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  1. 1. ReSAKSS2011 ATOR, Country SAKSS Progress Report, and 2012 Plans Sam Benin The CAADP 8th PP MEETING Hilton Hotel, Nairobi 3–4 May 2012 PARTNERSHIPS IN SUPPORT OF CAADP
  2. 2. Outline• Agricultural productivity study: feature topic of 2011 annual trends and outlook report (ATOR): in collaboration with IFPRI’s HarvestChoice program• Progress with establishment/strengthening of country SAKSS PARTNERSHIPS IN SUPPORT OF CAADP
  3. 3. Agricultural Productivity Study• How to raise and maintain high agricultural productivity across different parts of Africa? – fundamental and conceptual issues on the definition and measurement of agricultural productivity (temporal and spatial analysis) – more sophisticated analysis on understanding the determinants and drivers of agricultural productivity – seemingly-easy, but methodological- challenging case analysis of successful and failed agricultural productivity programs PARTNERSHIPS IN SUPPORT OF CAADP
  4. 4. Overview of Agricultural Productivity Study: Framework and Sequence A. Regional B. Key System Spatial Typologies for Characterization focusing of Agricultural productivity efforts Productivity (e.g. country x Opportunities & farming system) Challenges Focus Geographies/Systems Strategic Opportunities for Productivity D. Case Study Analysis C. Representative Farm of Factors Affecting the Enhancing Policies Analysis of Scale and Productivity Enhancing & Investments Options Sustainability of Productivity Growth PARTNERSHIPS IN SUPPORT OF CAADP
  5. 5. Measures of Productivity• Partial factor productivity (land and labor)• Total factor productivity and decomposition – efficiency arising from reallocation of productive factors – technical change arising from things that do not directly relate to the factors of production or the productivity of the factors PARTNERSHIPS IN SUPPORT OF CAADP
  6. 6. Trends and Spatial Patterns in Land and Labor Productivity PARTNERSHIPS IN SUPPORT OF CAADP
  7. 7. Land and labor productivity in SSA and sub-regions (1961-2009)Land productivity (2004-06 US$ Eastern & Central SSA Western (2004 PPP) Southern Labor productivity (2004-06 US$ PPP) PARTNERSHIPS IN SUPPORT OF CAADP
  8. 8. Land and labor productivity in selected countries (1961-2009)Land productivity (2004-06 US$ Ethiopia, 1993-2009 Nigeria (2004 Kenya PPP) South Africa Labor productivity (2004-06 US$ PPP) PARTNERSHIPS IN SUPPORT OF CAADP
  9. 9. Summary of Trends• Labor productivity has risen much faster than land productivity in Africa as a whole – particularly in the northern region a trend that is driven by Egypt• In SSA and many other countries, land productivity has risen much faster than labor productivity• In the southern Africa and in Morocco both measures have risen at about the same rate• General slowdown in the increase in both land and labor productivity in the 1990s than in preceding or subsequent sub-periods. PARTNERSHIPS IN SUPPORT OF CAADP
  10. 10. Spatial Patterns (annual avg. 2005-07) Land Labor• Land productivity • Closer for ECA ($690/ha) and SA ($756/ha); significantly higher in WA ($1300/ha) • In WA, rising from semi-arid Agro-Pastoral systems of the Sahel ($700/ha), through the higher rainfall Cereal- Root Crop system ($1293/ha) and Root Crop system ($2129/ha), to the sub-humid and humid Coastal PARTNERSHIPS Artisanal Fishing system ($2143/ha) IN SUPPORT OF CAADP
  11. 11. Trends in Total Factor Productivity (TFP) PARTNERSHIPS IN SUPPORT OF CAADP
