Amber Peterman, Elsa Valli and Tia Palermo
UNICEF Office of Research – Innocenti
On Behalf of the LEAP 1000 Evaluation Team
CSAE Conference 2019, Oxford
March 17, 2019
Government Anti-Poverty Programming and Intimate Partner Violence in Ghana
1. unite for
children
Government Anti-Poverty Programming
and Intimate Partner Violence in Ghana
Amber Peterman, Elsa Valli and Tia Palermo
UNICEF Office of Research – Innocenti
On Behalf of the LEAP 1000 Evaluation Team
CSAE Conference 2019, Oxford
March 17, 2019
2. 2
Background & motivation
1 in 3 women globally experienced physical and/or sexual
violence by an intimate partner (Devries et al. 2013)
In SSA: 37% lifetime IPV (Southern SSA 30% - Central SSA 66%)
In Ghana: 28-35% experienced IPV in last 12 months (GDHS 2009)
Large increases in social protection programmes globally, nearly
half the worlds population covered by at least one benefit (45%)
(ILO 2017) – key intervention for SDG 1
In SSA: Average country has 15 SSNs, average coverage 10%
(Beegle et al. 2018)
Can social protection also reduce intimate partner violence (IPV)?
If so, through what mechanisms?
Under which circumstances (for which populations, due to which
design features)?
3. 3
Global review: Cash transfers decrease
women’s experience of IPV
0
2
4
6
8
10
12
14
16
18
Decrease Mixed Increase No
relationship
identified
Quantiative Qualitative
• Majority of studies (73%) showed decreases, impacts stronger for physical/sexual
Overall impacts on IPV
[22 studies]
Gaps identified in that review:
• Little evidence on frequency
& severity of IPV
• Few studies examine
pathways
• Large regional gaps,
including Sub-Saharan
Africa and Western/Central
Africa in particular
Source: Buller A, Peterman A, Ranganathan M, Bleile A, Hidrobo M, & Heise L. (2018). A
Mixed Method Review of Cash Transfers and Intimate Partner Violence in Low- and Middle
Income Countries. World Bank Research Observer 33(2).
4. 4
Existing quantitative studies from SSA
1. Mali (Health et al., 2018): National programme given to male heads of
households on a quarterly basis + monthly BCC sessions. Impact: large
decreases in controlling behaviors, emotional and physical IPV (7 – 16 pps)
driven by polygamous sample (~40% of the sample). Mechanism: due to
increases in male emotional wellbeing, decrease in stress and anxiety.
2. Kenya (Haushofer et al. 2018): NGO (GiveDirectly) gave approximately
two years’ worth pc expend transfers. Impact: decreased physical IPV
(0.26-0.18 DS), decreased sexual IPV (0.22 SD). Also spillover effect:
reduction in physical violence (0.16 SD). Mechanism: change in woman’s
tolerance & men’s distaste for IPV.
3. South Africa (Pettifor et al. 2016; Kilburn et al., 2018): NGO CCT
targeting females in secondary school (conditional on attendance). Impact:
reduced past-year physical IPV (RR: 0.66; 0.56-0.74). Mechanism: young
women engaged in fewer partnerships (decreased sexual debut and
number of past year partners).
5. 5
Program theory & Mechanisms
Source: Buller A, Peterman A, Ranganathan M, Bleile A, Hidrobo M, & Heise L. (2018). A Mixed
Method Review of Cash Transfers and Intimate Partner Violence in Low- and Middle Income Countries.
World Bank Research Observer 33(2).
6. 6
Study aims
Examine whether a
government social protection
programme targeted to
extremely poor, rural
households with pregnant and
recently pregnant women in
Ghana had an impact on past-
year prevalence and frequency
of IPV;
Through which pathways;
Assess if family structure
matters (polygamous v.
