Asset Transfers and Anti-Poverty Programs:
Experimental Evidence from Tanzania *Sarah Baird
George Washington University
Craig McIntosh
University of California, San Diego
Berk Özler
The World Bank
Utz Pape
The World Bank
July 15, 2023
Abstract

We use a set of randomized experiments to examine the impact of a group business development program
implemented by the Tanzanian government, along with a set of complementary training and cash transfer
interventions targeted to vulnerable households in rural areas. In contrast with much of the recent literature,
we find little effect of the business development program. While most enterprises remain operative three
years after formation, even our highest estimates of effective wage rates suggest returns roughly equivalent
to the opportunity cost of time for these households. Trainings on business skills and group transparency
did not improve outcomes, although they appear to have exerted a redistributive effect from group elites torank and file members. Unconditional and unanticipated lump-sum cash transfers to randomly selected
members of these groups induce all members to invest more in the enterprise, with seemingly little to noreturn on these marginal investments. Our results emphasize the importance of profitability as the key
motivation for asset transfer-based social protection programs.
Keywords: Business development, training, cash transfers, social protection
JEL Codes: I38, O15, J24, L26,

* Sarah Baird, email: sbaird@gwu.edu, George Washington University; Craig McIntosh, email:ctmcintosh@ucsd.edu, University of California, San Diego; Berk Özler, email: bozler@worldbank.org and Utz Pape,
email: upape@worldbank.org, The World Bank. Corresponding Author: McIntosh, 9500 Gilman Drive, La Jolla CA,
92093-0519. We thank seminar and conference participants at CSAE, EGAP, WADES, WGAPE, UC Berkeley, and
the World Bank. We thank the following World Bank trust funds for research funding: Spanish Impact Evaluation
Fund, Gender Action Plan, Bank Netherlands Partnership Program, Knowledge for Change Program II, and TrustFund for Environmentally and Socially Sustainable Development. This study is a collaboration between the Tanzanian
government and the World Bank, neither of which required IRB for social science research at the time of the study.
Baird and McIntosh were given access to deidentified secondary data and UCSD deemed it did not need IRB. The
findings, interpretations, and conclusions expressed are entirely those of the authors. The findings, interpretations, andconclusions 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.

1. INTRODUCTION
Social protection programs are increasingly designed to drive sustainable pathways out ofpoverty by investing targeted transfers in income-generating activities run by poor households(Ravallion 2003). The design of such programs varies widely – from unconditional cash transfers(UCTs) to highly tailored and hands-on interventions that launch people into specific lines ofbusiness. In this paper, we evaluate a government program in Tanzania (the Tanzania Social
Action Fund, or TASAF) which provided substantial business startup funding to marginalized
individuals, similar to the Northern Uganda Social Action Funds (NUSAF) Youth Opportunities
Program (YOP) program studied by Blattman, Fiala, and Martinez (2014). 1 Two key differencesfrom that program are that first, the program was targeted to vulnerable individuals (such as theelderly, widowed, or disabled, who were significantly older than the typical NUSAF beneficiary),and second, the groups were encouraged to propose group-based enterprises – possibly to takeadvantage of economies of scale in veterinary and extension support for the primarily animalhusbandry and agriculture-based activities, as well as marketing and transport to trading centers.
We conducted a randomized evaluation of the Vulnerable Groups component of TASAF,
through which groups of ~15 individuals proposed a joint business plan and were provided with alarge grant of working capital (~$6,000) to execute the plan. 2 Most of the enterprises involved the1
Blattman, Fiala, and Martinez (2014) evaluated a government program in Uganda, designed to help poor andunemployed young adults to become self-employed artisans of a skilled trade, called Northern Uganda Social Action
Funds (NUSAF) Youth Opportunities Program (YOP). Potential beneficiaries were invited to form groups and submit
grant proposals to receive vocational training and funding for business start-up. The authors of the study reported
impressive short-term gains in business assets, work hours, and earnings, which were followed by catch-up by thecontrol group in the longer run (Blattman, Fiala, and Martinez 2014 & 2020). A similar increase in earnings in the
short run followed by convergence a few years later is observed in an entrepreneurship program in Ethiopia thatprovided a cash grant and business training to young people (Blattman and Dercon 2018a & 2018b).
2
This part of the experiment uses a pipeline (or delayed-treatment control group) design among successful applicationsin 100 rural communities in five districts of Tanzania as a part of the second phase of TASAF, taking advantage ofthe fact that the program did not have the capacity to fund and supervise all projects at once. A randomly drawn 50%
of clusters were assigned to start their projects with a 12-month delay and form the control group for the groupenterprise intervention.

1

rearing of livestock such as cows, goats, pigs, and poultry. To assess whether some additional
support to these new enterprises – to be run by individuals who did not necessarily haveentrepreneurial skills – could be effective in improving business survival and profits, we randomly
assigned two additional interventions to this government program. The first is a multi-day businessskills and group trust-building training, which followed the ILO’s Start Your Business and ImproveYour Business training modules. The training was assigned at the group level (32 of 59 of the Early
treatment group assigned to training) and conducted around the time of receipt of the grant. The
second is an individually randomized lump-sum UCT, randomly varied between $50 and $350. 3
We find that none of the interventions we study, and indeed no combination of them, hada strong effect on the earnings or consumption of beneficiaries even in the short term. The TASAF
groups were formed, investments made, and business activities diligently operated just as intended.
The groups themselves as well as the assets they held proved remarkably durable, at least for the
36-month follow-up period of our study, and group members not only devoted substantial time but
put their own financial resources into the operation of these groups. The lack of impact across thethree overlaid interventions appears to have a single root cause: these group-operated businesses
were simply not very profitable, at least not for the vulnerable population TASAF targeted and/orThis combination of an asset transfer, entrepreneurial training, and individual income support relates our study toanother type of asset transfer program aiming to build sustainable income for the poor, namely the Graduation
program – although the same key differences in the target population and the unit of intervention remain (ultra-poor
individuals in Graduation rather than vulnerable groups in TASAF). This multi-faceted intervention, also known as
Targeting the Ultra-Poor (TUP) and pioneered by BRAC, includes the transfer of assets (usually livestock), training
and coaching, consumption support, access to financial services, and female empowerment. TUP has been shown tohave consistently significant (if quantitatively modest) effects in Bangladesh (Bandiera et al. 2017) and in a sixcountry study (Banerjee et al. 2015), as well as continuing to confer benefits even 10 years after program
implementation (Banerjee et al. 2021) in one case, namely India. An offshoot of these programs has produced an effort
to understand which components of the bundle are necessary for generating large benefits (Sedlmayr, Shah, andSulaiman 2020) or what other components might be added or incorporated into the next generation of these productive
inclusion or adaptive social protection programs, such as cognitive behavioral therapy (Barker et al. 2021; Bossuroy
et al. 2022). Asking “whether a mere grant of productive assets would generate similar impacts,” a subset of theauthors of the six-country study cited above find that “it does not” – at least not in one of the original study sites in
Ghana (Banerjee et al. 2022). In Appendix B, we provide a more detailed comparison to related social protection
programs.
32

not without more intensive support. When we calculate an effective wage on the time invested inthese businesses it is close to the opportunity cost of time, and indeed lower than the food-forwork wage of $1.35 paid by the other major TASAF social protection program at the time. The
trainings altered the organization of the groups, empowering rank and file (non-leadership)
members and leading to some pull-back of time and contributions by group elites but did not
improve business outcomes overall. Most remarkably, the completely private and individual cashtransfers were largely invested into the group enterprises, which in turn induced substantial
additional individual investment by group members who did not receive any cash. Beneficiaries
found themselves in the same boat as the overall program; piling investment into an entrepreneurial
activity that yielded disappointing returns.
We can delve into the magnitudes of these effects using detailed data that we collectedfrom the group-based enterprises on reported inputs, assets, and earnings at six, 12, and 36 months
after baseline. Beginning with average disbursements of $5,867, groups retained about $5,000 in
assets at the 6-month follow-up and by 12 months had built the value back up almost to the originalvalue before beginning a long-run decapitalization. In groups where no one received a UCT, thetotal business assets declined to $2,660 or just about 40% of the mean value of the grants fromTASAF at 36 months, while groups in which at least one member received a UCT retained, on
average, $5,000 in assets. 4 The average net earnings of beneficiaries from the group business was$3.35 per month ($3.80 in no UCT and $2.80 in any UCT). Even assuming no depreciation ofgroup assets and that all decrease in stock value was consumed, the increase in consumption in the
no UCT arm cannot be larger than $1.50 per person per month when the flow of asset sales is
added to net monthly earnings. The corresponding figure in the groups receiving UCTs is $0.60,
All figures in this paper are in real 2008 US$, the time of the baseline, with subsequent survey amounts adjusted
using a district-specific CPI.

