Byerlee’s Biases

Accelerating agricultural growth from early 90s of about 4% annually• Higher than Non-Agricultural Growth• Positive per capita AgGDP growth and labor

productivity growth But decomposition analysis shows:

• Commodity prices• Export crops• Area expansion vs yield growth

And limits of time series statistical analysis Bottom line--20% area MVs, 10 kg/ha fertilizer, 4%

irrigated, low and stagnant yields

Diverse rainfed systems• Compare with similar systems in Asia and LA ?• Labor constraint

Policies, infrastructure and institutions• Macro and sectoral policies imposed high taxes• Vacuum after structural adjustment--weak state

capacity Sequencing technology and complementary

investments High transactions costs and risks

Need for a value chain approach—input and output markets, and post-harvest

Diversity and scale• Small heterogeneous countries cutting across AEZs

Technologically distant from other regions Late start on food crop research in Africa

• And then many false starts (maize, sorghum, rice)• Low stock of knowledge and low R&D investment

Dealing with high climatic and price risks• Climate and CC, small countries, nontradables,

markets, policies Sustainable soil fertility management (BR) Still--High exploitable yield gaps in medium and

high potential areas (Sasakawa etc)

African maize revolutions up to 1990• Effects of structural adjustment, conflicts• Policy discontinuities—e.g., Malawi• Private sector vs subsidies

Rice• Ofice du Niger, Mali• NERICAs?

Cassava• Biological control, MVs, post-harvest

Few sustained efforts on R&D • Drought tolerant maize

Production technologies• MVs for local biotic and abiotic stresses• Labor including gender roles• Soil and water management technologies• High risks Research vs using existing technologies

Beyond technologies• Production vs value chains• Technology vs complementary

interventions

Defining and outlining a Green Revolution• Rapid and sustained productivity gains for major

food crops Maize and rice. Cassava?

Constrained optimization problem• Adding value subject to time and data constraints• Assets: Unique data sets—mainly cross-sectional,

team with strong analytical skills, Asian and African experience, rice and maize focus

No Green Revolution after 40 years of effort

Many promising starts died on the vine

Data and analysis• Historical review of false starts in Africa with

particular reference to rice and maize Maize—Update Byerlee and Eicher, IFPRI Rice—update Stanford, recent WARDA review

Irrigation explains significant difference in African performance

But even after correcting for soils, climate etc, African farmers use low levels of MVs, inputs especially in med-high potential zones• Is rainfall more risky in the same AEZ?

Data and analysis• Use of climate change data sets, but within

defined AEZs• India district data

Short-run rapid gains can be achieved by using current technologies• Define cases such as hybrid maize, irrigated rice• Provide economic returns (e.g., which fertilizer

prices?) Analyze role of other constraints

• Price risks and transactions costs• Input markets and credit• Post-harvest for rice

Data sets—Mozambique, Uganda, Kenya• Descriptive statistics on prices etc from CC data

Other technological constraints• Soil and water management for local

conditions• Post-harvest

Data and analysis• Mozambique, Ethiopia• Good review of options to overcome the soil

fertility problem in local context

Knowledge stocks and investment in R&D over time• Late start in Africa on food crops—review• Efforts to catch up—CGIAR, Gates

Data and analysis• Review of available sources

Recognize Africa’s huge diversity• All five hypotheses may hold at one time

Framing the context• Kym Anderson study• Competitive Commercialization of African

Agriculture (Brazil, Thailand, Nigeria, Zambia, Mozambique)

• Michigan State University (esp. fertilizer)• UN/Academies of Science Report