http://www.fao.org/economic/PtoP/en/
Presented during the From Protection to Production project workshop, 24-25 September 2013, FAO HQ
The From Protection to Production (PtoP) project is a multi-country impact evaluation of cash transfers in sub-Saharan Africa. The project is a collaborative effort between the FAO, the UNICEF Eastern and Southern Africa Regional Office and the governments of Ethiopia, Ghana, Kenya, Lesotho, Malawi, Zambia and Zimbabwe. Project activities are mainly funded by the Regular Fund, the DFID Research and Evidence Division and the EU.
How to Effectively Monitor SD-WAN and SASE Environments with ThousandEyes
The impact of the Zambia Chid Grant Programme (CGP) on household economic activities and livelihoods
1. The impact of the Zambia CGP on
household economic activities and
livelihoods
Speaker: Silvio Daidone
On behalf of the the impact evaluation team:
Benjamin Davis, Joshua Dewbre, Mario González-Flores,
Sudhanshu Handa, David Seidenfeld, Gelson Tembo
Rome
September 25, 2013
2. Cash transfers targeted to poorest of the poor
can also have productive impacts
• Beneficiaries of cash transfer programmes in Sub
Saharan Africa predominately rural, most engaged in
agriculture
• Exit path from poverty not necessarily the
formal/informal labor market
• Impacts coming from changes in individual /
household behaviour and structure of the local
economy.
• Transfers can relax some of constraints brought on
by market failure
– Helping households manage risk
– Providing households with liquidity
• Transfers can reduce burden on social networks and
informal insurance mechanisms
3. The CGP programme
• Unconditional CT
• Targeting:
- Geographical: Kaputa, Kalabo, Shangombo
- Categorical: any HH with a child under 5 years
• Transfer amount independent of HH size
(60,000 ZMK per month)
• Primary recipient is a female in the HH
• Primary goal: build human capital and
improve food security
4. Study Design:
RTC with several levels of random selection
- 90 out of 300 Community Welfare Assistance
Committees (CWACs) in the three districts randomly
selected and ordered through a lottery
- Identification and selection of eligibles
- 28 HHs selected in each of 90 communities
- Baseline data collected before CWACs assigned to
treatment/control group
- Randomization of communities done with flip of coin
5. Agriculture is fundamental part of
livelihoods of CGP beneficiaries
0
.2 .4 .6 .8
1
control
Kaputa
Kalabo
Shang'ombo
0
.2 .4 .6 .8
1
treatment
Kaputa
Maize
Groundnut
Kalabo
Cassava
Sweet Potatoes
Shang'ombo
Rice
Sorghum
Source: CGP Zambia
Share of households producing each crop
(over all households producing crops).
Baseline
Millet
Other beans
6. Econometric analysis of impact of CGP on
household productive activities
• High quality data, collected in the same season
• Randomization worked, no need of reweighting or
matching estimators
• Diff-in-diff estimator for indicators available in both
waves. Single diff estimator for outcomes only at
follow-up.
• Attrition not relevant. To avoid any selection bias
issues, reweight for inverse of predicted attrition
probabilities.