4

3

smaller because of reduced consumption from liquidation of group assets. These numbers
correspond with the evidence from the household data, an insignificant average increase in
consumption of $1.36 per person per month over a baseline mean of $17.8. Hence the combinationof preserved (not consumed) group asset values and low profits limited the scope for increases inhousehold income.
Several features of TASAF may have been problematic in terms of return on investment.
NUSAF YOP selected youth at the beginning of their working careers, invested mostly in training
for skilled trades, allowed more scope for individuals to own enterprises, and avoided low-skilled
sectors such as livestock that make up the majority of TASAF investment. 5 In contrast, TASAF
targeted older individuals with little education and low literacy rates, put investments into lowskilled sectors without barriers to entry, and encouraged group-based enterprises. 6 The
beneficiaries of TASAF are poorer and have far lower baseline enterprise investment even than
the average eligible individual in their villages, although they are better connected politically.
Targeting such individuals, however well-justified on equity grounds, may not have been
conducive to the goal of creating profitable enterprises – at least not without the intensive training
and coaching provided in Graduation programs. 7
Group investments may have also imposed collective-action frictions on the operation of
the enterprises: business training that was overlaid on top of the group-based grants for businessstart-up appears to have done little to improve business processes or outcomes, perhaps because

In a more individualized context, Argent, Augsburg, and Rasul (2014) evaluate Rwanda’s Girinka One Cow Policy,
find that a short and inexpensive livestock management training caused large and long-lasting economic benefits up
to six years after the asset transfer on milk production and yields, household earnings, and assets.
6
The average age of beneficiaries in NUSAF YOP was 25, two thirds of whom were male, and 75% of whom had
primary school education. The corresponding figures in TASAF were 55, 40%, and 5%. NUSAF beneficiaries werealso more likely to reside in large towns or urban areas.
7
Haushofer et al. (2022), who find that cash transfers targeted based on deprivation (rather than, say, potential in theform of high expected conditional average treatment effects) may not be attractive for increasing social welfare – evenwhen the social planner cares about redistribution.
54

of the relatively short duration of our trainings (2-3 days, as compared training over the course of
1-2 years in Karlan and Valdivia 2011). 8 It is possible that more intensive training and/or trainingthat targeted technical aspects of specific business activities, such as the livestock management, or
dairy production, might have been a more effective in creating profitable microenterprises. 9
A voluminous literature documents the ability of cash transfers to build up business assets(see, e.g., Gertler et al. 2012, de Mel et al. 2012, among others). We have one stratum of eligible
individuals who did not participate in TASAF groups and were provided with UCTs; in this group
we effectively replicate the broader literature by finding modest increases in business assets andincome. Our transfers were smaller than the literature evaluating GiveDirectly and our outcome
measurement is relatively long after treatment (24 months) and so our impacts are muted relative
to Haushofer & Shapiro (2016) and McIntosh & Zeitlin (2022), but the general profile of impacts
is similar. 10 Where we find completely divergent results is in the UCT response for individuals
who participate in TASAF groups, among whom little of the value of the cash transfers seems tohave gone into household-level consumption or investment, instead being invested in the group
enterprise. Indeed, for every $100 transferred collectively to the members of a group we find $400
additional in total stock of business assets, a finding that can be explained by the strong effect of
cash transfers on the contributions to group enterprises even for individuals who did not themselves
receive any cash transfer (as well as lower decapitalization of these groups over time). The group

A study using the same ILO Start Your Business materials in Sri Lanka found some impacts on business starts but
none on profits, sales, or capital stock (de Mel et al. 2014).
9
Active labor market programs in low- and middle-income countries is a critical area of inquiry given the dominantrole of informality and self-employment as highlighted by Bandiera et al. (2022), and the literature on these programs
has yielded inconsistent results with low overall returns (Alaref et al. 2020; Bertrand et al. 2021) and few big wins
(McKenzie 2021), albeit for different target populations.
10
While several studies looking at conditional cash transfers (CCTs) have uncovered meaningful long-term effects(Barham et al. 2013, Araujo and Macours 2021), most analyses of UCT programs find benefits that dissipate quite
rapidly (Brudevold et al. 2017; Hicks et al. 2017, Haushofer and Shapiro 2018, Baird et al. 2019). Stoeffler et al.
(2020) find that cash transfers combined with enhanced savings mechanisms can generate asset accumulation among
the very poor, similar to our findings on total stock of assets in groups with UCT recipients in our study.
85ethos appears to have been strong enough to limit the decapitalization of the group enterprises,
while also reinforcing the ultimate centrality of the low returns to the group business investment.
2. MOTIVATION AND STUDY SETTING
2.1 Study Setting
Tanzania, the setting for this study, had a population of 42 million at the time the study
began in 2008. Approximately 44% of the land area is agricultural land with 68% of total
employment in agriculture. The GDP per capita in 2008 was $1,899 (PPP, constant 2017
international $). The annual GDP growth rate averaged around 6% for the period 2000-2020, witha high of 7.9% in 2011 (WDI 2021). Small and medium enterprises account for 50% of Tanzania’s
GDP and generate up to 40% of total employment, however most of these firms have remainedlargely informal. The study took place from 2008-2012 in five districts in Tanzania: Moshi,
Kwimba, Lushoto, Makete, and Nzega. While the selection was purposive, they represent a rangeof the conditions in Tanzania, from relatively richer and more connected Moshi and Lushoto, tothe more remote rural districts of Kwimba, Makete, and Nzega. Compared with the averagepoverty headcount in Tanzania, estimates suggest that poverty rates are lower than average inLushoto and Moshi, roughly average in Nzega, and slightly higher than average in Kwimba and
Makete (Baird, McIntosh, and Özler 2013).
2.2 TASAF’s Vulnerable Groups Program
Tanzania’s Social Action Fund (TASAF) was initiated in 2000 by the Government of
Tanzania as one of its core poverty reduction strategies. TASAF II (2005-2013) was a USD 120
million social funds program – fairly typical of such large programs in Sub-Saharan Africa. It
aimed to address the shortage of social services and income poverty in rural and urban areas aswell as enhance capacity of beneficiaries. The program's financing targeted three main groups:

6

service poor communities (improvement of social services and infrastructure), food insecurehouseholds (public works programs where beneficiaries receive cash for work) and vulnerable
groups (VGs).
The beneficiaries of VG projects are ‘vulnerable’ households, i.e., those containing elderly
individuals, people with disabilities, widows, orphans, and those affected by HIV/AIDS, who form
small groups and develop proposals to receive grants for income-generating activities. The
executive structure of the group consists of a Chairperson, Treasurer, and Secretary, whom weterm the group elite; the executive roles are determined by the group members at the inception of
the project. 11 Appendix Table A1 provides summary statistics for the rank and file, group leaders,and eligible non-beneficiaries in study villages, showing the progressive overall economic
targeting of TASAF and the superior socioeconomic status of the group leaders. 12 In addition, thesurvey team also identified the ‘prime mover’ in each group, defined as being the individual who
is primarily responsible for driving the application and business activity, and while this individual
need not be one of the formal executives of the group we nonetheless include him or her among
the group elites in our data analysis.
The program brings together groups of disadvantaged individuals around a single vulnerability
category (roughly a third are widow/widower groups, a third elderly, and the remaining are orphan
or disabled groups) and asks them to draft a business plan for a small collective enterprise. 13 These
groups vary in terms of business activities, size, and leadership structure. Our sample of 119 groups
consists of 28 cattle-keeping groups, another 53 keeping either goats, pigs, or chickens, 11
See Deserranno, Stryjan, and Sulaiman (2019) for evidence from Uganda as to the ways in which the leader selection
rules can drive the characteristics of those chosen to lead savings and loan groups, as well as the outcomes of thesegroups.
12
Baird, McIntosh, and Özler (2013) show that the actual beneficiaries of TASAF are poorer and more food insecurethan the average eligible member of their villages but are more educated as well as politically connected and engaged.
13Groups containing HIV-affected households benefitted from the program but were left out of the randomized
experiment.
11

