PRIME: ANNUAL HOUSEHOLD SURVEY

2016 REPORT

Kimetrica

P.O. Box 1327, Village Market 00621

Nairobi, Kenya

Tel: +254 (020) 201 8156

80 Garden Centre, Suite A-368

Broomfield, CO 80020

Tel: +1 303 997 0336

www.kimetrica.com

January 2017

PRIME: ANNUAL HOUSEHOLD SURVEY 2016 REPORT

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ACRONYMS AND ABBREVIATIONS

AHS Annual Household Survey

CAHWs Community Animal Health Workers

DAs Development Agents

FTFMS Feed the Future Monitoring System

FY15 Fiscal Year 2015

GCC Global Climate Change

GoE Government of Ethiopia

HEWs Health Extension Workers

IR Intermediate Result

LQAS Lot Quality Assurance Sampling

MFIs Microfinance Institutions

M&E Monitoring & Evaluation

NGOs Non-Governmental Organizations

NRM Natural Resource Management

ODK Open Data Kit

PSP Participatory Scenarios Planning advisories

PRIME Pastoralist Areas Resilience Improvement through Market Expansion

PSPs Participatory Scenarios Planning advisories

PVPs Private Veterinary Pharmacies

RUSACOs Rural Saving and Credit Cooperatives

SAA Social Analysis and Action for Livelihood Adaptation

TVETs Technical and Vocational Education Training

USAID United States Agency for International Development

USD United States Dollar

ii

US United States

USG United States Government

VSLA Village-level Savings and Loan Association

iii

TABLE OF CONTENTS List of Tables ............................................................................................................................. iv

List of Figures ............................................................................................................................. v

Executive summary .................................................................................................................... 1

Introduction ................................................................................................................................ 3

SECTION 1: Project background................................................................................................ 4

PRIME’s monitoring and evaluation: annual household survey ............................................... 4

SECTION 2: Survey background................................................................................................ 6

Households sampled .............................................................................................................. 6

Data collection and data quality assurance ............................................................................. 8

SECTION 3: Data analysis and indicator calculations ................................................................ 9

Indicator 1. New technologies for climate change resilience ................................................... 9

Indicator 2. Climate information .............................................................................................11

Indicator 3. Value of incremental sales ..................................................................................11

Indicator 4. Women’s participation in decision making ...........................................................12

Indicator 5. Supplementary feeding .......................................................................................12

Indicator 6. Average Number of Income Streams per household ...........................................13

Other parameters ..................................................................................................................13

Activities overlap among households for all IRs. ................................................................13

Activities overlap among households for IR5. .....................................................................14

Section 4: Results for main performance indicators ..................................................................15

Indicator 1. New technologies for climate change resilience ..................................................15

Indicator 2. Climate information .............................................................................................16

Indicator 3. Value of incremental sales ..................................................................................17

Indicator 4. Women’s participation in decision making ...........................................................18

Indicator 5. Supplementary feeding .......................................................................................19

Indicator 6. Average number of income streams per household ............................................20

Activities overlap ...................................................................................................................20

SECTION 5: Conclusions and Recommendations ....................................................................21

Annex 1.....................................................................................................................................22

Annex 2.....................................................................................................................................23

iv

LIST OF TABLES

Table 1: Number of Households Sampled in each Round .......................................................... 7

Table A1: A Summary of the Data Quality Check Results for 88 Households in the 2016 Survey22

Table A2: AHS Indicators Which Have 2016 Targets (2014, 2015 and 2016 Results of Number

of Adult Beneficiaries) ..............................................................................................23

Table A3: AHS Indicators Which Have 2017 Targets ................................................................24

Table A4: AHS Indicators which have 2017 Targets Disaggregated by Region for 2015 and

2016 ..........................................................................................................................24

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LIST OF FIGURES

Figure 1: Map of Households Surveyed in 2014-2016 ................................................................ 7

Figure 2: The Climate Change Resilience Indicator Across the Three AHS Surveys .................15

Figure 3: Climate Information Indicator Across the Three AHS Surveys ....................................16

Figure 4: Value of Incremental Sales (USD) at Farm Level Attributed to Feed the Future

Implementation 2014-2016 ........................................................................................17

Figure 5: Women’s Participation in Decision-Making .................................................................18

Figure 6: Percentage of Pastoralist Who Practice Supplementary Feeding for Animals ............19

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EXECUTIVE SUMMARY

The Pastoralist Areas Resilience Improvement through Market Expansion (PRIME) project was

launched in October 2012, and aims to enhance resilience for a quarter of a million households

in the drylands of the Somali, Afar and Oromiya regional states of Ethiopia. This study forms the

third in a series reporting on the findings of an annual household survey (AHS). For the last

three years (2014-2016), between 600-800 beneficiary households across these regions have

been interviewed to assess the performance of PRIME activities through a range of indicators

related to the adoption of new technologies and management practices; use of climate

information; value of incremental sales; women’s participation in decision making; use of

supplementary feeding and average number of income streams. This report summarizes the

values of these indicators obtained from the 2016 survey, compared to both the values from

previous years and the targets that were set by PRIME.

