A Conceptual Model of Incomplete Markets and the Consequences for Technology Adoption Policies in Ethiopia

In Africa, farmers have been reluctant to take up new varieties of staple crops developed to boost smallholder yields and rural incomes. Low fertilizer use is often mentioned as a proximate cause, but some believe the problem originates with incomp...

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Bibliographic Details
Main Authors: Larson, Donald F., Gurara, Daniel Zerfu
Format: Policy Research Working Paper
Language:English
en_US
Published: World Bank, Washington, DC 2014
Subjects:
Online Access:http://hdl.handle.net/10986/16895
Description
Summary:In Africa, farmers have been reluctant to take up new varieties of staple crops developed to boost smallholder yields and rural incomes. Low fertilizer use is often mentioned as a proximate cause, but some believe the problem originates with incomplete input markets. As a remedy, African governments have introduced technology adoption programs with fertilizer subsidies as a core component. Still, the links between market performance and choices about using fertilizer are poorly articulated in empirical studies and policy discussions, making it difficult to judge whether the programs are expected to generate lasting benefits or to simply offset high fertilizer prices. This paper develops a conceptual model to show how choices made by agents supplying input services combine with household livelihood settings to generate heterogeneous decisions about fertilizer use. An applied model is estimated with data from a panel survey in rural Ethiopia. The results suggest that adverse market conditions limit the adoption of fertilizer-based technologies, especially among resource-poor households. Farmers appear to respond to market signals in the aggregate and this provides a pathway for subsidies to stimulate demand. However, the research suggests that lowering transaction costs, through investments in infrastructure and market institutions, can generate deeper effects by expanding the technologies available to farmers across all pricing outcomes.