ONLINE APPENDIX.
Table A1: Comparison of Rank and File members to Group Leaders.
Per-capita
Consumption
Rank and File:
Mean
16.14
SD
9.51
Group Leaders:
Mean
19.94
SD
11.80
All Group Members:
Mean
17.98
SD
10.84

Per-capita
Per-capita
Food
Non-Food
Consumption Consumption

Improved
Roof

Livestock
Cost

Livestock
Revenue

Livestock
ProfitAgricultural
IncomeEnterprise
IncomeEnterprise
Assets

12.09
7.04

4.05
4.57

0.64
0.48

13.80
38.75

56.05
374.0842.25
368.0569.54
179.3454.16
364.5331.90
276.06

14.03
8.60

5.91
5.60

0.71
0.45

19.32
49.91

146.52868.09127.20861.80

56.68
99.68

69.25
240.91

51.42
177.60

13.03
7.89

4.95
5.18

0.67
0.47

16.47
44.57

99.91
662.4683.43
656.5363.31
146.2961.49
310.6041.37
233.61

Notes: Table presents means and standard deviations of the primary outcomes for Rank and File members, Group Leaders, and All Group Members.

Table A2: Attrition

TASAF treat
Training treatment
UCT treatment
UCT * TASAFTASAF MemberGroup Leader
Multiple Groups/Village
Livestock Group
Lushoto District
Makete District
Nzega District
Kwimba District

Observations
Mean Attrition in Control
F-test: TASAF = Training
F-test: TASAF = UCT

Attrited in
Midline Survey

Attrited inEndline Survey

0.00187(0.032)-0.0219(0.033)0.00444(0.009)0.0233(0.022)0.00493(0.022)-0.0360**(0.018)0.00197(0.038)-0.04(0.024)0.0541(0.043)0.027(0.032)-0.00427(0.030)0.0325(0.031)0.0279(0.051)-0.0491(0.046)-0.018(0.013)0.00484(0.024)-0.0298(0.028)-0.0739***(0.027)0.0651(0.068)-0.04(0.034)0.115*(0.059)0.205***(0.047)0.142***(0.044)
0.0978**(0.042)

1,017
0.05500.69400.93301,017
0.14200.39100.3680Notes: *** p<0.01, ** p<0.05, * p<0.1. The dependent variable for the table is an indicator for a baseline-surveyed
household if they attrited in the Midline (first column) or the Endline (second column). Analysis pools all eligible
households and includes treatment group dummies and interactions, as well as block randomization fixed effects anda dummy for being a group leader. Coefficients in the first four rows show tests for differential attrition in eachtreatment group versus the control, and the bottom two rows provide F-tests on the difference of attrition rates acrossarms. As with the outcome analysis, regressions are weighted to be representative of all eligible individuals andstandard errors are clustered at the village level (unit of assignment for the TASAF and Training interventions).

Table A3: Balance

TASAF treat
Training treatment
UCT treatment
UCT * TASAFGroup Leader
Multiple Groups/Village
Livestock Group
Lushoto District
Makete District
Nzega District
Kwimba District
Observations
R-squared
Control Group Mean
F-test: TASAF = Training
F-test: TASAF = UCT

Per-capita
Per-capita
Per-capita
Food
Non-Food
Consumption
Consumption Consumption
(1)
(2)
(3)
0.61
0.75
-0.12
(1.36)(1.07)(0.59)
-1.53
-1.58
0.012
(1.39)(1.01)(0.63)
0.30
-0.12
0.43*
(0.52)(0.36)(0.25)
-0.57
-0.32
-0.26
(0.76)(0.53)(0.39)
3.38***
1.45**
1.84***(0.85)(0.65)(0.37)
-2.41
-1.17
-1.23
(1.93)(1.42)(0.94)
2.20
2.38*
-0.21
(1.84)(1.31)(0.95)
0.53
0.64
-0.20
(1.96)(1.20)(1.09)
0.39
0.76
-0.36
(2.26)(1.43)(1.25)
0.62
1.01
-0.40
(1.81)(1.22)(1.01)-5.92***-3.63***-2.29**(1.59)(1.13)(0.88)
724
724
724
0.103
0.089
0.062
18.84
13.46
5.352
0.375
0.213
0.901
0.812
0.391
0.352