The first set of three indicators related to new technologies for climate change resilience can be

summarized as one value, since in the PRIME context “people”, “farmers,” and “stakeholders”

all count as beneficiaries of the PRIME project. In the 2016 survey, the number of people,

famers or stakeholders applying new technologies was estimated to be close to 46,000. This

reflects an increase from 2015 (37,200) and exceeds the 2016 target (27,380). The fourth

indicator, the number of stakeholders that increased their capacity by using climate information

in their decision-making as a result of USG assistance (climate information indicator) was

estimated at around 32,000 in 2016. This indicator exceeds the 2016 target (which was 18,070).

These indicators have seen rises because of the expansion in the Somali region on the use of

mobile banking services, facilitation of commercial destocking activities in Afar and Siti zones as

well as the expansion of mother infant and young children nutrition trainings. In addition, during

the reporting period, PRIME has improved the capacity of local and regional Disaster

Preparedness and Preservations Bureaus and units regarding their early warning information

management and dissemination methods. PRIME has also continued to facilitate participatory

scenario planning workshops. This helps creating a space for traditional and scientific

forecasters to communicate their respective seasonal forecasts to the stakeholders. It also

facilitates discussion on the different scenarios and the development of preparedness plans to

make sure the advisory messages are disseminated and used by stakeholders.

The value of incremental sales at the farm level attributed to Feed the Future implementation

has shown a steady improvement since 2014, reaching US$10.3 million in 2016 and exceeding

the 2016 target of US$8.1 million. The outstanding performance is the result of the integration of

Barwako and Addis Kidan milk processing plants; as well as the continuous support to local

small and medium enterprises which has extended the market for commodities produced by

pastoral and agro-pastoral households such as milk and livestock. These activities have been

complemented by market linkage events, trainings, technical assistance interventions and

exposure visits for value chain operators, suppliers and local public development agents in the

value chains.

2

The final three indicators relate to women’s participation in decision making, the use of

supplementary feeding for animals and average income streams per household. For each of

these it is possible to disaggregate the results by region for 2015 and 2016, and all have targets

set for end-of-project (2017) rather than annual targets. Women’s participation in decision-

making has increased overall (72 percent in 2016 compared to the 2017 target of 66 percent) as

well as in Afar and Somali regions. Nonetheless, it has remained constant in Oromiya. For

supplementary feeding, it has remained unchanged overall and in Afar and Somali regions. In

Oromiya region there was a significant decrease since 2015 (64 percent compared to 55

percent). However, this still represents a value higher than the 50 percent target set for 2017.

The final indicator is the number of income streams which has remained unchanged, in

statistical terms, for the whole project (at 2.58 in 2016) and in all three regions between 2015

and 2016. The PRIME management team will need to focus more during Year 5 on activities

oriented to increase households’ income sources in order to meet the 2017 target of three

income streams.

In conclusion, most indicators suggest that targets are being met. However, the project

management team need to be aware that income streams have remained unchanged overall,

and the use of supplementary feeding practices have decreased in Oromiya.

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INTRODUCTION

The Pastoralist Areas Resilience Improvement through Market Expansion (PRIME) project was

launched in October 2012, and aims to reach 250,000 households in the drylands of the Somali,

Afar and Oromiya regional states of Ethiopia. It is a five-year initiative funded by the United

States Agency for International Development (USAID), designed to support resilience among

pastoralist communities in Ethiopia. In order to measure the performance on impact indicators,

as well as outcome and output indicators, PRIME has developed a Monitoring and Evaluation

(M&E) system, under which the Annual Household Survey (AHS) is one component. The aim of

the AHS is to measure change over time and achievements against set targets on a range of

indicators related to the adoption of new technologies and management practices; use of

climate information; value of incremental sales; women’s participation in decision making; use of

supplementary feeding; and average number of income streams.

This report summarizes the indicator calculations for the data collected during the 2016 AHS,

alongside those estimated from the 2014 and 2015 surveys. The report is divided into five

sections. Section 1 summarizes the project’s background; section 2 describes the survey

background, including the processes followed in implementing the survey, from questionnaire

design through to data collection and data quality assurance procedures; section 3 explains the

methodology used for the indicator calculation; section 4 presents the findings regarding the

performance of project indicators in relation to previous years and targets; and finally, section 5

discusses the findings and provides recommendations for consideration of the PRIME

management team.

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SECTION 1: PROJECT BACKGROUND

PRIME is a five-year, USAID-funded initiative designed to support resilience among pastoralist

communities in Ethiopia. It was launched in October 2012 and aims to reach 250,000

households in the drylands of the Somali, Afar and Oromiya regional states of Ethiopia.

