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ETHIOPIAN DEVELOPMENT
RESEARCH INSTITUTE
Scaling up the Adoption of Improved
Technologies in Staple Food Production:
The C...
Introduction
• Agricultural growth matters
– Economic development and food security
– Low in Sub Saharan Africa
• Improved...
Introduction
• Lack of evidence on potential and impact of such
promotion campaigns
• Evaluation of on-farm productivity e...
BACKGROUND
Teff in Ethiopia
• Teff
– Major staple food
• 2 out of 3 Ethiopians consume teff daily
• Produced by 6 million farmers
• I...
Experimental Survey
• Rolled out in line with “pre-scale-up” phase (2013)
– Scientific recommendations and definitions int...
Survey outcome
Sample
Random (19)
n=537
Non-Random (17)
n=341
Compliers
n= 506
Non-compliers
n= 31
878 Farmers 36 Villages...
METHODOLOGY
Treatment effect
• The impact of promoting row planting
– Yield from crop-cut
– Reported yield after harvest
• Average Tre...
Randomized Control Trial
• Expected mean yield difference = ATT
– Assignment of treatment is independent of Yi and Ti
– Br...
Randomized Control Trial
Variable Traditional
Broadcasting
(n=173)
Row Planting
(n=333)
Mean Difference t-value
Household ...
Intention To Treat
• Imperfect compliance
– 6% are non-compliers
• Intention To Treat (ITT)
– No spill-over effects
– 𝑌𝑖 =...
Matching
• Full sample of farmers
• Possible selection bias because of purposive
selection
• Propensity Score Matching (PS...
RESULTS & DISCUSSION
Farm level
• RCT
– Positive, but non-significant, effect of row planting on
yields
Treatment
effect
Yield from crop-cut Re...
Heterogeneous effect
VARIABLES Yield from crop-cut harvest Reported yield after harvest
Level Interaction
with treatment
L...
Farm level
• Matching
– First stage: Probit model of selection
– Second stage: ATT; again positive effects but not signifi...
Village level
• Village level
– Plot is managed by an extension agent directly
– Stronger and significant effect
Yield fro...
Mechanisms
• Yield gap at farm level
– “Bad adoption”: plot management
– Roll out of promotion campaign
• “Problematic inp...
Mechanisms
Mechanisms Yield from crop cut reported yield after harvest
row planting
0.427*** 0.558***
(0.071) (0.149)
Bad ...
Farmers plans for next year
• Questions asked on plans after the experiment:
- Farmers overall positive and still planning...
CONCLUSION
Conclusion
• Large scale promotion campaign
– Low yields ask for adoption of new technologies
– Promising on-station resul...
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Scaling up the Adoption of Improved Technologies in Staple Food Production: The Case of Row Planting of Teff

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Scaling up the Adoption of Improved Technologies in Staple Food Production: The Case of Row Planting of Teff

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Scaling up the Adoption of Improved Technologies in Staple Food Production: The Case of Row Planting of Teff

  1. 1. ETHIOPIAN DEVELOPMENT RESEARCH INSTITUTE Scaling up the Adoption of Improved Technologies in Staple Food Production: The Case of Row Planting of Teff Joachim Vandercasteelen (LICOS, KU Leuven); Mekdim Dereje (EDRI, ESSP); Bart Minten (IFPRI, ESSP); and Alemayehu Seyoum Taffesse (IFPRI, ESSP) Ethiopian Economics Association (EEA) and the Econometric Society 19th Annual Conference of the African Region Chapter of the Econometric Society 12th International Conference on the Ethiopian Economy July 16-19, 2014 Addis Ababa 1
  2. 2. Introduction • Agricultural growth matters – Economic development and food security – Low in Sub Saharan Africa • Improved technology adoption crucial – Agricultural productivity to be increased – Welfare, food security and poverty implications – However, often not understood how to scale up adoption of technological innovations • We study effect of promotion campaigns – Transfer of knowledge and information – Awareness, teaching, training
