i
ABOUT IMPEL
The Implementer-Led Evaluation & Learning Associate Award (IMPEL) works to improve the design and implementation of 
Bureau for Humanitarian Assistance (BHA)-funded resilience food security activities (RFSAs) through implementer-led 
evaluations and knowledge sharing. Funded by the United States Agency for International Development (USAID) BHA, IMPEL 
will gather information and knowledge in order to measure performance of RFSAs, strengthen accountability, and improve 
guidance and policy. This information will help the food security community of practice and USAID to design projects and 
modify existing projects in ways that bolster performance, efficiency, and effectiveness. IMPEL is a seven-year activity (2019–
2026) implemented by Save the Children (lead), TANGO International, Tulane University, Causal Design, Innovations for Poverty 
Action, and International Food Policy Research Institute. 
RECOMMENDED CITATION
IMPEL. (2022). Baseline Evaluation of the Amalima Loko Resilience Food Security Activity in Zimbabwe (Vol. I). Washington, DC: 
The Implementer-Led Evaluation & Learning Associate Award. 
PHOTO CREDIT
Bridget Siziba / Cultivating National Frontier in Agriculture
DISCLAIMER
This report is made possible by the generous support of the American people through the United States Agency for 
International Development (USAID). The contents are the responsibility of the Implementer-Led Evaluation & Learning (IMPEL) 
award and do not necessarily reflect the views of USAID or the United States Government.
CONTACT INFORMATION
IMPEL Associate Award
c/o Save the Children
899 North Capitol Street NE, Suite #900
Washington, DC 20002
fsnnetwork.org/IMPEL 
IMPEL@savechildren.org
PREPARED BY:
Baseline Evaluation of the Amalima Loko RFSA in Zimbabwe (Vol. I)
Acknowledgments i
ACKNOWLEDGMENTS
This report was written by Matthew Summers (University of Maryland), Daniele Barro, Monserrat Lara, 
and Antoine Guilhin from Innovations for Poverty Action, Lasse Brune (Northwestern University), Craig 
McIntosh (University of California), and Emily Beam (University of Vermont).
This page is left intentionally blank.
Baseline Evaluation of the Amalima Loko RFSA in Zimbabwe (Vol. I)
List of Tables and Figures iii
TABLE OF CONTENTS
Acknowledgments...............................................................................................i
LIst of Tables.......................................................................................................v
LIst of Figures......................................................................................................v
Acronyms...........................................................................................................vi
Executive Summary ..........................................................................................vii
1. Baseline Household Survey ............................................................................1
1.1 Objective ........................................................................................................................................1
1.2 Questionnaire.................................................................................................................................1
1.3 Sampling.........................................................................................................................................2
1.4 Field Activities ................................................................................................................................3
1.5 Limitations and Challenges ............................................................................................................4
2. Results...........................................................................................................5
2.1 Household Demographics..............................................................................................................5
2.2 Poverty Indicators..........................................................................................................................5
2.3 Water, Sanitation, and Hygiene .....................................................................................................6
2.4 Housing Quality ..............................................................................................................................7
2.5 Assets .............................................................................................................................................8
2.6 Land and Agriculture ......................................................................................................................9
2.6.1 Land and Crops..............................................................................................................9
2.6.2 Agricultural Finance and Techniques..........................................................................10
2.7 Livestock Holdings........................................................................................................................10
2.8 Food Security................................................................................................................................11
2.8.1 Food Consumption Score............................................................................................11
2.8.2 Food Insecurity............................................................................................................12
2.8.3 Dietary Diversity..........................................................................................................13
2.9 Women and Children’s Health and Nutrition ..............................................................................13
2.9.1 Women’s Health and Diet...........................................................................................13
2.9.2 Children’s Health and Diet..........................................................................................14
2.9.3 Family Planning ...........................................................................................................15
2.10 Gender..........................................................................................................................................16
2.11 Resilience and Mental Health ......................................................................................................18
2.12 Savings and Loans.........................................................................................................................20
2.13 Collective Action and Government Support ................................................................................21
3. Next Steps....................................................................................................24
3.1 Preparation for Outcome Monitoring Survey ..............................................................................24
IMPEL | Implementer-Led Evaluation and Learning
iv Table of Contents
3.2 Devise Criteria for Propensity Score Matching ............................................................................24
Annex A: Additional Tables...............................................................................25
VOLUME II
Annex B: Baseline Survey Tools
Annex C: Field Manual
Annex D: Research Protocol
Baseline Evaluation of the Amalima Loko RFSA in Zimbabwe (Vol. I)
List of Tables and Figures v
LIST OF TABLES
Table 1. Key findings from the baseline survey .......................................................................................... vii
Table 2. Sample overview .............................................................................................................................3
Table 3. Enumerators' productivity ..............................................................................................................4
Table 4. Household demographics................................................................................................................5
Table 5. Poverty level....................................................................................................................................6
Table 6. Water, sanitation, and hygiene.......................................................................................................6
Table 7. Housing quality................................................................................................................................7
Table 8. Household assets.............................................................................................................................8
Table 9. Crops cultivated...............................................................................................................................9
Table 10. Agriculture...................................................................................................................................10
Table 11. Livestock assets in the last 12 months........................................................................................10
Table 12. Food Consumption Score ............................................................................................................11
Table 13. Food Insecurity Experience Scale................................................................................................12
Table 14. Dietary diversity ..........................................................................................................................13
Table 15. Women’s health..........................................................................................................................14
Table 16. Small children: diet and health ...................................................................................................14
Table 17. Family planning ...........................................................................................................................15
Table 18. Women empowerment...............................................................................................................17
Table 19. Resilience.....................................................................................................................................18
Table 20. Mental health in the last 12 months...........................................................................................19
Table 21. Savings.........................................................................................................................................20
Table 22. Loans ...........................................................................................................................................21
Table 23. Collective action..........................................................................................................................21
Table 24. Government support...................................................................................................................22
Table 25. Improved management practices and technologies for crop.....................................................25
Table 26. Improved management practices and technologies for livestock..............................................26
Table 27. Activity wards in the Hwange district .........................................................................................27
Table 28. Activity wards in the Lupane district...........................................................................................28
Table 29. Activity wards in the Binga district..............................................................................................29
Table 30. Activity wards in the Nyaki district..............................................................................................30
Table 31. Activity wards in the Tsholotsho district.....................................................................................31
LIST OF FIGURES
Figure 1. Amalima Loko wards......................................................................................................................3
IMPEL | Implementer-Led Evaluation and Learning
vi Acronyms
ACRONYMS
BHA Bureau for Humanitarian Assistance
CI Confidence Interval
CNFA Cultivating New Frontiers in Agriculture
FCS Food Consumption Score
FIES Food Insecurity Experience Scale
GPS Global Positioning System
HDDS Household Dietary Diversity Score
IMC International Medical Corps
IPA Innovations for Poverty Action
IUD Intrauterine Device
MAD Minimum Acceptable Diet
N Number Sampled
NGO Non-Governmental Organization
ORAP Organization of Rural Associations for Progress
PPP Purchasing Power Parity
QE Quasi-experimental research design
RFSA Resilience Food Security Activity
TMG The Manoff Group
USAID United States Agency for International Development
USD United States Dollar
VSLA Village Savings and Loan Association
WASH Water, sanitation, and hygiene
Baseline Evaluation of the Amalima Loko RFSA in Zimbabwe (Vol. I)
Executive Summary vii
EXECUTIVE SUMMARY
Under the Implementer-Led Evaluation and Learning (IMPEL) Associate Award funded by the United 
States Agency for International Development (USAID), Innovations for Poverty Action (IPA) is conducting 
an impact evaluation of the Amalima Loko Resilience Food Security Activity (RFSA) in Matabeleland 
North province, Zimbabwe. Amalima Loko is an activity led by Cultivating New Frontiers in Agriculture 
(CNFA) and partners with the Organisation of Rural Associations for Progress (ORAP), Dabane Water 
Workshops (Dabane), The Manoff Group (TMG), International Medical Corps (IMC), and Mercy Corps, 
with financial support from USAID. 
The goal of Amalima Loko is to sustainably improve food security through increased food access and sustainable 
watershed management among extremely poor and chronically vulnerable households and communities in 
Matabeleland North Province. The Amalima Loko interventions are grouped into three purposes: 
1. Enhanced and inclusive local ownership over food security and resilience planning and development. 
2. Improved health and availability of soil, water, and plant resources within the watershed and 
their individual and collective capacities to withstand the most common shocks and stressors. 
