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The Effects of Transfers on
Intra-household Time Allocation:
Evidence from Northern Uganda
Luisa Natali
UNICEF Office of Research—Innocenti
CSAE Conference
Oxford, 19th of March 2019
2
Motivation & Background
• Dammert et al. (2018), review of public policy on child labor, programs:
• household vulnerability & exposure to risk child work
• adult labour & entrepreneurial activities child labour
• De Hoop et al (2017): Two UCTs in Malawi and Zambia, expansion in
household productive investments increased reliance on children work
• Existing literature on impacts of cash transfers:
•Baird et al. (2014) systematic review: Cash transfers typically increase child
schooling
•De Hoop & Rosati (2014) review: No detrimental effects on child work,
rather reductions
3
Study objectives
• Test whether a food and cash transfer intervention in
Karamoja affect the intra-household allocation of
time
4
WFP food or cash transfers
• Overall Aim: Food security and early childhood development
• Target Group: households with children aged 3-5 years old enrolled
in UNICEF-supported community-run ECD centres (since 2007)
• Location: 3 districts of the Karamoja sub-region
• Transfers: Unconditional, paid/provided every 6 weeks:
• Nutrition-dense take-home food ration, distributed by truck or
• Cash transfers, paid electronically to cards
• Transfer modalities were equivalent in value (roughly USD 12 per
eligible child over 6 weeks) = ~10% of pre-program average
consumption per month
• Recipient: Transfers provided preferentially to a woman in the
household
5
Karamoja map
6
WFP Moroto compound & ECD centers
Photo credit: Amber Peterman
7
Key features & timeline of the evaluation
• Stratified cluster randomized control trial, run by IFPRI
• 98 ECD centres randomly allocated to one of three arms:
1. Food arm (35 clusters)
2. Cash arm (31 clusters)
3. Control group (32 clusters)
• ~ 2,500 households
• Longitudinal from 2010 to 2012
Baseline data
collection
First food transfer First cash transfer Endline data
collection
Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June
2010 2011 2012
Main harvest Lean season Main harvest Lean season
8
Existing evidence on program impacts
• Significant impacts of the cash (not food) transfer on primary
objectives:
•Consumption and food security (Gilligan et al 2013, 2014)
•ECD and young children outcomes (Gilligan and Roy 2015)
• Overall lack of – or limited – impacts of food intervention
•Due to ineffectiveness or lack of enforcement/implementation issues?
• In this presentation, focus on:
•Cash impacts
•Primary school-age children and prime-age adults
9
Main outcome indicators by age group
Primary school-age children
(7-12 at baseline)
School outcomes
(currently enrolled, number of days
attended, school expenditure)
Activities & chores outcomes
Participation (1/0);
Average hours per day (logged)
Productive work, last 7 days
(looking after livestock, help with
agricultural work, wage work)
Reproductive work, last 7 days
(looking after younger children,
caring for sick household members,
doing other chores outside, or near
the home)
Prime-age adults
(18-59 at baseline)
Time use outcomes
In the last six months (participation)
worked in agriculture, looking after
livestock, wage work, non-agricultural
self-employment
In the last two weeks (average hours per
day, logged)
domestic work, income-earning
activities#, leisure activities#Any
work
10
Main characteristics of sample at baseline
Mean
Household head
Age (years) 39.54
Female 0.11
Education: None 0.68
Marital status:
Never married 0.00
Polygamous 0.54
Monogamous 0.38
Divorced/separated 0.01
Widowed 0.07
Household level
Household size 6.32
Monthly consumption per capita,
('000 UGX)
31.14
Dwelling characteristics
Roof: Thatched/vegetable
matter/sticks
0.90
Floor: Cow dung/soil mix 0.77
Main source of lighting: Fire 0.83
Drinking water source:
Borehole, well, spring
0.87
Sanitation: No toilet 0.46
N 2,357
Presence of several
programmes in the study area:
• 83% of households received
assistance from at least one
programme
• No household was beneficiary of
any other cash transfer
intervention
Prime-age adults (past 6 months)
• 93% had worked in agriculture;
• 39% in wage work
• 27.5% in non-agricultural self-
employment
• 14% had spent some time looking
after livestock.