7

investing in milling machines, 8 in tailoring, 8 in bee keeping, and the remainder in assorted
agricultural activities such as vegetable production or tree nurseries. The median group has 15
members, with the smallest 6 and the largest 33. After a small amount of training provided by thegovernment on procurement and handling bank accounts, the successful groups are disbursed
substantial productive inputs for the project, with most groups receiving between $5,000 and$10,000, and the average group $6,650. Funds were disbursed from TASAF to an account ownedby the group but jointly supervised by the Treasurer and TASAF, and receipts for purchases ofequipment and services were audited regularly. While our study sample is admittedly a closely
monitored environment, within this group it appears that money was transferred and invested inaccordance with the initial group business plans.
3. STUDY DESIGN
3.1. The TASAF Pipeline ExperimentWithin the five study districts, groups of vulnerable individuals went through the sensitization,
application, and approval process required by TASAF and described in more detail in Baird,
McIntosh and Özler (2013). TASAF VG screening follows a Community Driven Development
rubric, with multiple stages of local participation including vetting eligibility status, a collective
participatory ranking exercise to help select projects with strong local support, and a technicalanalysis by a district-level TASAF official who screens each preliminary business proposal vis à
vis local skills and market conditions. TASAF then identified 100 villages that were close to theapproval stage within these districts, and all VG projects within these villages (119 groups) wererecruited into the study. We conducted a listing exercise in these 100 villages to classify
households as eligible or ineligible according to the VG criteria, and to identify key individuals.

8This pipeline of 119 active groups was randomized at the village level in to two tranches. The
Early group was to be treated right after baseline (59 groups receive TASAF early treatment), andthe Late group to be delayed for a year (60 groups receive TASAF late treatment), with the 12month midline survey conducted immediately before the Late group was treated. Thisrandomization was blocked by district and group type (livestock groups versus non-livestockgroups), and Moshi and Lushoto districts began implementation 10 months prior to the other three
districts, so all survey exercises were delayed in the same way to keep the time from treatment tosurvey consistent across the whole study. Figure A1 shows the timing of the surveys and theinterventions.
3.2. The Training Experiment
Human and managerial capital is a critical input to the generation of entrepreneurial returns(Ibarrarán et al. 2019, Bruhn et al. 2010), and in the context of group investments training also has
the capacity to alter the participation of disempowered members (Blattman et al. 2016). To
investigate this issue, the early treatment group was then further randomized to two groups; oneof which was to receive some form of training (32 groups) and the other would not receive any
training (27 groups). These activities were conducted by an NGO specialized in training activities
for rural citizens in Tanzania (Triodos Facet). The training had two primary components. The firstof these was a Trust Building training given to all trained groups; it was based on ILO’s Grassroot
Management Training and Guidelines for Group Actions. This component emphasized groupcohesion, as well as how to manage intra-group conflict and to create transparent guidelines forbusiness management. 14 A second training was based on ILO’s Start Your Business and Improve

Appendix Figure A2 provides a cartoon used in the training that is exemplary of this component’s emphasis ontransparency and rules-based financial management. As explained above, VG members were brought together by
their circumstances, i.e., by their specific vulnerability or eligibility criterion. As such, they did not necessarily knoweach other or work together before the project. Furthermore, rural villages in Tanzania can cover large spaces and be
14

9Your Business program, a three-day training given to 17 of the trained groups used a standard ILO
business skills curriculum, emphasizing bookkeeping, quality management, and market
development. 15 Attendance of the training activities among all group members was 85% andreported satisfaction with both trainings at the time of completion was very high.
3.3. The Cash Transfer Experiment
Roughly eight months after the Late TASAF treatment had begun in Moshi and Lushoto, andeffectively contemporaneous with the disbursement of the Late TASAF funds in the remaining
districts, we implemented a cash transfer experiment at the household level in study villages.
Figure 1 shows a CONSORT-style diagram of the research design for our study. Eligible
households in the study sample (who are comprised of TASAF member households as well as
those who satisfy the TASAF vulnerability criteria but are not TASAF members, who we refer toas eligible non-beneficiaries or ENBs) were randomized to a UCT control (36% of the eligible
sample in treatment villages), or to transfer amounts ranging in intervals of fifty dollars from $50
to $350, each transfer cell assigned with a probability of 9% and the average transfer being $200.
This randomization was blocked by district and the village-level TASAF Early treatment
experiment. These transfers were delivered by a special team that travelled to the residence of eachhousehold to administer them. This UCT intervention represents a particularly clean example of acompletely unframed, private, and unanticipated cash transfer. Because we were interested to see
how households would freely choose to allocate the transfer across consumption, household
investment, and investment in the group enterprise, we provided no framing for the reasons of thetransfer, saying only that it was being provided to them on a lottery basis because of theircomprised of a number of hamlets that are far away from each other. Hence, building some cohesion in these groups
were seen as potentially useful for the success of the group.
15
Appendix Figure A3 shows the curriculum for this two-day component, illustrating the emphasis on marketing,business management, and the formation of a formalized business development plan.

10

participation in the overall study, and that they were free to use the money as they wished. The
transfer was lump sum, made in cash, and in person to the survey respondent.
The cross-randomization of the UCT transfer against the pre-existing TASAF research
structure creates several subgroups on whom we can focus. First, at the household level, we can
examine the standalone benefits of cash transfers by looking at the Eligible Non-Beneficiarygroup, who never received any of the other interventions in the study and therefore provide astandard UCT experiment with a follow-up 16-24 months after intervention, depending on the
district. We can examine the effect of cash transfers within the TASAF group members bycomparing members who do and do not get transfers on a randomized basis. Finally, because wehave entire TASAF groups in which no individuals were assigned to receive UCTs, we generated
substantial heterogeneity in the cumulative amount of money transferred to group members(ranging from 0 for almost half of groups to a maximum of $1,300) and so we can use this variation
to study outcomes for the groups, looking both at the group-level totals as well as at the behaviorof other individuals in these groups who were not themselves treated with UCTs.
Because of this design, at midline we have a simple experimental analysis where we cancompare the trained and untrained TASAF groups to the control. By endline all of the TASAF
members are treated, and in the endline we can examine the persistent effects of the training, as
well as the experimental analysis of the UCT (crosscut over ENB and TASAF training status).
3.4 Data Collection and Outcomes
The listing exercise at the village level partitioned all households into those who would be
eligible (containing an individual meeting one of the VG criteria) versus ineligible (everyone else).
We also identified and surveyed key village-level elites (the Village Executive Officer andChairperson as well as the individual who was the ‘prime mover’ of the TASAF application,

11

whether they were a group member or not). Within TASAF groups we classify households as
belonging to Group Leaders (or GLs, comprised of the group’s Chairperson, Treasurer, orSecretary), or the Rank & File (or RF, if the household contains any other group member). For all
119 study groups, we sampled all three GLs into the study, and we also randomly sampled threemembers from the remaining RF. As shown in Baird, McIntosh and Özler (2013), GLs tended tobe substantially wealthier and better educated than RF. Finally, in each village, we sampled three‘eligible non-beneficiaries’ (ENB), who met the technical qualifications for inclusion in a TASAF
VG group but were not beneficiaries.
Within this sample, we conducted a number of surveys. 16 First, we conducted a comprehensive
three-wave household survey. The survey included data on consumption, income and revenue,
savings and borrowing, revenue, food security, productive assets, livestock, housing quality, foodsecurity, health, and education. We also tracked the progress of the groups, using a detailed
enterprise survey, which included the ability to track the contributions and profit-taking ofindividuals within the groups. For the enterprise survey we have an additional ‘rapid resurvey,’
conducted roughly six months after disbursement of TASAF funds to the Early treatment group,
intended to capture outcomes immediately after disbursement. 17
As this study began in 2008 with data collection ending in 2012, it pre-dated the standard useof trial registration and pre-analysis plans. Thus, we use two seminal papers in the literature –Banerjee et al. (2015) and Haushofer and Shapiro (2016) – to guide our grouping and selection ofprimary and secondary outcomes. Our primary outcomes include consumption (food, non-food,All survey instruments and enumerator manuals can be found here.
An important issue in survey design, given the capture of assets at both the group and household level, is avoiding
double-counting the same assets. In an attempt to avoid this, we carefully distinguished group assets as thoseconsidered to be owned collective by the group, and in the household survey we asked separate questions about
individually-owned assets versus group owned assets (typically livestock) that might be on household land or
supported with household labor and expenditure, but were not owned by the household.
16
17