3. Improved human health and livelihoods.
Amalima Loko’s interventions will be rolled out in 87 wards across the participating districts (Binga, 
Hwange, Lupane, Nkayi, and Tsholotsho), with the wards assigned to 21 watershed clusters of 3–5 wards 
each. Amalima Loko will generally be implemented in every village in the activity area, with an expected 
target population of 188,302. The expectation is that individuals will self-select into the most beneficial
interventions for them; as such, while all individuals are eligible, not everyone in each area is expected 
to participate. Table 1 below shows the intervention conceptual framework. The main objective of the 
impact evaluation is to assess Amalima Loko’s effectiveness in achieving its objectives. IPA will use a 
quasi-experimental (QE) design to compare outcomes among treated and non-treated households. This 
report describes the data collected as part of the baseline survey of the Amalima Loko activity. 
Additional surveys will be carried out during the process evaluation, the midline survey, and the final 
evaluation stage. 
This report provides summary statistics and indicator estimates based on a recently completed round of 
baseline data collection. IPA, with a team of 10 enumerators, administered a baseline survey to 511 
households between April 29 and May 22, 2022, in the districts of Binga, Hwange, Lupane, and Nkayi. 
Tsholotsho district, while part of the activity, only has a few treated wards due to only these wards 
being part of the Gwayi sub-catchment area and was thus omitted from the baseline survey. 
Table 1. Key findings from the baseline survey
Demographics and Poverty
511 households were interviewed, with an average size of 5.3 people.
The share of adults over 18 years was 48% in the targeted communities.
The share of children under 5 years was 16% in the targeted communities.
The share of women of reproductive age (15–49 years) was 20% in the targeted communities.
IMPEL | Implementer-Led Evaluation and Learning
viii Executive Summary
Demographics and Poverty
In the targeted communities, 84% of households lived on less than Purchasing Power Parity (PPP)
$1.90 per day and per adult.
WASH
25% of households report having access to a basic sanitation service.
64% of households report not using basic sanitation services.
Housing and Assets
65% of households have thatched roofs.
64% have an earth/sand floor.
Land, Agriculture, and Livestock
88% of households report owning land.
1
93% of households cultivated at least one crop in the last 12 months and have an average of 16.32 
acres of land.
88% of households report owning livestock.
Women’s and Children’s Nutrition
26% of women of reproductive age (18–49) reported having a diet of minimum diversity.
26% of children aged 6–23 months had a diet of minimum diversity.
8% of children 6–23 months had a minimum acceptable diet.
Access to Cash Resources
7% of women and 26% of men in union reported earning cash.
67% of women in unions report that their opinion is always heard in decisions about major purchases.
Household Food Access and Security
The mean food consumption score (FCS) was 40.40.
88% of households had moderate or severe food insecurity, based on the Food Insecurity Experience 
Scale (FIES).
Resilience
Households reported a mean ability to recover index of 3.27 (range of 2–6).
2
Households had a mean adaptive capacity of 40.48 (0–100).
3
Households had a mean transformative capacity index of 40.77 (0–100).
4
Collective Action and Government Support
35% of households reported that they had worked with others in their village to do something for the 
community’s benefiting.
51% of households report having a government or NGO program in their village.
 
1 In these areas (communal lands), land ownership means that the local authority has given the respondent access rights. All 
land is held by the government, and local leaders can assign limited property rights (i.e., the ability to derive income from land) 
but cannot grant the right to sell the land.
2 The Ability to Recover from Shocks and Stresses Index is an estimation of the ability of households to recover from the typical 
types of shocks and stressors that occur in the activity areas, such as loss of a family member, loss of income, hunger, drought, 
flood, conflict, or similar events. The Index is based on data regarding recovery from the shocks and stressors households 
experienced in the year before the survey and their perceived ability to meet food needs the following year. 3 The adaptive capacity index measures the ability of households to manage resources and make proactive and informed 
choices to better prepare for and adapt to future shocks. The Index is constructed from ten indicators and indices. 4 Transformative capacity involves system-level resources, governance, and institutions that comprise the enabling 
environment that promote or limit households’ capacity to respond to shocks and stressors. The index is constructed from 
fifteen indicators and indices. 
Baseline Evaluation of the Amalima Loko RFSA in Zimbabwe (Vol. I)
Baseline Household Survey 1
1. BASELINE HOUSEHOLD SURVEY
1.1 Objective
The primary objectives of the baseline household survey are: (1) to gain a better understanding of 
prevailing conditions and perceptions of the study population, (2) to guide the criteria used in the Quasi￾Experimental (QE) design, and (3) to improve the precision of our impact estimates. Innovations for 
Poverty Action (IPA) will conduct the midline survey 12 months after implementation of the activity 
begins to test differences between households in treatment and control areas. Then, IPA will administer 
an endline survey 36 months after completion of the baseline.
1.2 Questionnaire
IPA developed the baseline questionnaire in consultation with Cultivating New Frontiers in Agriculture
(CNFA), the United States Agency for International Development (USAID) Bureau for Humanitarian 
Assistance (BHA), and Save the Children over the period September 2021 to January 2022. Multiple 
consultations took place to determine which BHA indicators were pertinent, and IPA only included
indicators deemed relevant to inform activity implementation in the baseline survey. Anthropometric 
indicators were initially proposed but eventually left out to optimize budget resources.
The questionnaire included the following modules:
• Household roster and demographics
• Poverty and consumption
• Water, sanitation, and hygiene (WASH)
• Housing and assets ownership
• Land usage, crop cultivation, and agricultural practices
• Livestock holdings
• Women’s health, nutritional status, dietary diversity, and family planning
• Child nutrition
• Gender (cash-focused)
• Cash for assets
• Household food access and security
• Resilience
• Collective action and government support
• Women’s empowerment
• Income sources
• Financial health
• Savings and loans
• Perceived economic ladder
• Mental health
• Self-control
IMPEL | Implementer-Led Evaluation and Learning
2 Baseline Household Survey
• Gender access to credit and group participation
• Family planning
Some of the more in-depth modules were administered to a subsample of households to reduce cost 
and respondent fatigue. The results subsections indicate the number of households that were 
administered specific modules. Not all modules’ indicators are included in this report.
1.3 Sampling
CNFA originally targeted 87 communal wards5 in Binga, Hwange, Lupane, Nkayi, and Tsholotsho districts. 
At the time of writing, five additional wards were under consideration for being added to the activity. Of 
these original 87 wards, 45 were eventually chosen for the baseline survey, covering four districts 
(Binga, Hwange, Lupane, and Nkayi) of the activity. The wards were selected because they belong to 
CNFA’s Phase II sample. These are areas that are downstream of Phase 1 wards. Activity implementation 
had already begun in the Phase 1 wards when the baseline survey was undertaken, while activities in the 
Phase 2 wards were set to occur within the following year.
The actual participating households were selected randomly using the random walk technique. In this 
case, the starting point was identified as a central location within the community, which could be a 
market, a church, a health facility, or the junction between two roads. After that, the following steps 
were taken to select the households to include in the baseline survey:
1. The household nearest to the starting point was the first to be included. 
2. The field officer selected which direction to take by spinning a bottle or flipping a coin (for 
reference and a detailed plan, see the field manual in Annex C). 
3. Following a road or path, the field worker identified the next households. The fieldworker 
followed paths connecting to the main road to try and reach out even to those houses away 
from the road (For reference and detailed plan, see the field manual in Annex C).
4. For densely populated villages, enumerators approach every eighth household; for sparser 
villages, they approach every fourth or fifth household.
5. The fieldworker stopped whenever they reached the target number of households for the 
village.
Training for the baseline ran from April 7 until April 15, 2022. The baseline survey was piloted from April 
25–April 28, 2022. A total of 510 households were targeted out of 51 villages. To minimize the burden 
on respondents, we randomly selected 50% to complete the modules on women's health, nutritional 
status, dietary diversity, and family planning (Module E). We then independently sampled 50% to 
complete the gender (cash), resilience, and agriculture modules. In some cases, the number of 
respondents is less than half the total sample size because of other restrictions in the module. The 
smaller sample size overall (510) was intentionally chosen due to the QE research design, which is 
discussed in more depth in Section 1.4. In the context of this specific QE design, the baseline is not being 
used to compare treatment effects but rather to inform the QE choices made during the midline and 
endline surveys.
 5 Communal wards are contrasted with the other ward types, urban, national parks, forest conservation areas, private safari 
concessions, commercial farming, mining areas, or contested lands).
Baseline Evaluation of the Amalima Loko RFSA in Zimbabwe (Vol. I)
Baseline Household Survey 3 
Some indicators target respondents aged 15 and above, but IPA did not have Internal Review Board
approval to survey people under 18; thus, our indicators are truncated to be from 18 and above. This is 
particularly relevant for indicators BL11, BL13, and BL32.
Figure 1. Amalima Loko wards
1.4 Field Activities
Field data collection started on April 29 for Amalima Loko and was completed on May 21, 2022. A total 
of 511 respondents of the targeted 510 surveys had been completed and uploaded by May 21, 2022. Of 
these, 211 cases (41%) had opened the Resilience module, while 254 had opened the Gender module. 