monogamous)
7. 7
LEAP 1000 programme
Part of government-led, nationwide unconditional cash
transfer programme: Livelihood Empowerment Against
Poverty (LEAP) programme
Program objectives: 1) Alleviate short-term poverty and 2)
Encourage long-term human capital development
LEAP 1000 specific focus on nutrition and stunting
Targets pregnant women or women with a child <1 year
Bi-monthly cash transfer [approx. GH₵76 (EUR14)] and
health insurance (NHIS) premium waiver
Initial coverage of LEAP 1000: 6,220 households in 10
districts in Northern Ghana
8. 8
Methods: Evaluation Design and sample
2-year mixed method, quasi-
experimental, longitudinal study
8,058 households applied for LEAP
1000 and 3,619 deemed eligible
Baseline (Jul-Sept 2015), Endline
(Jul-Sept 2017)
BL evaluation sample N=2,497
households (1,262 T and 1,235 C)
Final analysis sample: N=2,083
women (1,060 T & 1,023 C)
Districts: Yendi, Karaga, East
Mamprusi, Bongo Garu Tempane
9. 9
Measures: IPV Outcomes
Based on modified Conflict Tactics Scale
Female enumerators, interviews conducted in privacy
Any experience in prior 12 months
Frequency in prior 12 months (0=never, 1=sometimes, 2=often for
each item; standardized)
Controlling behaviors, 7 questions (any; frequency 0 – 7)
Emotional IPV, 4 questions (any; frequency range 0 – 8)
Physical IPV, 7 questions (any; frequency range 0 – 14)
Sexual IPV, 2 questions (any; frequency range 0 – 4)
Emotional/Physical/Sexual IPV, 13 questions (any; frequency
range 0 – 26)
10. 10
Measures: Pathways
1. Economic strengthening and overall emotional wellbeing
• household-level poverty and extreme poverty
• household adult equivalent monthly total & food expenditures (cedis)
• woman’s perceived stress (Cohen perceived stress scale)
• women’s life satisfaction
2. Intra-household conflict
• partner often drunk
• partner sometimes/often drunk
• household monthly expenditure on alcohol (cedis)
3. Women’s empowerment
• agency index
• locus of control
• decision-making ability
• saving money (binary) & amount saved last month (cedis)
• social support score
• valid NHIS (binary),
• sought care for illness/injury – 2 weeks
11. 11
Statistical analysis
• Inspired by Regression Discontinuity Design approach: exploits
cutoff threshold applied to a continuous proxy means test
• Difference-in-difference (DID) to estimate program impacts
𝑌𝑖𝑗𝑡 = 𝛽0 + 𝛽1 𝑃𝑖𝑗 + 𝛽2 𝑇𝑡 + 𝛽3 𝑃𝑖𝑗 ∗ 𝑇𝑡 + 𝛽4 𝑿𝑖𝑗𝑡 + 𝜆𝑗 + 𝜀𝑖𝑗𝑡
• 𝑌𝑖𝑗𝑡 is the IPV or pathway outcome of interest for woman 𝑖 who lives in
community 𝑗 at time 𝑡.
• 𝑃𝑖𝑗 is program participation
• 𝑇𝑡 is time
• 𝑃𝑖𝑗 ∙ 𝑇𝑡 is the interaction term of the program and the time dummy
• 𝑿𝑖𝑗𝑡 represents a set of observed individual, spouse, and household
characteristics including polygamous marriage, PMT score
• 𝜆𝑗 represents a full set of community fixed effects
• 𝜀𝑖𝑗𝑡 is error term
12. 12
Results: Baseline Balance, IPV indicators
Baseline balance: Across 36 control, pathway & outcome variables,
3 are significant different at p<0.10 level or higher
Attrition: 10%, across 36, 2 show signs of differential attrition
13. 13
Background characteristics
Full sample
(1)
Monogamous sample
(2)
Polygamous sample
(3)
P-value of diff.
