Policies and Productivity Growth in African Agriculture
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Policies and Productivity Growth in African Agriculture

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By Keith Fuglie and Nicholas Rada. ...

By Keith Fuglie and Nicholas Rada.
Presented at the ASTI-FARA conference Agricultural R&D: Investing in Africa's Future: Analyzing Trends, Challenges, and Opportunities - Accra, Ghana, December 5-7, 2011. http://www.asti.cgiar.org/2011conf

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Policies and Productivity Growth in African Agriculture Presentation Transcript

  • 1. Policies and Productivity Growth in African Agriculture Keith Fuglie and Nicholas Rada* Economic Research Service U.S. Department of Agriculture Washington, DC*The views expressed in this presentation are the authors’ own and not necessarily those ofthe Economic Research Service.
  • 2. Is agriculture in SSA taking off?• Higher rates of agricultural GDP growth following structural adjustment – From 1.4% per year (1970-1984) to 2.9% per year (1985-2009)• Possible reasons for higher agricultural growth – Macroeconomic & political stability (Binswanger-Mkhize & McCalla, 2009) – Improved agricultural terms of trade (Anderson and Masters, 2008) – Technology diffusion and greater productivity (Block, 1995; Nin-Pratt & Yu, 2008; Alene & Coulaby, 2009)• Aims of study: – Has growth been primarily resource-led or productivity-led? – What are the policy drivers for agricultural growth? Especially, what is the role of national and international agricultural research?
  • 3. Framework for Analysis: Decomposing and Explaining Growth Productivity-led growth Total Factor Research & extension Productivity Human capital (TFP) growth Institutions & incentives Yield growth InfrastructureOutput growth Input intensification Resource-led growth Prices & costs Input policies Exchange rates Infrastructure Area growth Area growth
  • 4. Analytical strategyOutput Y Y2 Productivity-led growth Total factor productivity = f(policy) Resource-led growth Y1 Y = f(X) X1 X2 Input X
  • 5. Explaining Total Factor Productivity (TFP) Growth CGIAR research National research CGIAR technology dissemination Enabling factors CGIAR technology dissemination Agricultural TFP National research growth Enabling factors
  • 6. Agricultural Production Function Estimates Coefficient (all significant at 1% level) (elasticity)Production inputsLabor 0.248 Assume constant returns to scaleLand 0.315 (elasticities sum to 1.00)Livestock Capital 0.357 Production elasticity = input costMachinery Capital 0.024 share under competitive market equilibriumFertilizers 0.055Resource quality variablesIrrigation (%) 68% Coefficient indicate % increase in yield over unfavorable rainfedFavorable area (%) 125% cropland areaR 2 overall 0.700R 2 between countries 0.706R 2 within countries 0.700
  • 7. Increase in output growth has been primarily resource-led with some rise in TFP growth 3.5% 3.0% 2.5%Average Annual Growth 2.0% TFP 1.5% Input/Cropland Cropland 1.0% 0.5% 0.0% 1961-1984 1985-2009 -0.5%
  • 8. Agricultural TFP index for sub-Saharan Africa (1961=100)
  • 9. Agricultural TFP index for sub-Saharan Africa (1961=100)
  • 10. Agricultural TFP index for sub-Saharan Africa (1961=100)
  • 11. Can R&D investments explain TFP growth?• International (CGIAR) agricultural research – Invests about $200 million in SSA (25% for crops) – 1200 international scientists (40% for SSA) – Improved crop technology adopted on about 20% of cropland• National agricultural research in SSA – $US 350 million ($PPP 960 million) – 9000 scientists (15% with PhD) in 2000 – Low and declining level of research intensity
  • 12. National & international agricultural research in sub-Saharan Africa
  • 13. New technologies have impacted at least 25% of SSA cropland by 2001-05Source: Compiled by author from case studies of technology adoption and impact. These technologiesOriginated primarily from CGIAR centers except NRM technologies, which are primarily farmer innovations.
  • 14. Macro and price policies have become lessdiscriminating against agriculture since 1985Source: Anderson and Masters (2008).
  • 15. Data coverage for policy variables R&D (31, Obs=899) R&D, School, NRA, Roads (9+, Obs=273)R&D, School (27, Obs=783) R&D, Roads (17+, Obs=611) R&D, NRA (17, Obs=467)
  • 16. Some Findings from Regression Models• Lack of data coverage constrains analysis – Road data too limiting to draw inference• Technology policy – CGIAR technology adoption strongly correlated with TFP growth – NARS – absolute size seems to matter (small country problem) – CGIAR raises returns to NARS• Other factors – Economic policy and incentives matter – Schooling leads to higher adoption but not higher yield given adoption – War and HIV/AIDS (strongly) depress growth
  • 17. Returns to Agricultural Research in SSAMedian for countries grouped by size IRR IRR B/C ratio (%) without CGIAR (10% discount rate)Large countries Output > $3 bil. 25.0 19.5 4.0Medium-size countries Output, $1-$3 bil. 17.4 12.8 2.2Small countries Output < $1 bil. 7.4 3.9 0.7Returns to CGIAR in SSA 44.5 — 8.6
  • 18. Conclusions• Agricultural growth acceleration has been primarily resource-led• Some evidence of productivity improvement, especially in West Africa• Robust drivers of productivity and growth: – CGIAR research & technology dissemination – NARS R&D (except for small countries) – Improved economic policy• Implications for national R&D policy – Underinvestment by medium and large countries – Evidence for economies of size in NARS (small country problem) – Important to be open to international sources of technology