12

and total, measured as real USD monthly per capita adult equivalents – adjusted for differences inprice levels across districts and over time), housing quality, livestock, and productive assets. For
housing quality, we use an indicator for whether the household has an improved roof as its own
outcome (following the results in Haushofer and Shapiro 2016). For livestock, we measure thetotal value of all livestock (both including and excluding group owned livestock), and examine thenumbers of dairy cows, dairy goats, pigs, and all poultry. Productive assets include two outcomesof interest: the total value of durable productive assets and the total value of businesses. Secondary
outcomes include food security, health, education, income and revenue, and savings andborrowing. 18
3.5. Attrition and Balance.
We began the experimental component of the study with 1,017 eligible households having
responded to the baseline survey. In Table A2 we examine whether subsequent attrition from thestudy was driven by any of the treatments. We see that attrition from the study was 5.5% at 12
months and 14.2% at 36 months from baseline. While it was substantially lower among groupleaders than the rank and file, it was not correlated with being treated by TASAF, receiving trainingor the UCT, or getting both TASAF and the UCT (the UCT variable here, as in the impact
regressions, is in units of hundreds of dollars received by a household).
The study appears well-balanced; Table A3 shows balance using the household data, including
all TASAF members, and incorporating dummies for Early TASAF treatment and Training, as
well as the UCT and UCT*Training interactions as above. Across all primary outcomes we find18
Food security is measured by looking at the average number of meals eaten in a day by an individual in thehousehold. Health includes three measures: the proportion of household members who were sick or injured in the past
week, whether the respondent’s self-reported health was good or average, and in index of disability for those over 15.
Education looks at the proportion of school-aged children in school at the time of the survey and school expenditures.
Income and revenue, all in the past year, includes agricultural revenue, livestock revenue, livestock expenditures,
livestock profit and enterprise income. Finally, savings and borrowing looks at total savings and total borrowing.

13

only 1 out of 40 comparisons significant at the 5% level, slightly less than what we would expectby random chance. Because the TASAF groups do not exist at baseline we do not test for balanceon the group data.
4. Observational evolution of the TASAF groups over time.
A starting point in understanding what the TASAF investment did is a simple descriptive
analysis of the evolution of enterprise outcomes. In 92% of cases the TASAF program created thegroup enterprises from nothing, and so business outcomes such as business assets and profits are
typically zero prior to treatment (meaning the baseline for the Early group, and the baseline, therapid resurvey (RR) at six months, and the midline at one year for the Late group). 19 Using ourthree post treatment surveys we can construct four different durations since treatment: 6 months(RR), 12 months (R2), and 36 months (R3) for the Early treatment group, and 24 months (R3) for
the Late-treatment group. To avoid conflating the effects of the UCT with the normal operatingof the TASAF groups, which are only relevant for R3 outcomes and presented later in this section,
we only include the groups that received no UCTs.
Table 1 provides basic summary statistics of group outcomes (first six columns) andindividual contributions to/earnings from groups (remaining columns) across the four rounds ofthe survey. It illustrates the way the pipeline design worked, with no activity in any group atbaseline, the Early groups in full swing by the 6- month RR, and then despite some initial stirringsof activity in the Late groups during RR and R2, no sizeable business activity in them until R3. In
general, as we would expect based on a simple duration-from-treatment model, the Late group at
R3 has outcomes that are intermediate between the R2 and R3 outcomes for the Early group.

Six of the 60 groups in the delayed treatment arm had positive total stock values at the time of R2 data collection
with average stock values much smaller (USD 653) than the groups in the TASAF early treatment arm (USD 5,633).

19

14

The average disbursement to groups was $5,867. Within the first six months of
disbursements, groups spend nearly half of total available funds on set-up costs and working
capital, ending up with combined assets plus working capital at about 83% of the grant. Figure 2
shows how this number then evolves over time: group value climbs quickly between 6 and 12
months, peaks at about 96% of the originally disbursed value 12 months subsequent to
disbursement. This increase comes from some of the investments paying off (e.g., piglets are born;
pigs fatten). At the 36-month follow-up, the total value of the stock of assets at the enterprise levelin Early treatment groups that received no UCT has fallen to $2,660, or 45% of the disbursed
amount. Hence, in the absence depreciation or profit in the group enterprise, we would expect justover half of the disbursed money to have shown up in household balance sheets within three years
simply through consumption of the principal.
What then is the evolution of returns to group members? To examine this, we use questions
asked of each group member about individual investment and profit-taking. During the enterprisesurvey, we ask every individual in the group to report time inputs in managing the group activity
and the value of cash and kind investments in the group, as well the income taken out of the groupby individuals. By calculating the difference between income and investment at the individuallevel we have a net income per individual in the group, and by then dividing this by the averagetime input we can directly calculate an effective wage rate. Note that because we cannot distinguishbetween realized profit and consumption of business principal, this wage rate is inclusive of thepace at which overall group value is being drawn down. Wage changes over time in the UCT
control are plotted in Figure 3 (note that these are simple group averages relative to time of
disbursement, not causal impacts relative to a counterfactual), with a quadratic time trend
superimposed. We see negative effective wages at six months (reflecting that individual

15

investments into the enterprises still exceed profit taking). By 12 months the wage is effectively
zero; by 24 months it has grown to $.50 per day (using data from the Late treatment group), andby 36 months to almost exactly $1 per day, significantly different from zero.
How does the total value taken out of group enterprises compare to the draw-down in groupvalue? The difference between these two quantities, in principle, reveals the extent to which therealized income gains are driven by profits or consumption of principal. As an (admittedly
imperfect) way of doing this, we can take the observed values for the Early treatment group from
Table 1, linearly interpolate the stock values, contributions, and earnings across months. The
difference between these latter values, multiplied times 14.5 (the average group size) gives the net
contribution to the group in a month (where a negative number implies net withdrawals). We canthen aggregate the stock asset value we would expect to see in each period according to net
contributions in the prior month and compare this aggregated value to the observed (interpolated)
stock. The difference between the two should arise from profit (if positive) or depreciation (ifnegative). The results of this simulation are presented in Figure A4, which illustrates that at theirmaximum around R2 the TASAF groups had generated $678 in real profit, but that from there
group values deteriorated faster than would be expected given profit-taking, implying depreciation.
The average monthly profit net of contributions in the six-month accumulation phase was 1.92%
per month (as a percentage of the original grant), and the average depreciation in the 24-month
period between R2 and R3 was -1.74% per month.
There are reasons for some optimism in these results: the group enterprises funded by
TASAF are durable, they appreciate in total value over their first year, and pay effective wages
that grow monotonically over time. However, even at their highest observed value the effective
wage rate yielded by participation in the groups is just $1 per day, lower than TASAF’s own Food16

for Work daily wage of $1.35 per day. 20 Hence at no point in the study did the average return tolabor in the VG program equal what was paid in the standard workfare program. All of thissuggests that when we turn to the household analysis, we may expect to see very modest causal
effects of the TASAF VG program on outcomes like household consumption unless theopportunity cost of time in beneficiary households was extremely low.
5. MIDLINE ANALYSIS.
5.1 Household impacts of TASAF and training experiments.
We now use the midline comparison between untrained TASAF groups, trained TASAF
groups, and control to estimate the experimental impact of the program at the household level. We
can run the standard cross-sectional ANCOVA regression in the midline:(1) 𝑌𝑌𝑖𝑖𝑖𝑖 = β0 + γ1 𝑇𝑇𝑣𝑣 + γ2 𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑣𝑣 + β1 X𝑖𝑖𝑖𝑖 + β2 Y𝑖𝑖𝑖𝑖0 + ϵ𝑖𝑖𝑖𝑖

In this regression 𝑌𝑌𝑖𝑖𝑖𝑖 is the outcome for household i in village v, 𝑇𝑇𝑣𝑣 is a dummy for the Early

treatment group without treatment, the variable 𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑣𝑣 is a dummy for groups that receive bothTASAF and training (meaning that both dummies are compared to the control), X𝑖𝑖𝑖𝑖 includes blockrandomization strata fixed effects a dummy for whether the household contains a group leader,and Y𝑖𝑖𝑖𝑖0 is the baseline outcome. Regressions are weighted to be representative of all groupmembers, and standard errors are clustered at the village level, the unit of treatment assignment.
In the core tables we also provide p-values on the F-tests of the similarity of the treatment effects
coefficients (does the training add significant value over TASAF alone) and on the joint
significance of the two treatment terms (which maximizes sample size and power in the test of
TASAF bundled with training).