Primary Outcomes:
Improved
Roof

Livestock
Cost

Livestock
Revenue

Livestock
ProfitAgricultural
IncomeEnterprise
IncomeEnterprise
Assets(4)-0.097(0.071)
0.045(0.066)0.0084(0.021)-0.042(0.036)0.053(0.033)-0.0050(0.041)-0.083*(0.045)-0.27***(0.084)-0.28***(0.084)-0.70***(0.078)-0.68***(0.054)
724
0.391
0.713
0.259
0.127

(5)
-5.97
(3.94)
4.54(4.51)
0.099(1.74)
0.94(2.37)
2.81(3.30)-4.97(5.56)-8.14(6.72)-0.81(8.10)-17.5***(4.79)-16.8***(4.72)-10.9**(4.83)
724
0.029
17.37
0.109
0.0968(6)
21.4(25.7)
18.8(48.2)
14.9(15.0)
29.6(39.3)
54.2*(32.3)-24.1(30.2)-70.4***(25.1)-19.7(41.2)-72.4**(35.7)-9.15(53.2)-2.65(50.0)
724
0.021
52.68
0.967
0.811

(7)
24.3
(24.2)
15.8(43.9)
14.7(15.2)
27.4(36.9)
50.9*(30.4)-19.1(30.7)-61.6**(25.4)-21.1(38.1)-54.6(34.7)
3.26(49.6)
4.82(48.5)
724
0.022
35.03
0.884
0.718

(8)
0.86
(13.4)-27.0**(13.2)
4.21(11.2)
7.14(14.4)-2.98(10.6)-0.66(12.0)
2.82(11.0)
40.9*(21.9)
0.63(23.1)
60.8***(20.1)
49.4***(14.1)
724
0.049
62.52
0.211
0.806

(9)
-39.8
(29.8)-26.3(27.1)-9.97(13.1)
34.0(28.7)
17.7(18.1)
4.40(15.7)
1.37(12.1)
43.7*(25.9)
5.97(22.2)
152.4**(62.0)-1.96(14.2)
723
0.055
80.07
0.767
0.213

(10)
-15.5
(20.2)-13.9(21.6)-4.03(8.73)
24.5(20.8)
18.5(12.5)
6.96(9.14)
13.2(8.88)
24.1(14.6)
12.9(18.3)
87.8**(42.7)
4.47(6.81)
724
0.039
47.77
0.963
0.471

Notes: *** p<0.01, ** p<0.05, * p<0.1. Table estimated for the full household sample of TASAF group members at baseline, where the dependent variable isthe baseline outcome and this is regressed on treatment dummies, their interactions, and block randomization fixed effects. Standard errors clustered at thevillage level (unit of 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 assignment).

Table A4: Impact of TASAF Early Disbursement on Household Livestock Ownership

TASAF treatment
TASAF + training
Baseline outcome
Midline Control group mean
P-value: TASAF = TASAF + training
P-value: TASAF, TASAF + training jointly signif.
Observations
R-squared

Dairy
Cows
(1)
0.21**(0.084)0.33***(0.096)0.11(0.093)

Dairy
Goats
(2)
0.056
(0.053)0.060(0.041)0.65***(0.12)

Pigs

Poultry(3)
0.47**(0.22)
0.53***(0.16)
0.31(0.19)(4)
0.43(0.68)
0.016(0.74)
0.28***(0.085)0.047
0.36
0.000439
631
0.20

0.028
0.96
0.19
631
0.46

0.20
0.81
0.00142
631
0.24

4.21
0.67
0.817
631
0.14

Notes: *** p<0.01, ** p<0.05, * p<0.1. Analysis uses Midline data for TASAF group members, and provides the experimental difference in the ownership oflivestock for the TASAF and TASAF+training groups. Regression includes dummies for Group Leaders, Training, and their interaction, as well as blockrandomization fixed effects. The F-test at the bottom of the table gives the p-value on test for equality of the two treatment dummies. All outcomes Winsorized
at 1% and 99%. Standard errors clustered at the village level (unit of assignment).

