scholar search 4,290
2 Review titles and eliminate irrelevant papers 434
3 Eliminate 23 duplicate papers 411
4
Review abstracts and conduct word search and remove
papers that do not seem to look at the impact of
income on consumption of temptation goods
232
5
Add 7 papers recommended by colleagues and 12
papers referenced in bibliographies of papers identified
in previous phases
251
6
Read papers and remove those without impact
estimates, level estimates, or qualitative reports of the
impact of cash transfers on consumption of temptation
goods
42
7 Categorize papers into 3 groups:
i) Papers with impact estimates 19
ii) Papers with level estimates 11
iii) Qualitative reports 12
22
Table 3: Studies with estimated impact of transfer on alcohol or tobacco expenditures
Country Program name Temptation good Impact Detail on impact Methodology CCT/UCT Reference
Brazil Bolsa Alimentaria & Bolsa
Escola
Alcohol, tobacco, and
gambling
-1.961 (1.86) Difference in differences CCT Braido, Olinto, & Perrone 2012
2.822 (4.64) Urban
-1.536 (3.31) Rural
Alcohol -0.001
Tobacco -0.001ǂ
0.080 (0.53) Impact of transfer
-0.455 (0.53) Impact of transfer &
bank account
-0.0001*** (0.00) First disbursement
0.0001* (0.00) Second disbursement
0.0000 (0.00) Average across both
Alcohol -0.017 (0.02)
Tobacco -0.003 (0.00)
Alcohol -0.024ǂ
Tobacco 0.000
Alcohol 0.336 (0.40)
Tobacco -0.218 (0.14)
-0.029 (0.26) Benefit (dummy)
-0.001 (0.00) Benefit (level)
-0.010* (0.01) First year
-0.001 (0.01) Second year
Nicaragua Red de Protección Social Alcohol and tobacco 4.251 RCT CCT Maluccio & Flores 2005
-0.113** (0.05) Propensity score matching
0.210* (0.12) Instrumental variables
-0.002 (0.00) 2009 estimate
0.005 (0.00) 2010 estimate
-3.322 (3.16) ETT midline
-3.098 (4.24) ITT midline
-2.386 (3.16) ETT endline
-2.312 (4.31) ITT endline
Report total expenditures (presented in 2012 PPP)
Difference in differences CCT
CCT
RCT CCT
Gitter 2006
Mexico PROGRESA
Kenya CT-OVC Evaluation
Team 2012
Kenya The Kenya Cash Transfer
Program for Orphans and
Vulnerable Children
Difference in differences Conditionalities
in 3/7 districts
Notes: * denotes statistical significance at the 10% level, ** denotes statistical significance at the 5% level, *** denotes statistical significance at the 1 % level,
ǂ denotes that
statistical significance is reported but not a standard error, and ~ denotes that statistical significance is not reported. CCT is Conditional cash transfer; UCT is
unconditional cash
transfer. ETT is estimate of treatment on the treated. ITT is the intent-to-treat estimator. RCT is randomized control trial. TASAF is the Tanzania Social Action Fund.