20

See the TASAF Assessment Handbook at this link.

17

Our first household analysis focuses on the ownership of livestock, given that most of the
TASAF groups invest in some form of animal husbandry. This provides a clear way to begin
parsing what we can learn from the pipeline design of the study. In the first row of Table A4 we
see the midline experimental treatment-control difference, revealing the number of cows
significantly increasing (a coefficient of .2 representing a quadrupling from the baseline control
mean of .05), as well as an increase of almost .5 in the number of pigs owned. As we would expect
these increases are similar in trained and untrained groups. Interestingly, the livestock displaying
strong serial autocorrelation (goats and poultry) are not those driven by TASAF, suggesting thatthe program is inducing movement into new forms of animal husbandry. Given our efforts not todouble-count, these should be taken as impacts above and beyond the shift in strictly group values
reported in the previous section, i.e., these are animals that are reported by group members ownedby them as opposed to being a ‘group cow’ or a ‘group pig.’
Having illustrated these mechanical effects of treatment, we then move to examine thedeeper household impacts of TASAF. Given the results of the prior section, we may expect that
despite the presence of additional assets, the returns being generated by the assets are
disappointing. Indeed, Table 2 shows very muted household impacts of TASAF funding on
primary outcomes at midline. TASAF alone appears to have led to a modest increase in non-foodconsumption and an increase in expenditures on livestock, but these changes are relatively small
in absolute terms (this translates into a less than 8 percent increase in overall consumption relative
to the control, and while livestock expenditures have doubled at midline, livestock revenues are
actually somewhat lower than the control). Agricultural income from sales of crops is no higher,
and household-level enterprise profits and assets are not improved. Hence, this picture suggeststhat the flow of income from TASAF group enterprises is being invested in livestock assets but

18

has neither translated into flow consumption benefits nor helped the household to increase othersources of income. The groups receiving training do not show superior outcomes on any of ourprimary measures, a theme to which we return later.
Does this general lack of significance arise from a lack of power? For highly skewed
outcomes, the answer appears to be ‘yes.’ For livestock profit, for example, the standard error on
the impact estimate (62.4) is almost as large as the control group mean (71.3) and so we would
barely be able to detect a tripling of the outcome. Livestock revenue, and to a lesser extent
enterprise assets, are similarly underpowered. For other outcomes, our insignificant estimates aremuch better powered. Our core consumption aggregate, for example, has an impact standard errorof 1.29, meaning that we would have been able to detect a change of 2.6 dollars. This quantity isequivalent to moving from the median to the 59th percentile of endline consumption among thevulnerable, and hence supports a reasonably precisely estimated zero.
Analysis of a set of secondary outcomes in Table A5 arrives at a similarly pessimistic
conclusion. This analysis has the same structure as the previous one except that we do not havebaseline observation of these outcomes and so it is a simple midline cross-section rather than an
ANCOVA. We examine outcomes related to food security, durable consumption, savings,
borrowing, schooling of children, and health, and find no impacts significant at the 95% level for
either treatment, even when we use the F-test to look for joint significance of the two treatments.
We can also focus our analysis on the wellbeing of the specific vulnerable individual whose
presence was the basis of the household’s eligibility for TASAF. A core purpose of programs withelaborate targeting criteria that attempt to draw in vulnerable individuals is the desire to improve
the health and consumption of these individuals specifically. To examine whether household-level
impacts could be muting a stronger impact on the actual vulnerable group member, we exploit an19

individual-level survey module to report on the health and the consumption of the actual VG groupmember at the time of the round 2 survey, before the late-treated group was treated. These results,
in Table A6, examine illness, hospitalization, morbidity, self-reported health, and individual foodinsecurity for the targeted individual. The results provide no evidence that the VG group members
who had benefited from 12 months of TASAF treatment enjoyed better health or superior
individual-level consumption.
5.2. Digging into the impacts of training.
The simplest way to analyze the training experiment at the group level is to use only the
Early-treated TASAF groups, within which the training experiment was performed, and compare
the trained groups with the untrained at RR, midline, and endline to examine the additional effectof training using an interaction between the training dummy and round dummies. Table A7 showsthat at R2 trained groups are more likely to be keeping written records of group accounts, but theseeffects fade by R3, and do not carry over to other practices. Columns (5) – (7) of Table A7 examine
the key entrepreneurial outcomes at the group level (sales over the past month, stock value ofgroup assets, and 6-month profits). 21 We find no impacts of training either at midline or endline,
although the point estimates are large and imprecise due to the small sample size of groups andlarge variation in these outcomes.
What about the possibility that the trainings altered the functioning of groups, specificallythe division of spoils between group leaders (GLs) and Rank-and-File members (RF)? Table A8
presents the effects of the program on individual outcomes. In the absence of training, GLs weremuch more involved in the groups than RF, putting in more labor and inputs and particularly in

All but two of the groups in the early treatment arm are operating an income generating activity at RR– with average
total business stocks in the untrained groups valued at approximately $5,564, mean sales during the past month justover $40, and net losses in their first six months of $67.

21

20

the endline receiving more not just in terms of overall income but being paid a higher effective
wage as well. At midline, we already see some discouraging effect of the training on thisdifferential effort, with trained GLs putting in significantly less labor than untrained GLs (and no
more than their RF group members), although they continue to earn more income. By the endline
this divestiture is clearer, with negative interacted coefficients on all metrics of involvement by
the GLs, and their behavior in trained groups never being different from RF although GLs in
untrained groups are significantly more engaged across every measure. 22 The training intervention
seems to have led to a more equitable distribution of the group profits between its members, i.e.,
reducing within-group inequality, without reducing the modest total net earnings of the enterprises.
However, this equality was achieved in large part by a reduction in effort by the comparatively
higher skilled group elites.
6. IMPACTS OF CASH TRANSFERS.
For the cash transfer study, we first randomly selected half of the villages to be included in
the UCT experiment, blocked by TASAF treatment status (Early, Late, and ENB), and thenindividually randomized UCT treatment within selected clusters. Hence, we can consider the
impact of standalone transfers among the ENBs as well as the impact of transfers on top of TASAF
grants for the beneficiary households. Transfers were made shortly after the midline survey, so the
Early TASAF treatment group had received funding over a year earlier, while the Late TASAF
treatment group received their VG grant just several months before the UCT. The endline survey
captures outcomes roughly two years after the transfers were made. To analyze UCT impacts we

22
At the 36-month follow-up, a typical GL in an untrained group spends 55 hours per month working on the group
enterprise and has net earnings of USD 6.91, compared with 33 hours and USD 4.31 for the average untrained RF
member. These differences are statistically significant at the 95% level of confidence. However, if the groups havereceived training, these differences shrink substantially (even disappear) and become statistically indistinguishable:
trained GLs and RF members work 32 vs. 30 hours and earn USD 5.82 vs. USD 5.55 per month, respectively.