11
Primary school-age children:
 51% currently enrolled and attend half of the days in which school is
open (48 per cent)
 school expenditures per enrolled child in a year around UGX 5,744, or
roughly USD 2.5
Children’s outcomes at baseline
In the last 7 days:
 88% engaged in
domestic work; 5 hours
per day
 57% engaged in
economic work; 1.5
hour per day
0
.1.2.3.4.5.6.7
7 8 9 10 11 12
Age (years)
School only School and work
Work only Idle
12
Empirical strategy
• Analysis of Covariance (ANCOVA) model
𝑦𝑖𝑡 = 𝛽0 + 𝜷 𝟏 𝐹𝑜𝑜𝑑𝑖 + 𝜷 𝟐 𝐶𝑎𝑠ℎ𝑖 + 𝛽3 𝑦𝑖𝑡−1 + 𝛽4 𝑋𝑖𝑡−1 + 𝜃 + 𝜀𝑖
• 𝜷 𝟏, 𝜷 𝟐: ITT effects of being assigned to food/cash arm relative
to control group
• Strata fixed effects; gender and age controls
• OLS with robust standard errors clustered at the level of
randomization (ECD centre)
• Account for multiple testing approach
•Adjust p-values using the Sidak-Bonferroni adjustment
• Results robust to different specifications, models and samples
13
Validity of experimental setting
• Successful randomization:
• Baseline balance carried out on over 50 household key
characteristics and outcome variables
• Household attrition: 7.9%
• No significant differences between arms;
• No significant differential attrition
• Results robust to Lee bounds
14
Results
Photo credit: Amber Peterman
15
Primary school-age children (1/3)
No impact on schooling (neither cash nor food)
Currently
enrolled
Number days
attended school
Education
expenditure,
logged
(1) (2) (3)
Food impact -0.02 -0.03 -0.49
(0.04) (0.04) (0.32)
Cash impact -0.02 -0.01 -0.08
(0.03) (0.03) (0.32)
R2 0.22 0.20 0.22
N 2,478 2,432 2,448
Baseline Control
mean
0.538 0.495 4.510
16
Primary school-age children (2/3)
Increase in child productive work in cash arm
Any work Productive work Reproductive work
Part.
(1/0)
Hours
(logged)
Part.
(1/0)
Hours
(logged)
Part.
(1/0)
Hours
(logged)
Food impact -0.02 -0.03 -0.03 -0.07 -0.02 -0.01
(0.02) (0.06) (0.05) (0.07) (0.02) (0.05)
Cash impact 0.03* 0.17*** 0.27*** 0.31*** 0.02 0.07
(0.02) (0.05) (0.05) (0.06) (0.02) (0.05)
R2 0.04 0.13 0.14 0.14 0.05 0.12
N 2,273 2,207 2,244 2,213 2,273 2,258
Baseline
control mean
0.929 1.858 0.613 0.712 0.896 1.635
17
Primary school-age children (3/3)
…driven by increase in child agricultural work
Productive work
Last seven days
Looking after livestock
Helping with other
agricultural work on
own land
Doing wage work
Part.
(1/0)
Hours
(logged)
Part.
(1/0)
Hours
(logged)
Part.
(1/0)
Hours
(logged)
Food impact -0.02 -0.03 -0.02 -0.04 -0.00 -0.01
(0.02) (0.03) (0.05) (0.06) (0.02) (0.02)
Cash impact 0.02 0.02 0.29*** 0.31*** 0.01 -0.01
(0.02) (0.03) (0.05) (0.06) (0.02) (0.02)
N 2,256 2,256 2,267 2,267 2,224 2,224
Baseline control
mean
0.104 0.137 0.575 0.607 0.044 0.045
18
Prime-age adults:
Positive impact of cash (not food) on (agricultural) work
and time spent on income earning activities
In last six months… In last two weeks…
Worked in
agriculture
Spent time
looking after
livestock
Did work that
paid a salary
or wages
Non-agric. self-
employed
work
Domestic
work
Income-
earning
activities †
Leisure
activities†
Part.