  3. 3. Introduction • Lack of evidence on potential and impact of such promotion campaigns • Evaluation of on-farm productivity effects – Yield benefit at farm level using an experimental survey – Yield gaps • Specific study of row planting in teff production in Ethiopia – Low teff yield – Large scale promotion campaign
  4. 4. BACKGROUND
  5. 5. Teff in Ethiopia • Teff – Major staple food • 2 out of 3 Ethiopians consume teff daily • Produced by 6 million farmers • In value of production/area, most important crop – Low agricultural productivity • Limited knowledge • Constraints inherent to the crop (small seeds…) – Row planting • High agronomic yields • Promotion campaign – Package (fertilizer, improved seeds) – From 1,400 to 1,600,000 farmers targeted Broadcasting Row planting
  6. 6. Experimental Survey • Rolled out in line with “pre-scale-up” phase (2013) – Scientific recommendations and definitions intensively promoted during training days – Input provision (seed and fertilizer for free) – Selection and extension done by Development Agents (DAs) • 2 stage randomization approach – 4 Farmer Training Centers (FTC) in 9 Woreda’s of Oromia – 10 farmers row planting/ traditional broadcasting • Experiment – Farm and village level – Experimental plot of 300 m² – Free improved seed and fertilizer
  7. 7. Survey outcome Sample Random (19) n=537 Non-Random (17) n=341 Compliers n= 506 Non-compliers n= 31 878 Farmers 36 Villages 187 village demonstration plots
  8. 8. METHODOLOGY
  9. 9. Treatment effect • The impact of promoting row planting – Yield from crop-cut – Reported yield after harvest • Average Treatment effect on the Treated (ATT) • 𝑌𝑖 = 𝛼 + 𝛽 ∗ 𝑇𝑖 + 𝜀𝑖 • Identification of program effect – Confounding factors – Control group (counterfactual) – Sample selection bias
  10. 10. Randomized Control Trial • Expected mean yield difference = ATT – Assignment of treatment is independent of Yi and Ti – Broadcasting and row planting farmers are statistically identical • Balancedness of random sample – Household characteristics • Demographics, education, assets – Experimental plot characteristics • Plot quality, input use, production practices • But plot size – Unobserved heterogeneity • 𝑌𝑖𝑡 = 𝑐𝑖 + 𝛽 ∗ 𝑋𝑖𝑡 + 𝜀𝑖𝑡 • Management, intellectual capacities, networks
  11. 11. Randomized Control Trial Variable Traditional Broadcasting (n=173) Row Planting (n=333) Mean Difference t-value Household head characteristics Age (years) 43.8 -0.80 -0.72 Gender (male=1) 99.4 -2.73 -2.39** Literacy (yes=1) 68.9 4.79 -1.12 Primary education (yes=1) 65.9 3.17 0.72 Household characteristics Distance to FTC (minutes) 34.2 -0.60 -0.26 Household size (members) 7.1 -0.18 -0.86 Total agricultural assets value (ln of ETB) 6.8 0.00 0.03 Total assets value (ln of ETB) 7.2 0.14 0.72 Income from other activities (yes=1) 76.3 -7.83 -0.96 Experimental plot Area (m²) 599.5 -161.80 -4.29*** Number of plows (number) 4.9 0.04 0.29 Number of weedings (number) 1.9 0.07 0.66 Organic input used (yes=1) 11.6 -2.25 -0.77 Inorganic fertilizer used (yes=1) 99.4 -0.32 -0.42 Manure used (yes=1) 10.0 -3.20 -1.12 Rate of Urea used (g/m²) 9.2 1.91 1.06 Rate of DAP used (g/m²) 11.7 0.19 1.04 Rate of herbicides used (100 ETB/m²) 2.0 -0.11 -0.37 Teff characteristics in Meher 2011/2012 Teff cultivated in both seasons (yes=1) 0.7 0.01 0.21 Average teff area (ha) † 0.6 0.01 0.24 Average teff yield (ton/ha) † 0.9 0.08 1.61 Farmers’ unobserved heterogeneity (.) † 1.6 0.04 1.05
  12. 12. Intention To Treat • Imperfect compliance – 6% are non-compliers • Intention To Treat (ITT) – No spill-over effects – 𝑌𝑖 = 𝛼 + 𝛽 ∗ 𝑆𝑖 + 𝜀𝑖
  13. 13. Matching • Full sample of farmers • Possible selection bias because of purposive selection • Propensity Score Matching (PSM) – Estimate Propensity Score – Yield difference between matched farmers
  14. 14. RESULTS & DISCUSSION
  15. 15. Farm level • RCT – Positive, but non-significant, effect of row planting on yields Treatment effect Yield from crop-cut Reported yield after harvest control row planting Control row planting Coefficient 1.096*** 0.015 1.147*** 0.116 ATT se (0.049) (0.065) (0.051) (0.075) Observations 403 506 Coefficient 1.132*** 0.108 ITT se (0.051) (0.072) Observations 531