21

include the size of the transfer to a household as the treatment variable – in units of hundreds of
US dollars (randomized between $50 and $350, with the mean and median transfer amount among
UCT recipients equal to roughly $200) and set to zero for households who received no transfer.
Table 3 analyzes impacts of the cash transfers in the ENB stratum, which, given the absenceof any other interventions in that population, studies an intervention much like the large cashtransfer literature, such as the numerous studies on GiveDirectly transfers in Kenya (Haushofer
and Shapiro 2016, Egger et al 2019) and Rwanda (McIntosh and Zeitlin 2022), albeit with
substantially smaller transfer amounts. Perhaps given the relatively small size of our transfers andthe 24-month follow-up duration, we do not find any appreciable effects on consumption or
livestock value. We do detect a large but noisy increase enterprise assets and income, significant
at 90%, indicating an increase of $29 per $100 of UCT, or an average treated impact of $58 overa control-group mean of $78.
Given the complex research design among TASAF beneficiaries by R3 and the concerns
raised by Muralidharan et al. (2019) over the pooling of arms in factorial designs, we present theR3 UCT impacts in two distinct ways. In Panel A of Table 4, we follow the same structure as theprior table, pooling all UCT treatment and estimating a single ANCOVA regression for TASAF
beneficiaries. In Panel B, we show every cell of the research design separately to avoid conflating
the impacts of Early TASAF treatment, training, UCT, and their interactions. Each cell is defined
as a standalone treatment variable (so that all impacts are measured relative to the control group)and p-values from F-tests are provided at the bottom of the table for the joint effect of the three
UCT arms and the two training arms. Interestingly, however, we see quite a different pattern ofimpact on business investment, with the UCTs actually leading to a significant decrease inagricultural income, and rather than a significant improvement in enterprise income we see a22negative effect on both income and assets with t-statistics above 1. Hence, something distinct
seems to be occurring with the TASAF beneficiaries; they are failing to translate individual-level
cash transfers into improvements in household enterprise outcomes. 23 Table A8 (using an R3
ANCOVA regression model with an interaction term to test the difference between TASAF
members and the ENBs) shows that the UCT-receiving TASAF members are achieving lessenterprise income at the household level than are the ENBs who get UCTs.
The obvious explanation for this divergent pattern is that the TASAF group members havea unique non-household vehicle for investing cash transfers, namely the group business. We have
two distinct ways of approaching this question. The first is individual; we can bring the datacollected in the group survey about individual contributions to and receipts from the group together
with the treatment status from the UCT experiment to ask whether those who received cash behave
differently in the groups. The results of this analysis, presented in Table 5, show that indeed
recipients of UCTs engage more strongly with their groups. We see a 10% increase over the UCT
control group mean across the board per $100 transferred, which is only statistically significant
for labor inputs. In each case these treatment effects at the average transfer represent increases ofabout 20% over the no-UCT mean. Hence, those receiving the UCT are putting more effort towards
the group activity and yet not receiving sufficiently more from this investment for it to show up ineither earnings or consumption.
Our second means to address the relationship between the UCT and TASAF is at the grouplevel. The total amount of cash transferred to the members of a group is effectively randomized,
and so we can examine how this variation translates into changes in group outcomes. The UCT
represents a substantial positive liquidity shock and arrives in a lump-sum cash form ideal for
Appendix Table A9 shows that there are also no significant impacts on secondary outcomes from the UCT for
TASAF beneficiaries.
23

23

investing, and so a natural question is the extent to which cumulative UCT receipts are translated
into observable investments in the TASAF group activity. Despite the very private way in which
the transfers were made, the decision to invest in group businesses could arise either as anindividual investment decision or could be driven by social pressures from the group (at the endof this section, we present suggestive evidence that such a mechanism may have been present). In
making investment decisions, UCT recipients would face a private version of the same welfare
issue that motivates this paper: with liquid capital in hand, does making investments in group asset
generate higher net present value than the alternatives, or than simply consuming the money overtime?
Table 6 shows that there was a strong tendency for TASAF members to invest transfers in
the group enterprises. Indeed, for every $100 received collectively by group members we find thatthe total value of the stock in group businesses at endline is $402 higher (over a base of $2,284).
This somewhat remarkable finding indicates that the UCT provides a log-rolling opportunity
through which money received by some group members effectively generates a multiplier of 4 on
the stock value that groups succeed in maintaining in the joint enterprises two years later. Despite
the 25% increase in total stocks arising from the UCT, however, there is no concomitant
improvement either in the flow of sales or the profitability of the groups as a result of the cashtransfers. The finding that TASAF members invested heavily in group projects and saw very little
return on this investment, at least within the window of our study, squares the distinction between
the impacts of UCTs on TASAF members versus the ENBs. The substantial accumulated assets
may lead to future welfare benefits for group members but could not be used to drive household
enterprise outcomes within the window of the study.

24How is it possible for the cumulative group transfer to have driven such large increases inthe stock value of enterprises? The answer is that the receipt of the UCT by some group members
led to a strong increase in the contribution of other group members, whether or not they themselves
received money. We can show this in two related ways. First, Panel A of Table 7 uses the samestructure as Table 6 but analyzes only those individuals who do not themselves receive a UCT.
This simple experimental spillover analysis shows that there are significant increases in financial
and labor inputs to the groups occurring even for those who receive no cash directly, and again no
improvement in profits or wage. In Panel B, we use all group members and include the cumulativetransfer to everyone else in the group as well as the individual UCT in the analysis of individual
contributions to the group (now clustering at the village level). This structure, with both quantities
randomized but correlated because of the village-level assignment step in the UCT experiment,
allows us to separately identify the impact of transfers to others from receiving money oneself.
The rest-of-group cumulative cash transfer has a significant impact on the financial and labor
contributions by individual group members to the group. Remarkably, once we have controlled forthe cumulative group transfer the additional effect of own cash transfer amount becomesinsignificant, suggesting that the collective peer effect is entirely responsible for the contributions.
The implication is that the individual-level impact shown in Table 5 arises entirely from theintersection of the contribution spillover effect and the fact that own and other UCT treatments
status is mechanically correlated due to the village-level component of the UCT design (thecorrelation is .3775). Neither own nor other contributions improve profits, earnings, or effective
wages at the 95% significance level. 24

Table A11, which examines a set of social capital outcomes among vulnerable households in the endline, provides
some suggestive evidence for the possibility of social pressure from other group members. In this table the TASAF
dummy is observational and recreates the results from Baird, McIntosh, and Özler (2013), showing TASAF members
to be substantially more politically engaged than the eligible non-beneficiaries. The randomized UCT treatment never
24

25

This set of findings amplifies a major theme of this study. These group enterprises display
a remarkable collective ethos, with group members working together over the course of years andsacrificing at the individual level to build a joint enterprise. The notable durability of the TASAF
enterprises and the breadth of investment by GLs and RF alike attest to this dedication. This
collective ethos is so strong that improving the wealth of some group members effectively exerts
a tax on other group members in an effort to prevent the drawing-down of group value otherwise
observed. While the UCTs allow groups to protect collective asset investment from being
decapitalized, this is achieved by piling individual resources into enterprises in which the rate of
return may ultimately be too low to justify the cost.
7. CONCLUSION
Tanzania is distinctive for its socialist roots, combining the broader African traditions ofredistribution and risk-sharing (Jakiela and Ozier 2015) with the Ujamaa philosophy of its firstpresident Julius Nyerere and the Chama Cha Mapinduzi party that has ruled the country since
independence. While the economy has liberalized since reforms began in the 1990s, the results ofthis study serve as a parable for the uneasy ways in which the growth-based capitalist mindset
might relate to this underlying collectivist tradition.
For a group-based model to function at all, members must be able to overcome the tragedyof the commons, invest assets that could be coopted for individual purposes in a collective
endeavor, and remain involved with that endeavor over a long enough timeframe to give successa chance. All these hurdles were cleared under TASAF VG projects. We developed our ‘rapid
resurvey’ check-in six months after the groups had been treated, fearing that most of the assets

has any effect on trust or political participation among non-beneficiaries, but only amongst individuals participatingin TASAF, the receipt of a UCT leads to a substantial decline in trust in other village members – a drop of more than
6pp off a mean of 74%.

26

might have been already privatized and liquidated by that time. Instead, we found every single
treatment group operating robustly at that point, with enterprise asset values that had increased by
5% on average six months later, and with more than half of the original asset value in the groups
three years later. While labor contributions had tapered off by about a third between RR and
endline, financial contributions and profit-taking both increased over that interval. Only six of the
59 Early treatment groups report zero stock value three years later. So as collective entities, theVG projects had been durable.
As capitalist entities, however, they have been less successful: ultimately the justification
for this type of economic inclusion program relies on these groups to become profit-making
businesses. Precisely because members were so reluctant to draw down stocks quickly to consumethem, we did not see the types of short-term consumption gains that are typical in the cash transfer
literature. Because they were also unable to translate the investment into high entrepreneurial
returns to their labor, effective wages realized from the substantial devotion to these groupbusinesses appears not to have been superior to the returns from counterfactual labor returns,
generating scant benefits relative to the control. While a training intervention was successful ingenerating a more egalitarian pattern of contributions to and profit-taking from the group, this did
not result in improved overall group performance. In the most pyrrhic evidence we present, notonly those receiving UCTs but other members of their groups who do not receive transfers all pile
individual liquidity into this group investment achieving these same low returns.
The policy conclusion emphasizes the extent to which the logic of any entrepreneurial asset
transfer program is in fact predicated on the returns to investment. If livestock groups are unable
to turn an economic profit (generating durable returns to labor in excess of the prevailing wage),then they are effectively cash transfers ‘on the hoof,’ providing a medium-term consumption

27

support program that will dissipate as the original investment is consumed away. While a welfare
case can still be made for such a program, the relevant questions would then center around the risk
and smoothing properties of transfers provided in this manner (which pushes labor and livestockmortality risk on to the beneficiary but gives them more control over the pace of spend-down)
relative to a more predictable flow of payments as from a typical cash transfer program.
To have implemented multiple components of the successful TUP model and not beensuccessful in reducing poverty, the conclusions of this study are mostly sobering. First, while groupstructures may make sense for training and launching new businesses, it is not clear that they arean effective way to create strong dynamic profit motives. Second, generic short-term training on
business practices is likely to be less effective (if also less expensive) than a more long-term,
focused, vocational form of training that builds marketable skills in specific areas. Finally, thereturns to cash transfers are driven entirely by the way in which they are invested. When othercomponents of an intervention have been successful in succeeding profitable business
opportunities, cash is likely to achieve high returns, and where such opportunities are lacking, it
will not.