All districts met their allotted sample sizes. Nkayi and Binga had the largest sample sizes at 180 and 170, 
respectively, while Lupane had 131 households reached and Hwange 30.
Table 2. Sample overview
Province District # of Surveys
Matabeleland
Binga 170
Hwange 30
Lupane 131
Nkayi 180
The average number of households surveyed per day decreased from 24.3 to 22.2 between the first and 
second weeks and the third and fourth weeks. This was primarily due to difficulties accessing 
households, particularly in the last 2 days in Lupane, which substantially lowered the mean. 
IMPEL | Implementer-Led Evaluation and Learning
4 Baseline Household Survey
Table 3. Enumerators' productivity
Productivity
Start date in Washington, District of Columbia: April 29, 2022
End day of field work: May 22, 2022
Total enumerators 10
Number of days in the field: 23
Average per Day
Average per day – Completed surveys 22.2
Average per day per enumerator – Completed surveys 2.2
Average per day per enumerator – Incomplete surveys (found but partially
interviewed) 0 
A total of 516 households were approached, and interviews were secured with 511 (99% response rate). 
Five surveys were incomplete due to respondents not being found. All 511 respondents gave informed 
consent to participate in the household survey and to record their homestead’s Global Positioning 
System (GPS) coordinates. 
Surveys were administered on a tablet using SurveyCTO. Short audio recordings were collected only for 
quality control purposes. If respondents declined to be recorded, interviews were completed without 
recording. Five of the 511 respondents surveyed refused to give consent for audio recording. 
1.5 Limitations and Challenges
Availability of respondents due to competing schedules: The harvesting season had started when 
survey fieldwork began, and the local chiefs had set a date when free-range grazing of livestock would 
start. As a result, farmers were frantically harvesting their crops to ensure they met the deadline, 
resulting in challenges in securing interviews. As a result, five households could not be found and had to 
be replaced.
Baseline Evaluation of the Amalima Loko RFSA in Zimbabwe (Vol. I)
Results 5 
2. RESULTS
The following sections describe baseline findings for several key indicators, focused on several 
traditional areas: (1) poverty, consumption, and asset indicators; (2) WASH; (3) child and female adult 
nutrition; (4) land, cultivation, and livestock; (5) nutrition and food security; and (6) collective action and 
government support. Where applicable, IPA collected data on a sub-sample of the overall sample size. 
These choices on sub-sample were made to reduce respondent fatigue and keep the overall survey 
budgets manageable. We have included additional details about the sub-sampling in each section below.
2.1 Household Demographics
Table 4. Household demographics
Description Mean Confidence 
Interval (CI) Lower CI Upper Number (N) 
Sampled
Female household head 40% 36% 44% 511
Household head age 52.73 51.35 54.11 511
Household head married or living together 73% 69% 77% 511
Household head level of education
No formal schooling 11% 8% 14% 511
Some primary schooling 28% 24% 32% 511
Primary school completed 24% 21% 28% 511
Some secondary school 23% 19% 26% 511
Secondary school completed 13% 10% 15% 511
Household head occupation
Farmer 46% 41% 50% 511
Unemployed 30% 26% 34% 511
Notes: Confidence intervals for binary indicators are based on Normal approximations; for very small samples and indicator 
values near 0 or 1, these confidence intervals can exceed 0 or 1, and in this table, confidence interval bounds are censored at 0 
from below, and 1 from above.
2.2 Poverty Indicators
Three consumption-based indicators are used to assess the extent of poverty in the sample: (1) daily per 
capita consumption expenditures; (2) percentage of people living below $1.90 per day, expressed at 
2011 dollars inflated to 2022 levels and (3) the mean percentage shortfall of the poor relative to the 
$1.90/day 2011 poverty line. The baseline indicates that the target communities are quite poor, with 
84% of households falling below the poverty line of $1.90.
IMPEL | Implementer-Led Evaluation and Learning
6 Results
Table 5. Poverty level
Description Mean CI Lower CI Upper N
[BL40] Consumption per capita per day, United States Dollar (USD) 1.29 1.17 1.40 511
Female and male adults 1.26 1.14 1.39 414
Adult female no adult male 1.26 1.04 1.47 88
[BL01] Prevalence of Poverty, less than $1.90 per day 84% 81% 87% 511
Female and male adults 85% 81% 88% 414
Adult female no adult male 85% 78% 93% 88
[BL02] Depth of Poverty of the Poor: Mean percentage shortfall of 
the poor relative to the $1.90/day 0.62 0.59 0.65 429
Female and male adults 0.65 0.62 0.69 350
Adult female no adult male 0.46 0.40 0.53 75
Notes: The $1.90 threshold is inflated from 2011 to 2022 using the United States Consumer Price Index to match the year of the 
data collection. A PPP adjustment factor was not used, as the most recently available WB PPP deflator comes from 2018 before 
Zimbabwe instituted a new currency. The categories “Adult Male no Adult Female” and “Child no Adults” were omitted due to 
small sample sizes.
2.3 Water, Sanitation, and Hygiene
IPA collected household-level data on three WASH indicators: household access to a basic sanitation 
service, the type of toilet the household uses, and the main source of drinking water. Of 511 
households, 327 (64%) reported using “No facility/bush/field.” Among the 184 households that do not 
use open defecation, 134 report using an improved sanitation service, including ventilated improved pit 
latrines and flushing to a septic or sewer system. The remaining 50 households do not practice open 
defecation but do not utilize an improved system. This group primarily includes “covered pit latrine with 
slab” (41 households).
Table 6. Water, sanitation, and hygiene
Description Mean CI Lower CI Upper N
[BL27] HH with access to a basic sanitation service 26% 22% 30% 511
Female and male adults 25% 21% 29% 414
Adult female no adult male 30% 20% 39% 88
[BL19] HH that do not use sanitation facilities 64% 60% 68% 511
Female and male adults 64% 60% 69% 414
Adult female no adult male 65% 55% 75% 88
Kind of toilet the household uses:
No access 64% 60% 68% 511
Ventilated improved pit-latrine 22% 18% 26% 511
Covered pit-latrine with slab 8% 6% 10% 511
Baseline Evaluation of the Amalima Loko RFSA in Zimbabwe (Vol. I)
Results 7 
Description Mean CI Lower CI Upper N
Other 6% 4% 8% 511
Share toilet with other household 21% 15% 27% 184
Main source of drinking water:
Tube well/borehole 42% 38% 47% 511
Surface water 19% 16% 23% 511
Unprotected well 15% 12% 18% 511
Protected well 11% 8% 14% 511
Public tap/standpipe 9% 6% 11% 511
Other 4% 2% 6% 511
Notes: “Share toilet with other household” was administered only to households with any kind of toilet.
2.4 Housing Quality
Most households in the targeted area live in traditional dwellings, predominantly with earthen or sand 
floors, thatched roofs, and mud walls. Commensurate with these findings, only 6% of households have 
access to electricity, and most of those with electricity get it from a home solar system.
Table 7. Housing quality
Description Mean CI Lower CI Upper N
Household’s tenure status
Owner/purchaser without title 50% 45% 54% 511
Owner/purchaser with title 42% 37% 46% 511
Tied accommodation 7% 4% 9% 511
Other 2% 1% 3% 511
Type of dwelling
Traditional 67% 63% 71% 511
Mixed 25% 21% 29% 511
Detached 5% 3% 7% 511
Other 4% 2% 5% 511
Main material for floor
Earth/sand 64% 60% 68% 511
Cement 32% 28% 36% 511
Other 4% 2% 6% 511
Main material for roof
Thatch 65% 61% 69% 511
Metal/tin sheets 26% 22% 30% 511
IMPEL | Implementer-Led Evaluation and Learning
8 Results
Description Mean CI Lower CI Upper N
Asbestos 6% 4% 8% 511
Other 2% 1% 3% 511
Main material for walls
Mud 58% 53% 62% 511
Bricks 24% 20% 28% 511
Cement 9% 7% 12% 511
Cement blocks 7% 5% 9% 511
Other 2% 1% 4% 511
Number of rooms in the household 2.78 2.66 2.91 511
Access to electricity 6% 4% 8% 511
Sources of electricity:
Solar home system 60% 41% 79% 30
National grid 23% 7% 39% 30
Solar lantern/lighting system 17% 3% 31% 30
2.5 Assets
Most households report owning at least some land, which is consistent with the agricultural section, 
showing that over 90% of households cultivated some type of crop in the last year.
