the impact of a multipronged approach to poverty alleviation on household outcomes vilas gobin 11...

The impact of a multipronged approach to poverty alleviation on household outcomes

Vilas Gobin11 June 2015

Motivation The poorest of the poor often do not benefit

from poverty alleviation programs, for example: The poorest benefit the least from MFIs (Morduch,

1999; Rabbani et al., 2006). Public assistance programs and social safety nets

fail in targeting the poorest (Mukherjee, 2005; Jalan and Murgai, 2007; Banerjee et al., 2007).

There is also limited evidence that public assistance programs and social safety nets lead to any long-term sustained graduation from dependency (Independent Evaluation Group, 2011).

Motivation2

Motivation Evidence that removing credit constraints alone may

not be sufficient to alleviate poverty through microenterprises (Angelucci et al., 2014; Banerjee et al., 2014a; Banerjee et al., 2014b; de Mel et al 2012; Fafchamps et al., 2011; Karlan and Zinman 2010).

Relaxing human capital constraints alone may also not be sufficient to alleviate poverty through microenterprises (McKenzie and Woodruff, 2014).

Emerging evidence that both financial and human capital constraints need to be simultaneously addressed if microenterprises are to deliver on their transformative potential (de Mel et al., 2012; Berge et al., 2014; Bandiera et al. 2013; Banerjee et al., 2015).

Motivation3

The poverty graduation approach Challenging the Frontiers of Poverty Reduction – Targeting

the Ultra-Poor A package of interventions including: consumption support,

physical asset transfer, skills training, savings services. Ongoing support for 2 years at which time participants are

expected to graduate from extreme poverty and be able to participate in microfinance.

Reported Impacts Bandiera et al. (2013) – increase in earnings, expenditure, food security

and life satisfaction (rural Bangladesh) Ultra-Poor Poverty Graduation pilots in 6 countries:

India, Pakistan, Honduras, Peru, Ethiopia, Ghana Improvements in consumption, food security, assets, finance, income,

time use, mental health, women’s decision making Morduch et al. (2012) – no impact on income, consumption or

asset accumulation (Andhra Pradesh, India)

Poverty Graduation Models4

Study Site

Study Site5

Description of the intervention

The intervention6

Randomisation of Program Assignment 1755 eligible women identified in November

2012 across 14 locations Limited capacity to enrol all women resulted in

eligible women being split into three groups. Three groups were to be enrolled in either

March/April 2013, September/October 2013 or March/April 2014

A public lottery was used to randomly assign women to one of the three funding cycles

Research design, implementation, data

7

Funding Cycle

Sample Size

Group A Apr 2013 585

Group B Sep 2013 585

Group C Apr 2014 582

Randomisation of Program Assignment All women interviewed at baseline in

November 2012 Follow-up surveys conducted at 6 month intervals

to coincide with beginning of each funding cycle.


8

11/12

4/13 9/13 4/14

Baseline

survey

Group A 1stGrant

Group B 1stGrant

Group A 2ndGrant

GroupC 1stGrant

Group B 2ndGrant

Midline

survey

Endline

survey

Randomisation of Program Assignment

Interested is estimating the effect of which consists of business training, a cash grant of

USD 100, and mentoring which consists of savings training, participation in a

savings group, a cash grant of USD 50, mentoring and micro-trainings.


9

11/12

4/13 9/13 4/14

Baseline

survey

Group A 1stGrant

Group B 1stGrant

Group A 2ndGrant

GroupC 1stGrant

Group B 2ndGrant

Midline

survey

Endline

survey


To estimate impact of Use midline data to compare Group A to Group B

and C

Use endline data to compare Group B to Group C


10

11/12

4/13 9/13 4/14

Baseline

survey

Group A 1stGrant

Group B 1stGrant

Group A 2ndGrant

GroupC 1stGrant

Group B 2ndGrant

Midline

survey

Endline

survey


To estimate impact of Use endline data to estimate combined impact of

and by comparing Group A to Group C.