  16. 16. Heterogeneous effect VARIABLES Yield from crop-cut harvest Reported yield after harvest Level Interaction with treatment Level Interaction with treatment Row planting (yes=1) 0.653 0.120 (0.555) (0.543) Age of household head (years) 0.002 -0.002 0.004 0.011 (0.004) (0.006) (0.004) (0.008) Primary education household head (yes=1) 0.077 -0.175 0.234** -0.178 (0.094) (0.138) (0.096) (0.169) Gender of household head (male=1) -0.774*** 0.332 -0.805*** 0.341 (0.010) (0.368) (0.084) (0.313) Farm size (ln of ha) 0.047 -0.048 0.045 -0.051 (0.038) (0.043) (0.060) (0.079) Size of the household (number of persons) 0.052 -0.042 0.048 -0.046 (0.037) (0.043) (0.032) (0.042) Experimental plot size in line with guidelines (yes=1) -0.048 -0.208 0.204* -0.173 (0.043) (0.156) (0.109) (0.157) Constant 0.955*** 0.957*** (0.336) (0.321) Observations 403 0.045 506 0.045R-squared
  17. 17. Farm level • Matching – First stage: Probit model of selection – Second stage: ATT; again positive effects but not significant Matching algorithm Yield from crop-cut Reported yield after harvest Observations Row-planters 456 541 Controls 293 371 Nearest Neighbor Matching (NNM) ATT 0.027 0.060 Standard error (0.070) (0.076) Kernel Matching (KM) ATT 0.056 0.078 Standard error (0.058) (0.065) Radius Matching (RM) ATT 0.028 0.057 Standard error (0.058) (0.065)
  18. 18. Village level • Village level – Plot is managed by an extension agent directly – Stronger and significant effect Yield from crop-cut ATT 0.307** Standard error (0.117) Control 1.016*** Standard error (0.108) observations 187
  19. 19. Mechanisms • Yield gap at farm level – “Bad adoption”: plot management – Roll out of promotion campaign • “Problematic input supply” • “Extension quality” • Tested by interaction effects: – Seed rate different w.r.t. scientific recommendations – Receiving inputs too late – Yield benefit achieved by DA at village level
  20. 20. Mechanisms Mechanisms Yield from crop cut reported yield after harvest row planting 0.427*** 0.558*** (0.071) (0.149) Bad adoption° 0.001 0.000 (0.004) (0.001) Bad adoption * row planting -0.005*** -0.005*** (0.001) (0.001) Problematic input supply -0.254*** -0.201* (0.060) (0.101) Problematic input supply * row planting -0.144 -0.636** (0.123) (0.235) Extension quality° 0.020*** -0.001 (0.004) (0.010) Extension quality * row planting 0.022** 0.040*** (0.008) (0.011) Constant 1.064*** 1.125*** (0.052) (0.084) °=normalized with Kebele average difference
  21. 21. Farmers plans for next year • Questions asked on plans after the experiment: - Farmers overall positive and still planning to continue but on limited areas, possibly because of labor demand issues Percentage 1. “Will you allocate some part of your teff area to row planting?” 73% 2. “Share of the total teff production land allocated to row planting next year” 19% 3. “The major reasons for not doing row planting next year” (top three): - “Too much additional labor” 96% - “Difficulty of doing row planting after rain” 25% - “It does not give higher yields” 16%
  22. 22. CONCLUSION
  23. 23. Conclusion • Large scale promotion campaign – Low yields ask for adoption of new technologies – Promising on-station results – No empirical evidence • Promotion of row planting to increase yield in the first year – Moderate farm level effect on yields, seemingly partly explained by some issues with respect to implementation • Implications: – Higher effects found in recent ATA study on effect of TIRR package (improved seed + row planting): 44% increase in yield – Might be explained by learning-by-doing? Improved implementation afterwards? Package approach? External validity issues? Further monitoring and evaluation required that could help improve adoption processes of improved technologies – Mechanization potential to reduce labor issues?

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