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M&E in ESA: progress and the way ahead

M&E in ESA: progress and the way ahead. Carlo Azzarri, Beliyou Haile, Cleo Roberts IFPRI M&E team ESA Review and Planning Meeting 9-11 September 2014 Arusha, Tanzania. Overview. M&E Activities in ESA Mega-site stratification by drivers of SI and creation of “development domains”

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M&E in ESA: progress and the way ahead

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  1. M&E in ESA: progress and the way ahead Carlo Azzarri, Beliyou Haile, Cleo Roberts IFPRI M&E team ESA Review and Planning Meeting 9-11 September 2014 Arusha, Tanzania

  2. Overview • M&E Activities in ESA • Mega-site stratification by drivers of SI and creation of “development domains” • Identification of representative control sites • Site visits and focus groups • Babati IE of fertilizer vouchers and improved maize seeds • Open access M&E data management platform (PMMT) dev’t and trainings (TZ: July 25--12 trainees; MWI: Aug 2--12 trainees; ZA: Aug 5--10 trainees) • FtFindicators reporting • Meetings (survey design, project review & planning, annual M&E) • ARBES: Malawi and Tanzania

  3. MARBES: sample distribution in MWI

  4. TARBES: sample distribution in TZA

  5. MARBES: village characteristics in MWI

  6. MARBES: MWI basic statistics/1

  7. MARBES: MWI basic statistics/2

  8. MARBES: MWI agric statistics/1

  9. MARBES: MWI ploughing methods

  10. MARBES: MWI agric statistics/2

  11. MARBES: MWI agric statistics/3

  12. MARBES: MWI farming system

  13. MARBES: MWI typologies/1

  14. MARBES: MWI typologies/2

  15. MARBES: MWI livestock statistics

  16. MARBES: MWI child anthropometrics

  17. TARBES: village characteristics in TZA

  18. TARBES: TZA basic statistics

  19. TARBES: TZA agricultural statistics/1

  20. TARBES: TZA ploughing methods

  21. TARBES: TZA agricultural statistics/2

  22. TARBES: TZA agricultural statistics/3

  23. TARBES: TZA farming system

  24. TARBES: TZA typologies/1

  25. TARBES: TZA typologies/2

  26. TARBES: TZAlivestock statistics/1

  27. TARBES: TZAlivestock statistics/2

  28. TARBES: TZAchild anthropometrics

  29. Conclusions Malawi -targeting- Action communities not different than control -the former slightly more remote- Beneficiaries seem to have different characteristics than the general population Tanzania -targeting- Action and control communities very similar Again beneficiaries seem to be better-off, more educated, with higher wealth, larger land size, etc. ->Implications for scaling-up? What about the external validity of ex-ante evaluation?

  30. Way ahead • ARBES public good/service for AR! (ESA ARBES data (partially) shared with MSU, WUR, ICRISAT, BioSight, Montpellier) • Targeting analysis, tentatively matching • Ex-ante evaluation (results by November) • Continuous monitoring (now…)

  31. Thank You!

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