Table 8. Household assets
Description Mean CI Lower CI Upper N
Household owns:
Land (arable, industrial, residential) 88% 85% 91% 511
Cellphone 83% 80% 86% 511
Plough 56% 52% 61% 511
Goat 51% 47% 55% 511
Solar panel 48% 43% 52% 511
Cattle 45% 40% 49% 511
Hoe 37% 33% 41% 511
Radio 29% 25% 33% 511
Bicycle 28% 24% 32% 511
Scotch cart/water cart 23% 20% 27% 511
Axe 23% 19% 26% 511
Donkey 22% 19% 26% 511
Baseline Evaluation of the Amalima Loko RFSA in Zimbabwe (Vol. I)
Results 9 
Description Mean CI Lower CI Upper N
Lounge suite 18% 15% 22% 511
Wheelbarrow 16% 13% 19% 511
Knapsack sprayer 15% 12% 18% 511
Satellite dish and components 12% 9% 15% 511
Harrow 9% 6% 11% 511
Television 6% 4% 8% 511
Other 5% 3% 7% 511
2.6 Land and Agriculture
Most households have land, and an even higher percentage (93%) report cultivating anything in the last 
12 months. The dominant crops were maize and sorghum/millet, with a small number of groundnuts 
also cultivated. Notably, groundnuts are not listed as the most important crop for households.
2.6.1 Land and Crops
Table 9. Crops cultivated
Description Mean CI Lower CI Upper N
Households owns land, not including plot with home 90% 87% 92% 511
Total area of agricultural land (in acres) 16.32 0.00 1.00 459
Household cultivated anything in the last 12 months 93% 91% 95% 511
During the last rainy season, household cultivated
Maize 77% 74% 81% 474
Sorghum/millet 67% 62% 71% 474
Groundnuts 23% 19% 26% 474
Bean 9% 6% 11% 474
Cowpeas 8% 6% 10% 474
Millet 7% 5% 10% 474
Sunflower 5% 3% 8% 474
Vegetables 4% 3% 6% 474
Soybeans 4% 2% 6% 474
Other 20% 17% 24% 474
Most important crop cultivated
Maize 51% 47% 56% 474
Sorghum/millet 40% 35% 44% 474
Other 5% 3% 8% 474
IMPEL | Implementer-Led Evaluation and Learning
10 Results
Notes: Confidence intervals for binary indicators are based on Normal approximations; for very small samples and indicator 
values near 0 or 1, these confidence intervals can exceed 0 or 1, and in this table, confidence interval bounds are censored at 0 
from below, and 1 from above.
2.6.2 Agricultural Finance and Techniques
IPA also asked a subset of 211 households questions about farmers’ use of financial services. 
Additionally, IPA asked 175 households about improved management practices or technologies and 154 
more households about improved management practices on livestock.
Table 10. Agriculture
Description Mean CI Lower CI Upper N
[BL29] Percent of farmers who used financial services 
(savings, agricultural credit, and/or agricultural insurance) in 
the past 12 months
21% 16% 27% 211
Agricultural credit 0.06 0.03 0.09 211
Save any cash 0.16 0.11 0.21 211
Total savings USD 126.33 75.95 176.72 34
Agricultural insurance 0.01 0 0.02 211
Female 21% 14% 28% 125
Male 22% 13% 31% 86
[BL21] Percentage of producers who have applied targeted 
improved management practices or technologies 95% 92% 99% 175
Female 95% 91% 99% 104
Male 96% 91% 100% 71
[BL21] Improved management practices/technologies on 
livestock 78% 71% 85% 154
Female 76% 67% 85% 88
Male 80% 70% 90% 66
Notes: This section was administered to a random subsample of farmers over 18 years of age.
2.7 Livestock Holdings
Most households in the sample area reported owning some livestock: 452 out of 511. While poultry and 
goats were the most represented, a still significant percentage (66% of households that owned livestock 
or 58% of all households) reported owning cattle.
Table 11. Livestock assets in the last 12 months
Description Mean CI Lower CI Upper N
Household owned livestock 88% 86% 91% 511
Household-owned [animals]:
Poultry 90% 87% 92% 452
Baseline Evaluation of the Amalima Loko RFSA in Zimbabwe (Vol. I)
Results 11 
Description Mean CI Lower CI Upper N
Goats 73% 69% 77% 452
Cattle 66% 61% 70% 452
Donkey/mule 22% 18% 25% 452
Pigs 10% 8% 13% 452
Other 9% 6% 12% 452
2.8 Food Security
Food security is essential to well-being, and the United Nations Sustainable Development Goal (SDG) 2 
calls for the elimination of hunger by 2030. Food diversity is also important to ensure sufficient intake of 
micro-nutrients that are key for the individual development of their full potential, particularly in the first 
years of life. 
In terms of food insecurity at the household level, IPA computed two indicators, the Food Consumption 
Score (FCS) and the Food Insecurity Experience Scale (FIES).
2.8.1 Food Consumption Score
The FCS is a frequency-weighted diet diversity score, also referred to as a “food frequency indicator.” 
The FCS is calculated using the frequency of consumption (number of days) of eight food groups 
consumed by a household during the 7 days before the survey, weighted by the nutrient density of the 
food group.6
Table 12. Food Consumption Score
Description Mean CI Lower CI Upper N
[BL10] Food Consumption Score 40.40 38.59 42.20 511
[BL10] Poor Food Consumption Score (0–21) 21% 18% 25% 511
[BL10] Borderline Food Consumption Score (21.5–35) 26% 22% 29% 511
[BL10] Acceptable Food Consumption Score (> 35) 53% 49% 58% 511
Over the past 7 days, number of days household consumed
Main staples 6.25 6.08 6.41 511
Sugar 3.32 3.04 3.59 511
Fruit 3.00 2.75 3.26 511
Meat and fish 2.79 2.55 3.03 511
Oil 2.67 2.40 2.94 511
Vegetables 2.31 2.06 2.55 511
Condiments 2.09 1.83 2.34 511
 
6 WFP, Vulnerability Analysis and Mapping Branch (ODAV). (2008). Food consumption analysis—Calculation and use of the food 
consumption score in food security analysis. Rome, Italy.
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12 Results
Description Mean CI Lower CI Upper N
Milk and dairy 1.51 1.30 1.72 511
Pulses 0.80 0.65 0.95 511
2.8.2 Food Insecurity
The Food and Agricultural Organization, in consultation with global food security actors, developed the 
FIES to help mark progress toward meeting SDG 2. SDG 2 commits countries to “end hunger, achieve 
food security and improved nutrition and promote sustainable agriculture” by 2030. The FIES helps 
actors understand the severity of food insecurity in a country’s population. 
The FIES asks respondents directly about their experience of food insecurity through eight direct yes or 
no questions. These eight questions are reproduced in the annex. 
Table 13 below shows the results of the FIES module. The FIES score ranges from 0 to 8. The households 
in the sample had a mean of 5.52, putting them at fairly high levels of food insecurity. 81% of 
households report having either moderate or severe food insecurity. 
Table 13. Food Insecurity Experience Scale
Description Mean CI Lower CI Upper N
BL06: Prevalence of moderate and severe food insecurity in 
the household, based on the FIES 81% 65% 97% 511
Female and male adults 81% 65% 97% 350
Adult female no adult male 82% 65% 98% 75
Prevalence of severe food insecurity 52% 39% 65% 511
Female and male adults 51% 38% 63% 350
Adult female no adult male 59% 45% 72% 75
Raw FIES Score 5.52 5.28 5.75 511
During the last 12 months, because of a lack of money or resources, you or others in your household...
Were unable to eat healthy and nutritious food 85% 82% 88% 511
Ate only a few kinds of foods 82% 79% 86% 511
Had to skip a meal 74% 70% 78% 511
Were worried you would not have enough food to eat 71% 67% 75% 511
Ate less than you thought you should 68% 63% 72% 511
Did not have food 64% 60% 69% 511
Were hungry but did not eat 59% 54% 63% 511
Went without eating for a whole day 49% 45% 53% 511
Baseline Evaluation of the Amalima Loko RFSA in Zimbabwe (Vol. I)
Results 13 
2.8.3 Dietary Diversity
IPA administered a section on dietary diversity to determine if households in the sample had sufficiently 
nutritious diets. This section mirrors the questions on dietary diversity targeted toward women of 
reproductive age and children.
Table 14. Dietary diversity
Description Mean CI Lower CI Upper N
Household Dietary Diversity Score (HDDS) (1–12)[1] 3.62 3.46 3.77 511
Food groups consumed yesterday by any member of the household...