  12. 12. Share (%) in Africa’s total AgGDP (annual average 2003-2010) Nigeria Egypt Morocco • Drivers of trends Algeria Sudan Kenya South Africa Ethiopia at Africa-wide Tanzania Côte dIvoire Cameroon Ghana level (top 9) Tunisia Congo, Dem. Rep. Uganda Libya Mali – Nigeria Mozambique Madagascar Zimbabwe Benin – Egypt Burkina Faso Guinea Niger Rwanda Senegal – Morocco Angola Zambia Chad Malawi – AlgeriaCentral African Republic Togo Sierra Leone Namibia Liberia – Sudan* Gabon Mauritius Mauritania Burundi Congo, Rep. of – Kenya Swaziland Botswana Gambia, The Equatorial Guinea – South Africa Guinea-Bissau Comoros Eritrea Lesotho Cape Verde – Ethiopia Djibouti Seychelles Somalia Sao Tome and Principe – Tanzania Mayote PARTNERSHIPS 0 5 10 15 20 25 IN SUPPORT OF CAADP
  13. 13. TFP in SSA (1961=1) 1961 1971 1981 1991 2001 TFP Eff Tech• Slight improvement in 1960s followed by a rapid deterioration in TFP and efficiency till mid-1980s and then recovery starting in 1984-1985• Very little technical change PARTNERSHIPS IN SUPPORT OF CAADP
  14. 14. Major Drivers of the trends in SSA: Nigeria and South Africa3 Nigeria21 • Nigeria exerts0 downward 1961 1971 1981 1991 2001 TFP Eff Tech pressure3 South Africa • South Africa2 exerts upward1 pressure0 1961 1971 1981 1991 2001 TFP Eff Tech PARTNERSHIPS IN SUPPORT OF CAADP
  15. 15. Annual Average Growth Rate in TFP by Region (%, 1985-2005) SSA Central Eastern Southern Western LI-1 LI-2 LI-3 MI SSA Geograpic Location Economic Classification Technical change Efficiency• High TFP growth in western, but little technical change• Southern Africa outperforms in technical change• Technical change in the central region was also high PARTNERSHIPS IN SUPPORT OF CAADP
  16. 16. -8 -6 -4 -2 0 2 4 6 8 10 Lesotho Senegal Swaziland Madagascar Gambia Zimbabwe Mauritania Mali Guinea Kenya Zambia Ethiopia Cote dIvoire Burkina Faso Guinea Bissau Technical change Cameroon Togo Sudan Mozambique Chad Tanzania Sierra Leone by country (%, 1985-2005) Benin performance for Big 9 agricultural economies South AfricaOF CAADPIN SUPPORT • Except South Africa, average or below average Efficiency GabonPARTNERSHIPS Malawi Annual Average Growth Rate in TFP Nigeria Ghana Angola
  17. 17. Factors Affecting Productivity• Typology of agricultural production (IFPRI spatial allocation model, several secondary and GIS data, and cluster analysis )• Typology of rural households (household survey data and cluster analysis)• Farm profit maximization analysis (household survey data and data envelopment analysis)• Case study analysis (22 cases out of 120 potential) PARTNERSHIPS IN SUPPORT OF CAADP
  18. 18. Typology of Production and Rural Households• Agricultural production (IFPRI spatial allocation model and data) – Farming systems (Dixon et al. 2001) – Normalized Difference Vegetation Index (NDVI) for agricultural potential – Market access – Population density• Typology of rural households (household survey data) – Human capital – Physical capital – Financial capital PARTNERSHIPS IN SUPPORT OF CAADP
  19. 19. Typology of Ag. Production in SSAFarming System Sub-systemTree-root crop Cassava+cocoa; Roots+cattle; LivestockHighlands Pulse+cassava+banana+cattle; Maize+ cattle; Cattle; Sheep/GoatsCereal-Root Crop Cattle; Sorghum/Millet+groundnut+ cattle; RootsMaize Mixed Roots; Maize+tobacco+cattle; Livestock; Sugarcane+cattlePastoral/Agro-pastoral Sorghum/Millet+groundnut; Rice+ livestock; Sorghum/Millet+livestock; Livestock; Maize+cattleIrrigatedLarge commercial and PARTNERSHIPSsmallholder IN SUPPORT OF CAADP