(1/0)
Part.
(1/0)
Part.
(1/0)
Part.
(1/0)
Hours per
day
(logged)
Hours per
day
(logged)
Hours per
day
(logged)
Food impact 0.01 0.02 0.00 -0.00 -0.00 -0.02 -0.04
(0.03) (0.02) (0.03) (0.03) (0.03) (0.05) (0.03)
Cash impact 0.09*** -0.01 0.00 -0.00 0.03 0.25*** -0.02
(0.03) (0.02) (0.03) (0.03) (0.03) (0.04) (0.03)
R2 0.06 0.08 0.03 0.07 0.38 0.11 0.15
N 4,401 4,387 4,391 4,395 4,402 4,399 4,371
Baseline (•)
control mean
0.929 0.161 0.380 0.278 1.363 1.266• 1.165•
19
Mechanisms: Cash beneficiary
households invest more in land
Any investment on land
(1/0)
Food impact 0.006
(0.044)
Cash impact 0.117***
(0.044)
R2 0.06
N 2,357
Baseline control mean 0.548
• No impact on irrigation, crop patterns, livestock or productive
assets.
• No data on agricultural input use, etc.
20
Summary
• Positive impact of the cash (not food) transfer on
•Investments in land
•Adults’ participation in agriculture
•Children’s involvement in productive activities – mainly agricultural
• No significant impact on schooling outcomes
No ‘laziness’ or
welfare dependency
• How to reconcile results with cash transfer literature?
•Transfers not high enough to offset opportunity cost (de Hoop and Rosati, 2014;
Dammert et al., 2018)
•Sufficient excess capacity to accommodate additional students
•Perceived returns to education -> under-investment in schooling?
•Parents value on-the-job-learning
•Importance of context
No impact on
long-working
hours
21
Research & Policy Implications
• For a comprehensive child impact assessment: broader
indicators of child well-being & further info on type of work;
long-term
• More research to understand the level of cash transfer needed
to improve schooling and work outcomes
• How to better design programmes – apart from conditionalities
or larger transfers – to encourage human capital investment
overall for the household, without children engaging in
hazardous labour?
• Cash plus?
• Invest in sensitization/communication
• Closely monitor possible unintended impacts on child labour
22
• Transfer Project website: www.cpc.unc.edu/projects/transfer
• Briefs: http://www.cpc.unc.edu/projects/transfer/publications/briefs
• Facebook: https://www.facebook.com/TransferProject
• Twitter: @TransferProjct email: lnatali@unicef.org
For more information
Ghana, credit: Ivan Griffi
Thank you!
23
References
• Dammert, A.C., J. de Hoop, E. Mvukiyehe, and F.C. Rosati (2018). Effects of Public Policy
on Child Labor: Current Knowledge, Gaps, and Implications for Program Design. World
Development, 110: 104-123.
• Gilligan, D., A. Margolies, E. Quiñones, and S. Roy (2013). WFP/UNICEF/IFPRI Impact
Evaluation of Cash and Food Transfers at Early Childhood Development Centers in
Karamoja, Uganda: Final Impact Report. Submitted to: World Food Programme, Rome;
World Food Programme, Kampala; and UNICEF, Kampala, May 2013.
• Gilligan, D.O., M. Hidrobo, J. Hoddinott, S. Roy, and B. Schwab (2014). Much Ado about
Modalities: Multicountry Experiments on the Effects of Cash and Food Transfers on
Consumption Patterns. IFPRI Conference Paper, International Food Policy Research
Institute.
• Gilligan, D. O. and S. Roy (2015). Resources, Stimulation, and Cognition: How Transfer
Programs and Preschool Shape Cognitive Development in Uganda, IFPRI Conference
Paper, International Food Policy Research Institute.
• De Hoop, J., Groppo, V., and S. Handa on behalf of the Malawi SCTP and Zambia MCTG
study teams (2017) Household Micro-entrepreneurial Activity and Child Work: Evidence
from Two African Unconditional Cash Transfer Programs, Presented at NEUDC 2017.