Cereals 68% 64% 72% 511
Oils and fats 62% 57% 66% 511
Other fruits 47% 42% 51% 511
Dark green leafy vegetables 40% 35% 44% 511
Other vegetables 36% 32% 40% 511
Milk and milk products 29% 25% 33% 511
Legumes, nuts, and seeds 23% 19% 27% 511
Vitamin A-rich fruits 16% 12% 19% 511
Flesh meats 15% 12% 18% 511
Rich vegetables and tubers 10% 8% 13% 511
Fish and seafood 10% 7% 12% 511
Eggs 9% 6% 11% 511
Eat anything OUTSIDE the home 8% 5% 10% 511
White roots and tubers 7% 4% 9% 511
Sweets 6% 4% 9% 511
Spices, condiments, beverages 6% 4% 8% 511
Organ meat 4% 2% 5% 511
Notes: HDDS is calculated by summing up consumption of 12 different food categories: vegetables (dark leafy greens, other 
vegetables or rich vegetables, and tubers), fruits (other fruits, vitamin-rich fruits), meat (flesh meats, fish, and seafood), cereals, 
tubers, eggs, fish, legumes, milk, oils, sweets, and spices.
2.9 Women and Children’s Health and Nutrition
2.9.1 Women’s Health and Diet
Women ages 18–49 years were asked whether they consumed at least five of 10 specific food groups 
during the previous day and night to evaluate the diversity of their consumption. As shown in Table 15, 
the share of women of reproductive age with a diet of minimum diversity was 26% in the targeted areas.
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14 Results
Table 15. Women’s health
Description Mean CI Lower CI Upper N
[BL11] Prevalence of women of reproductive age consuming 
a diet of minimum diversity 26% 19% 33% 148
Women of reproductive age < 19 years --- --- --- 5
Women of reproductive age +19 years 26% 19% 33% 143
Food groups consumed:
Grains, white roots, tubers, plantains 85% 79% 91% 148
Dark green leafy vegetables 51% 43% 59% 148
Other fruits 49% 41% 57% 148
Other vitamin A-rich fruits and vegetables 42% 34% 50% 148
Pulses 31% 24% 39% 148
Meat, poultry, and fish 27% 20% 34% 148
Other vegetables 26% 19% 34% 148
Dairy 18% 12% 25% 148
Nuts and seeds 11% 6% 17% 148
Eggs 9% 4% 13% 148
Notes: This section was administered to a random subsample of women between 18 and 49 years of age.
2.9.2 Children’s Health and Diet
As with women of reproductive age, IPA asked for specific information about children’s diets. Two main 
indicators were calculated, the percentage of children aged 6–23 months receiving a Minimum 
Acceptable Diet (MAD) and minimum dietary diversity. The MAD measures the percentage of children 
6–23 months who receive a minimum feeding frequency and minimum dietary diversity. IPA asked 
caregivers about the liquid and solid types of food consumed by these children in the day and night 
preceding the survey. The minimum dietary diversity indicator is calculated similarly to the indicator for 
women of reproductive age, this time calculated as the share of children who consumed 5 of 8 different 
food groups during the previous day and night.
In the targeted area, only 8% of children were deemed to have reached a MAD, while 25% had a diet of 
minimum diversity, which is comparable to that of reproductive-age women interviewed in the targeted 
area.
Table 16. Small children: diet and health
Description Mean CI Lower CI Upper N
[BL13] Prevalence of exclusive breastfeeding of children 
under 6 months 66% 48% 83% 32
[BL12] Percentage of children 6–23 months receiving a MAD 8% 2% 14% 84
Female 8% 0% 16% 39
Baseline Evaluation of the Amalima Loko RFSA in Zimbabwe (Vol. I)
Results 15 
Description Mean CI Lower CI Upper N
Male 9% 0% 18% 45
Minimum dietary diversity
Breastfed 26% 15% 38% 61
Non-breastfed --- --- --- 23
Minimum meal frequency
Breastfed 41% 28% 54% 61
Non-breastfed --- --- --- 23
[BL39] Prevalence of children 6–23 months consuming a diet 
of minimum diversity 25% 16% 34% 84
Female 28% 13% 43% 39
Male 22% 10% 35% 45
Foods group consumed:
Breast milk 89% 83% 96% 84
Other fruits and vegetables 73% 63% 82% 84
Eggs 60% 49% 70% 84
Vitamin-A-rich fruits and vegetables 39% 29% 50% 84
Dairy products 32% 22% 42% 84
Grains, roots, and tubers 31% 21% 41% 84
Legumes and nuts 19% 10% 28% 84
Flesh foods 7% 2% 13% 84
2.9.3 Family Planning
IPA administered questions about family planning methods to all women of reproductive age currently 
in a union, totaling 111 women. The survey showed high levels of knowledge about contraceptive 
practices, but only 63% of the respondents reported making decisions about contraceptive usage in the 
past 12 months. A further sub-sample of respondents of reproductive age but not currently pregnant 
were asked about their current contraceptive use. 71% of these women reported currently using some 
sort of modern contraceptive.
Table 17. Family planning
Description Mean CI Lower CI Upper N
[BL36] Knowledge of modern family planning methods 95% 90% 99% 111
Knowledge of modern family planning methods score (1–13) 6.87 6.4 7.35 111
Modern family planning method:
Contraceptive pill 96% 93% 100% 111
Male condom 90% 84% 96% 111
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16 Results
Description Mean CI Lower CI Upper N
Injectables 86% 80% 93% 111
Female condom 84% 77% 91% 111
Implants 69% 61% 78% 111
Standard days method 59% 49% 68% 111
Intrauterine device (IUD) 56% 46% 65% 111
Lactational Amenorrhea Method 48% 38% 57% 111
Female sterilization 41% 32% 51% 111
Emergency contraception 27% 19% 35% 111
Male sterilization 18% 11% 25% 111
Diaphragm with spermicidal foam, cream, or gel 7% 2% 12% 111
Other modern methods 5% 1% 10% 111
[BL37] Percentage of women in a union who made decisions 
about modern family planning methods in the past 12 months 63% 54% 72% 111
Partner used modern contraceptive method in past 12 months 76% 68% 84% 111
Usually makes the decision whether or not to use 
contraceptive methods:
Respondent 44% 33% 55% 84
Respondent jointly with husband/partner 39% 29% 50% 84
Husband/partner 17% 9% 25% 84
Non-pregnant women 95% 90% 99% 111
[BL20] Contraceptive prevalence rate 71% 63% 80% 105
Women using any method to delay or avoid getting pregnant 71% 63% 80% 105
Method used:
Contraceptive pill 41% 30% 53% 75
Injectables 27% 16% 37% 75
Implants 21% 12% 31% 75
Other 11% 4% 18% 75
Notes: This section was administered to each woman in union aged 18 to 49 years. The indicator [BL20] Contraceptive 
Prevalence Rate was administered to non-pregnant women.
2.10 Gender
Questions about cash earnings and decisions about cash spending were administered to both male and 
female adults in the responding households. A total of 445 women were asked about cash decisions, 
while 401 men were also asked. A total of 333 married women were then interviewed about household
purchasing decisions, with a majority (67%) reporting that the wife’s opinion is always heard when 
deciding what to buy. 
Baseline Evaluation of the Amalima Loko RFSA in Zimbabwe (Vol. I)
Results 17 
Table 18. Women empowerment
Description Mean CI Lower CI Upper N
[BL32] Percentage of women and men in a union who 
earned cash in the past 12 months 16% 13% 18% 846
Female 7% 4% 9% 445
18–29 years old 9% 4% 14% 128
30–49 years old 6% 2% 9% 194
> 49 years old 7% 2% 11% 123
Male 26% 22% 30% 401
18–29 years old 23% 13% 34% 64
30–49 years old 40% 32% 47% 163
> 49 years old 14% 9% 19% 174
When the household makes a major purchase, the wife's opinion is heard in deciding what to buy
Never 3% 1% 5% 333
Very rarely 1% 0% 2% 333
Rarely 4% 2% 6% 333
Yes, sometimes 14% 10% 18% 333
Yes, usually 10% 6% 13% 333
Yes, always 67% 62% 72% 333
Wife has to ask other household members for permission to buy clothes for her
No 47% 41% 52% 333
Yes 51% 45% 56% 333
Have never bought 2% 1% 4% 333
Wife is allowed to buy things in the market without asking permission:
Never 7% 4% 10% 333
Very rarely 11% 7% 14% 333
Rarely 3% 1% 5% 333
Yes, sometimes 13% 9% 17% 333
Yes, usually 9% 6% 12% 333
Yes, always 51% 45% 56% 333
Wife is allowed to visit women from other villages to talk to them without asking permission:
Never 10% 7% 13% 333
Yes, but never alone 7% 4% 10% 333
Yes, alone, with permission 46% 41% 52% 333
Yes, alone, do not need permission 33% 28% 38% 333
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18 Results
Notes: This section was administered to each married woman over 18 years of age. Confidence intervals for binary indicators are 
based on Normal approximations; for very small samples and indicator values near 0 or 1, these confidence intervals can exceed 
0 or 1, and in this table, confidence interval bounds are censored at 0 from below and 1 from above.
