1. Photo Credit Goes Here Ms. Jymdey Yeffimo – PRIME Technical leader May 10, 2016 PPT prepared by Jenny Spencer- Kimetrica Economist Pastoralist Areas Resilience Improvement through Market Expansion 2015 Annual Household Survey

2. Photo Credit Goes Here Overview

3. OBJECTIVES PRIME: Reduce poverty and hunger M&E system: Measure changes in impact, outcome and output indicators AHS: Measure annual performance of 7 key outcome indicators as well as provide estimates for important parameters: –Overlap of all IR activities –Overlap of IR5 activities

4. INDICATORS Number of farmers applying new (improved) technologies or management practices Number of people implementing risk-reducing practices/actions to improve resilience to climate change Number of stakeholders with increased capacity to adapt to the impacts of climate variability and change. This indicator has two components: –implementing risk-reducing practices/actions to improve resilience to climate change. –using climate information in their decision- making

5. INDICATORS Value of incremental sales at farm level Percentage of women reporting meaningful participation in decision- making Percentage of pastoralists who practice supplementary feeding for animals Average number of income streams per household (HH)

6. Photo Credit Goes Here Methods

7. QUESTIONNAIRE Survey modifications –Community feedback section dropped –Improvements from IR leader suggestions Field testing –June 15 & 16, Awash, Afar –June 27, Dire Dawa – Erre, Somali Data collection using KoboToolbox

8. SAMPLE SIZE AND COMPOSITION

9. DATA COLLECTION AND CLEANING 40 enumerators, 8 supervisors, 5 coordinators Training in Adama from August 10-14 Data collected from August 15-29 Lot Quality Assurance Sampling

10. ANALYSIS 1.Change over time 2.Comparison of new vs. old households 3.Multivariate regression results using 2015 data for old and new HHs 4.Comparing multivariate regression results for 2014 and 2015 for old HHs

11. Photo Credit Goes Here Findings: Change over time

12. NUMBER OF FARMERS APPLYING NEW TECHNOLOGIES AND PEOPLE IMPLEMENTING RISK REDUCING PRACTICES/ ACTIONS TO IMPROVE RESILIENCE TO CLIMATE CHANGE Increased nearly 50 percent from 2014 to 2015 Target exceeded Due to financial services, including mobile and agent banking, and VSLAs; as well as access to veterinary input and services.

13. Minimal increase Target not met if it was set as number of people NUMBER OF STAKEHOLDERS USING CLIMATE INFORMATION IN THEIR DECISION MAKING

14. Increase by about 28% Exceeded target by 21% Thanks to coordinated effort in the dairy value chain VALUE OF INCREMENTAL SALES AT FARM LEVEL

15. WOMEN HAVING MEANINGFUL PARTICIPATION IN DECISION-MAKING From 63% in 2014 to 67% in 2015, representing a 6% increase Met end-of-project target of 5% increase by 2017 Final target should be revised upward to encourage continued impact

16. PASTORALISTS USING SUPPLEMENTARY FEEDING From 43% in 2014 to 51% in 2015 Met end-of-project target of 50% Final target should be revised upward to encourage continued impact

17. NUMBER OF INCOME STREAMS Increased from 2.48 to 2.55 Target for 2017 is 3

18. Photo Credit Goes Here Findings: Comparison of New and Old HHs

19. NEW VS. OLD HOUSEHOLDS New households are not new beneficiaries.

20. NEW VS. OLD HOUSEHOLDS New households have greater participation across PRIME activities Old HH New HH Women's Group Saving & Credit Assn. Member/MFI Client Cooperatives (eg. milk collection) Trader Association/ Producer Association VSLA Members TVET/ Scholarship Recipients Livestock Trader Client Field agent/Private Service Provider Trade Fair Radio Listener Groups

21. NEW VS. OLD HOUSEHOLDS Similar head of household characteristics –Years of schooling –Source of livelihood Similar livestock wealth, sales, and consumption patterns Similar number of income streams. Agro-Pastoralist Pastoralist Non-Pastoralist

22. NEW VS. OLD HOUSEHOLDS Some differences regarding access to services and resources, though neither group consistently show higher access. Old HHs New HHs Access to top 3 programs for household nutrition Old HH New HH Human health services Transportation Woodlots Improved water sources for livestock Savings

23. Photo Credit Goes Here Which Households Are…

24. USING PRIME SUPPORTED SERVICES? Those involved for more than a year and whose HoH is more educated are more engaged. Pastoralists are less engaged than agro-pastoralists. Agro-pastoralist HHs are more likely to increase the number of relationships with PRIME over time rather than pastoralist HHs. Households in Afar and Oromiya are more engaged than those in Somali.

