Adoption of agricultural technology in the developing world: A meta-analysis of the empirical literature

Abstract

• Large farms are more likely to adopt improved crop varieties. • Land tenure security encourages the adoption of sustainable land management practices. • For improved varieties, extension substitutes for formal education. • For natural resource management, extension and formal education are complementary. • Effects are heterogeneous and no variables are universal predictors of adoption. Agricultural technologies have long been promoted by governments and development organizations as effective ways to increase farm productivity and reduce poverty. However, adoption of many seemingly beneficial technologies remains low. Empirical adoption studies attempt to identify the motivation for adoption based on differences in characteristics between adopters and non-adopters. This study investigates variables that regularly explain adoption across technologies and contexts using a meta-analysis of 367 regression models from the published literature. We find that, on average, farmer education, household size, land size, access to credit, land tenure, access to extension services, and organization membership positively correlate with the adoption of many agricultural technologies. Technologies in the categories of improved varieties and chemical inputs are adopted more readily on larger farms, which casts doubt on the scale-neutrality of these technologies. Agricultural credit can positively influence adoption, but researchers should measure whether farmers are credit constrained, rather than simply whether or not they have access to credit. While extension services may substitute for education in the case of improved varieties, the two variables appear to be complementary for natural resource management technologies. Land tenure can encourage adoption of natural resource management techniques, and we find it to be most influential in the adoption of technologies with long planning horizons, such as erosion control methods. Unsurprisingly, although some patterns are identified when results are averaged, most adoption determinants vary widely by technology, cultural context, and geography. Based on these observations, we provide some recommendations for adoption researchers and policy makers, but, given the variability of the results, conclude that efforts to promote agricultural technologies in the developing world must be adapted to suit local agricultural and cultural contexts.