Table A5: TASAF Early Impact on Household Secondary Outcomes

TASAF treatment
TASAF + training
Midline Control group mean
P-value: TASAF = TASAF + training
P-value: TASAF, TASAF + training jointly signif.
Observations
R-squared

Number of
Meals Eaten

Consumptionof Durables(1)
0.0031(0.17)
0.077(0.17)
0.70
0.75
0.903
630
0.037

(2)
0.23
(0.45)-0.21(0.22)
0.44
0.28
0.385
631
0.039

Total
Livestock
Value
(3)
99.9
(118.5)87.3(132.0)
370.8
0.93
0.645
631
0.10

Savings

BorrowingChildren in
School(4)
1.37(21.9)-2.08(13.0)
51.6
0.88
0.983
628
0.041

(5)
-5.25
(13.6)-7.43(6.56)
24.5
0.86
0.528
631
0.025

(6)
0.028
(0.040)-0.068(0.041)
0.70
0.047
0.121
513
0.12

HH member Ability to carry
Schooling Respondent insick/injuredout physicalExpenditures Good Healthpast 4 wks
tasks
(7)
(8)
(9)
(10)
2.76
0.028
-0.0098
0.13(4.03)(0.040)(0.040)(0.13)-1.85-0.052*0.033
0.092(5.10)(0.030)(0.029)(0.11)
28.4
0.70
0.26
4.18
0.41
0.075
0.29
0.78
0.673
0.128
0.412
0.549
513
631
631
631
0.074
0.16
0.028
0.047

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-section including block randomization fixed
effects The 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. Standard errors clustered at the village level (unit of assignment). 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 assignment).

Table A6: Impact of TASAF Early Treatment on the Vulnerable Individual in the Household
Number Days
Too Sick to
Ability to carryunable toRequired
Health reported
Health has
Perform normal
out PhysicalSick or Injured
perform normal
Hospitalization
as Good or Very Improved over
Activities past 12
Tasks, 5-point
in past 4 weeks
Activities, pastin past 4 weeks
Good
past 12 months
monthsscale
12 months
(1)
(2)
(3)
(4)
(5)
(6)
(7)
TASAF treatment-0.066-0.016
0.019
-5.56
0.070
0.085
0.035
(0.066)(0.019)(0.061)(4.85)(0.21)(0.060)(0.045)TASAF + training
0.031
0.0063
0.020
-0.37
0.018
-0.077-0.035(0.054)(0.021)(0.055)(5.42)(0.19)(0.053)(0.046)
Midline Control group mean
0.36
0.028
0.56
16.1
3.81
0.59
0.30
P-value: TASAF = TASAF + training
0.16
0.32
0.99
0.34
0.83
0.013
0.19
P-value: TASAF, TASAF + training jointly signif.
0.363
0.56
0.915
0.457
0.946
0.0447
0.427
Observations
631
631
631
631
628
631
631
R-squared
0.040
0.0089
0.051
0.030
0.048
0.13
0.065

Number ofMissed Meal in
Meals Missed in
Past 7 days
Past 7 days
(8)
0.091*(0.050)0.0014(0.046)
0.16
0.15
0.193
630
0.039

(9)
0.48
(0.34)
0.19(0.34)
0.88
0.51
0.367
630
0.011

Notes: *** p<0.01, ** p<0.05, * p<0.1. Table estimated for the full household sample of TASAF group members at midline, focusing on the outcomes of thetarget beneficiary individual within the household, comparing the group experimentally offered TASAF and those offered TASAF + training to the control group.
The regression is a cross-section including block randomization fixed effects The F-test at the bottom of the table gives the p-value on the F-statistic for thedifference between the treatment coefficients, and so tests the additional impact of the training. Standard errors clustered at the village level (unit of assignment).
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 assignment).