And


11

11/12

4/13 9/13 4/14

Baseline

survey

Group A 1stGrant

Group B 1stGrant

Group A 2ndGrant

GroupC 1stGrant

Group B 2ndGrant

Midline

survey

Endline

survey

Balance Checks


12

Summary Statistics and Balance Checks for the Treatment and Control Groups

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15) (16) (17)

Monthly expenditure per capita

Monthly food

expenditure per

capita

Monthly non-food

expenditure per

capita

Monthly income per

capita

Total savings

per capita

TLU per capita

Durable asset index

Meals per day

# nights that child has gone to bed hungry

Proportion of

children in school

Household Size

# children Married

Years of educatio

n

Business Experienc

e

Benefitting from

HSNP

Participating in CARE VSLA

Panel A: T-test comparison of means of baseline characteristics between treatment and control groupsGroup A mean (standard error)

34.562(1.516)

24.182(1.188)

10.380(0.747)

21.770(0.925)

3.772(0.344)

0.683(0.030)

-0.234(0.169)

1.941(0.016)

0.549(0.027)

0.435(0.012)

5.778(0.079)

3.875(0.071)

0.800(0.017)

0.328(0.060)

0.576(0.020)

0.106(0.013)

0.089(0.012)

Group B mean (standard error)

34.480(1.402)

23.862(1.075)

10.617(0.770)

22.319(0.933)

3.920(0.328)

0.640(0.037)

0.113(0.189)

1.950(0.016)

0.576(0.029)

0.442(0.012)

5.692(0.075)

3.737(0.070)

0.831(0.016)

0.470(0.072)

0.562(0.021)

0.103(0.013)

0.106(0.013)

Group C mean (standard error)

32.825(1.215)

22.494(0.874)

10.331(0.648)

22.449(0.995)

5.123(0.598)

0.684(0.034)

0.124(0.179)

1.933(0.014)

0.576(0.029)

0.412(0.011)

5.596(0.077)

3.711(0.070)

0.773(0.017)

0.414(0.070)

0.538(0.021)

0.113(0.013)

0.108(0.013)

P-value from t-test of equality of means of group A and groups B and C combined 0.610 0.466 0.916 0.593 0.123 0.540 0.099 0.994 0.430 0.588 0.163 0.083 0.919 0.145 0.302 0.899 0.220P-value from t-test of equality of means of group B and group C 0.373 0.323 0.776 0.927 0.078 0.379 0.967 0.426 0.991 0.075 0.373 0.798 0.014 0.575 0.411 0.551 0.901P-value from t-test of equality of means of group A and group C 0.372 0.253 0.961 0.617 0.051 0.307 0.146 0.711 0.496 0.171 0.100 0.102 0.264 0.351 0.192 0.685 0.268Panel B: F-test from regression of treatment on 15 variables above (excluding (2) and (3)) Treatment group Control Group F-Stat p-value

A B and C 0.76 0.723

B C 1.18 0.283

A C 1.15 0.308

All monetary values are reported in 2014 USD, PPP terms

Regression Model


13

Results14

(1) (2) (3) (4) (5) (6)

Monthly expenditure per

capita

Monthly income per capita

Total savings per capita TLU per capita Durable asset index

# nights that child has gone to bed

hungry

3.669(3.127)

10.663***(2.846)

0.888(0.557)

-0.023(0.060)

0.335(0.325)

-0.110*(0.062)

Sub-location FEs

Yes Yes Yes Yes Yes Yes

Observations 1682 1682 1682 1682 1682 1597R-squared 0.282 0.106 0.116 0.332 0.318 0.260Control Group Mean 50.805 24.849 3.430 1.075 2.050 0.514

Note: Regressions include sub-location fixed effects, in addition to control variables for 1) loans taken from REAP savings groups, and 2) the number of REAP businesses in a manyatta. Robust standard errors in parentheses. Standard errors are clustered at the business group level. All monetary values are reported in 2014 USD, PPP terms*Significant at the 10% confidence level, **Significant at the 5% confidence level, ***Significant at the1% confidence level

