Mar2003Madagascarsta keholderworkshopslid es EN

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RURAL MARKETS, NATURAL CAPITAL AND DYNAMIC POVERTY TRAPS IN EAST AFRICA Introducing Cornell University and the USAID Broadening Access and Strengthening Input Market Systems Collaborative Research Support Program (BASIS CRSP)

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Objectives of Stakeholder Consultation To share information about this project and to learn from you about (i) other relevant research taking place (ii) current policy concerns we could/should address (iii) key information gaps in understanding and addressing rural poverty (iii) research outputs and outreach modes that would be most useful for stakeholders. RURAL MARKETS, NATURAL CAPITAL AND DYNAMIC POVERTY TRAPS IN EAST AFRICA

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Introducing the BASIS CRSP Began 1996, based at U. Wisconsin-Madison Mission: To promote economic growth and agricultural development by conducting collaborative research and training on ways to improve access to and efficiency of land, water, labor, and financial markets. Strategies proposed in Africa, Asia, Eastern Europe/Eurasia, and Latin America help increase income, purchasing power, and food availability while promoting sustainable resource management.

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BASIS CRSP overall goals - Remove constraints to economic growth and raise standard of living for the poor. - Increase food security by broadening the poor's access to key factors of production. - Reduce environmental destruction with policies and programs fostering sustainable land use. - Support US universities and researchers in collaboration with scientists and institutions abroad.

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BASIS CRSP Phase II Eight projects: Building Assets for Sustainable Recovery and Food Security Constraints to Growth in Russian Agriculture Deepening of Financial Services through Credit-Reporting Bureaus - Financial Markets Structure and Performance—Welfare Impacts on Rural Poor Improving Household Well Being through Access to Credit Innovative Institutions to Help Land Reform Beneficiaries Promoting Equitable Access to Water Resources Rural Markets, Natural Capital and Dynamic Poverty Traps in East Africa

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Project Problem Statement Many rural Africans suffer chronic poverty and vulnerability due to insufficient initial assets and poor market access that limit efficient investment in or use of productive assets. They depend heavily on natural capital (especially soils), but have strong incentives to deplete natural capital in order to sustain human capital, thereby aggravating pre-existing poverty traps. This project therefore focuses on dynamic poverty traps and their agroecological causes and consequences.

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Project objective 1: Test four hypotheses about poverty traps in East Africa: (i) High return production strategies (e.g., livestock) exhibit increasing returns at low production levels, with a minimum efficient scale of production beyond the means of the poor lacking adequate financing. (ii) Poor market access creates significant fixed costs to market participation, giving larger producers net price advantages and inducing poorer producers in areas of weak market access to opt out of markets in favor of low-return self-sufficiency.     

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Project objective 1 (continued): (iii) Poorer households lacking access to capital to finance productive investments may be unable to undertake lumpy investments, regardless of their expected returns (iv) Risk and subsistence constraints discourage long-term investment for asset accumulation and productivity growth among poorer, more risk averse households.              

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Project objective 2:       Use bioeconomic simulation modeling methods to explore how the existence of poverty traps conditions natural resource conservation, particularly soil quality dynamics that centrally affect future agricultural and labor productivity and food security.       

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Project objective 3: Identify and document effective policies, technologies and programs to combat dynamic poverty traps in this setting. Use models to simulate policy experiments, allowing for differences according to market and agroecological conditions Examples: - new agroforestry technologies - improved fertilizer distribution - restocking herds after droughts

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Project objective 4:       Help build analytical capacity in local partner institutions (FOFIFA, KARI) through degree and non-degree training.

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Research Output Direct dissemination of research findings to policy analysts at national and regional levels, and to decision takers at study sites and areas with similar agroecological and market conditions Provide an empirical basis for policy recommendations and implementation Publications (English, French) Capacity building (FOFIFA, KARI) Generate relevant data bases for future use

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Project Timeline

Research Sites: 

Research Sites Kenya Madagascar

Research Design: 

Research Design MARKET ACCESS Worse Better Wetter 1. North Central Kenya (Baringo) AGRO-ECOLOGICAL CONDITIONS 1.Central highlands, Kenya (Embu) 2. Central highlands, Madagascar (Vakinankaratra) 1. Northern Kenya (Marsabit) 1. Western Kenya (Siaya /Vihiga) 2. Southern highlands, Madagascar (Fianarantsoa)

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We can use transition regressions, like this one depicting livestock herd dynamics in southern Ethiopia, showing “threshold effects” due to highly nonlinear dynamics that generate poverty traps: Describing Welfare Dynamics Empirically

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SOIL QUALITY & DEPTH HUMAN BEHAVIOR & WELFARE (income, health, wealth) LIVESTOCK HERD SIZE PLANT BIOMASS - Natural vegetation - crops and agroforestry Milk meat traction Savings Manure Herd size + species husbandry, feeding practices Forage, feed crops, green manure crop production practices land use patterns CLASSES MODELING FRAMEWORK A dynamic process model integrating soils, crops, livestock and human behavior and welfare Soil/water conservation, fertilizer, brown & green manure application ENVIRONMENTAL & POLICY FACTORS - rainfall, - temperature - slope - prices - land tenure - land use restrictions State or decision variables Excreta, litter, - Soil cover - Soil organic matter (SOM) -Soil nutrients, - moisture Geographical effects

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Project Current Year Objectives Complete field survey data collection, entry and cleaning for each study site Qualitative field data collection to follow-up quantitative survey Estimate income and asset transition matrices Build and parameterize bioeconomic model (CLASSES) Local and national level stakeholder consultations Degree (Cornell) and non-degree (e.g., bioeconomic modeling short-course) training

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