Table A7: Group-Level Impacts of the Training
Group keeps
Group issues
Records areGroup has written
written records of available to group
written reciepts
business planbusiness activities
to customers
members
Trained x RR
Trained x R2
Trained x R3
R2
R3
RR Untrained mean
Observations
R-squared(1)
0.13(0.087)0.17*(0.091)
0.075(0.11)-0.037(0.086)-0.037(0.10)
0.78
177
0.19

(2)
-0.10*(0.059)-0.095(0.12)-0.19(0.12)-0.26***(0.089)-0.22***(0.080)
0.96
177
0.20

(3)
-0.015(0.026)-0.038(0.096)0.025(0.078)0.15**(0.072)0.15**(0.072)
0
177
0.16

(4)
0.028
(0.038)-0.046(0.064)0.060(0.068)0.074(0.053)-1.9e-16(0.055)
0.037
177
0.095

Total Sales over
Past Month

Total Group
Stock Value

Total Group
Profits over past
6 Months(5)-23.5(24.4)-26.1(37.1)-11.0(37.8)
51.7*(26.4)
48.7(33.8)
40.9
177
0.12

(6)
-788.9(555.0)-486.8(658.9)-442.6(738.0)379.6(418.3)-1692.2***(489.6)5564.7
177
0.36

(7)
-64.8
(96.2)-103.1(164.7)185.3(153.8)263.7**(122.1)
267.9**(119.8)
-67.5
177
0.17

Notes: *** p<0.01, ** p<0.05, * p<0.1. Analysis includes the Early TASAF group members in which the training experiment is conducted.
The regression is a three-round panel regression including the Rapid Resurvey (RR), midline (R2) and endline (R3). Regressions include
dummy variables for round and the interaction between the randomized Training treatment and round dummies, as well as block randomization
fixed effects. Standard errors are clustered at the village level, and outcomes are winsorized at 99%. All outcome variables are in 2008 real US
dollars.

Table A8: Individual Impacts of Training for the Group Leaders versus Rank & File
MidlineTrained * Group Leader
TrainedGroup Leader
Untrained RF mean
F-test Trained GL + GL
Observations
R-Squared

EndlineMonthly Monthly
Earnings Inputs

Monthly
Profits

MonthlyLabor(hours)

Daily
Wage

Monthly Monthly
Earnings Inputs

Monthly
Profits

MonthlyLabor(hours)

Daily
Wage

(1)
-0.29
(1.26)-0.60(0.92)
3.40***(0.93)
3.66
0.0018
346
0.15

(3)
0.14
(1.29)
0.25(1.58)
1.33(0.87)
0.24
0.16
346
0.13

(4)
-20.4*(12.0)-10.1(11.5)
25.6**(10.6)
50.5
0.39
346
0.15

(5)
0.15
(0.43)-0.19(0.52)
0.28(0.23)
0.21
0.25
346
0.10

(6)
-2.33
(1.48)
1.24(1.63)
2.60**(0.99)
4.31
0.81
346
0.20

(8)
-1.58
(1.43)
1.42(1.44)
1.89**(0.90)
2.80
0.77
346
0.19

(9)
-19.7*(10.3)-3.18(5.91)
21.7**(8.96)
33.3
0.62
346
0.33

(10)
-0.56
(0.43)
0.36(0.47)
0.62*(0.33)
0.55
0.84
346
0.056

(2)
-0.30
(1.39)-1.59(2.27)
1.52(1.09)
4.00
0.16
346
0.13

(7)
-0.36
(0.44)-0.26(0.51)
0.63*(0.35)
1.37
0.16
346
0.21

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, thegroup activity. Results give heterogeneity in the impact of the training on Group Leaders, as compared to Rank and File members. Separate regressions run in
the midline and endline survey including only the Early TASAF group members among whom the training experiment was conducted, including dummies forGroup Leaders, Training, and their interaction, as well as block randomization fixed effects. The F-test at the bottom of the table gives the p-value on the Fstatistic for the sum of the Group Leader and Trained dummies, so tests whether there is a treatment effect among group leaders. All outcomes Winsorized at 1%
and 99%. Standard errors clustered at the village level (unit of assignment).