Financed through the Feed the Future and Global Climate Change (GCC), PRIME is designed

to be transformative, innovative, and to achieve scale through market-driven approaches to

livestock production and livelihood diversification that simultaneously support dryland

communities to adapt to a changing climate. In order to achieve its overall goal of reducing

poverty and hunger by enhancing resilience to climate change through market linkages, the

project works to meet the following Intermediate Results (IRs):

IR1: Improve productivity and competitiveness of livestock and livestock products.

IR2: Enhance pastoralists’ adaptation to climate change.

IR3: Strengthen alternative livelihoods for households transitioning out of pastoralism.

IR4: Ensure enhanced innovation, learning and knowledge management.

IR5: Improve nutritional status of targeted households through targeted, sustained and

evidence-based interventions.

PRIME’S MONITORING AND EVALUATION: ANNUAL HOUSEHOLD

SURVEY

As part of the fourth intermediate result (IR4), PRIME developed a monitoring and evaluation

(M&E) system that supports the tracking and measurement of the impact, outcome and output

indicators established in its M&E Plan. The AHS is one component of this system and aims to

evaluate PRIME’s performance with respect to the following indicators:

1. Number of farmers and others who have applied new (improved) technologies or

management practices as a result of US assistance 4.5.2(5).

2. Number of people implementing risk-reducing practices/actions to improve resilience to

climate change as a result of United States Government (USG) assistance 4.5.2(34).

3. Number of stakeholders with increased capacity to adapt to the impacts of climate

variability and change as a result of USG assistance PPR-4.8.2-26: This indicator has two

components: (a) Implementing risk-reducing practices/actions to improve resilience to

climate change 4.8.2-26a; and (b) Using climate information in decision making 4.8.2-26b.

4. Value of incremental sales at farm level attributed to Feed the Future implementation

4.5.2(23).

5. Percentage of women reporting meaningful participation in decision-making regarding

economic activities, nutrition and Natural Resource Management (NRM) governance.

6. Percentage of farmers/pastoralists who practice supplementary feeding of animals.

7. Average number of income streams per households.

5

In addition to these indicators, the AHS data is used to calculate two parameters that are used

for both these and other calculations within the project. These parameters are:

Percent of households participating in more than one activity in more than one IR

(“activities overlap”).

Percent of households participating in more than one activity in IR5.

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SECTION 2: SURVEY BACKGROUND

One of the main objectives of this survey was to assess how key indicators have changed over

the past year. For this reason, the current survey (2016) was based on the questionnaire used

during the previous survey (2015) with some minor modifications. Four new alternatives were

added to the section of the questionnaire measuring the access to resources and services1, and

two new options were included in the section measuring the adoption of improved technologies

and management practices2.

HOUSEHOLDS SAMPLED

During the 2014 AHS, 600 households were surveyed. However, after data cleaning, only 583

were kept for analysis. The 2015 survey was designed to follow part of the panel of “old”

households surveyed in 2014 plus “new” households added in 2015, because IR leaders

expected that both types of households would be important to determine the performance of

indicators measured with the AHS. The total number of households surveyed in 2015 was

capped at 800 by PRIME’s IR4 leader due to budgetary constraints. To determine the proportion

of new versus old households in the 2015 sample of these 800 households, Kimetrica staff met

with all IR leaders. The consensus was to balance the sample equally, so the final sample

included 433 old households and 367 new households. The old households selected to remain

in the 2015 sample were chosen to assure that all IR components could be well represented3.

The new households were selected from list of beneficiaries participating in activities reported in

the first half of Fiscal Year 2015 and were distributed among IRs and regions according to the

proportion of PRIME activities that each IR had implemented as per data in ki-projects™. These

households were expected to be new beneficiaries. Among the 800 households in the planned

sample, two were not surveyed because they had moved out of the area.

The 2016 AHS sample followed the 2015 panel (which included the “old” households from 2014

as well as the “new” households added in 2015). There was a two percent attrition rate due to

households that relocated to different areas between 2015 and 2016. This resulted in the loss of

fourteen households (nine in Somali, three in Oromiya, and two in Afar). In addition, security

issues prevented data collection in Miyo Woreda in Oromiya region, resulting in the loss of two

households. The number of households surveyed across the three regions for each survey is

outlined in Table 1.

1 The new options were: access to milk collection center – buyer; access to livestock market – buyer; agricultural inputs supplier; and solar energy appliances market. 2 The new options were: improved milk handling and marketing, and improved herd or flock nutritional (grazing and feeding practice). 3 Most of the sample (60 percent) was composed of IR2 households, the remaining 40 percent

representing the other three IR components. Therefore, in agreement with IR4 leader, Kimetrica dropped 150 households surveyed for IR2 in 2014 to allow the overall sample for 2015 to be balanced between new and old households.

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Table 1: Number of Households Sampled in each Round

Year

of

survey

Afar Oromiya Somali PRIME

Total Old New Total Old New Total Old New Total

2014 n/a n/a 118 n/a n/a 238 n/a n/a 227 583

2015 63 89 152 174 148 322 161 163 324 798

2016 63 87 150 173 146 319 158 157 315 784

The distribution of households sampled in the three surveys is shown in Figure 1. The

distribution of the sample reflects PRIME activity intensity during FY2014 and FY2015, as

households were drawn from the beneficiary database extracted from sub-activity reports. The

red dots show the 2016 AHS households which shows that overtime the AHS is surveying the

same households to assure that results can be comparable.