The reported impacts
on total expenditures (and corresponding standard errors) presented in 2012 PPP are calculated by inflating the impact in local currency in the various base years (the
year the data
were collected, or as close to that as could be inferred) to their 2012 values using the inflation GDP deflator (annual %), before dividing by the 2012 PPP conversion
factors for private
consumption (LCU per international $). Both indicators used in the PPP conversion come from the World Development Indicators database available at
http://data.worldbank.org/datacatalog/world-development-indicators
Juntos Alcohol
CCT Schluter & Wahba 2004
Nicaragua Red de Protección Social Alcohol and tobacco
Perova 2011
Peru Juntos Alcohol: beer,
whisky, rum, pisco
Compare recently paid to
less recently paid
CCT Dasso & Fernandez 2013
Peru
Alcohol and tobacco Difference in differences
Mexico Programa de Apoyo
Alimentario
RCT
Colombia Familias en Acción Alcohol and tobacco Difference in differences CCT Attanasio & Mesnard 2005
India Unconditional Cash
Transfer Pilot
Alcohol Difference in differences
India Unconditional Cash
Transfer Pilot
Before-after UCT Bhowmik, Gartenberg, &
Sarker 2009
Evans, Hausladen, Kosec, &
Reese 2014
Cigarettes, tobacco
& snuff
Tanzania TASAF CCT Pilot Program
UCT Cunha 2012
UCT Gangopadhyay, Lensink, &
Yadav 2013
Tobacco RCT
UCT Bazzi, Sumarto, & Suryahadi
2012
Kenya The GiveDirectly
Unconditional Cash
Transfer Program
RCT UCT Haushofer & Shapiro 2013
Indonesia Unconditional cash
transfer
23
Table 4: Studies with alternative estimated impact of transfer on alcohol or tobacco consumption
Country Program name Temptation good Impact Detail on impact Methodology CCT/UCT Reference
Brazil Bolsa Alimentaria & Bolsa
Escola
Alcohol, tobacco, and
gambling
−0.003 (0.002) Difference in differences CCT Braido, Olinto, & Perrone 2012
Mexico Oportunidades Alcohol and tobacco -0.0025 (0.0018) RCT CCT Rubalcava, Teruel, & Thomas
2002
-0.02 (0.09) Benefit (dummy)
-0.51 (0.398) Benefit (level)
Nicaragua Red de Protección Social Alcohol and tobacco 0.1 RCT CCT Maluccio & Flores 2005
Mexico Oportunidades Alcohol abuse -0.042*** (0.016) RCT CCT Angelucci 2008
-11%*** (0.026)
Rural, 10 – 21 year olds
incorporated in 1998
-13%***(0.029)
Rural, 10 – 21 year olds
incorporated in 2000
-4%***(0.015)
Urban, 15 – 21 year olds
-15%***(0.029)
Rural, 10 – 21 year olds
incorporated in 1998
-13%***(0.024)
Rural, 10 – 21 year olds
incorporated in 2000
-2%**(0.007)
Urban, 15 – 21 year olds
Alcohol -40%~ Females
Tobacco -46%~ Males
Uganda WFP Cash Transfers to
UNICEF-supported ECD
centers
Beer -0.198 (0.198) ITT RCT CCT Gilligan & Roy 2012
Galárraga & Gertler 2009
Schluter & Wahba 2004
Report probability of alcohol abuse in household
Report probability of consumption (for adolescents only)
Mexico Oportunidades Alcohol Propensity score matching CCT Gutiérrez, Bautista, Gertler,
Hernández, & Bertozzi 2004
Tobacco
Mexico PROGRESA Tobacco RCT CCT
Mexico Oportunidades Instrumental variables CCT
Report number of days consumed in past week (for children 1-7 only)
Notes: * denotes statistical significance at the 10% level, ** denotes statistical significance at the 5% level, *** denotes statistical significance at the 1 % level,
ǂ denotes that
statistical significance is reported but not a standard error, and ~ denotes that statistical significance is not reported. CCT is Conditional cash transfer; UCT is
unconditional cash
transfer. ETT is estimate of treatment on the treated. ITT is the intent-to-treat estimator. RCT is randomized control trial. TASAF is the Tanzania Social Action Fund.
