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Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
Strategies for Raising and  Sustaining High Agricultural  Productivity in Africa_2011
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Strategies for Raising and Sustaining High Agricultural Productivity in Africa_2011

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"Strategies for Raising and Sustaining High Agricultural Productivity in Africa", presented at Agricultural Productivity and Food Security in Africa Conference, Addis Ababa,1-3 November 2011 …

"Strategies for Raising and Sustaining High Agricultural Productivity in Africa", presented at Agricultural Productivity and Food Security in Africa Conference, Addis Ababa,1-3 November 2011

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  • 1. 1-3 November 2011 UNECA, Addis Ababa Strategies for Raising and Sustaining High Agricultural Productivity in Africa ReSAKSS Plenary session Chair: Samuel Benin Presenters: Zhe Guo, Bingxin Yu, Alejandro Nin Pratt, Stella Massawe Research Team: Stan Wood, Melanie Bacou, Linden McBride,Joseph Karugia, Paul Guthiga, Maurice Ogada, Emmanuel Musaba, Pius Chilonda, Precious Zikhali, Mbaye Yade, Manson Nwafor, Maurice, Taondyande, Claude Bizimana
  • 2. Strategic Analysis and Monitoring of CAADPReSAKSS organized around and Agricultural Performance in Africa 4 nodes of operation Knowledge Management, Capacity Strengthening, and Policy Communications support review and dialogue evidence- and outcome-based planning and implementation of agricultural-sector policies and strategies in Africa
  • 3. Background to this Study• CAADP provides an agriculture-led integrated framework of development priorities for reducing poverty and hunger and increasing food security – CAADP target: 6% AgGDP growth rate per year – Possible for many African countries – Substantial investments required (greater than the 10% target in many cases) because of moderate and slow productivity growth
  • 4. As countries enter operational phase of investment program design and execution,Key Question: how to raise and maintain high agricultural productivity across different parts of the continent?
  • 5. ReSAKSS 2011 M&E work• Answer above question, which requires addressing several follow-up questions: – Fundamental and conceptual: definition and measurement of agricultural productivity – Complex: understanding the determinants and drivers of productivity – Challenging: program design and implementation by translating the knowledge into effective action
  • 6. What is “Productivity”?• Partial Factor Productivity – Land Productivity Yield = Output / Harvested area – Labor Productivity LP = Output / Total hours worked  Useful measures but:  do not measure productivity of all resources  can lead to misleading policy prescriptions
  • 7. Land and Labor Productivity in SSA, 1961-2009 Land productivity (2004-06 US$ PPP) Labor productivity (2004-06 US$ PPP)SSA as a whole: labor productivity >> land productivity; butland productivity increased much faster, more than tripled
  • 8. As expected, different picture whenconsider different sub-regions of Africa Eastern &Land productivity (2004-06 US$ Central SSA Western PPP) Southern Labor productivity (2004-06 US$ PPP)
  • 9. Again, different picture when considerdifferent countries Land productivity (2004-06 US$ Ethiopia, 1993-2009 Nigeria Kenya PPP) South Africa Labor productivity (2004-06 US$ PPP)
  • 10. Total Factor Productivity• Productivity of a production unit (farm, district, region, country, etc) is the ratio of the outputs that it produces to the inputs it uses to produce those outputs Total Output• TFP = Total Inputs• Agricultural growth in the long run depends on TFP – Efficiency: reallocation of productive factors – Technical change: technological advancement