28

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against Unconditional Cash Transfers in Rwanda. arXiv preprint arXiv:2106.00213.
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31

TABLES AND FIGURES.
Table 1: Descriptive Statistics on Group Activity for Early and Late Treatment Groups
Group-Level Outcomes:

Individual-Level Group Interaction:

Sales 1 month
Late
Early
0
0
(0)
(0)

Total Stock
Late
Early
0
0
(0)
(0)

Profit 6 months
Late
Early
0
0
(0)
(0)

Labor Inputs(Hours/Wk)
Late
Early
0
0
(0)
(0)

Financial Inputs($/Mo)
Late
Early
0
0
(0)
(0)

Earnings Taken($/Mo)
Late
Early
0
0
(0)
(0)

Rapid Resurvey

0.1
(1.1)

29.6
(85.2)

19.0(75.1)-96.1(418.2)

0.6
(3.5)

0.8
(3.7)

14.4
(15.6)

0.1
(0.3)

3.2
(5.4)

0.0
(0)

1.3
(3.7)

Midline (R2)

2.4
(18.6)

80.8(142.1)65.3
5658.4(326.0) (3090.5)

74.2
-7.4
(1055.5) (294.4)

0.1
(0.7)

11.6
(14.4)

0.0
(0.1)

4.7
(12.0)

0.0
(0.3)

5.9
(13.9)

Endline (R3)77.0
(117.3)74.7(159.0)3403.7 2659.7(2517.5) (2376.0)

86.9
439.0
(333.6) (948.5)

10.3(12.9)

9.0(11.3)

1.4
(3.2)

1.1
(2.9)

2.7
(5.5)

6.5
(11.8)

60

59

372

358

372

358

372

358

Round:
Baseline (R1)N

60

5089.2(2444.9)

59

60

59

Notes: Table gives the mean and SD (in parentheses) of outcomes at the group level (first six columns) and at the individual group-member level (remainingcolumns) across each of the four rounds of the group survey. The "Early" group was treated immediately after the baseline survey (R1), and the "Late" group
immediately after the midline (R2). Values for R3 use only the TASAF groups that did not receive UCTs to avoid conflating the effect of cash transfers withTASAF. All currency values are in constant 2008 USD.

Table 2: Midline Analysis of Primary Outcomes at the Household LevelTASAF treatment
TASAF + training
Baseline outcome
Midline Control group mean
P-value: TASAF = TASAF + training
P-value: TASAF, TASAF + training joint signif.
Observations
R-squared

Per-capita Per-capita
Per-capita
Food
Non-Food Improved Livestock Livestock Livestock Agricultur Enterprise Enterprise
Consumpt
Consumpt Consumpt
Roof
Cost
Revenue
Profit al Income Income
Assets
ion
ion
ion
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(10)
1.36
-0.36
1.72**
0.036
17.0**
-6.20
-18.8
-6.58
-4.16
6.26
(1.29)(0.67)(0.85)(0.033)(8.57)(66.7)(62.4)(12.5)(27.2)(22.8)
-0.51
-0.50
-0.21
0.037
11.9
29.2
22.9
10.6
-11.7
-23.5
(0.86)(0.65)(0.39)(0.037)(7.90)(64.4)(62.2)(13.2)(25.5)(14.9)
0.51*** 0.31*** 0.53*** 0.68*** 0.43***
0.018
0.00420.30*** 0.72*** 0.66***(0.054)(0.051)(0.085)(0.053)(0.12)(0.032)(0.035)(0.067)(0.086)(0.045)
17.8
0.13
0.642
631
0.32

12.2
0.84
0.453
631
0.23

5.52
0.022
0.146
631
0.25

0.74
0.98
0.185
631
0.65

17.7
0.63
0.0235
630
0.16

91.4
0.66
0.827
631
0.033

71.3
0.58
0.968
630
0.039

72.4
0.27
0.846
631
0.25

131.8
0.78
0.724
630
0.58

82.9
0.16
0.594
631
0.55

Notes: *** p<0.01, ** p<0.05, * p<0.1. Table estimated for the full household sample of TASAF group members at midline, comparing the groupexperimentally offered TASAF and those offered TASAF + training to the control group. The regression is a cross-sectional ANCOVA including blockrandomization fixed effects The first F-test at the bottom of the table gives the p-value on the F-statistic for the difference between the treatment coefficients,and so tests the additional impact of the training. The second F-test is the p-value on the significance of the sum of the two treatment dummies. Standard errors
clustered at the village level (unit of random assignment). Consumption numbers are monthly adult equivalents, and all monetary figures are in constant 2008
USD, and survey weights are used to make the analysis representative of all TASAF group members in study villages. All outcomes Winsorized at 1% and 99%.
Standard errors clustered at the village level (unit of random assignment).

33

Table 3: Cash Transfer Impacts on the Eligible Non-Beneficiaries

Primary Outcomes:
Per-capita
Per-capita
Per-capita
Improved
Livestock
Livestock
Livestock
Agricultural
EnterpriseEnterprise
Food
Non-Food
Consumption
Roof
Cost
Revenue
ProfitIncomeIncomeAssetsConsumption Consumption
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(10)
UCT Effect in R3 (100 USD)
0.52
0.26
0.37
0.015
0.79
-12.0
-10.7
-4.40
29.3*
20.3
(0.58)(0.39)(0.29)(0.016)(2.13)(19.7)(18.5)(8.08)(15.8)(17.2)
Baseline Outcome
0.38***
0.17***
0.71***
0.62***
0.38***
0.0096-0.00910.32***
0.79***
0.0080***(0.050)(0.049)(0.078)(0.058)(0.069)(0.019)(0.018)(0.11)(0.062)(0.000048)
Endline Control group mean
18.7
12.9
5.71
0.74
26.1
116.4
89.9
102.5
77.5
42.4
Observations
245
245
245
245
245
245
245
245
245
245
R-squared
0.26
0.083
0.34
0.47
0.37
0.000990.00090
0.17
0.40
0.24
Notes: *** p<0.01, ** p<0.05, * p<0.1. Table estimated using endline (R3) data, with an ANCOVA controlling for baseline outcomes. The UCT variable is measured in hundredsof US dollars received by the household. Survey weights are used to make the analysis representative of all ENBs in study villages. Consumption numbers are monthly adultequivalents, and all monetary figures are in constant 2008 USD. All outcomes Winsorized at 1% and 99%. Standard errors clustered at the village level (unit of assignment).

34

Table 4: Cash Transfer Impacts on TASAF Group Members
Panel A.