Figure 1: Map of Households Surveyed in 2014-2016

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DATA COLLECTION AND DATA QUALITY ASSURANCE

The household data was collected using tablets and the Kobo Collect platform, an Open Data

Kit (ODK)-compatible application. For the 2016 survey, Kimetrica hired and trained a team of 40

enumerators, eight supervisors (each supervised a team of five enumerators), and six

coordinators on the use of Kobo Collect, details of the data collection tool, and procedures to be

followed in the field. In addition to this team, Kimetrica recruited four enumerators and two

supervisors who supported the work of the two data collection teams in the Eastern area of

Somali region4. The training of data collection teams was undertaken in Adama from July 26 to

30, 2016. After training, the enumerators were assigned a list of households to survey and were

deployed to each of the areas: Afar, Somali, and Oromiya regions.

Data collection was carried out from August 1 to 18, 2016. Data was uploaded routinely but with

some delays due to internet connectivity issues. Before data cleaning, all data was reviewed by

the Kimetrica team to ensure that household IDs had been correctly assigned and that there

was no duplication of cases.

In parallel to data collection, supervisors and coordinators carried out: accompaniments (to

assure that enumerators understood how to use the tablets, asked the questions, and

completed the questionnaire before submission); spot checks (to verify high quality

enumeration); and random back checks (to review the quality of data submitted by

enumerators). Supervisors back checked ten percent of households surveyed. During back

checks the supervisor asked the household respondent 19 randomly selected questions. Data

from back checks and data collected by enumerators was then compared. Kimetrica used a Lot

Quality Assurance Sampling (LQAS) approach to measure the quality of data that was being

collected. Kimetrica set a 95 percent benchmark for all questionnaires back checked. Results

showed that on average 18.3 questions out of the 19 back checked per household had similar

answers, which corresponds to 95 percent under the LQAS approach and 96 percent using the

conventional approach (see Annex 1).

4 The additional team members were recruited based on a recommendation from the Bureau of Finance and Economic Development in the Somali region to assure that the teams working in that area had native Somali speakers.

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SECTION 3: DATA ANALYSIS AND INDICATOR CALCULATIONS

Data was analyzed based on guidance from USAID’s Feed the Future Indicator Handbook and

consultation with IR leaders. The indicators, mostly descriptive statistics, were calculated using

the survey data as well as beneficiary information from ki-projects™5. The main assumption in

the calculations is that the parameters estimated from the AHS can be extrapolated to all

PRIME beneficiaries.

The AHS uses the ki-projects™ data on the number of beneficiaries participating in PRIME

activities to estimate indicators that require beneficiary population totals. However, because ki-

projects™ records the number of households participating in each activity, summing the total

number of households in the system overestimates the number of people benefiting from the

project as a whole. This is because households are counted every time they participate in a

project activity. For example, a household participating in two IR1 activities would be counted

twice in the total number of beneficiaries. This also applies across different IR activities.

Because households frequently participate in multiple activities within an individual IR or in

multiple IRs, simply summing the number of households in the M&E system overestimates the

number of beneficiary households.

To partially correct this overestimation, Kimetrica has calculated a parameter which estimates

the percentage of households with activity overlap across IRs. This parameter is calculated from

the AHS data, and has been applied to the indicator calculations in an effort to correct for

households participating in multiple IR activities. It should be noted that this indicator is based

on a number of assumptions, but provides our best estimate for the frequency of overlap given

current data availability. Finally, for clarification, Feed the Future indicators referring to “people,”

“farmers,” and “stakeholders” are all based on calculations of adult beneficiaries of the PRIME

project.

INDICATOR 1. NEW TECHNOLOGIES FOR CLIMATE CHANGE

RESILIENCE

As a result of the assumption that “people,” “farmers,” and “stakeholders” all refer to

beneficiaries of the PRIME project, in the PRIME context, the following indicators are

considered to be equivalent in meaning.

4.5.2(34): Number of people implementing risk-reducing practices/actions to improve

resilience to climate change as a result of USG assistance.

4.5.2(5): Number of farmers and others who have applied new (improved) technologies or

management practices as a result of US assistance.

5 Kimetrica has tailored ki-projects™ to serve as PRIME’s M&E system. It serves as a platform in which

activities are initiated and project implementation and reporting are linked for management and

performance evaluation purposes.

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PPR-4.8.2-26a: Number of stakeholders with increased capacity to adapt to the impacts of

climate variability and change as a result of USG assistance by implementing risk-reducing

practices/actions to improve resilience to climate change

Using the PRIME M&E Plan Kimetrica has measured these indicators applying the following

approach. First, the total number of technologies used by each household, out of a total of 22

possible technologies6 from a PRIME-related source7, was calculated. This was then summed

across all households to get the total number of PRIME-supported technologies used by

households in the sample. A proportion was then calculated by dividing this value by the product

of the number of technologies measured (22) by the number of households in the sample (784).