• Some issues of contamination: ITT estimator, not
pure ATT
7. Hypotheses to be tested
•
Household investment in productive assets
― Ownership of livestock and agricultural implements
•
Household impact on agricultural production
― Crop production, crop and livestock labor and input use
•
Household impact on non agricultural
production
By household size
― Operation of non farm business enterprise
•
Impact on individual labor activities
― Participation and intensity of wage labor (agricultural
and non agricultural) and own farm labor
By gender
8. Large increase in proportion of households with
crop input expenditures
Impact
Baseline
Baseline
≤5 HH members
All
crop expenses
Impact
Impact
Baseline
≥6 HH members
0.225
0.223
0.213
0.134
0.236
seeds
0.100
0.131
0.135
0.12
0.067
0.143
hired labour
0.054
0.029
0.072
0.024
0.038
0.034
fertilizers
0.032
0.009
0.034
0.007
0.029
0.012
other exp
N
0.177
0.151
0.104
0.153
0.105
0.150
0.103
4,596
Bold <5% significant, underlined <10%
22% at base
2,336
2,260
9. Large increase in proportion of households with
crop input expenditures
Impact
Baseline
Baseline
≤5 HH members
All
crop expenses
Impact
Impact
Baseline
≥6 HH members
0.225
0.223
0.213
0.134
0.236
seeds
0.100
0.131
0.135
0.12
0.067
0.143
hired labour
0.054
0.029
0.072
0.024
0.038
0.034
fertilizers
0.032
0.009
0.034
0.007
0.029
0.012
other exp
N
0.177
0.151
0.104
0.153
0.105
0.150
0.103
4,596
2,336
Bold <5% significant, underlined <10%
Stronger in relative terms
for inputs with low baseline
2,260
10. Large increase in proportion of households with
crop input expenditures
Impact
Baseline
Baseline
≤5 HH members
All
crop expenses
Impact
Impact
Baseline
≥6 HH members
0.225
0.223
0.213
0.134
0.236
seeds
0.100
0.131
0.135
0.12
0.067
0.143
hired labour
0.054
0.029
0.072
0.024
0.038
0.034
fertilizers
0.032
0.009
0.034
0.007
0.029
0.012
other exp
N
0.177
0.151
0.104
0.153
0.105
0.150
0.103
4,596
2,336
2,260
Bold <5% significant, underlined <10%
Greater impacts for
smaller HHs
11. Increase in the intensity of crop
input use
Impact
Baseline
Baseline
Impact
Baseline
≥6 HH members
≤5 HH members
All
operated land (ha)
Impact
0.179
0.496
0.162
0.43
0.197
0.563
31,174
20,817
42,856
13,331
18,394
28,545
seeds
9,860
6,187
11,092
4,578
8,618
7,848
hired labour
8,417
7,093
14,682
2,845
1,155
11,479
fertilizers
7,606
1,413
8,924
721
6,499
2,127
other exp
5,226
6,092
7,967
5,124
2,092
7,091
crop expenses
N
4,596
2,336
2,260
Bold <5% significant, underlined <10%. Expenses in Zambian
Kwacha
Big impact for seeds and
fertilizers
12. Increase in the intensity of crop
input use
Impact
Baseline
Baseline
Impact
Baseline
≥6 HH members
≤5 HH members
All
operated land (ha)
Impact
0.179
0.496
0.162
0.43
0.197
0.563
31,174
20,817
42,856
13,331
18,394
28,545
seeds
9,860
6,187
11,092
4,578
8,618
7,848
hired labour
8,417
7,093
14,682
2,845
1,155
11,479
fertilizers
7,606
1,413
8,924
721
6,499
2,127
other exp
5,226
6,092
7,967
5,124
2,092
7,091
crop expenses
N
4,596
2,336
2,260
Bold <5% significant, underlined <10%. Expenses in Zambian
Kwacha
30% increase in land use, but still
small average size
13. Increase in the intensity of crop
input use
Impact
Baseline
Baseline
Impact
Baseline
≥6 HH members
≤5 HH members
All
operated land (ha)
Impact
0.179
0.496
0.162
0.43
0.197
0.563
31,174
20,817
42,856
13,331
18,394
28,545
seeds
9,860
6,187
11,092
4,578
8,618
7,848
hired labour
8,417
7,093
14,682
2,845
1,155
11,479
fertilizers
7,606
1,413
8,924
721
6,499
2,127
other exp
5,226
6,092
7,967
5,124
2,092
7,091
crop expenses
N
4,596
2,336
2,260
Bold <5% significant, underlined <10%. Expenses in Zambian
Kwacha
Much bigger
for smaller HHs
14. Moderate increase in maize and rice production;
decrease in cassava production
Impact Baseline
Impact Baseline
≤5 HH members
All
Impact Baseline
≥6 HH members
maize
cassava
rice
49.5
148.2
35.1
117.8
63.8
179.5
-68.1
146.6
-17.0
103
-129.2
191.7
20.4
78.9
39.4
78.1
2.7
79.7
N
4,596
2,336
2,260
Bold <5% significant, underlined <10%. Production in KGs.