Results15

(1) (2) (3) (4) (5) (6)


capita




hungry

0.282(3.900)

7.439***(2.660)

1.680**(0.747)

0.202**(0.102)

0.700*(0.381)

-0.192**(0.077)

Sub-location FEs




(1) (4) (5) (6) (7) (9)


capita




hungry

-1.960(1.681)

3.809***(1.109)

2.868***(0.374)

0.077(0.051)

0.398**(0.174)

-0.084**(0.040)

Sub-location FEs




(1) (2) (4) (5)

Treatment effect

[p-value]

q-value for all 6 hypotheses

Treatment effect

[p-value]


Treatment effect

[p-value]


Treatment effect

[p-value]



3.6687[0.241] 0.362 0.2824

[0.942] 0.942 -1.9596[0.244] 0.244 -5.6283

[0.0860] 0.172


10.663***[0.000] 0.001 7.4387***

[0.005] 0.03 3.8089***[0.001] 0.003 -6.8541

[0.0146] 0.044

Total savings per capita

0.8882[0.111] 0.222 1.6805**

[0.025] 0.05 2.8683***[0.000] 0.001 1.9801

[0.0008] 0.005

TLU per capita -0.0226[0.704] 0.704 0.2023**

[0.047] 0.071 0.0769[0.133] 0.16 0.0995

[0.1411] 0.212

Durable asset index

0.3352[0.303] 0.364 0.7000*

[0.067] 0.081 0.3981**[0.023] 0.046 0.0629

[0.825] 0.825


-0.1103*[0.073] 0.219 -0.1917**

[0.014] 0.042 -0.0837**[0.038] 0.057 0.0266

[0.7027] 0.825

q-values are estimated using the Benjamini-Hochberg step-up method

Conclusion

Results18

Providing ultra-poor women with capital and skills enables them to improve household incomes through entrepreneurial activities.

Women are also better able to plan for future shocks through the accumulation of liquid savings as well as livestock.

The poverty graduation model appears to have passed an extreme test of its ability to improve the lives of the ultra-poor Implemented in low population density region that is

prone to insecurity and extreme climatic conditions, lacks infrastructure, and has limited access to markets.

Thank You

(1) (2) (4) (5)

Treatment effect

[p-value]


Treatment effect

[p-value]


Treatment effect

[p-value]


Treatment effect

[p-value]



3.6687[0.241] 0.362 0.2824

[0.942] 0.942 -1.9596[0.244] 0.244 -5.6283

[0.0860] 0.172


10.663***[0.000] 0.001 7.4387***

[0.005] 0.03 3.8089***[0.001] 0.003 -6.8541

[0.0146] 0.044

Total savings per capita

0.8882[0.111] 0.222 1.6805**

[0.025] 0.05 2.8683***[0.000] 0.001 1.9801

[0.0008] 0.005

TLU per capita -0.0226[0.704] 0.704 0.2023**

[0.047] 0.071 0.0769[0.133] 0.16 0.0995

[0.1411] 0.212

Durable asset index

0.3352[0.303] 0.364 0.7000*

[0.067] 0.081 0.3981**[0.023] 0.046 0.0629

[0.825] 0.825


-0.1103*[0.073] 0.219 -0.1917**

[0.014] 0.042 -0.0837**[0.038] 0.057 0.0266

[0.7027] 0.825

q-values are estimated using the Benjamini-Hochberg step-up method

Survey Attrition On average, less than 2 percent of women

could not be reached for a follow-up interview in either the midline or endline rounds of data collection


21

Table 2: Number of individuals interviewed at baseline, midline and endline and the number of businesses they come from.