25. USING NEW (IMPROVED) TECHNOLOGIES? Households in Oromiya and Afar more than in Somali. HHs in Afar tend to increase over time the use. Those with past experience using technologies. Agro-pastoralists more than pastoralists Households with disabled members use fewer technologies # technologies used

26. IMPLEMENTING RISK-REDUCING PRACTICES TO IMPROVE RESILIENCE TO CLIMATE CHANGE?

27. USING CLIMATE INFORMATION IN THEIR DECISION MAKING? Households in Afar and Oromiya HHs using the EWI for avoiding conflict areas rather than for other reason are less likely to use it in decision making.

28. OBTAINING GREATEST SALES VALUES? Agro-pastoralists sell ETB 6,091 more per year than non-pastoralists. HoH with high school sell on average ETB 14,356 more per year than HoH that never attended. Farm level sales are higher for Somali households than those in Oromiya. Somali HHs also increase their sales over time in comparison to Oromiya HHs.

29. WOMEN PARTICIPATE MEANINGFULLY IN DECISION MAKING? Those with a university- educated head of household. Women who have children Households with women that earn money, particularly that earn more than their spouse. # of activities with women meaningful participation

30. PRACTICING SUPPLEMENTARY FEEDING FOR ANIMALS? Households purchasing it from the market and households using it in the dry season. Those in Afar and Oromiya compared to Somali. Those with a high school level education vs. those who never attended school. Consumption and wealth do not seem to have an influence. # of supplementary feeds used

31. HAVE A GREATER NUMBER OF INCOME STREAMS? Households in Afar. Agro-pastoralists. Households with high school degrees (vs no school attended) or a disabled member. Households that have been with PRIME for more than one year. # income streams

32. Photo Credit Goes Here Conclusions

33. TARGETS MET Application of new (improved) technologies Implementation of risk-reducing practices to improve resilience to climate change Use of climate information in stakeholder decision making implementing risk-reducing practices/actions to improve resilience to climate change Value of incremental sales

34. HOUSEHOLD CHARACTERISTICS THAT MATTER Location is important: Afar and Oromiya outpace Somali. Education level of head of household matters. Primary livelihood has significant effects: Agro-pastoralists perform better than others. Households with a disabled member use fewer technologies.

35. ADDITIONAL CONCLUSIONS End-of-project targets for some indicators have been achieved and now need to be revised to encourage continued achievement. –Women with meaningful participation in decision making –HHs using supplementary feeding of animals

36. Photo Credit Goes Here Credit for all photos in this presentation: Abate Damte Jymdey Yeffimo, jymdey.yeffimo@kimetrica.com Thank you

37. Photo Credit Goes Here Annex

38. 4.5.2(34): Number of people implementing risk-reducing practices/actions to improve resilience to climate change as a result of USG assistance and 4.5.2(5): Number of farmers and others who have applied new (improved) technologies or management practices as a result of US assistance 4.8.2-26a Implementing risk-reducing practices/actions to improve resilience to climate change Information from households replying “Yes” to: – “In the last 12 months have you applied to your livestock or farm or participated in community actions to use any of the following technologies?” Calculated parameter: Applied to total # of households from ki-projects, after deducting overlap. Final calculation:

39. 4.5.2(23): Value of incremental sales at farm level attributed to feed the future implementation where and where reporting year mean sale is calculated using information from the AHS sections on value of livestock and dairy sales the number of beneficiaries is calculated from ki-projects during the reporting year, and takes into account the overlap factor

40. PPR-4.8.2-26: Number of stakeholders with increased capacity to adapt to the impacts of climate variability and change as a result of USG assistance 1.4.8.2-26a Implementing risk-reducing practices/actions to improve resilience to climate change – Calculated in the same way as indicators 4.5.2(34) and 4.5.2(5) 2.4.8.2-26b Using climate information in their decision-making – Calculated as: the percentage of households that have used at least one of: seasonal rainfall forecast, pasture conditions or water availability from one of: Early Warning Committee (EWC), Rangeland Council (RLC), Social Analysis and Action for Livelihood Adaptation (SAA) or Participatory Scenarios Planning advisories (PSP).

41. Percentage of women reporting meaningful participation in decision-making regarding economic activities, nutrition, NRM/governance Asked the most senior and knowledgeable woman member in each household how much input she had in each of 13 decisions listed in the questionnaire. Average number of income streams per household Calculated from the question: “Did you or any member of your household obtain income from any of the following sources in the last 12 months?”

42. Percentage of farmers/pastoralists who practice supplementary feeding for animals Calculated from the question: “Do you feed any of the following to your livestock?” To ensure sure that data were comparable to 2014, did not include households that used commercial feed mixture, as this option was not included in the 2014 survey and its inclusion considerably changes the estimates.

43. www.feedthefuture.gov