Switching out of cassava production?
Drop in cassava coincides with consumption
results
15. Moderate increase in maize and rice production;
decrease in cassava production
Impact Baseline
Impact Baseline
≤5 HH members
All
Impact Baseline
≥6 HH members
maize
cassava
rice
49.5
148.2
35.1
117.8
63.8
179.5
-68.1
146.6
-17.0
103
-129.2
191.7
20.4
78.9
39.4
78.1
2.7
79.7
N
4,596
2,336
2,260
Bold <5% significant, underlined <10%. Production in KGs.
Moderate significant impact on other staple
goods
16. Moderate increase in maize and rice production;
decrease in cassava production
Impact Baseline
Impact Baseline
≤5 HH members
All
Impact Baseline
≥6 HH members
maize
cassava
rice
49.5
148.2
35.1
117.8
63.8
179.5
-68.1
146.6
-17.0
103
-129.2
191.7
20.4
78.9
39.4
78.1
2.7
79.7
N
4,596
2,336
2,260
Bold <5% significant, underlined <10%. Production in KGs.
Big impact on input use, but not on crop production.
1) Diffuse impacts at crop level? 2) Still not
sufficient inputs? 3) Inefficient combination?
17. Increase in market participation
Impact Baseline
Impact Baseline
≤5 HH members
All
Impact Baseline
≥6 HH members
% selling crops
0.120
0.226
0.144
0.210
0.092
0.242
% consuming crops at home
0.059
0.761
0.063
0.732
0.057
0.790
N
4,596
2,336
2,260
Bold <5% significant, underlined <10%. Production in KGs.
Moderate increase in home production.
Why? Food security achieved with
food purchases!
18. Explicit goal of CGP:
”Increase the number of households owning assets
such as livestock”
Impact
Baseline
Proportion
milk cows
Impact
Baseline
Number
0.033
0.053
-0.061
0.196
other cattle
0.084
0.094
0.263
0.417
chickens
0.154
0.404
1.234
1.949
goats
0.036
0.023
0.142
0.057
ducks
0.030
0.032
0.198
0.129
total
0.209
0.480
0.138
0.347
N
4,596
Bold <5% significant, underlined <10%.
Objective met
4,596
19. Labour activities:
Cross-section
Impact Follow-up
All
Impact Follow-up
Males
Impact Follow-up
Females
paritcipation of HH members in
wage labour
-0.091
0.497
-0.049
0.439
-0.136
0.405
paid agriculture
-0.145
0.337
-0.081
0.261
-0.174
0.292
paid non-agriculture
0.037
0.189
0.040
0.181
0.032
0.112
0.171
0.378
0.120
0.178
0.155
0.327
paid agriculture
-13.75
35.7
-3.04
22.3
-12.37
18.6
paid non-agriculture
3.03
19.9
2.08
15.5
1.09
8.1
non-farm enterprise
1.57
2.65
0.62
0.94
0.98
1.76
N
2,296
non-farm enterprise
intensity of (days in)
1,764
Bold <5% significant, underlined <10%.
Decrease in wage
employment driven by
agricultural labour …
2,282
20. Labour activities:
Cross-section
Impact Follow-up
All
Impact Follow-up
Males
Impact Follow-up
Females
paritcipation of HH members in
wage labour
-0.091
0.497
-0.049
0.439
-0.136
0.405
paid agriculture
-0.145
0.337
-0.081
0.261
-0.174
0.292
paid non-agriculture
0.037
0.189
0.040
0.181
0.032
0.112
0.171
0.378
0.120
0.178
0.155
0.327
paid agriculture
-13.75
35.7
-3.04
22.3
-12.37
18.6
paid non-agriculture
3.03
19.9
2.08
15.5
1.09
8.1
non-farm enterprise
1.57
2.65
0.62
0.94
0.98
1.76
N
2,296
non-farm enterprise
intensity of (days in)
1,764
2,282
Bold <5% significant, underlined <10%.