• De Hoop, J., and F.C. Rosati (2014). Cash Transfers and Child Labor. The World Bank
Research Observer, 29: 202–34.

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Effects of Transfers on Intra-Household Time Allocation: Evidence from Northern Uganda

  • 1. unite for children The Effects of Transfers on Intra-household Time Allocation: Evidence from Northern Uganda Luisa Natali UNICEF Office of Research—Innocenti CSAE Conference Oxford, 19th of March 2019
  • 2. 2 Motivation & Background • Dammert et al. (2018), review of public policy on child labor, programs: • household vulnerability & exposure to risk child work • adult labour & entrepreneurial activities child labour • De Hoop et al (2017): Two UCTs in Malawi and Zambia, expansion in household productive investments increased reliance on children work • Existing literature on impacts of cash transfers: •Baird et al. (2014) systematic review: Cash transfers typically increase child schooling •De Hoop & Rosati (2014) review: No detrimental effects on child work, rather reductions
  • 3. 3 Study objectives • Test whether a food and cash transfer intervention in Karamoja affect the intra-household allocation of time
  • 4. 4 WFP food or cash transfers • Overall Aim: Food security and early childhood development • Target Group: households with children aged 3-5 years old enrolled in UNICEF-supported community-run ECD centres (since 2007) • Location: 3 districts of the Karamoja sub-region • Transfers: Unconditional, paid/provided every 6 weeks: • Nutrition-dense take-home food ration, distributed by truck or • Cash transfers, paid electronically to cards • Transfer modalities were equivalent in value (roughly USD 12 per eligible child over 6 weeks) = ~10% of pre-program average consumption per month • Recipient: Transfers provided preferentially to a woman in the household
  • 6. 6 WFP Moroto compound & ECD centers Photo credit: Amber Peterman
  • 7. 7 Key features & timeline of the evaluation • Stratified cluster randomized control trial, run by IFPRI • 98 ECD centres randomly allocated to one of three arms: 1. Food arm (35 clusters) 2. Cash arm (31 clusters) 3. Control group (32 clusters) • ~ 2,500 households • Longitudinal from 2010 to 2012 Baseline data collection First food transfer First cash transfer Endline data collection Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June 2010 2011 2012 Main harvest Lean season Main harvest Lean season
  • 8. 8 Existing evidence on program impacts • Significant impacts of the cash (not food) transfer on primary objectives: •Consumption and food security (Gilligan et al 2013, 2014) •ECD and young children outcomes (Gilligan and Roy 2015) • Overall lack of – or limited – impacts of food intervention •Due to ineffectiveness or lack of enforcement/implementation issues? • In this presentation, focus on: •Cash impacts •Primary school-age children and prime-age adults
  • 9. 9 Main outcome indicators by age group Primary school-age children (7-12 at baseline) School outcomes (currently enrolled, number of days attended, school expenditure) Activities & chores outcomes Participation (1/0); Average hours per day (logged) Productive work, last 7 days (looking after livestock, help with agricultural work, wage work) Reproductive work, last 7 days (looking after younger children, caring for sick household members, doing other chores outside, or near the home) Prime-age adults (18-59 at baseline) Time use outcomes In the last six months (participation) worked in agriculture, looking after livestock, wage work, non-agricultural self-employment In the last two weeks (average hours per day, logged) domestic work, income-earning activities#, leisure activities#Any work
  • 10. 10 Main characteristics of sample at baseline Mean Household head Age (years) 39.54 Female 0.11 Education: None 0.68 Marital status: Never married 0.00 Polygamous 0.54 Monogamous 0.38 Divorced/separated 0.01 Widowed 0.07 Household level Household size 6.32 Monthly consumption per capita, ('000 UGX) 31.14 Dwelling characteristics Roof: Thatched/vegetable matter/sticks 0.90 Floor: Cow dung/soil mix 0.77 Main source of lighting: Fire 0.83 Drinking water source: Borehole, well, spring 0.87 Sanitation: No toilet 0.46 N 2,357 Presence of several programmes in the study area: • 83% of households received assistance from at least one programme • No household was beneficiary of any other cash transfer intervention Prime-age adults (past 6 months) • 93% had worked in agriculture; • 39% in wage work • 27.5% in non-agricultural self- employment • 14% had spent some time looking after livestock.