This proportion was then multiplied by the estimated number of adult beneficiaries (the number

of beneficiary households calculated from ki-projects™ after deducting the overlap, as indicated

above, then multiplied by the average number of adults per household as calculated from the

AHS sample). Mathematically, the calculation used can be represented as:

As indicated in the PRIME M&E Plan, this formula is used to calculate the three indicators

mentioned above, representing PRIME beneficiaries’ adoption of new technologies to reduce

their risk in the face of climate change. Henceforth these indicators will be referred as the new

technologies for climate change resilience indicator.

6 These included: 1) Managing dry and wet grazing areas; 2) Invasive species management such as controlled fire, bush thinning, prosopis removal (mechanical and manual); 3) Water point rehabilitation or upgrade; 4) Gully treatment; 5) Seeding degraded areas (grass); 6) Reserve grazing for selected species like milking animals; 7) Area closure/cut and carry; 8) Solar lanterns, fuel efficient cooking stoves; 9) Postharvest storage technology (plastic storage bags); 10) Agricultural inputs (improved seeds, fertilizers, equipment); 11) Planned management of herds (modifying herd size or composition); 12) Planned and timely sale of livestock and milk; 13) Herd diversification; 14) Planned and timely slaughtering of animals and killing of calves; 15) Changed vaccination practice; 16) Increased parasite control practice; 17) Drip, surface, and sprinkler irrigation, irrigation schemes; 18) Savings; 19) Loans/credits; 20) Insurance; 21) Improved milk handling and marketing; 22) Improved herd or flock nutritional (grazing and feeding practice). 7 PRIME-supported sources included: Government of Ethiopia (GoE) (Health Extension Workers-HEWs, Development Agents-DAs, Early warning and other experts); Non-Governmental Organizations-NGOs; Association; Cooperative/union; Community leadership/clan leaders, customary institutions/rangeland councils; Traditional forecasters; Family member, friends; Private sector (Private Veterinary Pharmacies-PVPs, Community Animal Health Workers-CAHWs, Technical and Vocational Education Training-TVET, Agricultural input suppliers, solar dealers); Radio/TV; Neighbors; Marketplace; Public enterprises; Formal financial institutions (Rural Saving and Credit Cooperatives-RUSACOs, banks, Microfinance Institutions-MFIS); Informal financial services (Village Saving and Loan Association-VSLA); Participatory Scenarios Planning advisories (PSPs)

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INDICATOR 2. CLIMATE INFORMATION

The number of stakeholders with increased capacity to adapt to the impacts of climate variability

and change by using climate information in their decision-making as a result of USG assistance

(PPR-4.8.2-26b) is referred to as the climate information indicator. Again, it is important to

note that “stakeholders” is taken to mean “adult beneficiaries” in the PRIME context. This

indicator is calculated based on the proportion of AHS sample households that reported having

access to at least one of three types of climate-related information (seasonal rainfall forecast,

pasture conditions and/or water availability) provided by a PRIME-related source (this included

rangeland council, early warning committee, participatory scenarios planning advisories and/or

SAA (social analysis and action for livelihood adaptation) group participation). This parameter

was then multiplied by the estimated number of adult beneficiaries after deducting the overlap. It

can be expressed mathematically as:

INDICATOR 3. VALUE OF INCREMENTAL SALES

The value of incremental sales at farm level attributed to Feed the Future implementation is

generated by the Feed the Future Monitoring System (FTFMS) based on values calculated from

the AHS and ki-projects™. Importantly, the indicator is based on sales from cattle (including

oxen), shoats, camels and milk.

The data for the total value of each household’s cattle/oxen, shoats, camels and milk sales over

the 12 months prior to the survey date was cleaned and summed. The top one percent of this

distribution (total value of sales from cattle/oxen, shoats, camels and milk > 250,000 birr) was

trimmed and the eight households with higher sales excluded from the remainder of the

calculation. Although these eight households were determined to represent real earnings rather

than data entry errors (these households were PRIME-supported livestock traders), they were

excluded because of the extent to which they influenced the mean sales value. In this instance,

all eight also represented traders. The mean value of sales for each livestock type (cattle/oxen,

shoats, camels and milk) was then calculated from the remaining sample (776 households).

The total number of IR1 beneficiaries was estimated using data from ki-projects™ and the AHS.

This was scaled down to account for “double counting” of those households that participated in

multiple activities within IR1. The IR1 overlap factor was calculated from the AHS as the

proportion of households participating in more than one IR1 activity.

Once the total number of IR1 beneficiaries had been estimated, these were then distributed

across the livestock types and products (cattle/oxen, shoats, camels, and milk only) based on

the proportion of total sales value for each livestock type. This is necessary because although

12

most households own multiple types of livestock, the FTFMS is designed based on an

assumption that each household owns only one type of livestock.