(2) = (3)
Woman’s age (years) 29.74 28.66 32.08 0.00
Woman any formal education (0,1) 0.19 0.24 0.09 0.00
Partner's age (years) 36.71 34.26 41.98 0.00
Partner any formal education (0,1) 0.28 0.33 0.18 0.00
Age difference (partner-woman) 6.96 5.60 9.90 0.00
Difference in spouse-woman any education 0.09 0.09 0.09 0.81
Household size 6.71 5.93 8.41 0.00
Pathway indicators
Poverty status (0,1) 0.87 0.87 0.88 0.58
Household monthly AE expenditure (cedis) 120.41 122.31 116.31 0.18
Cohen perceived stress scale 31.72 31.66 31.86 0.45
Satisfied with life (some of the time or more, 0,1) 0.58 0.60 0.55 0.05
Partner sometimes or often drunk (0,1) 0.15 0.15 0.17 0.38
Household monthly expenditure on alcohol (cedis) 1.27 1.51 0.74 0.15
Women’s agency index (z-score) 0.00 0.02 -0.03 0.32
Women saving any money (0,1) 0.08 0.08 0.10 0.08
Amount of money saved last month (cedis) 4.52 3.83 6.00 0.15
Social support score (standardized) 52.85 52.51 53.58 0.28
Sought care for illness in last 2 weeks (0,1) 0.52 0.51 0.53 0.25
IPV in the last 12 months
Experienced controlling behaviors (0,1) 0.82 0.79 0.88 0.00
Frequency controlling behaviors (sum; range: 0-7) 2.44 2.29 2.75 0.00
Experienced emotional IPV (0,1) 0.60 0.57 0.67 0.00
Frequency emotional IPV (sum; range: 0-8) 1.18 1.07 1.41 0.00
Experienced physical IPV (0,1) 0.36 0.32 0.44 0.00
Frequency physical IPV (sum; range: 0-14) 1.17 1.01 1.52 0.00
Experienced sexual IPV (0,1) 0.19 0.17 0.23 0.00
Frequency sexual IPV (sum; range: 0-4) 0.20 0.18 0.26 0.00
Experienced emotional/physical/sexual IPV (0,1) 0.66 0.63 0.73 0.00
Frequency emotional/physical/sexual IPV (sum; range: 0-26) 2.55 2.26 3.19 0.00
N 2,083 1,423 660
Descriptive statistics by family structure
14. 14
Results: Impacts on Experience of IPV
Controlling behavior Emotional IPV Physical IPV Sexual IPV
Emotional,
physical or sexual
IPV
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)
Impact -0.02 -0.03 -0.03 -0.06 -0.04 -0.05 -0.01 -0.03 -0.03 -0.08
(0.02) (0.03) (0.02) (0.03)** (0.03) (0.03)* (0.02) (0.03) (0.03) (0.03)**
Polygamous 0.05 0.07 0.09 0.14 0.07 0.14 0.05 0.12 0.08 0.18
(0.01)*** (0.02)*** (0.02)*** (0.04)*** (0.02)*** (0.03)*** (0.01)*** (0.03)*** (0.02)*** (0.04)***
Impact X Polygamous 0.04 0.10 0.05 0.06 0.15
(0.04) (0.06)* (0.05) (0.05) (0.06)***
R2 0.14 0.14 0.09 0.09 0.11 0.12 0.08 0.08 0.09 0.10
Endline comparison means 0.834 0.834 0.566 0.566 0.278 0.278 0.211 0.211 0.624 0.624
Net treatment polygamous 0.00 0.04 -0.00 0.03 0.08
(0.03) (0.05) (0.04) (0.03) (0.05)
No impacts in full sample
5-8 pp decreases among monogamous sample only (emotional, physical &
combined)
Polygamous union associated with 5 pp – 18 pp increase across all measures
Standard errors in parenthesis clustered at the community level. * p<0.1 ** p<0.05; *** p<0.01. All regressions include the following covariates at baseline: Women's age, dummy
for having any formal education (0,1), dummy for polygamous marriage (0,1), partner's age and dummy for having any formal education (0,1); PMT score, household size;
community fixed effects.