UCT Effect in R3 (100 USD)
Baseline outcome ANCOVA
Endline Control group mean
Observations
R-squared
Panel B.
Late TASAF & UCT
Early TASAF only
Early & UCT
Early & Training
Early & Training & UCT
Baseline outcome ANCOVA
Endline Control group mean
Observations
R-squared
F-test on all UCT arms
F-test on both Training arms

Per-capita
Per-capita
Per-capita
Food
Non-Food
Consumption
Consumption Consumption
(1)
(2)
(3)
0.42
0.15
0.20
(0.51)(0.27)(0.29)
0.56***
0.33***
0.57***(0.061)(0.057)(0.10)
6.63
20.5
13.8
645
645
645
0.25
0.16
0.20

0.64
(0.6)
-0.857
(1.4)
1.194
(1.3)
1.434
(1.6)
-0.828(0.6)
0.546***
(0.1)
20.5
645
0.257
0.154
0.196

0.116
(0.3)
-1.610*
(0.9)
0.561
(0.6)
0.658
(0.9)
-0.434(0.5)
0.331***
(0.1)
13.8
645
0.175
0.601
0.484

Pooled UCT Effect, TASAF Members
Improved
Roof

Livestock
Cost

Livestock
Revenue

Livestock
ProfitAgricultural
IncomeEnterprise
IncomeEnterprise
Assets(4)
0.013(0.013)0.43***(0.070)
0.78
640
0.49

(5)
2.14
(1.91)
0.18**(0.074)
25.7
645
0.23

(6)
22.3
(17.6)-0.026**(0.013)
75.9
645
0.078

(7)
21.1
(17.3)-0.030**(0.015)
49.0
645
0.056

(8)
-12.7**(5.11)
0.30***(0.079)
105.4
640
0.21

(9)
-7.50
(7.06)
0.65***(0.061)
118.9
642
0.52

(10)
-5.59
(4.99)
0.65***(0.034)
77.9
644
0.53

Each treatment cell individually, TASAF Members
0.467
0.00
4.536
37.90
34.28
(0.330)(0.012)(2.739)(28.4)(27.4)
1.115
0.0151
12.22
117.8
102.7
(1.013)(0.042)(10.240)(92.0)(88.1)
0.716
0.0762***
6.577**
11.11
5.759(0.695)(0.025)(2.669)(14.2)(14.8)
0.727
0.072317.89***-7.643-22.73(0.868)(0.049)(6.277)(32.3)(33.3)-0.605**0.0369
2.584
16.94
15.36
(0.278)(0.029)(2.953)(24.1)(26.3)
0.560***
0.433***
0.178**-0.0232**-0.0262**(0.100)(0.068)(0.072)
(0.0)
(0.0)
6.63
0.78
25.7
75.9
49.0
645
640
645
645
645
0.216
0.51
0.242
0.086
0.064
0.006150.0101
0.06350.38
0.548
0.03310.174
0.02010.733
0.618-19.07***(5.358)-5.107(16.980)
6.201(14.470)
0.151(16.690)-16.11*(8.689)0.293***(0.072)
105.4
640
0.225
0.002090.165-10.34(8.640)-9.529(37.090)-6.889(14.800)-17.38(25.850)-12.12(12.950)
0.652***(0.060)
118.9
643
0.524
0.631
0.641

-8.91
(6.872)-24.21(22.850)-15.21*(9.126)-39.72**(17.200)-12.99(8.384)0.647***(0.036)
77.9
644
0.534
0.393
0.0726

Notes: *** p<0.01, ** p<0.05, * p<0.1. Both panels are estimated as endline (R3) cross-sectional ANCOVA regressions, including randomization block fixed effects. Panel A
includes the UCT treatment amount in hundreds of dollars, and Panel B estimates separate impacts for each cell in the research design (all cells compared to the control). F-tests atthe bottom report p-values on joint tests of significant for the three UCT arms (penultimate row) and the two Training arms (last row). Consumption numbers are monthly adultequivalents, and all monetary figures are in constant 2008 USD. Survey weights are used to make the analysis representative of all TASAF group members in study villages. All
outcomes Winsorized at 1% and 99%. Standard errors clustered at the village level (unit of assignment).

35

Table 5: Impact of Cash Transfers on Contributions to GroupMonthly Earnings
Monthly Inputs
Monthly Profits
Monthly Labor (hours)
Daily Wage
(1)
(2)
(3)
(4)
(5)
UCT Effect in R3 (100 USD)
0.47
0.19
0.27
3.70*
0.056
(0.32)(0.14)(0.24)(2.09)(0.077)
UCT Endline Control group mean
4.11
1.20
2.77
41.1
0.54
Observations
702
702
702
702
702
R-Squared
0.11
0.13
0.11
0.18
0.037
Notes: *** p<0.01, ** p<0.05, * p<0.1. Analysis uses the survey conducted at the group member level describing contributions to, and earnings from, the group
activity. Regressions use only Round 3 data for TASAF group members, including the UCT amount in hundreds of USD as well as block randomization fixed
effects to compare the members who were assigned a cash transfer at the individual level to those who were not. All outcomes Winsorized at 1% and 99%.
Standard errors clustered at the village level (unit of assignment).

36

Table 6: Group-level Impacts of Cumulative Cash Transfers to All Group Members

UCT effect (100 USD)
Mean (no UCT)
Number of observations

Total Stock
Winsorized
Transformed

Total Sales (last month)
Winsorized
Transformed

Total Profits (last 6 months)
Winsorized
Transformed

402.107***(140.810)
2,984.315***(401.169)
119-0.805(2.703)77.016***(18.151)119

3.907(11.907)245.426***(86.612)1190.188***(0.062)
7.252***(0.503)119

0.041(0.055)2.286***(0.361)119

0.127(0.110)1.642**(0.683)
119

Notes: *** p<0.01, ** p<0.05, * p<0.1. Table uses R3 outcomes from the Group survey to analyze the impact of the cumulative UCT amount randomized to allmembers of the group. UCT impact is measured in hundreds of USD, and all outcomes are in constant 2008 USD. All outcomes Winsorized at 1% and 99%.
Standard errors clustered at the village level (unit of assignment).

37

Table 7: Spillover Effect of Cash Transfer on Contributions of Other Group Members
Panel A: Only individuals not themselves receiving a UCTMonthly Earnings(1)
Cumulative Group UCT (100 USD)
0.21
(0.16)
Mean in groups with no UCT
3.61
Observations
467
R-Squared
0.14
Panel B: All Surveyed Group Members

Individual UCT Transfer (100 USD)
Cumulative UCT to others in group (100 USD)
Mean for individuals not receiving UCTObservations
R-Squared

Monthly Earnings(1)
0.14(0.18)
0.22(0.13)
4.11
702
0.12

Monthly Inputs(2)
0.17**(0.066)
0.87
467
0.13

Monthly Profits
(3)
0.056
(0.12)
2.57
467
0.17

Monthly Labor (hours)
(4)
1.61*
(0.94)
36.9
467
0.19

Daily Wage
(5)
0.031
(0.036)
0.45
467
0.083

Monthly Inputs(2)-0.034(0.092)0.15***(0.052)
1.20
702
0.15

Monthly Profits(3)
0.17(0.15)
0.073(0.100)
2.77
702
0.11

Monthly Labor (hours)(4)
1.55(1.30)
1.45*(0.74)
41.1
702
0.19

Daily Wage
(5)
0.016
(0.040)0.027(0.030)
0.54
702
0.039

Notes: *** p<0.01, ** p<0.05, * p<0.1. Analysis uses the survey conducted at the group member level describing contributions to, and earnings from, the group
activity. Regressions use only Round 3 data for TASAF group members. Panel A uses all surveyed members, and includes control for transfers to an individual
as well as transfer for that individual to all other members of the group. Panel B uses only the group members who were not themselves assigned to receive any
UCT. Regressions include the UCT amount in hundreds of USD as well as block randomization fixed effects. All outcomes Winsorized at 1% and 99%.
Standard errors clustered at the village level (unit of random assignment).

38

Figure 1: Diagram of Study Design

100 villages, 119 Groups, 1017 sampled eligible

50 villages (59 Groups)
Allocated to Early Treatment

50 villages (60 Groups) Allocatedto Late TASAF Treatment(N=358)(N=366)25 villages (32 Groups)
Additional Training

25 villages (27 Groups)
No Training(N=195)(N=163)

Cash Grants

No Grant

Cash Grant

No Grant(N=144)(N=51)(N=93)(N=70)All 100 Villages Eligible
Non-Beneficiary (noTASAF)(N=293)

Cash Grants

No Grant

Cash Grants

No Grant(N=245)(N=121)(N=155)(N=138)39

Total Group Value
4000
6000
2000

8000

Figure 2: Evolution of Group Total Asset + Working Capital Value over Time.

0

Amount Disbursed

0

6

12
24
Months since treatment
Early Treatment
Quadratic fit

Late Treatment
lowage/hiwage

36

-.5

Effective Daily Wage, US$
0
.5
1

1.5

Figure 3: Effective Daily Wage Rate from Business, USD.

0

6

12
24
Months since treatment
Early Treatment
Quadratic fit

36

Late Treatment
Lower/Upper CI

41