  • 11. TFP growth in SSA Two different periods: both driven more by efficiency change than technical change 1.01 1 TFP levels 1970=1 0.99 0.98 0.97 0.96 0.95 1970 1975 1980 1985 1990 1995 2000 2005 Growth Rate (%) TFP components 1970-1984 1985-1994 1995-2009 Efficiency change -0.28 0.07 0.15Based on Technical change -0.03 0.05 0.10FAOSTAT TFP -0.32 0.12 0.25
  • 12. More workers; and Less land and inputs per worker Yield Labor productivity TFP 2 1.8 TFP (green) 1.6 Index 1970=1 1.4 Yield (blue) 1.2 1 Labor productivity (red) 0.8 1970 1975 1980 1985 1990 1995 2000 2005 Inputs/Ha Inputs/Worker HA/worker 21.81.6 Inputs per hectare (brown)1.41.2 1 Inputs per worker (yellow)0.80.6 Land-labor ratio (pink)0.4 1970 1975 1980 1985 1990 1995 2000 2005
  • 13. Livestock, root crops, and oil crops explainmore than 60% of output growth in 1995-2009 Contribution to growth Share in output 30% 25% 20% 15% 10% 5% 0%
  • 14. Best performing countries (annual average growth rates, 1995-2009) Yields Labor productivity TFPMozambique 3.50 2.72 2.32Angola 6.62 4.28 1.97Rwanda 3.26 2.56 1.79Tanzania 3.59 2.01 0.67Ethiopia 2.49 1.87 0.65Côte dIvoire 1.91 1.94 0.62Senegal 2.39 1.01 0.43Niger 4.53 1.99 0.40Zambia 3.92 2.51 0.37Ghana 2.33 3.19 0.27Mali 1.72 3.08 0.25
  • 15. Why is agricultural productivity growth in SSA so low?• Intrinsic lower productivity of natural resources?• No technology available?• Poor infrastructure, high transaction costs and constrained market access?• Policy: high prices of inputs as a result of distortions?• Underdeveloped markets, institutions?
  • 16. No simple answers• Multiple factors interacting differently – Natural resource quality – Population pressure – Infrastructure – Distance to major markets and road density – Market for outputs, inputs and services, labor markets – Policies and government interventions – Household characteristics• This diversity suggests that spatial heterogeneity matters and that answers should be geographically focused
  • 17. Overview of Session (and Study) Framework and Sequence A. Regional Spatial B. Key System Typologies Characterization of for focusing productivity Agricultural Productivity efforts (e.g. country x Opportunities & farming system) Challenges Focus Geographies/Systems D. Case Study Analysis of C. Representative Farm Factors Affecting the Scale Analysis of Productivity and Sustainability of Enhancing Options Productivity Growth
  • 18. Spatial Dimensions of Agricultural Productivity Zhe Guo and Stanley Wood HarvestChoiceInternational Food Policy Research Institute z.guo@cgiar.org
  • 19. Regional Spatial Data/Analysis Platform• A harmonized set of spatial variables, conformed to a standardized 10km (5 arc minute) grid covering the whole of Africa (focusing on SSA), generated by HarvestChoice.• About 300,000 grid cell records each with 200+ gridcell attributes. Attributes range from observed, e.g. rainfall through imputed, e.g. poverty, to highly-modeled, e.g. potential maize yields under different management practices.• Provides a basis for undertaking consistent region-wide assessment of agricultural development opportunities and constraints, such as the ReSAKSS productivity study.• Facilitates regional targeting and prioritization of agricultural development hotspots, e.g. AGRA breadbaskets, Feed the Future Farming Systems, Gates Ag. Development Strategy, CGIAR CRPs** As well as the type of regionally-strategic, agroecosystem-based concentration zones foragricultural production and processing proposed by Josue Dione in his plenary address.