15. 15
Results: Impacts on Frequency of IPV
Controlling behavior Emotional IPV Physical IPV Sexual IPV
Emotional,
physical or sexual
IPV
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)
Impact -0.04 -0.07 -0.11 -0.11 -0.09 -0.11 -0.05 -0.06 -0.11 -0.12
(0.06) (0.07) (0.05)* (0.07)* (0.05)* (0.06)* (0.05) (0.06) (0.05)** (0.06)**
Polygamous 0.15 0.22 0.22 0.23 0.14 0.25 0.14 0.18 0.19 0.27
(0.04)*** (0.07)*** (0.04)*** (0.08)*** (0.05)*** (0.08)*** (0.04)*** (0.06)*** (0.05)*** (0.08)***
Impact X Polygamous 0.10 0.02 0.07 0.03 0.06
(0.12) (0.13) (0.11) (0.12) (0.11)
R2 0.18 0.18 0.14 0.14 0.09 0.10 0.08 0.08 0.12 0.12
Endline comparison means -0.000 -0.000 0.000 0.000 0.000 0.000 0.000 0.000 -0.000 -0.000
Net treatment polygamous 0.03 -0.09 -0.04 -0.03 -0.07
(0.10) (0.10) (0.10) (0.10) (0.09)
Small impacts in full sample (0.09 – 0.11 SD decreases)
No difference by polygamous status
Polygamous union associated with 0.14 - 0.27 SD increase across all measures
Standard errors in parenthesis clustered at the community level. * p<0.1 ** p<0.05; *** p<0.01. All regressions include the following covariates at baseline: Women's age, dummy
for having any formal education (0,1), dummy for polygamous marriage (0,1), partner's age and dummy for having any formal education (0,1); PMT score, household size;
community fixed effects.
16. 16
Results: Summary of pathway impacts
Positive impacts on:
Economic security (less likely to be poor
and extremely poor; 3-5 pp)
Monthly expenditures (~ 7 Cedis AE)
Monthly food expenditures (~ 5-6 Cedis
AE)
Locus of control (monogamous women)
Savings
Social support
Valid NHIS card; health seeking behavior
No impacts on:
Self perceived stress
Life satisfaction
Partner drinking
Expenditures on alcohol
Women’s decision-making
Agency
17. 17
Discussion & conclusion
LEAP 1000 reduced frequency of emotional, physical, any IPV
measures in the full sample
Any experience of IPV only reduced in the monogamous sample
No impacts on experience among polygamous sample, which is at
highest risk of IPV
Pathways include economic standing/emotional wellbeing and
women’s empowerment
Limitations: Local average treatment effects, underreporting possible
Results underscore that cash transfers can improve wellbeing beyond
primary program objectives
Findings indicate that family structure matters in designing programs
– yet we know little about why or how (more research needed +
qualitative inquiry)
18. 18
References
• Beegle, Kathleen, Aline Coudouel, and Emma Monsalve (2018). Realizing the Full Potential of Social Safety Nets in
Africa. Africa Development Forum series. Washington, DC: World Bank. doi:10.1596/978-1-4648-1164-7
• Buller A, Peterman A, Ranganathan M, Bleile A, Hidrobo M, & Heise L. (2018). A Mixed Method Review of Cash
Transfers and Intimate Partner Violence in Low- and Middle Income Countries. World Bank Research Observer
33(2): 218-258.
• Devries et al. (2013). The Global Prevalence of Intimate Partner Violence Against Women. Global Health, 340.
• GDHS, and ICF Macro (2009). Ghana Demographic and Health Survey 2008. Calverton, Maryland, USA: GSS,
GHS, and ICF Macro.
• Haushofer, Johannes, Ringdal, Charlotte, and Shapiro, Jeremy (2018). Income changes and intimate partner
violence: Evidence from unconditional cash transfers in Kenya (working paper).
• Health, R., Hidrobo, M. & Roy, S. (2018). Cash transfers, polygamy and intimate partner violence: Experimental
evidence from Mali (working paper).
• ILO (2017). World Social Protection Report 2017–19: Universal social protection to achieve the Sustainable
Development Goals International Labour Office – Geneva.
• Kilburn, K., Pettifor, A., Edwards, J.K., Selin, A., Twine, R., MacPhail, C. et al. (2018). The effect of a conditional
cash transfer for HIV prevention on the experience of partner violence for young women: Evidence from a
randomized experiment in South Africa HPTN 068. Journal of International AIDS Society (in press).
• Pettifor, A., MacPhail C, Hughes, JP, Selin A, Wang J, Gomez-Olive FX et al. (2016). The effect of a conditional
cash transfer on HIV incidence in young women in rural South Africa (HPTN 068): a phase 3, randomized controlled
trial. The Lancet Global Health 4(12): e978-e988.