The total value of sales for each of the measured livestock types was estimated by multiplying

the mean value of sales for each type by the estimated number of beneficiaries selling each

type. Finally, the volume of sales (mt) - the third input variable that is fed in the FTFMS is

calculated using the monetary value of the total value of sales and the conversion factor of 1.7

USD is equivalent to 1kg8. These values are then fed into the FTFMS, which calculates the final

indicator value. For simplicity, the remainder of this report will refer to this indicator as value of

incremental sales.

INDICATOR 4. WOMEN’S PARTICIPATION IN DECISION MAKING

As indicated in the PRIME M&E Plan, the percentage of women reporting meaningful

participation in decision-making regarding economic activities, nutrition, NRM/governance,

henceforth referred to as the women’s participation in decision making indicator, was

calculated by summing, for each household, the number of activities (out of the 13 listed on the

questionnaire) in which the adult female respondent reported having some, most or all input.

This value was then summed across all households. The total was then divided by the product

of the number of decisions measured (13) and the number of households in the sample that had

an adult female present and available to answer the questions (750). Mathematically, it is

represented as:

INDICATOR 5. SUPPLEMENTARY FEEDING

Following the PRIME M&E Plan the percentage of farmers/pastoralists who practice

supplementary feeding for animals, henceforth the supplementary feeding indicator, was

calculated as the number of supplementary feed types used by each household (out of salt,

crop residue, hay/grass, industrial byproduct and other), summed across all households, then

divided by the product of the number of supplementary feed types asked about on the

questionnaire (5) and the number of households in the sample (784). It is mathematically

represented as:

8 This conversion factor was provided by PRIME IR1 leader based on information from the field.

13

INDICATOR 6. AVERAGE NUMBER OF INCOME STREAMS PER

HOUSEHOLD

The final indicator is the average number of income streams per household. This is represented

mathematically as follows:

OTHER PARAMETERS

In addition, Kimetrica calculated the activity overlap among households for all IRs and the

activity overlap among households for IR5.

Activities overlap among households for all IRs.

Households can be reached by more than one activity and by more than one IR. As mentioned

above, each time a household participates in any activity, it is recorded by the ki-projectsTM

system. In an effort to adjust the number of total activity participants down to the number of

unique household participants, an overlap factor was estimated. This parameter was used in

several indicators described above. To calculate the overlap factor, households participating in

more than one activity in more than one IR were identified.

Estimating the overlap factor was a multi-stage process. First, for each IR, households that

participated in more than one activity within a given IR were identified as having within-IR

activity overlap. For example, a household that participated in two or more IR1 activities was

identified as having IR1 overlap. Second, households that had within-IR overlap for two or more

IRs were identified as having between-IR overlap. These were households that had participated

in two or more activities in two or more IRs. Finally, the overlap factor was calculated as the

sum of all households with between-IR overlap divided by the number of households in the

sample. The use of this calculation systematically biases the indicators upwards, but is the only

approach to dealing with this overlap given the data available. The equation below summarizes

this calculation.

14

Activities overlap among households for IR5.

This parameter is an input provided to the PRIME management team to calculate indicator

3.1.9(15), the number of children under-five reached by USG-supported nutrition programs.

Kimetrica has identified households with overlap on IR5 activities from a list of 11 IR5 activities.

These are households reached by more than one nutrition program. The total number of

households with IR5 activities overlap was then divided by the total number of households

surveyed (784).

15

SECTION 4: RESULTS FOR MAIN PERFORMANCE INDICATORS

Following USAID recommendations, the indicators related to number of beneficiaries were

changed in 2015 to number of people rather than number of households (as in 2014). Indicators

for 2014 were recalculated for the 2015 report in order to assess the change over time.

INDICATOR 1. NEW TECHNOLOGIES FOR CLIMATE CHANGE

RESILIENCE

The number of people applying new (improved) technologies or management practices as a

result of US assistance 4.5.2(5), and the number of people implementing risk-reducing

practices/actions to improve resilience to climate change 4.5.2(34) and 4.8.2-26(a) were all

measured with the same formula, as they are equivalent in the PRIME context.

This indicator increased markedly from 2014 (24,839) to 2015 (37,200) (see Figure 2). In 2016,

it increased by 22 percent to 45,542. The 2016 target set for this indicator was 27,380. Results

have surpassed the targets by 66 percent. Although the use of technologies has remained

stable in comparison to the previous year, the number of beneficiaries has substantially

increased. This has been the result of the expansion in the Somali region on the use of mobile

banking services, facilitation of commercial destocking activities in Afar Zone 3 and Somali Siti

zone as well as the expansion of mother infant and young children nutrition trainings. In

addition, during the reporting period, PRIME has improved the capacity of local and regional

Disaster Preparedness and Preservations Bureaus and units regarding their early warning

information management and dissemination methods. PRIME has also continued to facilitate

participatory scenario planning workshops. This helps creating a space for traditional and

scientific forecasters to communicate their respective seasonal forecasts to the stakeholders. It

also facilitates discussion on the different scenarios and the development of preparedness plans

to make sure the advisory messages are disseminated and used by stakeholders.