The reported impacts
on total expenditures (and corresponding standard errors) presented in 2012 PPP are calculated by inflating the impact in local currency in the various base years (the
year the data
were collected, or as close to that as could be inferred) to their 2012 values using the inflation GDP deflator (annual %), before dividing by the 2012 PPP conversion
factors for private
consumption (LCU per international $). Both indicators used in the PPP conversion come from the World Development Indicators database available at
http://data.worldbank.org/datacatalog/world-development-indicators
Report proportion of expenditures
24
Table 5: Distribution of Estimates of the Impact of Cash Transfers on Temptation Goods
Table 6: Percentage distribution of Estimates of the Impact of Cash Transfers on Temptation
Goods
Table 7: Percentage distribution of Estimates of the Impact of Cash Transfers on Temptation
Goods – Conditional Cash Transfers (CCTs) versus Unconditional Cash Transfers (UCTs)
Negative &
significant
Negative (or 0)
& insignificant
Positive &
insignificant
Positive &
significant Total
Estimates 12 24 6 2 44
From [–] studies 6 14 5 2 19
From [–] interventions 6 12 5 2 13
Estimates 5 17 5 2 29
From [–] studies 5 11 5 2 14
From [–] interventions 5 10 5 2 11
Estimates 1 13 3 0 17
From [–] studies 1 6 2 0 8
From [–] interventions 1 5 2 0 7
Estimates 0 9 2 0 11
From [–] studies 0 4 2 0 5
From [–] interventions 0 4 2 0 5
Panel D: Only expenditure levels – RCTs only
Panel C: All estimates – RCTs only
Panel B: Only expenditure levels
Panel A: All estimates
Negative &
significant
Negative (or 0)
& insignificant
Positive &
insignificant
Positive &
significant Total
All estimates 27% 55% 14% 5% 100%
Only expenditure levels 17% 59% 17% 7% 100%
All estimates – RCTs only 6% 76% 18% 0% 100%
Only expenditure levels – RCTs only 0% 82% 18% 0% 100%
Negative &
significant
Negative (or 0)
& insignificant
Positive &
insignificant
Positive &
significant Total
All estimates, CCTs 29% 55% 13% 3% 100%
All estimates, UCTs 18% 55% 18% 9% 100%
All estimates, CCTs – RCTs only 8% 77% 15% 0% 100%
All estimates, UCTs – RCTs only 0% 75% 25% 0% 100%
Notes: This table excludes the evaluation of The Kenya Cash Transfer Program for Orphans and Vulnerable Children, which
imposed conditions in 3 of the 7 districts in which it was implemented.
25
Table 8: Percentage distribution of Estimates of the Impact of Cash Transfers on Temptation
Goods by Region
Table 9: Studies with estimated survey or focus group levels of transfer on alcohol or tobacco
expenditure
Negative &
significant
Negative (or 0)
& insignificant
Positive &
insignificant
Positive &
significant Total
All estimates, Latin America 32% 46% 18% 4% 100%
All estimates, other regions 19% 69% 6% 6% 100%
All estimates, Latin America – RCTs only 10% 60% 30% 0% 100%
All estimates, other regions – RCTs only 0% 100% 0% 0% 100%
Country Program name Temptation
good Impact Reference
Democratic Republic
of Congo
Doughnuts and
beer
<1% of households Aker 2013
Jordan UNHCR cash grants Alcohol,
tobacco, and
medicines
1.3% of households Biron 2012
Kenya Kerio Valley Cash Transfer
Pilot
General No reports of use on
temptation goods
Brewin 2008
Lesotho World Vision Cash and Food
Transfers Pilot Project
Alcohol &
tobacco
No significant
increase
Slater & Mphale
2008
Lesotho The Cash and Food
Transfers Pilot Project
Alcohol and
cigarettes
6.4% of recipients Devereux &
Mhlanga 2008
Malawi Mchinji Social Cash Transfer
Pilot Scheme
Alcohol 1.1% of recipients Miller, Tsoka &
Reichert 2008
Malawi Food & Cash Transfers Alcohol,
cigarettes,
entertainment
0.1% of transfer Devereux, Mvula
& Solomon 2006
Malawi & Zambia Oxfam’s cash transfers Alcohol No reports of use on
temptation goods.
Harvey & Savage
2006
Vietnam Non-emergency cash grants
in An Loc commune
Alcohol and
gambling
No reports of use on
temptation goods.