2.11 Resilience and Mental Health
The resilience module of the baseline survey focuses on households' ability to recover from shocks. The 
ability to recover index is the combination of two questions about the households’ ability to recover 
from last year’s shocks and expectations about their recovery from next year’s shocks:
● “To what extent has your ability to meet food needs returned to the level it was before the 
shocks and stressors you experienced in the last 12 months?” with possible responses and 
weighted values: 
o Ability to meet food needs is the same as before the shocks (= value of 2) 
o Ability to meet food needs is better than before the shocks (= value of 3) 
o Ability to meet food needs is worse than before the shocks (= value of 1) 
● “In light of the shocks you faced in the last 12 months, to what extent do you believe you will be 
able to meet your food needs in the next year?” with possible responses and weighted values: 
o Ability to meet food needs will be the same as before the shocks (= value of 2) 
o Ability to meet food needs will be better than before the shocks (= value of 3) 
o Ability to meet food needs will be worse than before the shocks (= value of 1) 
The aggregate index ranges from 2 to 6, with 6 indicating a high level of resilience. The respondents 
reported an average of 3.27, implying that their aggregate ability to respond to shocks is slightly worse 
than it was before the shock occurred. Additionally, IPA collected data on the: 
1. Adaptive capacity index, the ability of households to plan for future shocks; 
2. Absorptive capacity index, which captures the ability to plan for shocks that affect well-being 
outcomes; and 
3. Transformative capacity index, which captures system-level capacities to respond to shocks.
Finally, the resilience module also asked all households if they engage in savings groups or micro-finance 
programs, with a yes rate of only 3%.
Table 19. Resilience
Description Mean CI Lower CI Upper N
[BL23] Ability to recover index (2–6) 3.27 3.07 3.47 207
Female and male adults 3.23 3.01 3.45 173
Adult female no adult male 3.43 2.91 3.96 30
[BL24] Household that believes local government will 
respond effectively to future shock 60% 54% 67% 211
Female and male adults 63% 56% 70% 175
Adult female no adult male 47% 29% 65% 32
[BL31] Household participates in group-based savings, 
micro-finance, or lending programs 3% 1% 4% 511
Baseline Evaluation of the Amalima Loko RFSA in Zimbabwe (Vol. I)
Results 19 
Description Mean CI Lower CI Upper N
Female and male adults 3% 1% 5% 414
Adult female no adult male 1% 0% 3% 88
[BL08] Adaptive capacity index (0–100) 32.74 29.38 36.10 112
[BL09] Absorptive capacity index (0–100) 40.48 36.55 44.41 160
[BL25] Transformative capacity index (0–100) 40.77 37.87 43.67 160
[BL38] Index of social capital (0–6) 2.18 2.00 2.37 211
Index for bridging social capital (0–6) 2.01 1.81 2.21 211
Bonding Social Capital Index (0–6) 2.36 2.16 2.57 211
Notes: This section was administered to a random subsample of respondents.
IPA asked a series of questions about generalized mental health. The Kessler Psychological Distress Scale 
(K6) is a series of six questions with five values, ranging from “none of the time” (0) to “all of the time” 
(4). It is used as a quick assessment of physiological distress. The baseline results show a reasonable 
level of the K6 scale, but a high percentage of respondents reported feeling that “everything was 
difficult” all the time. Similarly, most respondents reported having a period in the last 30 days when they 
felt worried, tense, or anxious. Unsurprisingly, respondents reported that their major concern is food 
shortage.
Table 20. Mental health in the last 12 months
Description Mean CI Lower CI Upper N
Kessler 6 (0–24) 8.45 7.87 9.02 511
Respondent felt ... all or most of the time
That everything was difficult 37% 33% 41% 511
Restless or fidgety 25% 21% 29% 511
So depressed that nothing could cheer you up 23% 19% 26% 511
Worthless 23% 19% 26% 511
Hopeless 23% 19% 26% 511
Nervous 17% 14% 20% 511
Had a period lasting 30 days or longer when felt worried, 
tense, or anxious most of the time 57% 52% 61% 511
Ended 18% 14% 22% 289
Still going on 62% 57% 68% 289
Still going on, but reduced 20% 15% 24% 289
These worries interfered with their ability to carry out normal activities
A lot 65% 60% 71% 289
Some 10% 7% 14% 289
A little 17% 12% 21% 289
Not at all 8% 5% 11% 289
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20 Results
Description Mean CI Lower CI Upper N
Issues that sometimes are reasons for concern:
Food shortage 48% 44% 52% 511
Health 29% 25% 33% 511
Living situation 24% 21% 28% 511
Children's education 23% 19% 26% 511
Financial constraints 19% 15% 22% 511
Nothing 17% 13% 20% 511
Clothing 11% 9% 14% 511
Domestic issues 9% 7% 12% 511
Employment 9% 6% 11% 511
Other 10% 7% 12% 511
2.12 Savings and Loans
IPA administered modules on savings and loans of all 511 households in the sample communities. This 
section covers loans not associated with village savings and loans or group-based savings but rather 
interactions with more formal lending institutions.
The module on savings shows a low rate of savings among households, with only 35% of households 
reporting keeping any savings in the past month, and of those that save, only a small percentage stored 
money outside the home, either with a financial institution or trusted individual.
Table 21. Savings
Description Mean CI Lower CI Upper N
Has kept any savings in the past 6 months
No savings 65% 60% 69% 511
In your pocket/clothes/bag that you carry 13% 10% 15% 511
A secret place in your home 11% 9% 14% 511
Village Savings and Loans Association 9% 6% 11% 511
Box in the household 5% 3% 6% 511
Savings groups, including Savings and Credit Cooperative 
Organization, unions 3% 1% 4% 511
Mobile money 3% 1% 4% 511
With family members outside the household 1% 0% 2% 511
Commercial bank 1% 0% 2% 511
With a friend 0% 0% 1% 511
With a shopkeeper 0% 0% 1% 511
With a neighbor 0% 0% 0% 511
Baseline Evaluation of the Amalima Loko RFSA in Zimbabwe (Vol. I)
Results 21 
Notes: Confidence intervals for binary indicators are based on Normal approximations; for very small samples and indicator 
values near 0 or 1, these confidence intervals can exceed 0 or 1, and in this table, confidence interval bounds are censored at 0 
from below, and 1 from above.
Similarly to savings, IPA found that only a small percentage of households reported getting a loan (4%). 
Among those that had loans in the past 12 months, the average amount was around $49.
Table 22. Loans
Description Mean CI Lower CI Upper N
In the last 12 months, obtained loans from:
Microfinance institution 2% 1% 3% 511
Savings and Credit Cooperative Organization 1% 0% 2% 511
Banks 0% 0% 1% 511
None 96% 95% 98% 511
Total loan (USD) 49.20 24.00 74.40 19
Household members regularly save cash 24% 20% 27% 503
Notes: Confidence intervals for binary indicators are based on Normal approximations; for very small samples and indicator 
values near 0 or 1, these confidence intervals can exceed 0 or 1, and in this table, confidence interval bounds are censored at 0 
from below, and 1 from above.
2.13 Collective Action and Government Support 
As part of the resilience module in the baseline survey, a random sub-sample of households was asked 
questions relating to collective action, i.e., the experiences they have had of community members 
working together to solve a local problem.
One of the main components of the Amalima Loko activity combines community visioning with greater 
local control of resources, and in particular, improvement and care of watershed resources. 35% of 
respondents report having engaged in a community project to improve their village.
Table 23. Collective action
Description Mean CI Lower CI Upper N
Household that has worked with others in their village to do 
something for the benefit of the community
35% 28% 41% 211
Activities:
Repaired/built schools 29% 18% 39% 73
Repaired/built health posts or centers 18% 9% 27% 73
Improved community access to drinking water 15% 7% 23% 73
Area enclosure, sow grasses, manage pasture 11% 4% 18% 73
Road maintenance/construction 8% 2% 15% 73
Repaired/built communal irrigation system 7% 1% 13% 73
Formed a cooperative 5% 0% 11% 73
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22 Results
Description Mean CI Lower CI Upper N
Soil conservation 5% 0% 11% 73
Water harvesting at the household level 3% 0% 7% 73
Planted trees on communal land 1% 0% 4% 73
Flood diversion activities 1% 0% 4% 73
Other (specify) 15% 7% 23% 73
Notes: Soil conservation includes: terracing, bunds, half-moons, and gabions. This section was administered to a random 
subsample of respondents. Confidence intervals for binary indicators are based on Normal approximations; for very small 
samples and indicator values near 0 or 1, these confidence intervals can exceed 0 or 1, and in this table, confidence interval 
bounds are censored at 0 from below and 1 from above.
As part of the resilience module in the baseline survey, a random subsample of households was asked 
about access to government or non-governmental organization (NGO) programs in their village. 