19. 19
Acknowledgements
We are grateful for the support of the Government of Ghana for the implementation
of this evaluation, in particular William Niyuni, Mawutor Ablo and Richard Adjetey
from the Ministry of Gender, Children and Social Protection. In addition, the
UNICEF Ghana team was instrumental to the success of this report: Sara
Abdoulayi, Luigi Peter Ragno, Jennifer Yablonski, Sarah Hague, Maxwell Yiryele
Kuunyem, Tayllor Spadafora, Christiana Gbedemah and Jonathan Nasonaa
Zakaria.
We would also like to acknowledge the hard-working field teams of ISSER and
NHRC, who conducted the data collection for this study to the highest standards.
Funding for the evaluation was generously provided by the United States Agency
for International Development (USAID) and the Canadian International
Development Agency (CIDA). Additional funding to include intimate partner violence
modules in the evaluation and to produce this paper was received from an
Anonymous donor and the American World Jewish Services by the UNICEF Office
of Research—Innocenti via the US Fund for UNICEF. We thank Laura Meucci and
Michelle Kate Godwin for grant administrative support.
20. 20
LEAP 1000 Evaluation Team
UNICEF Office of Research – Innocenti: Tia Palermo (co-Principal
Investigator), Richard de Groot, Elsa Valli;
Institute of Statistical, Social and Economic Research (ISSER), University
of Ghana: Isaac Osei-Akoto (co-Principal Investigator), Clement Adamba,
Joseph K. Darko, Robert Darko Osei, Francis Dompae and Nana Yaw;
Carolina Population Center, University of North Carolina at Chapel Hill:
Clare Barrington (co-Principal Investigator), Gustavo Angeles, Sudhanshu
Handa (co-Principal Investigator), Frank Otchere, Marlous de Miliano;
Navrongo Health Research Centre (NHRC): Akalpa J. Akaligaung (co-
Principal Investigator) and Raymond Aborigo.
WHO estimates of lifetime IPV prevalence by region (2016): https://apps.who.int/iris/bitstream/handle/10665/85239/9789241564625_eng.pdf;jsessionid=6B10A3A7028671B3DEA540E4014AC733?sequence=1
IDS estimates of IPV in last 12 months in Ghana
Linkages between poverty and violence can be ambiguous, non-linear and interact at different levels (personal, situational, socio-cultural).
Beegle K, Coudouel, A & E Monsalve (Eds) (2018). Realizing the Full Potential of Social Safety Nets in Africa. World Bank.
A recent mixed method review found evidence that CTs decrease experience of IPV, but the review identified the following gaps.
Gaps identified in that review:
Little evidence on frequency & severity of IPV
Few studies examine pathways
Large regional gaps, including Sub-Saharan Africa and Western/Central Africa in particular
RR (relative risk): If the risk ratio is 1 (or close to 1), it suggests no difference or little difference in risk(incidence in each group is the same). A risk ratio > 1 suggests an increased risk of that outcome in the exposed group. A risk ratio < 1 suggests a reduced risk in the exposed group.
Mention they are all RTCs (2 yrs, 1 yrs, 3 yrs)
Pettifor et al. study gave transfers to girls + guardians
Specifically, cash transfers have been posited to reduce IPV through the following three pathways
In the current study, we aim to provide evidence around three of these gaps
Value of transfer as a share of study households’ consumption at baseline= 13.9%. (And median value is even lower=10%).
80% of households receive a transfer lower than 20% (benchmark target).
However, It is worth noting that while the low value of the transfer as a share of consumption might constrain the impacts of the programme, the households included in the study are those that are close to the PMT cut-off score and thus are not the worst off among all LEAP 1000 beneficiaries. As a consequence, the value of transfer as a share of these households’ consumption is not representative of the entire beneficiary population and is lower than the average share among the entire distribution of LEAP 1000 beneficiaries.
We then standardize the frequency measures by subtracting the control group mean for each round and dividing by the control standard deviation
For controlling behaviors, we simply sum each behaviorally binary specific indicator, and the raw frequency ranges from zero to seven. We use standardized indices for the impact analysis, however present raw frequencies for descriptive tables and figures for ease of interpretation
Economic strengthening and overall emotional wellbeing
1) household-level poverty (binary as per national poverty line), 2) household-level extreme poverty (binary as per national extreme poverty line), 3) household adult equivalent monthly expenditures (cedis), 4) household adult equivalent monthly food expenditures (cedis), 5) woman’s perceived stress (Cohen perceived stress scale) and 6) women’s life satisfaction (binary, satisfied with life some/most/all of the time).