  • 20. Spatial variables influencing productivity• Agricultural potential• Footprint of agriculture• Market access• Demographics• Human welfare
  • 21. Agricultural potentialRainfall & Length of Growth Period Long term average of annual rainfall Length of growth period
  • 22. Agricultural potentialNormalized Difference Vegetation Index & Potential Yield 7 Maize Yield Potential 6 t[DM]/ha 5 4 3 2 40 1 30 20 0 10 Irrigation 0 100 Threshold 80 NA % of Available 60 40 Fertilizer Application Rate 20 Soil Water 0 kg[N]/ha Long term average of NDVI Simulated potential yield
  • 23. Footprint of agricultureCrop Land & Pasture Land Cropland density Pasture land density
  • 24. Footprint of AgricultureFarming System & Crop Farming systems Maize harvested area
  • 25. Footprint of AgricultureProductivity Constraints Aluminum toxic Drought severity
  • 26. Market AccessTravel time to major settlementsTravel time to market with population Travel time to market withgreater than 20,000 population greater than 500,000
  • 27. Market AccessTravel Time to Ports Travel time to major ports Major port command area
  • 28. DemographicsPopulationPopulation density (GRUMP 2000) Population density Landscan 2009
  • 29. Human WelfarePoverty & Global Hunger Index Absolute number of poor Global Hunger Index living under $1.25 per day
  • 30. Flexible approach to spatial aggregation and analysis POVERTY (1000 people) FS_NAME E S W Total Cum % Cereal-root crop mixed 2,764 11,811 30,570 45,145 15.5 Maize mixed 28,065 16,277 9 44,352 30.7 Root crop 14,219 2,451 27,644 44,314 45.9 Agro-pastoral millet/sorghum 384 1,868 24,729 26,981 55.1 Forest based 20,365 87 3,535 23,988 63.3 Highland perennial 23,278 23,278 71.3 Tree crop 1,569 541 17,199 19,308 77.9 MAIZE AREA (1000 ha) FS_NAME E S W Total Maize mixed 2,860 3,197 0 6,057 24.2 Cereal-root crop mixed 128 1,214 2,718 4,059 40.4 Large commercial_smalholder 3,440 3,440 54.1 Root crop 711 329 2,228 3,268 67.2 Tree crop 145 4 1,647 1,796 74.3 HIGH PHOSPHORUS FIXATION (SHARE OF GRID CELL AREA, %) TRAVEL TIME TO CLOSEST PORT (hours) E S W Total FS_NAME perennial Highland E S 34.0 W Total 34.0 Forest based Coastal artisanal fishing 15 14.0 22 26.0 15 15.0 15 16.0 Tree crop Large commercial_smalholder 13.0 19 37.0 9.0 19 12.0 Tree crop Highland temperate mixed 17 13.0 16 11.0 20 8.0 19 11.0 Maize mixed Highland temperate mixed 26 17.0 18 6.0 19 6.0 21 11.0 Rice-Tree crop 26 26
  • 31. Example of Potential RegionalDevelopment Strategies Ag. Mkt Pop Pot. Access Density Potential Development StrategiesHigh High High HHH Perishable cash crops HHH Dairy, intensive livestock HHH Non-perishable cash crops HHH Rural non-farm development Low High HLH Non-perishable cash crops HLH High input perennials HLH Livestock intensification, improved grazingMedium High High MHH High Input cereals MHH Perishable cash crops MHH Dairy, intensive livestock MHH Rural non-farm development Low High MLH High Input cereals MLH Non-perishable cash crops MLH Livestock intensification, improved grazingLow High High LHH with irrigation investment LHH High Input cereals LHH Perishable Cash Crops LHH Dairy, intensive livestock LHH Rural non-farm development Low Low LLL Low input cereals LLL Limited livestock intensification LLL Emigration Source: ASARECA Strategy. Omamo et al. 2006
  • 32. Summary• We use a region-wide, consistent, high-resolution spatial database to underpin our efforts to; • delineate and characterize regionally-significant focus areas • identify the nature and severity of specific productivity constraints & opportunities• Enables the study to take account of spatial (and spatio-temporal) heterogeneity of conditions under which we seek to raise productivity• Provides a framework for scaling up/out the results of the farm level and case study analyses
  • 33. A Typology ofAgricultural Productivity Zones Bingxin Yu International Food Policy Research Institute b.yu@cgiar.org
  • 34. Overview of Session (and Study) Framework and Sequence A. Regional Spatial B. Key System Typologies Characterization of for focusing productivity Agricultural Productivity efforts (e.g. country x Opportunities & farming system) Challenges Focus Geographies/Systems D. Case Study Analysis of C. Representative Farm Factors Affecting the Scale Analysis of Productivity and Sustainability of Enhancing Options Productivity Growth