Humphreys 2008
Zimbabwe Government of Zimbabwe
Harmonised Social Cash
Transfer
Alcohol Marginal increase in
consumption
Phiri 2012
Zimbabwe Zimbabwe Emergency Cash
Transfer (ZECT) Pilot
Program
Alcohol &
tobacco
<0.5% of transfer
used on temptation
goods
Román 2010
26
Table 10: Overall Consumption Impacts for Studies with Positive and Insignificant Estimates on Temptation Goods
Country Program name Significant impact on
total consumption
Number of significant
disaggregated consumption
estimates / total disaggregated
consumption estimates
Percentage of disaggregated
consumption estimates that
are significant
Reference
Colombia Familias en Acción x 17/34 50% Attanasio & Mesnard 2005
India Unconditional Cash Transfer Pilot x 4/6 67% Gangopadhyay 2013
Mexico Programa de Apoyo Alimentario x 7/32 22% Cunha 2012
Nicaragua Red de Protección Social x 9/16 56% Maluccio and Flores 2005
Peru Juntos x 4/14 29% Dasso & Fernandez 2013
Nicaragua Red de Protección Social x 9/16 56% Maluccio and Flores 2005
Report proportion of expenditures
Report total expenditures
Notes: This table presents an analysis of the statistical power of evaluations to identify significant impacts on consumption, for those studies which find positive
insignificant impact estimates
on the consumption of temptation goods. To do this, we present both whether or not these studies find significant impacts on total consumption, as well as the number
and percentage of
significant estimates they find for disaggregated consumption items. We are conservative in our calculations of the latter, counting only the most disaggregated
estimates in a given study (for
example, we exclude the estimates for grains in studies which further disagreggate this into estimates for rice, pasta, and cereal). When considering disaggregated
consumption estimates, we
exclude estimates on alcohol and tobacco in these calculations so as to compare the statistical power of the evaluations to identify non-temptation good consumption
estimates with that for
identifying temptation good estimates.
27
Figures
Figure 1: Countries with Estimates of the Impact of Cash Transfers on Temptation Goods or
with Estimates of the Level of Consumption of Temptation Goods from Transfer Income
Note: Areas in red are countries covered (in part or entirely) in our impact and level estimates.
28
Figure 2: Distribution of Estimates of the Impact of Cash Transfers on Temptation Goods
Panel A: All estimates Panel B: Only expenditure levels
Panel C: All estimates – RCTs only Panel D: Only expenditure levels – RCTs only
12 24 6 2
0% 100%
All estimates
Negative &
significant
Negative or zero
& insignificant*
Positive &
insignificant
Positive &
significant
5 17 5 2
0% 50% 100%
Only
expenditure
levels
Negative &
significant
Negative or zero
& insignificant*
Positive &
insignificant
Positive &
significant
1 13 3 0
0% 50% 100%
All estimates –
RCTs only
Negative &
significant
Negative or zero
& insignificant*
Positive &
insignificant
Positive &
significant
0 9 2 0
0% 50% 100%
Only
expenditure
levels – RCTs
only
Negative &
significant
Negative or zero
& insignificant*
Positive &
insignificant
Positive &
significant
Number of
estimates
29
Figure 3: Distribution of Estimates of the Impact of Cash Transfers on Temptation Goods by
Program Type
Panel A: Conditional cash transfers – All estimates Panel B: Unconditional cash transfers – All estimates
Figure 4: Distribution of Estimates of the Impact of Cash Transfers on Temptation Goods by
Region
Panel A: Latin America – All estimates Panel B: Other regions – All estimates
9 17 4 1
0% 50% 100%
CCTs: All
estimates
Negative &
significant
Negative or zero
& insignificant*
Positive &
insignificant
Positive &
significant
2 6 2 1
0% 50% 100%
UCTs: All
estimates
Negative &
significant
Negative or zero
& insignificant*
Positive &
insignificant
Positive &
significant
9 13 5 1
0% 50% 100%
Latin America:
All estimates
Negative &
significant
Negative or zero
& insignificant*
Positive &
insignificant
Positive &
significant
3 11 1 1
0% 50% 100%
Other regions:
All estimates
Negative &
significant
Negative or zero
& insignificant*
Positive &
insignificant
Positive &
significant
30
Annex 1: Studies Included in the Systematic Review
Impact Estimates
Angelucci, Manuela. 2008. “Love on the Rocks: Domestic Violence and Alcohol Abuse in Rural Mexico.”
The B.E. Journal of Economic Analysis & Policy 8 (1).
Attanasio, Orazio, Erich Battistin, Emla Fitzsimons, Alice Mesnard, and Marcos Vera-Hernández. 2005.
“How Effective Are Conditional Cash Transfers? Evidence from Colombia.”