… especially female HH
members
21. Labour activities:
Cross-section
Impact Follow-up
All
Impact Follow-up
Males
Impact Follow-up
Females
paritcipation of HH members in
wage labour
-0.091
0.497
-0.049
0.439
-0.136
0.405
paid agriculture
-0.145
0.337
-0.081
0.261
-0.174
0.292
paid non-agriculture
0.037
0.189
0.040
0.181
0.032
0.112
0.171
0.378
0.120
0.178
0.155
0.327
paid agriculture
-13.75
35.7
-3.04
22.3
-12.37
18.6
paid non-agriculture
3.03
19.9
2.08
15.5
1.09
8.1
non-farm enterprise
1.57
2.65
0.62
0.94
0.98
1.76
N
2,296
non-farm enterprise
intensity of (days in)
1,764
2,282
Bold <5% significant, underlined <10%.
Significant also on the intensity
of labour
22. Labour activities:
Cross-section
Impact Follow-up
All
Impact Follow-up
Males
Impact Follow-up
Females
paritcipation of HH members in
wage labour
-0.091
0.497
-0.049
0.439
-0.136
0.405
paid agriculture
-0.145
0.337
-0.081
0.261
-0.174
0.292
paid non-agriculture
0.037
0.189
0.040
0.181
0.032
0.112
0.171
0.378
0.120
0.178
0.155
0.327
paid agriculture
-13.75
35.7
-3.04
22.3
-12.37
18.6
paid non-agriculture
3.03
19.9
2.08
15.5
1.09
8.1
non-farm enterprise
1.57
2.65
0.62
0.94
0.98
1.76
N
2,296
non-farm enterprise
intensity of (days in)
1,764
2,282
Bold <5% significant, underlined <10%.
So, what are these people now doing?
They are running an off-farm
business!
23. No impact on child labour
Impact Baseline
All
Impact Baseline
Males
Impact Baseline
Females
total
0.047
0.525
0.083
0.512
0.016
0.537
paid
-0.018
0.043
-0.017
0.039
-0.014
0.047
unpaid
0.039
0.484
0.079
0.470
0.002
0.498
N
8,054
4,005
Bold <5% significant, underlined <10%.
4,049
24. Consistent story in terms of positive
impact on livelihoods
•
CGP leads to increase in agricultural
investment and capital accumulation
― In both crop and livestock production
― Production towards increased market
participation instead of increased home
consumption of output
•
Impact on production is still moderate
• Shift from agricultural wage labour to non
agricultural wage labor and off farm business
26. Small, but significant, increase in
agricultural implements
Impact
Baseline
Proportion
Impact
Baseline
Number
axes
0.008
0.773
0.184
1.114
hoes
0.010
0.912
0.296
1.532
hammers
0.044
0.047
0.042
0.055
shovels
0.031
0.053
0.027
0.063
plough
0.036
0.065
0.033
0.07
N
4,596
4,596
Bold <5% significant, underlined <10%.
Low base – impact
on proportion
owning
High base –
impact on
number
27. Labour supply, baseline
Adult, by sector
agriculture
farming
fishing
forestry
wage labour
casual
self enterprise
not working
Children, by age groups
female
33.08
32.67
0.10
0.31
male
48.61
41.79
6.46
0.35
0.51
26.11
17.29
23.00
1.86
24.79
8.50
16.25
female
overall
5-10 yrs
11-13 yrs
14-18 yrs
5-18 yrs
male
40.47
68.39
78.51
54.32
35.73
69.94
76.92
50.91
28. Increase in the intensive margin of
crop input use
Impact
Baseline
All
operated land (ha)
Impact
Baseline
Impact
<6
Baseline
>5
0.179
0.496
0.162
0.43
0.197
0.563
31,174
20,817
42,856
13,331
18,394
28,545
seeds
9,860
6,187
11,092
4,578
8,618
7,848
hired labour
8,417
7,093
14,682
2,845
1,155
11,479
fertilizers
7,606
1,413
8,924
721
6,499
2,127
other exp
5,226
6,092
7,967
5,124
2,092
7,091
crop expenses
N
4,596
2,336
2,260
Bold <5% significant, underlined <10%. Expenses in Zambian
Kwacha
Moving from family
labour to hired
labour?