Figure 2: The Climate Change Resilience Indicator across the Three AHS Surveys

16

INDICATOR 2. CLIMATE INFORMATION

A consistent positive trend is also observed in the number of stakeholders using climate

information in their decision-making (Indicator 4.8.2-26b). The 2016 survey suggests that the

indicator reached 32,178 stakeholders, which was 14,108 more than the target set for 2016,

(18,070). Similar to above, these increases have been the result of the expansion in the Somali

region on the use of mobile banking services, facilitation of commercial destocking activities in

Afar Zone 3 and Somali Siti zone as well as the expansion of mother infant and young children

nutrition trainings. Other activities that might have contributed to this indicator include the work

done with the Disaster Preparedness and Preservations Bureaus and units regarding their early

warning information management and dissemination methods; as well as the participatory

scenario planning workshops.

Figure 3: Climate Information Indicator across the Three AHS Surveys

17

INDICATOR 3. VALUE OF INCREMENTAL SALES

The value of incremental sales at the farm level attributed to Feed the Future implementation

(indicator 4.5.2(23)) showed an improvement from 2014 (US$6 million) to 2015 (US$7.7 million).

This exceeded the 2015 target set of US$6,353,000. As a result, the 2016 target was revised to

US$8.1 million. The 2016 target has also been met, with the value of incremental sales reaching

US$10,876,985 (see Figure 4). The outstanding performance is the result of the integration of

Barwako and Addis Kidan milk processing plants as well as the continuous support to local

small and medium enterprises which has extended the market for commodities produced by

pastoral and agro-pastoral households such as milk and livestock. These activities have been

complemented by market linkage events, trainings, technical assistance interventions and

exposure visits for value chain operators, suppliers and local public development agents in the

value chains.

Figure 4: Value of Incremental Sales (USD) at Farm Level Attributed to Feed the Future Implementation 2014-2016

6,027

7,701

10,877

6,3056,353

8,100

Targets

2014 2015 2016

Actuals

18

INDICATOR 4. WOMEN’S PARTICIPATION IN DECISION MAKING

The women’s participation in decision making indicator increased from 63 percent in 2014 to

67 percent in 2015. In the 2016 survey, it was estimated to be 72 percent. The end-of-project

(2017) target was set as an increase of five percent from the 2014 value (66 percent).

As seen in Figure 5, the 2017 target was already achieved in 2015. Results show that

performance has continued to improve, especially in Somali region, though this remain lower

than that observed in Oromiya (which has remained stable but high at 78 percent). The increase

seen is the result of the NRM activities that have been promoting the participation of women in

these committees; as well as the SAA and Village-level Savings and Loan Association (VSLA)

groups whose members are mostly women.

Figure 5: Women’s Participation in Decision-Making

19

INDICATOR 5. SUPPLEMENTARY FEEDING

In 2014, 43 percent of pastoralists reported that they used supplementary feeding, and in 2015

this percentage increased to 51 percent (see Figure 6). The end-of-project target was set at

having 50 percent of pastoralists using supplementary feeding by 2017. In this 2016 survey, the

supplementary feeding indicator was 48 percent. In statistical terms there has not been changed

on the percentage of households using supplementary feeding between 2015 and 2016. When

looking at changes over time across regions analysis shows a statistically significant decrease

(from 64 percent in 2015 to 55 percent in 2016) in the use of supplementary feeding in the

Oromiya region. However, this still represents a value higher than the end-of project target of 50

percent. No changes between 2015 and 2016 were registered for the other regions.

Figure 6: Percentage of Pastoralists Who Practice Supplementary Feeding for Animals

45%

39%

64%

55%

42%

45%

51%

48%

2015 2016

Afar Oromiya Somali PRIME

2017 target: 50%

20

INDICATOR 6. AVERAGE NUMBER OF INCOME STREAMS PER

HOUSEHOLD

The number of income streams has remained unchanged, in statistical terms, for the whole

project and in all three regions between 2015 and 2016. For the whole project the number of

income streams for 2016 is estimated at 2.58. The target for 2017 is 3 income streams. The

PRIME management team will need to focus more during Year 5 on activities oriented to

increase households’ income sources in order to meet this target.

At regional level, in Somali and Afar regions the number of incomes in 2016 is estimated at 2.37

and 2.52, respectively. Oromiya region continues being the region with the higher number of

income streams with 2.82 for 2016.

ACTIVITIES OVERLAP

As described in section 3, Kimetrica has also estimated the activities overlap among households

for all IRs (68.49 percent in 2016). PRIME activities are implemented integrating components to

maximize the impact at household level. For example, PRIME has facilitated cash transfers to

5000 households in Afar and Somali regions through IR3 activities. For the same beneficiaries.

PRIME nutrition team (IR5) provided training so that the beneficiaries use the cash to improve

their household nutrition status.