  • 35. Farming Systems• Spatial heterogeneity exists• Common pattern across country border• Concept of farming systems • Bridge between macro (regional, national) and micro (household, pixel) analysis • Identify pathways of technology adoption and agricultural productivity growth • Design localized agri. development strategy and policy intervention based on sub-system
  • 36. Farming Systems – cont’d• Similarity in agricultural potential/ existing production pattern• Definition: farmers, resources, interactions• Biophysical, socio-economic and human elements interdependent• Biophysical: land, water, forest, climate• Human: demography• Socio-economic : market access
  • 37. Approach• Expand FAO definition of farming system• Quantify factors affecting productivity of each farming system • Agricultural activities • Agricultural potential • Population density • Market access • Nuance within each farming system
  • 38. Methodology Spatial and Statistical Methods1. Combine similar FAO farming systems2. Sub-national spatial info • Crop and livestock production • Socio-economic indicators3. Identify appropriate number of groups4. Define groups within each farm system based on major agricultural activities
  • 39. Data• Country X farming system X agricultural potential• Crop and livestock output value (SPAM and FAO international prices)• Population density• Market access• Agricultural potential (NDVI)
  • 40. 6 Major Farming SystemsUnique constraints and comparative advantagesFarming Pop. Marketsystem density access Population Crop area Livestock per ha hours million million ha mill. coweqTree-rootcrop 0.4 7.0 99.3 28.3 27.3Forest based 0.1 10.5 43.1 5.1 5.5Highlands 1.0 6.1 70.5 8.0 38.2Cereal-rootcrop 0.3 6.4 83.1 30.3 61.0Maize mixed 0.3 7.9 91.0 16.9 46.7Pastoral 0.2 9.6 83.2 33.0 77.4
  • 41. Tree-Root Crop Farming System• Value share • Major activities • cassava • sweet potato • cocoa • cattle • banana/plantain • ricegoat/sheep groundnut maize • maizerice banana cattleother cocoa sweetpotato • groundnutcassava • goat/sheep
  • 42. Tree-Root Crop Farming System West and Central Africa• Statistics determine 3 distinctive groups Sub- Dominant agri. Population Agricultural Market system activities density potential access Maize + banana 1 + cattle high medium medium Rice + sweet 2 potato + cocoa medium high high 3 roots high high low
  • 43. Forest-Based Farming System• Major activities: rice, sweet potato, cassava, groundnut, banana/plantain, coffee, cattle, pig/chicken Sub- Dominant agri. Population Agricultural Market system activities density potential access 1 Rice + cattle low high low Cassava + 2 banana low high very low 3 Root + banana low high very low 4 Coffee high low very low
  • 44. Highlands Farming System • Major activities: maize, pulses, sweet potato, cassava, banana, cattle, sheep/goatSub- Dominant agri. Population Agricultural Marketsystem activities density potential access Maize + sweet1 potato + livestock high medium medium Cattle dominate2 livestock very high medium medium3 Maize + cattle high medium low4 Roots + cattle high high medium Pulse + sweet extremely5 potato + banana high high medium
  • 45. Cereal-Root Crop Farming System• Major activities: rice, maize, sorghum/ millet, pulse, sweet potato, cassava, groundnut, cotton, cattle, sheep/goat Sub- Dominant agri. Population Agricultural Market system activities density potential access 1 Cassava medium high medium 2 Cattle medium medium medium sorghum/millet + groundnut + 3 cattle high medium medium
  • 46. Pastoral Farming System• Major activities: maize, sorghum/millet, pulse, cassava, groundnut, cattle, sheep/goatSub- Dominant agri. Population Natural Marketsystem activities density endowment (NDVI) access1 Cattle medium medium low sorghum/millet +2 pulse + cattle medium low high Cattle dominate3 livestock low medium very low Maize + cassava4 + cattle low medium low sheep/goat extremely extremely5 dominant livestock low low low
  • 47. Maize Mixed Farming System East and Southern Africa• Major activities: maize, sorghum/millet, pulse, cassava, sugarcane, tobacco, cattle, sheep/goatSub- Dominant agri. Population Agricultural Marketsystem activities density potential access Maize + tobacco +1 cattle medium high low2 Tobacco + cattle medium medium medium3 Sugarcane + cattle medium medium medium Cattle dominate4 livestock high medium low