  20. 20. Characteristics of the tree-root crop farming system and subsystems Tree-Root Crop Farming System Cassava + Roots + cattle Livestock cocoaShare of total agricultural value in subsystem (%) Rice 5.2 6.7 1.2 Maize 4.1 9.3 2.4 Sweet potato 5.0 10.3 1.0 Cassava 10.8 16.5 3.8 Groundnut 1.7 6.0 1.2 Banana 8.5 8.3 1.9 Coffee 1.9 2.7 0.6 Cocoa 48.2 1.4 0.1 Cattle 1.7 10.1 43.0 Sheep/goat 2.2 4.3 29.6Share of total in farming system (%) Population 61.3 34.1 4.6 Crop area 55.0 40.7 4.3Production environment Pop. density high highPARTNERSHIPS high IN SUPPORT NDVI high high CAADP OF med
  21. 21. Rural households in tree-root crop farming system and subsystems: case of GhanaSub- Hhd type Physical Capital Financial Capital Main cropssystem Area & Input Machine Hired Access Income per assets intensity labor to loans capita 1 (TC1) +++ +++ - +++ ++++ ++++ Cassava, maize 2 (TC2) + ++++ - +++ ++++ ++++ Cassava, plantain,Tree maizeCrop 3 (TC3) +++++ +++++ + ++ +++++ +++++ Cassava/Yam, maize, cocoa 1 (CR1) +++++ ++ - ++ +++ +++ Sorghum/millet,Cereal- maize, groundnuts,Root riceCrop 2 (CR2) ++++ + - ++ ++ + Sorghum/millet, maize, groundnuts 1 (RC1) + + - +++++ +++ ++ Maize, groundnuts, roots 2 (RC2) + + - +++++ + +++ Yam, cassava 3 (RC3) + + - +++++ + ++++ YamRoot 4 (RC4) ++ + - ++++ ++ + Sorghum, maizeCrop 5 (RC5) + +++ - + ++ ++ Maize, groundnuts 6 (RC6) ++ ++++ - ++ ++ +++ Maize, groundnuts, cassava PARTNERSHIPS IN SUPPORT 7 (RC7) +++ ++ +++ +++ +++ + Groundnuts, maize OF CAADP
  22. 22. Ghana Farm Analysis Results ISubsystem Profit Land Labor Land and Hhd type eff. oriented oriented labor oriented profit eff. profit eff. profit eff.Tree crop 0.23 0.22 0.63 0.64Cereal-root crop 0.34 0.14 0.43 0.43Tree crop Type 1 0.23 0.23 0.60 0.62 Type2 0.23 0.23 0.66 0.67 Type 3 0.22 0.22 0.63 0.64Cereal-root crop Type 1 0.35 0.15 0.42 0.41 Type 2 0.33 0.14 0.43 0.43Profit efficiency in labor-direction measure ismuch higher than other efficiency measures PARTNERSHIPS IN SUPPORT OF CAADP
  23. 23. Ghana Farm Analysis Results II• Labor is the most limiting resource across all three subsystems and all household types – Shadow price of labor is much larger than that of land• Higher yields are related to more intensive use of labor than to input use• Thus, technical change and greater use of chemical inputs more likely to occur if channeled as part of a labor-saving technology package PARTNERSHIPS IN SUPPORT OF CAADP
  24. 24. Case Studies: conceptual framework5. Conditioning and 1. Problem identificationcross-cutting factors • Is the problem correctly diagnosed?• Participation or involvement of 2. Design and targeting • Right solution to the problem/socioeconomic beneficiaries (including conditions of an area? gender considerations) • Right area? Where the poor are located• Funding/Financial • Right enterprise (suitability, community needs) • Right beneficiaries (SHF) Resources• Complementary 3. Implementation interventions • Appropriate strategy• Necessary partnerships • Clarity of the intervention logic/result based?• Supporting • Adaptive Management? / Learning from M&E? Infrastructure 4. Sustainability• Supporting • Natural Resource Management (soil, water) policies, policy • Financing/ resource after (e.g. project end), instruments, legislation Maintenance costs • Beneficiaries motivated? Ownership and• Capacity building to the responsibility to sustain the success recipients PARTNERSHIPS IN SUPPORT OF CAADP