  • 11. 11 Primary school-age children:  51% currently enrolled and attend half of the days in which school is open (48 per cent)  school expenditures per enrolled child in a year around UGX 5,744, or roughly USD 2.5 Children’s outcomes at baseline In the last 7 days:  88% engaged in domestic work; 5 hours per day  57% engaged in economic work; 1.5 hour per day 0 .1.2.3.4.5.6.7 7 8 9 10 11 12 Age (years) School only School and work Work only Idle
  • 12. 12 Empirical strategy • Analysis of Covariance (ANCOVA) model 𝑦𝑖𝑡 = 𝛽0 + 𝜷 𝟏 𝐹𝑜𝑜𝑑𝑖 + 𝜷 𝟐 𝐶𝑎𝑠ℎ𝑖 + 𝛽3 𝑦𝑖𝑡−1 + 𝛽4 𝑋𝑖𝑡−1 + 𝜃 + 𝜀𝑖 • 𝜷 𝟏, 𝜷 𝟐: ITT effects of being assigned to food/cash arm relative to control group • Strata fixed effects; gender and age controls • OLS with robust standard errors clustered at the level of randomization (ECD centre) • Account for multiple testing approach •Adjust p-values using the Sidak-Bonferroni adjustment • Results robust to different specifications, models and samples
  • 13. 13 Validity of experimental setting • Successful randomization: • Baseline balance carried out on over 50 household key characteristics and outcome variables • Household attrition: 7.9% • No significant differences between arms; • No significant differential attrition • Results robust to Lee bounds
  • 15. 15 Primary school-age children (1/3) No impact on schooling (neither cash nor food) Currently enrolled Number days attended school Education expenditure, logged (1) (2) (3) Food impact -0.02 -0.03 -0.49 (0.04) (0.04) (0.32) Cash impact -0.02 -0.01 -0.08 (0.03) (0.03) (0.32) R2 0.22 0.20 0.22 N 2,478 2,432 2,448 Baseline Control mean 0.538 0.495 4.510
  • 16. 16 Primary school-age children (2/3) Increase in child productive work in cash arm Any work Productive work Reproductive work Part. (1/0) Hours (logged) Part. (1/0) Hours (logged) Part. (1/0) Hours (logged) Food impact -0.02 -0.03 -0.03 -0.07 -0.02 -0.01 (0.02) (0.06) (0.05) (0.07) (0.02) (0.05) Cash impact 0.03* 0.17*** 0.27*** 0.31*** 0.02 0.07 (0.02) (0.05) (0.05) (0.06) (0.02) (0.05) R2 0.04 0.13 0.14 0.14 0.05 0.12 N 2,273 2,207 2,244 2,213 2,273 2,258 Baseline control mean 0.929 1.858 0.613 0.712 0.896 1.635
  • 17. 17 Primary school-age children (3/3) …driven by increase in child agricultural work Productive work Last seven days Looking after livestock Helping with other agricultural work on own land Doing wage work Part. (1/0) Hours (logged) Part. (1/0) Hours (logged) Part. (1/0) Hours (logged) Food impact -0.02 -0.03 -0.02 -0.04 -0.00 -0.01 (0.02) (0.03) (0.05) (0.06) (0.02) (0.02) Cash impact 0.02 0.02 0.29*** 0.31*** 0.01 -0.01 (0.02) (0.03) (0.05) (0.06) (0.02) (0.02) N 2,256 2,256 2,267 2,267 2,224 2,224 Baseline control mean 0.104 0.137 0.575 0.607 0.044 0.045
  • 18. 18 Prime-age adults: Positive impact of cash (not food) on (agricultural) work and time spent on income earning activities In last six months… In last two weeks… Worked in agriculture Spent time looking after livestock Did work that paid a salary or wages Non-agric. self- employed work Domestic work Income- earning activities † Leisure activities† Part. (1/0) Part. (1/0) Part. (1/0) Part. (1/0) Hours per day (logged) Hours per day (logged) Hours per day (logged) Food impact 0.01 0.02 0.00 -0.00 -0.00 -0.02 -0.04 (0.03) (0.02) (0.03) (0.03) (0.03) (0.05) (0.03) Cash impact 0.09*** -0.01 0.00 -0.00 0.03 0.25*** -0.02 (0.03) (0.02) (0.03) (0.03) (0.03) (0.04) (0.03) R2 0.06 0.08 0.03 0.07 0.38 0.11 0.15 N 4,401 4,387 4,391 4,395 4,402 4,399 4,371 Baseline (•) control mean 0.929 0.161 0.380 0.278 1.363 1.266• 1.165•
  • 19. 19 Mechanisms: Cash beneficiary households invest more in land Any investment on land (1/0) Food impact 0.006 (0.044) Cash impact 0.117*** (0.044) R2 0.06 N 2,357 Baseline control mean 0.548 • No impact on irrigation, crop patterns, livestock or productive assets. • No data on agricultural input use, etc.
