Adoption of agricultural technologies in the developing world: A meta-analysis dataset of the empirical literature
Sacha Ruzzante, Amy Bilton
Data in Brief · 2021
doi:10.1016/j.dib.2021.107384 (opens in a new tab)
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Abstract
The meta-analysis dataset presented is a convenience sample from 218 separate studies of agricultural technology adoption in Africa, Asia, and Latin America. Each study uses survey data to estimate a form of multiple regression of adoption of a technology (dependent variable) with a diverse array of predictor variables. Fifteen predictor variable categories are included in this dataset: Age, education, gender, household size, farming experience, land size, soil fertility, land slope, distance to inputs/outputs, access to credit, land tenure, livestock ownership, non-farm income, access to extension, and organization membership. Data have been cleaned and transformed to common units. A total of 384 statistical models are recorded, with a total of 2875 effect size estimates.
Abstract licence: CC BY-NC-ND
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