Intra-household conflict
1) partner often drunk (binary), 2) partner sometimes/often drunk (binary), 3) household monthly expenditure on alcohol (cedis).
Women’s empowerment
agency index (aggregate of agency in six domains), 2) locus of control, 3) decision-making ability assessed based on a vignette, 4) saving money (binary), 5) amount of money saved last month (cedis), 6) social support score (aggregate of social support in eight domains), 7) valid NHIS (binary), 8) sought care for illness or injury in the last two weeks (binary).
Based on six positive questions about perceptions of her capacities of protecting her own interests and her feelings of being in power to give a direction to her own life, such as "How often did you feel that your life is determined by your own actions" and "How often did you feel that you have the power to make important decisions that change the wellbeing of your children." Answers were given based on the frequency with which they experienced the feeling specified in each statement, which could range from 1 to 5 with higher numbers corresponding to higher frequency (i.e., 1 corresponds to “never,” 5 to “always”). The answers to each question were summed and then standardized in relation to the comparison group in each wave.
Locus of control Based on a question aimed at capturing women's locus of control: "Some people feel they have completely free choice and control over their lives, while other people feel that what they do has no real effect on what happens to them. Imagine a ladder where on the bottom step, the first step are people with who have no free choice and no control over their lives, and on the highest step, the tenth are people who have completely free choice and total control over their lives. On which step of the ladder would you say you are today?" with response options ranging from 1 to 10.
All regressions include the following covariates at baseline: Women's age, dummy for having any formal education (0,1), dummy for polygamous marriage (0,1), partner's age and dummy for having any formal education (0,1); PMT score, household size; community fixed effects.
In the overall targeting exercise conducted, the PMT scores ranged from 6.136 to 8.667, while in the evaluation sample, the PMT scores range from 7.009 to 7.296, with the program eligibility cutoff at 7.158 (SD=0.32). Households were systematically sampled around the cut-off for evaluation purposes, and the resulting households in the treatment sample are within 0.46 SD of the cut-off, and all comparison households are within 0.43 SD of the cut-off. Given the small threshold of the distribution of sampled households around the PMT score, a simple difference-in-difference (DID) was used to evaluate the impacts of the program. In subsequent versions of this working paper we will present robustness checks using the formal RDD approach.
Control variables utilized in the analysis included individual-, household-, and community-level characteristics. At the individual-level, we controlled for age (in years) and indicators for any formal education of both woman and partner. Further, in analysis of the full sample, we control for being in a polygamous partnership (reference group is monogamous partnership). Household-level control variables included household size and the PMT score. Community-level controls included districts of residence (Karaga, Yendi, in the Northern Region; Bongo, and Garu Tempane in the Upper East Region; reference district is East Mamprusi in the Northern Region). To assess variations by family structure, we interact the indicator for polygamous partnership with the treatment indicator, time indicator and impact estimate (creating a triple interaction term). For sampling purposes, a household was defined as a person or group of related or unrelated persons, who live together in the same housing unit, who acknowledge one adult male or female as the head of the household, who share the same housekeeping and cooking arrangements, and are considered as one unit. For polygamous households, enumerators were instructed as follows: “If a man does not live in the same house as his wife or wives, the man and his wife/wives must be considered as separate households. Any children and others must be included in the household of the one in whose house they sleep. Thus, if a man and his wife live in different houses and their two sons sleep in the father's house after eating in their mother's house, the children must be included in the father's household while the mother is listed as a single-person household.”
We use any formal education, as the variation in educational attainment is low in our sample: only 19 percent of women have had any formal education and only 23 percent of partners have had any formal education. Using attainment instead of a binary indicator does not change results.
Although we control for the PMT score in all regression analysis, our results are robust to excluding this control variable (available upon request).
Note that we do not see a discontinuity here
Similar for Controlling behaviors and sexual IPV – not shown here
“impact” line is for monogamous women
Net treatment = impact + impact * polygamous impact
Net is for polygamous women
LEAP reduced frequency in full sample from 0.09 to 0.11 standard deviation decreases,
No impacts on help-seeking for IPV