Table A9: Unconditional Cash Impacts on Secondary Outcomes for TASAF members.

UCT Effect, R3
Observations
R-squared
Endline Control group mean

Number Consumpt
Totalof Meals
ion ofLivestock
Eaten
DurablesValue

Children
Schooling
Savings Borrowing
in School Expenditures(1)
0.0334
(0.1)
640
0.04
0.56

(4)
-3.673(4.188)
638
0.02
65.5

(2)
0.104
(0.1)
645
0.02
0.23

(3)
-50.69(36.360)
645
0.10
534.1

(5)
3.077
(5.313)
645
0.02
25.1

(6)
-0.0125
(0.0)
490
0.06
0.68

(7)
1.817
(1.578)
490
0.14
24.8

Respondent HH member
in Goodsick/injured
Healthpast 4 wks(8)
0.00619(0.011)
640
0.03
0.78

(9)
-0.00217
(0.0)
640
0.02
0.30

Ability tocarry out
physicaltasks(10)-0.0341
(0.0)
632
0.09
4.40

Notes: *** p<0.01, ** p<0.05, * p<0.1. Regression estimated as endline cross-section, including randomization block fixed effects, examining the study secondary outcomes. 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).

Table A10: Comparison of Cash effects on TASAF Members versus ENBs.
Per-capita
Consumption
UCT * TASAFUCTTASAF member
Baseline outcome
Endline Control group mean
Observations
R-squared

(1)
0.094
(0.76)
0.34(0.56)
0.85(1.20)
0.42***(0.044)
19.8
890
0.26

Per-capita
Food
Consumption(2)-0.014(0.45)
0.16(0.37)
0.49(0.74)
0.21***(0.045)
13.5
890
0.13

Per-capita
Non-Food
Consumption
(3)
-0.17
(0.41)
0.32(0.29)-0.025(0.66)
0.63***(0.066)
6.28
890
0.27

Improved
Roof

Livestock Cost

Livestock
Revenue

Livestock
ProfitAgricultural
IncomeEnterprise
IncomeEnterprise
Assets(4)-0.0029(0.019)0.017(0.015)0.0077(0.036)
0.48***(0.055)
0.77
885
0.51

(5)
2.46
(2.33)-0.23(1.97)-4.42(3.90)
0.31***(0.056)
25.9
890
0.32

(6)
40.8*
(22.1)-19.4(19.8)-73.5(49.4)-0.011(0.013)
91.3
890
0.077

(7)
36.8*
(21.8)-16.9(18.8)-64.6(48.5)-0.016(0.013)
64.5
890
0.059

(8)
-7.84
(9.45)-5.08(7.09)
5.15(16.9)
0.29***(0.067)
104.3
885
0.23

(9)
-32.7*(17.2)
25.3(15.6)
15.0(32.6)
0.70***(0.048)
103.2
887
0.46

(10)
-21.8
(19.9)
18.4(15.8)
33.8(33.1)
0.0083***(0.00033)
64.4
889
0.14

Notes: *** p<0.01, ** p<0.05, * p<0.1. Regression is estimated as an endline (R3) cross-sectional ANCOVA, including randomization block fixed effects. The regression
includes a dummy for being a TASAF member, the UCT variable measured in hundred dollars, and their interaction, and so tests the differential impact of the UCT between the
TASAF members and ENB. Regressions also include block fixed effects. Consumption numbers are monthly adult equivalents, 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).