  • 20. 20 Summary • Positive impact of the cash (not food) transfer on •Investments in land •Adults’ participation in agriculture •Children’s involvement in productive activities – mainly agricultural • No significant impact on schooling outcomes No ‘laziness’ or welfare dependency • How to reconcile results with cash transfer literature? •Transfers not high enough to offset opportunity cost (de Hoop and Rosati, 2014; Dammert et al., 2018) •Sufficient excess capacity to accommodate additional students •Perceived returns to education -> under-investment in schooling? •Parents value on-the-job-learning •Importance of context No impact on long-working hours
  • 21. 21 Research & Policy Implications • For a comprehensive child impact assessment: broader indicators of child well-being & further info on type of work; long-term • More research to understand the level of cash transfer needed to improve schooling and work outcomes • How to better design programmes – apart from conditionalities or larger transfers – to encourage human capital investment overall for the household, without children engaging in hazardous labour? • Cash plus? • Invest in sensitization/communication • Closely monitor possible unintended impacts on child labour
  • 22. 22 • Transfer Project website: www.cpc.unc.edu/projects/transfer • Briefs: http://www.cpc.unc.edu/projects/transfer/publications/briefs • Facebook: https://www.facebook.com/TransferProject • Twitter: @TransferProjct email: lnatali@unicef.org For more information Ghana, credit: Ivan Griffi Thank you!
  • 23. 23 References • Dammert, A.C., J. de Hoop, E. Mvukiyehe, and F.C. Rosati (2018). Effects of Public Policy on Child Labor: Current Knowledge, Gaps, and Implications for Program Design. World Development, 110: 104-123. • Gilligan, D., A. Margolies, E. Quiñones, and S. Roy (2013). WFP/UNICEF/IFPRI Impact Evaluation of Cash and Food Transfers at Early Childhood Development Centers in Karamoja, Uganda: Final Impact Report. Submitted to: World Food Programme, Rome; World Food Programme, Kampala; and UNICEF, Kampala, May 2013. • Gilligan, D.O., M. Hidrobo, J. Hoddinott, S. Roy, and B. Schwab (2014). Much Ado about Modalities: Multicountry Experiments on the Effects of Cash and Food Transfers on Consumption Patterns. IFPRI Conference Paper, International Food Policy Research Institute. • Gilligan, D. O. and S. Roy (2015). Resources, Stimulation, and Cognition: How Transfer Programs and Preschool Shape Cognitive Development in Uganda, IFPRI Conference Paper, International Food Policy Research Institute. • De Hoop, J., Groppo, V., and S. Handa on behalf of the Malawi SCTP and Zambia MCTG study teams (2017) Household Micro-entrepreneurial Activity and Child Work: Evidence from Two African Unconditional Cash Transfer Programs, Presented at NEUDC 2017. • De Hoop, J., and F.C. Rosati (2014). Cash Transfers and Child Labor. The World Bank Research Observer, 29: 202–34.

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