  25. 25. Case Study Findings I• Problem identification, targeting, and choice of commodity were generally well done in both successful and failed interventions – most of the interventions seem to be based on good needs assessment as well as local knowledge• Gender consideration and sustainability issues were problematic and not adequately incorporated in most of the reviewed case studies• With sustainability, main issue was little complementary funding to that provided by donors, and so many of the activities were not carried on once the projected ended PARTNERSHIPS IN SUPPORT OF CAADP
  26. 26. Unsuccessful Case Study Findings I• Conceptualization and design phase: – Imposed plans and top-down approaches that take no consideration of local community beliefs, preferences and perceptions; – Poorly defined or unrealistic scope of operation with no clearly defined objectives and time lines.• Start-up phase: – Limited coordination among stakeholders; – Poor implementation capacity of beneficiaries especially at the sub-national levels; – Lack of ownership and responsibility of the intervention by the recipient – Delays in project start up (release of funding and procurement of goods and services) PARTNERSHIPS IN SUPPORT OF CAADP
  27. 27. Unsuccessful Case Study Findings II• Project implementation and follow-up phase: – Lack of financial support to maintain the program e.g. no system to cater for the maintenance costs of irrigation infrastructure, cannot afford money to maintain boreholes, farmers cannot afford the high costs of fertilizers at the end of a subsidy program; – Farmer mistrust of programs due to past disappointments; – Leadership and management challenges—e.g. who should be in-charge of what remains at the end of the project period – Imported technologies with little or no local maintenance and spare parts. PARTNERSHIPS IN SUPPORT OF CAADP
  28. 28. Conclusions and Implications: raising and maintaining highagricultural productivity in Africa PARTNERSHIPS IN SUPPORT OF CAADP
  29. 29. Conclusions and Implications• Agricultural productivity growth in Africa, and particularly in SSA, has been impressive since the mid-1980s• But the performance represents a mere catching up with the levels achieved in the early 1960s, and there has been very little technical change• Sustaining growth in labor productivity faces challenge of population growth and slowdown in land availability• This will require policy improvements and significant investments in agricultural R&D an other investments that accelerate the expansion of Africa’s technical frontier PARTNERSHIPS IN SUPPORT OF CAADP
  30. 30. • AgR&D infrastructure and capacities have eroded over time through years of neglect, primarily from lack of public funding for agR&D. • Growth in spending on agR&D and number of researchers have only recently picked up; reflects the trends in agricultural productivity growth annual average growth rate (%) 6 5 4 3 2 1 0 1971-1981 1981-1991 1991-2001 2001-2008 1971-1981 1981-1991 1991-2001 2001-2008 PARTNERSHIPS IN SUPPORTSource: Beintema and Stads (2011) OF CAADP
  31. 31. 0 5 10 15 20 25 0 5 10 15 20 25 30 Angola Angola Benin Benin Botswana Botswana Burkina Faso Burkina Faso Burundi Burundi Cameroon Cameroon Central African… Central African… Chad Chad Comoros Comoros Congo, Dem. Rep. Congo, Dem. Rep. Congo, Rep. Congo, Rep. Côte dIvoire Côte dIvoire Djibouti Djibouti Egypt Egypt Ethiopia Ethiopia Gambia Gambia Ghana Ghana Guinea Guinea Guinea-Bissau Guinea-Bissau Kenya Kenya Lesotho Lesotho Liberia Liberia Madagascar Madagascar Malawi Malawi Mali Mali Mauritania Mauritania Mauritius Mauritius Morocco Morocco Mozambique Mozambique Namibia Namibia Niger Niger Annual Average (1995-2003) Annual Average (2003-2010) Nigeria Nigeria Rwanda Rwanda STP STP Senegal Senegal Seychelles Seychelles Sierra Leone Sierra Leone Sudan Sudan Swaziland Swaziland Tanzania TanzaniaExcept Ethiopia, none of Big 9 has achieved target Togo Togo Meeting the Maputo 10% target Tunisia Tunisia Uganda Uganda CAADP Zambia Zambia CAADP 10% target 10% target Zimbabwe Zimbabwe