Table A11: Impact of UCT Treatment on Social Capital Measures

UCT
TASAF member
UCT * TASAF
Non-TASAF, Non-UCT mean
Observations
R-squared

Trust Village
Members

AttendedVillage
Assembly

Voted in
Village
ChairmanElections

Discuss
Problems with
Village
Officials(1)
0.00669(0.017)0.0468(0.035)-0.0621**(0.029)
0.74
885
0.045

(2)
-0.026(0.022)0.134***(0.044)0.00964(0.037)
0.50
885
0.055

(3)
-0.0131(0.016)
0.0713*(0.036)0.00601(0.021)
0.80
885
0.04

(4)
-0.00673(0.015)0.0951**(0.040)0.00659(0.030)
0.15
885
0.033

Notes: *** p<0.01, ** p<0.05, * p<0.1. Regression is estimated as an endline (R3) cross-section, including randomization block fixed effects. The regression includes a dummy
for being a TASAF member, the UCT variable measured in hundred dollars, and their interaction, and so tests the differential impact of the UCT between the TASAF members
and ENB. Regressions also include block fixed effects. The ‘TASAF member’ variable is non-experimental, comparing group members to ENBs, the UCT dummy is theexperimental impact of cash transfers in the ENB group, and UCT*TASAF gives the experimental differential effect of UCTs for those who are TASF members. ‘Trust Village
Members’ is a dummy for the respondent answering yes to the question “Generally speaking, would you say that most people in this village can be trusted?”. ‘Attended Village
Assembly’ is a dummy for having been to a meeting in the past three months. Standard errors clustered at the village level (unit of assignment).

Figure A1: Study Timeline

Project Activities:

TASAF group identification begins
Selection of study villages, randomization

TASAF Late Treatment begins

TASAF Early Treatment begins

Cash transfer experiment begins

Training begins in Early group

2007
Q1 Q2

Q3

Q4

2008
Q1 Q2

Q3

Q4

2009
Q1 Q2

Q3

Q4

2010
Q1 Q2

Q3

Q4

2011
Q1 Q2

Q3

Q4

2012
Q1 Q2

Research Activities:
Baseline survey begins

Midline survey begins
Rapid Resurvey of Group Outcomes

In all cases the timeline for project and research activities in Moshi and Lushoto districts begin ten months before the same activities in Kwimba, Nzega, and Makete.

Q3

Q4

Endline survey begins

FIGURE A2. Training on Group Rules

FIGURE A3. Content of Business Skills Training

-2000USD Group Stock Value
2000
0
4000

6000

Figure A4: Stock Values and Net Contributions.

6

12

18
24
Months since Treatment

Actual Stock Value
Stock explained by contributions

30
Appreciation/Dep36

Appendix B. Comparison to Related Social Protection Programs
There are three obvious points of comparison for the TASAF VG program and the training
and cash transfer interventions we lay on top of it. The first is Uganda’s NUSAF (Northern Uganda
Social Action Funds), as described in Blattman, Fiala, and Martinez (2018). Under both programs,
the government provided lump-sum transfers tied to the purchase of assets to groups ofbeneficiaries both for administrative convenience and to avoid the funds being used for
consumption rather than investment purposes. Like their NUSAF counterparts, TASAF
beneficiaries formed groups with a median size of 15 members, with the groups receiving
approximately USD 7,000 in 2009 dollars on average (or about USD 525 per member). However,
NUSAF targeted underemployed young adults who were, on average, much younger, moreeducated/literate, and less poor than TASAF. NUSAF required that the groups invest in a nonagricultural skilled trade, for which training was available nearby. This contrasts with TASAF
activities, which were primarily animal husbandry. 1 While a significant share of funds in eachsuccessful proposal was earmarked and later used for skills training under NUSAF, almost noneof this happened under TASAF. Further, in Uganda group members ultimately operated individual
businesses in contrast to TASAF members who operated group enterprises and reported assets thatbelonged to the group activity years after receiving lump-sum transfers.
The second point of comparison is BRAC’s Graduation or ‘targeting the ultra-poor
program,’ (TUP) designed and originally implemented by BRAC (Bandiera et al. 2017). The TUP
beneficiary population is more like that of TASAF, in that they are likely to be as poor and illiteratebut, on average, significantly younger than TASAF beneficiaries (median age of beneficiaries in

Blattman, Fiala, and Martinez (2018) states that NUSAF had a separate program for vulnerable groups that provided
cash grants for livestock purchases, more similar to TASAF both in terms of target group of beneficiaries and scope.
However, this program was not chosen for evaluation.