29. Increase in savings and loan repayments
Impact
Baseline
All
HH saved cash
0.240
54,371
0.168
0.017
19,392
-256
0.177
55,198
0.010
0.011
19,820
-2,428
0.251
50,610
0.009
0.020
1,170
1,444
(-1.14)
(1.85)
4,596
2,336
2,260
For everyone on both
the extensive and
intensive margin
18,949
0.011
(2.05)
(-0.24)
N
0.158
(4.12)
(1.07)
895
Baseline
(5.54)
(4.72)
(2.44)
loan repayments amount
0.230
Impact
HH size>5
(4.78)
(5.79)
HH repaid loan
Baseline
HH size<6
(5.73)
savings amount
Impact
Increase
just for
larger HH
611
Editor's Notes
The amount of the grant is the same regardless of household size, in order to reduce the incentive for misrepresenting households’ membership, but also to reduce administrative costs associated with delivering the transfer.As with other transfer programs (such as Oportunidades in Mexico) the primary recipient of the transfer is a female in the household that is considered to be the primary caretaker of the household.
Large majority are agricultural producers.Almost 80% produce crops; almost 50% have livestockEach district has quite different crop production patterns. Looking at the share of households producing each crop, Kaputa has mixed maize and cassava production (with a larger share of cassava), while Kalabo has mixed maize and rice production (with larger share of rice). Maize dominates in Shangombo.Most have just a few assets.A bit more than 1/2 HA of agricultural land, a couple of chickens, basic agricultural tools and low levels of education
Further, contamination does not appear to be a big issue: thirty-five control households declared to receive CGP payments and thirty-two of them reported having at least one household member currently a beneficiary. There could be a number of reasons for this occurrence: control households received a payment because they moved to a new area or cheated the system and found a way to register in a neighbouring treatment CWAC. Further it is possible that respondents simply lied about receiving the payment or misunderstood the question. In our impact estimates we decided to keep these household to avoid introducing selection bias that we cannot account for. This clearly leads to a lower impact estimate than a pure ATT.
Greater impacts for smaller HHs
The moderate increase in production seems to go to salesWe don’t find impact on increased home consumption Similar results in amounts
No change in participation and increased intensity of on farm labour activities for males
No change in participation and increased intensity of on farm labour activities for males
No change in participation and increased intensity of on farm labour activities for males
So what are these people doing? Are women more involved in domestic chores? Are generally beneficiaries more involved in on-farm labour? We cannot answer to the former question, but we can say that there is no change in participation of on-farm labour and just a moderate increased intensity for males.
The results found in this paper paint a promising picture in terms of the impact of the program on investments in productive assets, input use and agricultural production. Households invested more in livestock: large and significant effects are found on both the share of households owning animals and on the number of animals owned, especially for larger sized households. Further, the CGP is facilitating the purchase and/or increased use of agricultural inputs use, especially land, seeds, fertilizers and hired labour, both on the share adopting those inputs and the corresponding monetary amount, especially for smaller households. The increase in the use of agricultural inputs led to expansion in the production of maize and rice, though statistically significant only for smaller sized households—and beneficiary households reduced the production of cassava. In contrast with cash transfer results from other countries such as Malawi and Kenya, the increase in agricultural production did not lead to an increase in consumption of goods produced on farm, but instead to more market participation. More detailed analysis can be carried out to ascertain whether these average impacts are similar across different types of agricultural producers. The program has had a positive and significant impact in improving the livelihood position and options of treated households, which after intervention derive a much greater share of income from off-farm enterprises and much lower from wage employment, especially temporary agricultural labour. Taken together with adult labour supply response, these results suggest that, for some beneficiary households, the programme satisfies a cash flow need that was otherwise met through less preferred casual agricultural work, allowing households to concentrate on household business activities, whether in agriculture or off farm.