A B C # Women # Businesses # Women # Businesses # Women # Businesses

Baseline(Nov 2012)

585(100%)

195(100%)

585(100%)

195(100%)

582(100%)

194(100%)

Midline(Sep 2013)

549(93.8%)

186(95.4%)

565(96.6%)

193(99.0%)

565(97.1%)

193(99.5%)

Endline(Apr 2014)

534(91.3%)

189(96.9%)

556(95%)

192(98.5%)

561(96.4%)

190(97.9%)

Description of the intervention

The intervention22

Table 1: Summary of REAP’s graduation criteria Graduation category Criteria

1) Food security a. no family member goes to bed hungry in the last weekb. Participants consume at least 2 meals daily

2) Durable asset ownership a. Participant owns at least two of the following durable assets: mobile phone, panga, korobois/lantern, blanket, mattress, nylon, or latrine.

3) Sustainable livelihoods a. Participant’s REAP business value, or her total productive asset base (total livestock value + REAP business) is worth 125% of its value at the time of disbursementb. Participant can demonstrate at least KES 3,840 in non-BOMA monthly income.

4) Shock preparedness a. Participant is an active member in a savings group and can access KES 4,680 between her savings and share of BOMA business.*

5) Human capital investment a. Participant spends at least KES33 on school- and medical-related expenditures per capita per month.b. One of three school-aged children enrolled in school.c. Participant has participated in an Adult Literacy program since enrolment in REAP.

* An active member of a savings group is defined as a member with an attendance rate equal to or greater than 90%.

Table 10: Proportion of participants that attain REAP’s graduation criteria and indicators at endline

Graduation Criteria IndicatorProportion of participants that meet

graduation criteria at endline Group A Group B Group C1) Food security a. no family member goes to bed hungry in the last week 68.9% 70.5% 62.9%

b. Participants consume at least 2 meals daily 99.4% 99.6% 99.3%2) Durable asset ownership

a. Participant owns at least two of the following durable assets: mobile phone, panga, korobois/lantern, blanket, mattress, nylon, or latrine.

96.6% 95.3% 95.5%

3) Sustainable livelihoods

a. Participant’s REAP business value, or her total productive asset base (total livestock value + REAP business) is worth 125% of its value at the time of disbursement

88.6% 85.8% 68.3%

b. Participant can demonstrate at least KES 3,840 in non-BOMA monthly income. 50.9% 44.8% 45.8%

4) Shock preparedness

a. Participant is an active member in a savings group and can access KES 4,680 between her savings and share of BOMA business.*

87.3% 68.0% 3.6%

5) Human capital investment

a. Participant spends at least KES33 on school- and medical-related expenditures per capita per month. 64.8% 59.9% 58.3%

b. One of three school-aged children enrolled in school. 87.3% 89.2% 86.1%c. Participant has participated in an Adult Literacy program since enrolment in REAP. 1.3% 0.9% N/A

Overall Graduation Rate 81.4% 64.2% 3.2%* We do not have enough information to determine active membership in a savings group; so we focus on access to savings and share of the BOMA business.

Spillover Effects Not randomised by location so increased

likelihood of spillover effects Control households may benefit from reduced

prices in goods or increased availability of goods in location >90% enterprises are petty trade of primarily food

items Not expected to be substantial given large number of

pre-existing businesses


24

Spillover Effects


25

Table 5: Population, Villages and Number of Businesses by Location

Location Population*Number

of Villages

Pre-existent businessesBusinesses formed between 2013 and

2014

Non-Program Program

April 2013 September 2013

April 2014

1 13012 38 55 186 20 20 20

2 8357 30 54 105 10 10 10

3 7000 18 61 85 10 10 10

4 7800 11 91 136 10 10 10

5 4078 9 29 70 10 10 10

6 3300 13 10 60 10 10 10

7 10238 27 77 90 20 20 20

8 8935 15 31 100 20 20 20

9 4226 17 32 55 10 10 10

10 11220 19 119 70 20 20 20

11 3076 14 9 18 10 10 10

12 4065 13 21 35 10 10 10

13 8030 7 19 70 20 20 20

14 11223 33 119 25 15 15 14*Population numbers based on the 2009 Kenya Census.