1

Bangladesh is 40 vs. 55 years in TUP and TASAF, respectively). Under TUP, leading women inultra-poor households are offered a menu of productive assets with a package of complementarytraining and support. 2 Where the TUP differs most substantially from TASAF, however, is in the
support and training package that accompanies the asset transfer: beneficiary households are (i)encouraged to retain the transferred asset for two years, (ii) given a stipend for the first 40 weeks
to manage earnings fluctuations and to avoid liquidating their productive assets, (iii) visited by alivestock specialist 6-12 times over the first year, covering the life cycle of livestock, and (iv)visited by a BRAC program officer weekly for two years. 3 TASAF simply provides a one-day
training on procurement and management of group funds before making a lump-sum transfer into
the groups’ bank accounts. While the support and training package under the TUP is expensive,
the total per household cost of TUP at $1,120 in 2007 PPP terms is similar to that under TASAF,
which is approximately $1,175 in 2009 PPP terms. 4
The cash transfer literature forms our third point of comparison. Given our context and theunconditional nature of our transfers, the most relevant studies are those involving UCTs from
GiveDirectly in East Africa. Haushofer and Shapiro (2016) study UCTs with a nominal value
randomized to either $400 or $1,000, and also randomly vary whether the transfers were provided
as a monthly flow or as a lump sum. Considering the base effect (small lump-sum transfers, themost comparable to our single payment averaging $200), they find increases in asset values ofIn the case of Bangladesh, while the menu included a variety of assets, all households chose a livestock bundle, withmore than 90% containing at least one cow (in comparison, 68% of TASAF groups operated a livestock business,
although keeping dairy cattle, pigs, chickens, and goats were more or less equally popular in Tanzania, in contrast to
the preference for cows in Bangladesh).
3
The program also provides other forms of support to beneficiary households, including encouragement of savings
with BRAC, borrowing from BRAC microfinance at the end of the program, as well as activities to empower womenin non-economic dimensions.
4
However, the per household program cost in Bangladesh appears smaller than programs attempting to replicate TUP
in other countries. The six-country study by Banerjee et al. (2015) reports total direct costs ranging from $1,257 inIndia to $5,150 in Pakistan in 2014 PPP terms.
2

61% ($301 over a base of $495), and in household revenue of 33% ($16 over a base of $49), as
well as improvements in consumption and savings nine months after baseline. 5 A pair of studies
in Rwanda with comparable transfer amounts found significant increases in assets and decreases
in debt, and with transfers just over the top end of our amounts also saw increases in consumption
and income (McIntosh & Zeitlin 2022). 6 Hence it is clear that UCTs in the range studied here ($50350) can have meaningful effects on economic outcomes. What is unique and interesting in thisstudy is the opportunity to understand the complementarities and strategic interactions that lie at
the intersection of group investment, human capital formation, and the use of unconditional cash
when these three are independently randomized on top of each other.

The larger cash transfer amounts are found to have more transformative effects, and a study that makes mass-scaletransfers to Kenyan households, equivalent to 15% of local GDP, also finds substantial benefits to non-recipients
through the mechanism of increased labor demand from the income shock (Egger et al. 2019).
6
The ‘Gikuriro’ benchmarking study had smaller transfers averaging $85 and found significant increases in
productive and consumer assets and decreases in debt after 12 months (McIntosh & Zeitlin 2021), while the‘Huguka Dukore’ benchmarking study’s smallest transfer was $317 and found these same benefits plus significant
improvements in consumption, income, and savings after 18 months, with a fade of about 50% after 36 months(McIntosh & Zeitlin 2022).
5