Approximately half of the 211 households interviewed said a government or NGO program existed in 
their village.
Table 24. Government support
Description Mean CI Lower CI Upper N
Any government or NGO programs in the village 51% 44% 58% 211
Types of programming:
Food/cash transfers 59% 49% 68% 107
Agricultural inputs (seeds, fertilizer) 38% 29% 48% 107
Educational assistance 25% 17% 34% 107
Livestock inputs (feed, fodder, medicine) 7% 2% 11% 107
WASH 6% 1% 10% 107
Child malnutrition/infant feeding 2% 0% 4% 107
Disaster planning/response 1% 0% 3% 107
Other (specify) 3% 0% 6% 107
HH received any government or NGO assistance 50% 43% 57% 211
Type of assistance:
Food/cash transfers 77% 69% 85% 105
Agricultural inputs (seeds, fertilizer) 30% 21% 38% 105
Educational assistance 10% 4% 15% 105
Livestock inputs (feed, fodder, medicine) 2% 0% 5% 105
There is an emergency plan for livestock off-take if a drought 
hits 5% 2% 8% 211
There is an active Peace Committee in the village 46% 39% 53% 211
There is an active Area Land Committee in the village 37% 30% 44% 211
Baseline Evaluation of the Amalima Loko RFSA in Zimbabwe (Vol. I)
Results 23 
Description Mean CI Lower CI Upper N
The village has a security or police force 66% 60% 73% 211
Nearest security/police force:
Community members 81% 74% 87% 140
National government 9% 4% 14% 140
District government 5% 1% 9% 140
Local militia 1% 0% 3% 140
Sub county government 1% 0% 2% 140
Other 3% 0% 6% 140
Distance to the nearest police station
Over one hour 53% 45% 62% 135
About one hour 24% 16% 31% 135
Half an hour 16% 10% 23% 135
Minutes 7% 2% 11% 135
Notes: This section was administered to a random subsample of respondents. Confidence intervals for binary indicators are 
based on Normal approximations; for very small samples and indicator values near 0 or 1, these confidence intervals can exceed 
0 or 1, and in this table, confidence interval bounds are censored at 0 from below and 1 from above. Security or police forces 
include both formal (with a police station) and informal (i.e., local community members).
IMPEL | Implementer-Led Evaluation and Learning
24 Next Steps
3. NEXT STEPS
3.1 Preparation for Outcome Monitoring Survey
A midline survey will take place 1 year after the baseline survey. The midline survey aims to interview 
2,250 households evenly split between treated and untreated areas. Currently, Amalima Loko is being 
implemented in 87 of the 125 wards that comprise the five activity area districts. CNFA proposes
expanding into five more adjacent wards, bringing the total of treated wards to 92, potentially leaving 
33 comparison wards. However, most of these wards are not communal wards, and among the 
untreated communal wards, most are located in the Tsholotsho district, which has received less 
attention due to only a few wards being part of the Gwayi sub-catchment. IPA is currently determining 
the suitability of locating control wards outside the Gwayi catchment area.
An endline survey will be conducted 2 years after the midline survey (3 years after the baseline). The 
midline survey will catalog a sufficiently exhaustive breadth of variables to allow for robust propensity 
score matching between treatment and control households. This information will be used to refine the 
sample in the endline: of the 2,250 randomly selected households at the midline, 1,500 high-propensity 
households will be re-interviewed at endline. In the next section, we will explain how this propensity 
score methodology works and how it will be applied here. 
3.2 Devise Criteria for Propensity Score Matching 
IPA will use propensity score matching to compare outcomes measured at follow-up surveys between 
households in the intervention areas to those in the comparison areas. The matching approach 
compares the difference in weighted average outcomes at the endline between treated and untreated 
households. The weights flexibly control for pre-intervention observables captured during the baseline 
survey. In the first stage, IPA will estimate the propensity to select for the intervention, modeling the 
selection as 𝐷𝐷𝑖𝑖 = 𝛾𝛾𝑋𝑋𝑖𝑖 + 𝜇𝜇𝑖𝑖 for household 𝑖𝑖 in intervention areas (only), where 𝐷𝐷𝑖𝑖 is an indicator of
intervention participation, 𝑋𝑋𝑖𝑖 is a vector of pre-intervention household characteristics (collected at 
baseline) that predicts intervention participation. In the second step, IPA will predict 𝐷𝐷𝑖𝑖 in the 
intervention and comparison areas—this prediction is the propensity score. Lastly, IPA will match 
intervention area households to comparison area households on the propensity score (potentially after 
first enforcing common support conditions).
Baseline Evaluation of the Amalima Loko RFSA in Zimbabwe (Vol. I)
Annex A: Additional Tables 25 
ANNEX A: ADDITIONAL TABLES
Table 25. Improved management practices and technologies for crop
Description Mean CI Lower CI Upper N
[BL21] Applied targeted improved management practices or 
technologies on crops (A, B, or C below) 95% 92% 99% 175
A. Has applied any improved management practices 91% 87% 95% 175
Type of improved management practices or technology used:
Cultural practices7 85% 79% 90% 175
Crop genetics 21% 15% 27% 175
Irrigation 8% 4% 12% 175
Agriculture water management—non-irrigation-based 6% 2% 9% 175
Pest and disease management 6% 2% 9% 175
Natural resource or ecosystem management 4% 1% 7% 175
Post-harvest handling and storage 3% 0% 5% 175
Soil-related fertility and conservation 3% 0% 5% 175
Livestock management 2% 0% 4% 175
Climate mitigation 2% 0% 4% 175
Climate adaptation/climate risk management 1% 0% 2% 175
Marketing and distribution 1% 0% 2% 175
Value-added processing 1% 0% 2% 175
Other 1% 0% 2% 175
None 20% 14% 26% 175
B. Has applied any improved storage practices 45% 47% 62% 175
Type of improved storage practices used:
Sealed/air-tight bags 41% 34% 49% 175
Post-harvest practices that reduce pre-storage losses 15% 10% 20% 175
Locally made storage structures 11% 7% 16% 175
Grain treatment with agro-chemicals 6% 2% 9% 175
Community storage facilities 5% 1% 8% 175
Seed or grain treatment techniques 5% 1% 8% 175
None 55% 47% 62% 175
C. Has applied any natural resource management practices 43% 36% 51% 175
Type of natural resource management practices used:
 
7 Cultural practices in this study refers to crop rotation, intercropping, mulching, and weeding.
IMPEL | Implementer-Led Evaluation and Learning
26 Annex A: Additional Tables
Description Mean CI Lower CI Upper N
Area enclosure 27% 20% 33% 175
Land conservation, restoration, and protection 12% 7% 17% 175
Agriculture on-farm practices 12% 7% 17% 175
Water extraction technologies 9% 4% 13% 175
Flood diversion 3% 1% 6% 175
Water harvesting at the household-level 2% 0% 5% 175
Planting trees 1% 0% 3% 175
Improving access to drinking water 1% 0% 3% 175
Other 1% 0% 2% 175
None 57% 49% 64% 175
Notes: This section was administered to a random subsample of farmers over 18 years of age. Confidence intervals for binary 
indicators are based on Normal approximations; for very small samples and indicator values near 0 or 1, these confidence 
intervals can exceed 0 or 1, and in this table, confidence interval bounds are censored at 0 from below and 1 from above.
Table 26. Improved management practices and technologies for livestock
Description Mean CI Lower CI Upper N
[BL21] Improved management practices/technologies on 
livestock (A or B below) 78% 71% 85% 154
A. Has applied any practices when caring for the livestock 66% 58% 73% 154
Type of livestock practices used:
Vaccinations 47% 39% 55% 154
Castration 21% 15% 28% 154
Homemade animal feeds made of locally available 
products 21% 14% 27% 154
Deworming 18% 11% 24% 154
Dehorning 14% 9% 20% 154
Services of community animal health workers/para-vets 8% 4% 13% 154
Services of a government animal health extension worker 8% 4% 12% 154
Improved shelters 5% 2% 9% 154
Pen feeding 4% 1% 7% 154
Services of community animal health extension worker 3% 0% 5% 154
Fodder production, veld reinforcement with legumes 3% 0% 5% 154
Periodic replacement of male breeding stock 2% 0% 4% 154
Animal feed supplied by stock feed manufacturer 1% 0% 3% 154
None 34% 27% 42% 154
Baseline Evaluation of the Amalima Loko RFSA in Zimbabwe (Vol. I)
Annex A: Additional Tables 27 
Description Mean CI Lower CI Upper N
B. Has applied any natural resource management
practices 44% 36% 52% 154
Type of natural resource management practices used:
Area enclosure 27% 20% 34% 154
Agriculture on-farm practices 15% 9% 21% 154
Land conservation, restoration, and protection 14% 8% 19% 154
Water extraction technologies 10% 5% 14% 154
Flood diversion 4% 1% 7% 154
Water harvesting at the household-level 3% 0% 6% 154
Planting trees 2% 0% 4% 154
Improving access to drinking water 1% 0% 2% 154
Other 1% 0% 2% 154
None 56% 48% 64% 154
Notes: This section was administered to a random subsample of farmers over 18 years of age. Confidence intervals for binary 
indicators are based on Normal approximations; for very small samples and indicator values near 0 or 1, these confidence 
intervals can exceed 0 or 1, and in this table, confidence interval bounds are censored at 0 from below and 1 from above.
