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New Maize Variety Adoption in Mozambique: A Spatial Approach
Author(s) -
Fang Di,
Richards Timothy J.
Publication year - 2018
Publication title -
canadian journal of agricultural economics/revue canadienne d'agroeconomie
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.505
H-Index - 37
eISSN - 1744-7976
pISSN - 0008-3976
DOI - 10.1111/cjag.12166
Subject(s) - leverage (statistics) , variety (cybernetics) , productivity , cluster analysis , business , social learning , marketing , work (physics) , developing country , knowledge management , industrial organization , economics , computer science , economic growth , engineering , artificial intelligence , mechanical engineering
Farmers in developing countries can dramatically improve their productivity by adopting new plant varieties. Yet, informational barriers often mean adoption rates remain low. In this study, we focus on how learning from others represents one means of removing informational barriers. We capture the effect of social learning through an explicitly spatial econometric model applied to farm‐level maize adoption rates in Mozambique. We find that social learning is significant and can help explain the apparent clustering of adoption among farmers. Agencies interested in promoting variety adoption, therefore, would be well served to leverage the strength of existing information networks, rather than imposing solutions that work against interfarmer information flow.