Spillover Effects Treatment groups may also experience decreased

revenue and profits due to presence of other businesses Include business density as a control variable in

estimation of program effect Control households may benefit from access to

loans from SGs established under the program. SGs already exist in all locations prior to April 2013 We capture information on borrowing from program SGs

so can control for this effect.


26

Program Anticipation Participants may change behaviour in

anticipation of receiving funding Participants informed of when they will receive

funding during initial selection stage. If anticipation resulted in changes in behaviour

that affect the outcomes of interest we would expect to see differences in these outcomes between Groups B and C at midline. Group B would have anticipated receiving funding 6

months before Group C We compare means of outcome variables between

Groups B and C to check for any differences.


27


28

Table 6: Comparison of groups B and C, six months after group A is enrolled in REAP and prior to group B’s enrolment in REAP

(1) (2) (3) (4) (5) (6)



Total savings per capita TLU per capita Durable asset index # nights that child has

gone to bed hungry

Panel A: T-test comparison of means of characteristics of group B and C

Group B mean (standard error)

49.906(1.949)

26.263(2.198)

3.683(0.408)

1.031(0.052)

2.014(0.265)

0.565(0.044)

Group C mean (standard error)

51.703(2.191)

23.437(1.354)

3.178(0.544)

1.119(0.057)

2.086(0.272)

0.463(0.058)

P-value from t-test of equality of means of group B and group C

0.540 0.274 0.458 0.254 0.848 0.163

Panel B: F-test from regression of treatment on 6 variables above

F-Stat p-value 0.99 0.432 All monetary values are reported in 2014 USD, PPP terms

Results

Results29

Table 8: Impacts of REAP on income from various sources

(1) (2) (3) (4) (5) (6) (7)

Monthly total income per capita

Monthly income from livestock per

capita

Monthly income from other

agriculture per capita

Monthly income from non-agri trade

per capita

Monthly income from labour per

capita

Monthly income from transfers per

capita

Monthly income from other sources

per capita

426.878*** 36.514 -0.075 393.472*** -7.097 -1.230 0.680(121.624) (103.661) (2.926) (56.946) (14.713) (15.148) (2.652)281.926** 78.971 4.136 173.321*** 26.610 5.185 0.814(131.318) (111.565) (4.959) (32.983) (38.679) (11.029) (1.738)255.660** 38.603 1.774 180.736*** 47.473 -8.489 1.142(107.805) (89.830) (4.947) (36.146) (44.504) (14.591) (2.714)

Time FEs Yes Yes Yes Yes Yes Yes YesLocation FEs Yes Yes Yes Yes Yes Yes YesN 5062 5062 5062 5062 5062 5062 5062R-Squared 0.049 0.043 0.034 0.096 0.026 0.070 0.014Note: Regressions include time and location fixed effects, in addition to control variables for 1) loans taken from REAP savings groups, and 2) the number of REAP businesses in a manyatta. Robust standard errors in parentheses. Standard errors are clustered at the business group level.*Significant at the 10% confidence level, **Significant at the 5% confidence level, ***Significant at the1% confidence level

Results30

Relative change in outcome compared to control group

Monthly total expenditure per capita

1.4% -1.9% -11.1%

Monthly total income per capita

42.0%*** 32.3%** 28.6%**

Savings per capita 54.9%** 61.4%** 163.0%***TLU per capita 2.1% 16.1%* 13.9%Durable asset index 29.3% 25.7%* 37.2%**Nights child has gone to bed hungry in last week

-15.2% -25.2% -16.6%

Figures displayed are percentage changes in outcome variables relative to the control group.*Significant at the 10% confidence level, **Significant at the 5% confidence level, ***Significant at the1% confidence level

the impact of a multipronged approach to poverty alleviation on household outcomes vilas gobin 11...

Documents

grant group b

poverty graduation approach

extreme poverty

poverty alleviation

group bsep

group capr

baseline survey group

frontiers of poverty