FIES index questions:
“During the last 12 months, was there a time when...”
1. You were worried you would not have enough food to eat because of a lack of money or 
other resources?
2. Were you unable to eat healthy and nutritious food because of a lack of money or other 
resources? 
3. You ate only a few kinds of foods because of a lack of money or other resources?
4. You had to skip a meal because there was not enough money or other resources to get 
food?
5. You ate less than you thought you should because of a lack of money or other resources?
6. Your household ran out of food because of a lack of money or other resources? 
7. You were hungry but did not eat because there was not enough money or other 
resources for food?
8. You went without eating for a whole day because of a lack of money or other resources?
Table 27. Activity wards in the Hwange district
Ward no. Ward name Population Households Covered by AL
2 Chidobe 4,153 1,012 Covered
3 Kachecheti 4,018 959 Covered
4 Nemananga 3,278 742 Covered
5 Chikandakubi 2,025 494 Covered
IMPEL | Implementer-Led Evaluation and Learning
28 Annex A: Additional Tables
Ward no. Ward name Population Households Covered by AL
6 Mbizha 2,864 706 Covered
7 Jambezi 3,514 818 Covered
8 Sidinda 1,681 412 Covered
9 Mashala 1,498 373 Proposal additional
10 Simangani 4,474 1,083 Covered
12 Nekabandama 2,141 496 Covered
13 Nekatambe 593 128 Covered
14 Makwandara 3,825 826 Proposal additional
15 Silewu 4,016 895 Proposal additional
16 Lupote 3,454 723 Proposal additional
17 Mabale 3,142 677 Proposal additional
20 Change 4,959 1,139 Covered
Total 49,635 11,483
Non-communal wards
1 Matetsi 4,105 914 Not covered
11 Kamative 2,954 723 Not covered
18 Dete 3,315 1,121 Not covered
19 Chinamatila 828 293 Not covered
Total 11,202 3,051
Table 28. Activity wards in the Lupane district
Ward no. Ward name Population Households Covered by AL
1 Dongamuzi 2,747 537 Covered
2 Matshokotsha 1,845 393 Covered
3 Dandanda 4,550 892 Covered
4 Mzola East 2,433 472 Covered
5 Sibombo 4,400 824 Covered
6 Lusulu 2,931 508 Covered
7 Ndimimbili 2,001 357 Covered
8 Sobendle 3,813 703 Covered
9 Tshongokwe 2,791 536 Covered
10 Lupaka 5,171 894 Covered
11 Pupu 4,854 838 Covered
Baseline Evaluation of the Amalima Loko RFSA in Zimbabwe (Vol. I)
Annex A: Additional Tables 29 
Ward no. Ward name Population Households Covered by AL
12 Gomoza 3,888 743 Covered
13 Jotsholo 4,103 872 Covered
14 Menyezwa 3,217 643 Covered
15 Matshiya 5,798 1,380 Covered
16 St Paul’s 3,978 738 Covered
17 Malunku 3,976 694 Covered
18 Gwamba 3,041 606 Covered
19 Daluka 4,195 798 Covered
20 Jibajiba 3,846 721 Covered
21 St Paul’s 4,574 824 Covered
23 Mbembesi 3,310 659 Covered
27 Mzola West 3,906 728 Covered
Total 85,368 16,360 Covered
Non-communal wards
22 Lupanda (East and West) 7,092 1,440 Not covered
24 Kana Block 1,207 264 Not covered
25 Gwayi 1,365 347 Not covered
26 Sotani 870 179 Not covered
28 Lupanda (SSCFA) 1,330 255 Not covered
Total 11,864 2,485
Table 29. Activity wards in the Binga district
Ward no. Ward name Population Households Covered by AL
1 Luunga 3,098 762 not covered
2 Nabusenga 4,704 1,174 Covered
3 Nagangala, sinampande 4,736 1,256 Covered
4 Sinansengwe 3,180 849 Covered
5 Sinakoma 4,199 1,047 Covered
6 Sikalenge 4,843 1,252 Covered
7 Manjolo 4,737 1,217 Covered
8 Simatelele 3,812 1,005 Covered
9 Sianzyundu 5,360 1,441 Covered
10 Siachilaba 3,720 969 Covered
IMPEL | Implementer-Led Evaluation and Learning
30 Annex A: Additional Tables
Ward no. Ward name Population Households Covered by AL
11 Lubu 3,383 871 Covered
12 Muchesu 3,237 753 Covered
13 Saba 4,006 1,005 Covered
14 Dobola 7,740 1,709 Covered
15 Kariangwe 3,265 772 Covered
16 Chinonge 9,229 2,077 Covered
17 Kabuba 9,950 2,111 Proposed additional
18 Tinde 5,182 1,125 Covered
19 Pashu 5,156 1,075 Covered
20 Lubimbi 4,232 833 Not covered
21 Sinamagonde 17,775 3,338 Proposed additional
22 Tyunga 2,517 634 Not covered
23 Kalungwizi 6,920 1,522 Not covered
24 Kaani 5,204 1,411 Covered
25 Lubanda 3,837 867 Not covered
Total 134,022 31,075
Table 30. Activity wards in the Nyaki district
Ward no. Ward name Population Households Covered by AL
1 Manguni I 4,813 949 Covered
2 Manguni Ii 4,116 771 Covered
3 Ngomambi Central 3,578 739 Covered
4 Ngomambi North 3,116 641 Covered
5 Ngomambi South 6,200 1,208 Covered
6 Sibangalwana Ii 4,575 893 Covered
7 Sibangelana I 3,627 721 Covered
8 Jojo West 3,982 719 Covered
9 Jojo East 2,370 418 Covered
10 Jojo South 3,212 582 Covered
11 Sivalo 2,632 489 Covered
12 Sikhobokho 3,961 759 Covered
13 Malandu West 4,211 807 Covered
14 Malandu East 3,278 595 Covered
Baseline Evaluation of the Amalima Loko RFSA in Zimbabwe (Vol. I)
Annex A: Additional Tables 31 
Ward no. Ward name Population Households Covered by AL
15 Faroni 1,920 349 Covered
16 Phillip 3,597 736 Covered
17 Manomano 2,697 532 Covered
18 Fanisoni 2,937 545 Covered
19 Malindi 3,703 762 Covered
20 Nkalakatha 3,233 679 Covered
21 Nhlanganiso 3,427 705 Covered
22 Mpande 5,637 1,161 Covered
23 Mlume 2 2,712 573 Covered
24 Mlume 1 4,399 837 Covered
25 Siphunyuka 4,147 766 Covered
26 Sikobokobo East 2,883 517 Covered
29 Malindi East 4,861 1,220 Covered
30 Gwampa 2,261 428 Covered
Total 107,613 21,112
Table 31. Activity wards in the Tsholotsho district
Ward no. Ward name Population Households Covered by AL
1 Sodaka, Samahuru 3,583 734 Not covered
2 Dlamini 4,736 958 Not covered
3 Kapane,Mlevu 5,284 1,018 Not covered
4 Dibutibu 2,817 558 Covered
5 Siphepha 5,118 1,108 Covered
6 Jimila, Tshino 7,272 1,508 Covered
7 Pumula 4,112 801 Not covered
8 Mbiriya, Tshitatshawa 8,839 1,707 Not covered
9 Jowa, Phondo, Mpanedziba 6,525 1,270 Not covered
10 Sikente, Maphane 3,536 711 Not covered
11 Nanda 3,809 771 Not covered
12 Manqe 6,899 441 Not covered
13 Magama 6,049 1,380 Covered
14 Makhaza 3,712 769 Not covered
15 Mbamba 7,790 1,637 Not covered
16 Nshaba 5,497 1,197 Not covered
IMPEL | Implementer-Led Evaluation and Learning
32 Annex A: Additional Tables
Ward no. Ward name Population Households Covered by AL
17 Bubude 4,444 938 Not covered
18 Nkunzi 4,645 945 Not covered
19 Chefunye 5,500 1,191 Not covered
21 Tshibizina 2,223 432 Not covered
22 Mbambangamandla, Nembe 7,624 1,851 Covered
Total 110,014 21,925