The activities overlap among households for IR5 is estimated at 44.01 percent in 2016. This

refers to the percentage of households participating in more than one IR5 activity out of 11

different nutrition related type of activities.

21

SECTION 5: CONCLUSIONS AND RECOMMENDATIONS

During 2016, PRIME achieved all of its annual targets which pertained to the indicators related

to use of new technologies for climate change resilience (45,542 compared to 2016 target of

27,380) and climate information (32,178 compared to 2016 target of 18,070). The increase in

these indicators has been the result of the expansion in the Somali region on the use of mobile

banking services, facilitation of commercial destocking activities in Afar Zone 3 and Somali Siti

zone as well as the expansion of mother infant and young children nutrition trainings. Other

activities that might have contributed to this indicator include the work done with the Disaster

Preparedness and Preservations Bureaus and units regarding their early warning information

management and dissemination methods; as well as the participatory scenario planning

workshops.

The value of incremental sales for 2016 totaled USD 10,877 compared to the 2016 target of

USD 8,100). The outstanding performance is the result of the integration of Barwako and Addis

Kidan milk processing plants as well as the continuous support to local small and medium

enterprises which has extended the market for commodities produced by pastoral and agro-

pastoral households such as milk and livestock. These activities have been complemented by

market linkage events, trainings, technical assistance interventions and exposure visits

for value chain operators, suppliers and local public development agents in the value chains.

For those indicators that had end-of-project targets, most showed that these performance

indicators were moving in the right direction. Women’s participation on decision making has

continued increasing since 2014, with a five percent increase from 2015, and the target of 2017

(66 percent) being exceeded even in 2015. Project management need to assess whether they

want to revise the end-of-project target for this indicator.

The use of supplementary feeding in 2016 has remained unchanged, in statistical terms at 48%.

When disaggregating the data by region it is clear that the use of supplementary feeding has

reduced significantly in Oromiya region, and remains well below the 50 percent target in the

other regions. On the other side, the number of income streams has remained unchanged in

comparison to 2015. The PRIME management team might need to focus more on activities

oriented at increasing this indicator. Otherwise, the end-of-project target of three income

streams could be missed.

22

ANNEX 1

Table A1: A Summary of the Data Quality Check Results for 88 Households in the 2016 Survey

Description Afar Oromiya Somali All areas

surveyed

Number of questions with

consistent information 441 591 570 1,602

Number of questions with

inconsistent information 15 17 39 71

Total number of questions 456 608 609 1,673

Consistency average out of 19

questions asked per respondent 18 19 18 18.3

Data quality in percentage – LQAS

approach 95 95 95 95

Data quality in percentage –

conventional approach 97 97 97 96

23

ANNEX 2

Table A2: AHS Indicators Which Have 2016 Targets (2014, 2015 and 2016 Results of Number of Adult Beneficiaries)

Indicator 2016 target

Actual

2014*

Actual 2015

Actual 2016

4.5.2(5): Number of farmers and others who

have applied new (improved) technologies

or management practices as a result of US

assistance

27,380 24,839 37,200 45,542

4.5.2(34): Number of people implementing

risk-reducing practices/actions to improve

resilience to climate change as a result of

USG assistance

27,380 24,839 37,200 45,542

4.8.2-26a: Number of stakeholders

Implementing risk-reducing practices/actions

to improve resilience to climate change

27,380 24,839 37,200 45,542

4.8.2-26b: Number of stakeholders using

climate information in their decision-making 18,070 24,422 24,785 32,178

In USD thousands

Value of incremental sales 8,100 6,027 7,701 10,877

*Values have been recalculated to be expressed as number of people for this report to allow comparison with 2015 and 2016 estimates

24

Table A3: AHS Indicators Which Have 2017 Targets

Indicator 2017 target

Actual 2014

Actual 2015

Actual 2016

Percentage of women reporting

meaningful participation in decision-

making regarding: economic

activities, nutrition, NRM/

governance

5% increase

from 2014 value

(equivalent to

66%)

63% 67% 72%

Percentage of farmers/pastoralists

who practice supplementary feeding

for animals

50% 43% 51% 48%

Average number of income streams

per household 3 2.48 2.55 2.58

Table A4: AHS Indicators which have 2017 Targets Disaggregated by Region for 2015 and 2016

Indicator

Actual 2015 Actual 2016

Afar Somali Oromiya Afar Somali Oromiya

Percentage of women reporting meaningful participation in decision-making regarding economic activities, nutrition and Natural Resource Management (NRM) governance.

61% 58% 80% 71% 67% 78%

Percentage of farmers/pastoralists who practice supplementary feeding of animals.

45% 42% 64% 39% 45% 55%

Average number of income streams per households. practices/actions to improve resilience to climate change

2.61 2.25 2.83 2.52 2.37 2.82

Note: Over time the only differences that are statistically significant are the increase in the

percentage of women participation in decision making in Somali region and the decrease in the

Oromiya region on the use of supplementary feeding. All other differences are not statistically

significant at 95 percent confidence level