  • 48. Heterogeneity within a Country case of Ethiopia • Identify comparative advantages Sorghum Sheep/ Sub- Maize / millet Cattle goat Agricultural MarketFarm system system share share share share Pop. den potential accessHighlands 2 10.1 4.8 55.5 7.4 high high lowCereal-root verycrop 2 6.9 5.2 63.5 8.9 high medium lowMaize verymixed 3 8.4 8.7 51.8 9.2 medium medium lowPastoral 1 9.9 13.7 46.9 7.9 medium medium lowPastoral 5 4.0 25.3 17.4 47.5 medium high medium
  • 49. Determinants of Agricultural Productivity Growth andEconomic Analysis of Alternative Strategies Alejandro Nin Pratt International Food Policy Research Institute a.ninpratt@cgiar.org
  • 50. Overview of Session (and Study) Framework and Sequence A. Regional Spatial B. Key System Typologies Characterization of for focusing productivity Agricultural Productivity efforts (e.g. country x Opportunities & farming system) Challenges Focus Geographies/Systems D. Case Study Analysis of C. Representative Farm Factors Affecting the Scale Analysis of Productivity and Sustainability of Enhancing Options Productivity Growth
  • 51. The Case of Maize Other, 23% Maize- mixed, 39% Tree- root crop, 20% Cereal-root crop, 18%
  • 52. 1) Identify predominant production systems grouping households with similar crops Maize- Permanent Beans-maize specialized crops-maizeShare in regional maize 45% 10% 46%productionNumber of households 0.86 0.45 2.2Share of maize in output 77% 23% 25%value
  • 53. 2) Identify groups of households within theprevious groups that are different in theirbehavior and welfare under differentscenarios• Input use• Assets• Labor• Sales and market access
  • 54. Maize- Perm. Crops- specialized maize Low High Low High inputs inputs inputs inputs% over total households 18 3 47 6Yield (Kgs/HA) 1,319 2,610 1,049 2,519Value of inputs/HA 2.9 151 14 184ASSETSArea (HA) 1.3 1.5 1.86 2.44Cow equivalents/HA 1 1.15 2.23 1.89Value of equipment/HA 70 81 78 102LABORFamily work days 156 106 176 165Hired work days 36 23 31 63SALESMaize sales as share of output % 18 24 11 10Total sales/output value % 9 11 50 36
  • 55. 3) Use this information in household models• Simulate household behavior given – Available technologies for different crops and livestock activities – Cash constraint – Labor constraint – Land constraint – Transaction costs• Understand the importance of different constraints on household decisions
  • 56. 4) Link household models in an economy-wide model• Analyze impact of different events on individual household decisions and the effect of these decisions on other households and the economy – Output prices in local, regional and national markets – Labor markets – Consumption and demand• Derive policy implications
  • 57. Case Studies of Productiveand Sustainable Agricultural Investment Programs Joseph Karugia and Stella Massawe International Livestock Research Institute s.massawe@cgiar.org
  • 58. Overview of Session (and Study) Framework and Sequence A. Regional Spatial B. Key System Typologies Characterization of for focusing productivity Agricultural Productivity efforts (e.g. country x Opportunities & farming system) Challenges Focus Geographies/Systems D. Case Study Analysis of C. Representative Farm Factors Affecting the Scale Analysis of Productivity and Sustainability of Enhancing Options Productivity Growth
  • 59. Learning from successes and failures• Positive or negative outcomes provide useful basis for learning.• Incorporating lessons in the design and implementation of agricultural interventions-better quality• How do we define success? – Increase in yields, agricultural labour productivity, introduction of new higher- value enterprise
  • 60. Framework for reviewing SPATIAL VARIATION the case studies
  • 61. Wei Wei Integrated project in Kenya• Initiated in 1987, outputs were: – Construction of intake weir on the Wei Wei river; – Laying of an underground steel and PVC pipeline network to distribute water through gravity-fed sprinkler irrigation units on each plot; – Reclaiming and improving over 700 hectares of land; Setting up of a pilot farm of 50 hectares to provide logistical, equipment and other inputs support to the whole scheme; – Developing and allocating 540 individual plots of 1 hectare each.• The project has generated a number of benefits to the community: – Crop yields, earnings and food security: maize and sorghum yields have increased from a paltry 0.5 tonnes/ha to 3.5 tonnes/ha and 4 tonnes/ha, respectively. – New crops such as green grams, cow peas and okra were introduced.