  32. 32. How much is spent on agR&D? AgR&D spending as a share of agGDP (%), 2008 Source: Beintema and Stads (2011)• Only 8 of the 31 countries studied met the NEPAD 1% target• Except Kenya and South Africa, the other big agricultural economies spent less than 0.5 percent• The other high performers (Botswana, Burundi, Mauritania, Mauritius, Namibia, and Uganda) together account for only 3.2 percent of Africa’s total agGDP; little impact on the performance for Africa/SSA as a whole PARTNERSHIPS IN SUPPORT OF CAADP
  33. 33. How has the increase in agR&D expenditure been allocated? Ghana Tanzania Nigeria Uganda Source: Beintema and Stads (2011)• Ghana: mostly salaries• Tanzania: capital investments in 2002-2004 and operating costs in following years• Uganda: operating costs PARTNERSHIPS IN SUPPORT OF CAADP
  34. 34. What types of investment are needed?• Those that deliver location-specific technologies and account for diversity of potentials in and constraints faced by farmers – But many small economies and limited capacities and resources for developing effective agR&D systems – Regional agricultural R&D strategy can help fill these gaps and facilitate scale economies. – African centers of excellence initiatives are laudable – Need complementary polices and extension systems that enhances and maximizes the technology spillovers from centers to all places PARTNERSHIPS IN SUPPORT OF CAADP
  36. 36. SAKSS: Broker of Strategic Analysis/Knowledge Broker Demand Supply Parliament, PS, Policy Think Statistics Analysis Tanks, Centra Bureaus, Universiti FBOs, Donors, Units l Bank es, FBOs Directors SAKSS SAKSS SAKSS Network Oversight Body Node •Identify and sensitize •Express interest and• Credence of SAKSS in knowledge gaps buy into vision CAADP process •Synthesize knowledge •Align knowledge• Governance •Mobilize and coordinate generation activities• Channel knowledge knowledge generation •Receive funding and and evidence to policy •Facilitate training training makers •… •…•…
  37. 37. Country SAKSS Approach• Group countries – SAKSS-ready: Benin, DRC, Ethiopia, Ghana, Kenya, Malawi, Mali, Niger, Nigeria, Senegal, Tanzania, Togo (15) – SAKSS-sensitized: Burkina Faso, Burundi, Cape Verde, Central Africa Republic, Côte d’Ivoire, Gambia, Guinea, Guinea Bissau, Liberia, Mauritania, Seychelles, Sierra Leone, Swaziland, and Zambia (14) – SAKSS-beginning: remaining countries• Regional Workshop: SAKSS concepts and launch capacity needs assessment work (2 done, 3 to go)• Conduct capacity needs assessments: individual country reports and synthesis (complete by end June)• Develop and implement capacity strengthening strategy (start in July) PARTNERSHIPS IN SUPPORT OF CAADP
  38. 38. SAKSS: capacity strengthening activities Parliament, PS, Policy Think Statistics Analysis Tanks, Centra Bureaus, Universiti FBOs, Donors, Units l Bank es, FBOs Directors OB Node Network Level 100 Rationale and Concepts (CAADP; Policy Level 200 Analysis) Concepts and Application (Policy Analysis; Level 300 … Report Writing) Application and Modeling (CGE, Econometrics, Data Work)