Bazzi, Samuel, Sudarno Sumarto, and Asep Suryahadi. 2012. “Evaluating Indonesia’s Unconditional Cash
Transfer Programme, 2005‒2006.”
Bhowmik, Sharit K., Indira Gartenberg, and Kanchan Sarker. 2013. “Food or Cash: Assisting the Urban
Poor in India.” In The Food Crisis: Implications for Labor, edited by Cristoph Scherrer and Debdulal
Saha. ICDD.
Braido, Luis H. B., Pedro Olinto, and Helena Perrone. 2012. “Gender Bias in Intrahousehold Allocation:
Evidence from an Unintentional Experiment.” Review of Economics and Statistics.
Cunha, Jesse M. 2012. “Testing Paternalism: Cash versus In-Kind Transfers.” Unpublished Mimeo. Naval
Postgraduate School.
Dasso, Rosamaría, and Fernandez Fernando. 2013. “Temptation Goods and Conditional Cash Transfers in
Peru”. Washington, DC.
Evans, David K., Stephanie Hausladen, Katrina Kosec, and Natasha Reese. 2014. Community-Based
Conditional Cash Transfers in Tanzania: Results from a Randomized Trial. Washington, DC: World
Bank: © World Bank.
Galárraga, Omar, and Paul J. Gertler. 2009. “Conditional Cash & Adolescent Risk Behaviors: Evidence
from Urban Mexico.”
Gangopadhyay, Shubhashis, Robert Lensink, and Bhupesh Yadav. 2013. “Cash or Food Security Through
the Public Distribution System? Evidence from a Randomized Controlled Trial in Delhi, India.”
Evidence from a ….
Gilligan, Daniel O., and Shalini Roy. 2013. “Resources, Stimulation ,and Cognition: How Transfer
Programs and Preschool Shape Cognitive Development in Uganda”. Washington, DC.
Gitter, SR. 2006. “Women and Targeted Cash Transfers in Nicaragua.” Aae.wisc.edu.
Gutiérrez, Juan Pablo, Sergio Bautista, Paul Gertler, Mauricio Hernández, and Stefano M. Bertozzi. 2004.
“External Evaluation of the Impact of the Human Development Program Oportunidades:” Mexico
City.
31
Haushofer, Johannes, and Jeremy Shapiro. 2013. “Household Response to Income Changes: Evidence
from an Unconditional Cash Transfer Program in Kenya”. Massachusetts Institute of Technology.
Maluccio, John A., and Rafael Flores. 2005. “Impact Evaluation of a Conditional Cash Transfer Program”.
Washington, DC.
Perova, Elizaveta. 2011. “Three Essays on Intended and Not Intended Impacts of Conditional Cash
Transfers”. University of California, Berkeley.
Rubalcava, Luis, Graciela Teruel, and Duncan Thomas. 2002. “Welfare Design, Women’s Empowerment
and Income Pooling”. Mexico City.
Schluter, Christian, and Jackline Wahba. 2004. “Are Poor Parents Altruistic? Evidence from Mexico.”
The Kenya CT-OVC Evaluation Team. 2010. “Cash Transfer Program for Orphans and Vulnerable Children
(CT-OVC), Kenya: Operational and Impact Evaluation, 2007 – 2009 Final Report”. Oxford Policy
Management.
Level Estimates
Aker, Jenny. 2013. “Cash or Coupons? Testing the Impacts of Cash versus Vouchers in the Democratic
Republic of Congo.”
Biron, Aurélie. 2012. “Adapting to Urban Displacement: The Use of Cash Transfers in Uraban Areas”.
Sciences Po Grenoble.
Brewin, Mike. 2008. “Evaluation of Concern Kenya’s Kerio Valley Cash Transfer Pilot (KVCTP), April – June
2008.”
Devereux, S, and M Mhlanga. 2008. “Cash Transfers in Lesotho: An Evaluation of World Vision’s Cash
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Phiri, Swedi. 2012. “A Comparative Assessment of the Impact of Unconditional Cash Transfers for Urban
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Vaughan, Andres. 2010. “Unconditional Cash Transfers: Will Redistribution in Bolivia Work?” Oregon
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doi:10.1111/j.0361-3666.2005.00323.x.
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