  • 62. Wei Wei Integrated project continued• The project has also created employment and income-generation opportunities, either on the farms or through commerce• Adoption of innovations, not only within the project area but also in those areas outside the project. The community members are expanding land under irrigation on their own initiative;• Strengthening social capital through increased commercial activities. The farmers have also organized themselves into groups to negotiate for better prices for their produce.• Lessons: Community involvement, introduced in an area with a tradition of irrigation, complementary investments, cost effectiveness of the irrigation approach used, capacity building, government support
  • 63. Investment on Irrigation through ASDP in Tanzania• Since 2006, rehabilitated old irrigation schemes and constructed some new ones• As a result of the schemes, the area under irrigation increased from 264,388 ha in the year 2006/2007 to 317,245 ha in 2010 (20 % increase) 2006 2009 Average Rice yields in 1.8 to 2.0 4.0 to 5.0 irrigation schemes (t/ha) Rice yields in Mbeya 1.5 2.0-2.5 Rice yields in Morogoro 1.5 5 Rice yields in Manyara 1.5 6 Maize yield in Siha 0.7 3.5-4.5 Onions From one season per year Three seasons per year. Each season 60 bags Factors for success: involvement of the farmers, government support, complimentary investments
  • 64. Bura Irrigation Scheme in Kenya• In Tana River District, started in 1981 production of cotton, maize and groundnuts, vegetables• No cash crops planted for 15 years (from 1990-2005), no subsistence crops for 9 years (1994-2002): frequent breakdowns of the Nanighi Pumping Station or lack of adequate funds to operate the pumping units, lack of water• Famine, increased poverty levels and unemployment for the Scheme farmers and community; at some point, farmers at the project were relying on famine relief food supplies.• The irrigation canal network was heavily silted up covered by bushes• Management challenges, several changes. In 2005, the Scheme was taken over by NIB
  • 65. Hifadhi Ardhi Dodoma (HADO) in Tanzania• Soil rehabilitation in Kondoa District; very deep gullies• The objective was to reclaim degraded lands and improve agricultural and livestock keeping productivity by primarily enabling the local farmers to adopt effective land husbandry practices.• Specific objectives: i) Ensure self-sufficient in wood requirements; ii) Encourage communal wood-growing schemes in the region; iii) Promote communal bee keeping and other income generating activities; iv) Encourage the establishment of shelter belts, windbreaks, shade trees, avenues and fruit tree growing; v) Conserve soil and water and to reclaim depleted land.• The approach was top-down with little real participation of the local people in planning and implementing project activities. It emphasized cattle de-stocking, soil conservation measures such as contour banking and tree planting for shelterbelts, agro forestry and village woodlots.• In severely eroded areas, cattle were excluded, effectively evicting their owners as well.
  • 66. HADO Cont’d• The HADO programme did demonstrate that restoration of vegetative cover on some degraded semi-arid lands is possible.• No baseline study was carried out at the beginning of the project, consequently, no basis for comparison• Though large areas were conserved, the project was criticized for relocating people.• Lessons: HADO project was a failure, mainly because: – Like the earlier efforts in the colonial period, HADO was a top-down and technocratic project with little real participation by the local people in setting goals or in designing and implementing the project; – A multi-disciplinary approach was not used, so forestry technical staff did all rehabilitation work – Through the eviction of farmers the project exported problems elsewhere.
  • 67. Key Messages• Proper targeting: correct intervention for the Farming system?• Involvement of the local communities and appropriate partnerships• Correct implementation strategies: Avoid extreme actions drastic measures, targeting issues• Invest in capacity; financial, technical, managerial• Ensure supporting policy and institutional environment• Complementary interventions• Conditions for sustainability
  • 68. Next Steps
  • 69. Overview of Session (and Study) Framework and Sequence A. Regional Spatial B. Key System Typologies Characterization of for focusing productivity Agricultural Productivity efforts (e.g. country x Opportunities & farming system) Challenges Focus Geographies/Systems Strategic Opportunities for D. Case Study Analysis of Productivity C. Representative Farm Factors Affecting the ScaleEnhancing Policies & Analysis of Productivity and Sustainability of Enhancing Options Investments Productivity Growth
  • 70. Some Discussion Points• How can we improve the analysis  implementable results? – Data, methods, …• What are key case studies (specific agricultural productivity) investment programs to learn from – both successful and not-successful?• …

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