A Meta-Analysis Dataset of the Empirical Agricultural Technology Adoption Literature
This meta-analysis dataset is a convenience sample of empirical results 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. These data were used in the following publication: Ruzzante, S., Labarta, R., & Bilton, A. (2021). Adoption of Agricultural Technology in the Developing World: A Meta-Analysis of the Empirical Literature. World Development, 146, 105599. https://doi.org/10.1016/j.worlddev.2021.105599. The data collection and curation procedures are described in the following publication: Ruzzante, S., & Bilton, A. (2021). Adoption of Agricultural Technologies in the Developing World: A Meta-Analysis Dataset of the Empirical Literature. Data in Brief, Submitted. Three data files are included: 1) AgTechAdoption.xlsx: This is the main data file, which contains effect size estimates for certain predictor variables on adoption of agricultural technologies in the developing world, drawn from 384 statistical models published in 218 studies. 2) Data Column Descriptions.pdf: This file provides detailed definitions for each of the column headings in AgTechAdoption V3.xlsx 3) Reference List: This file provides formatted citations for each of the 218 studies included in the meta-analysis dataset.
Steps to reproduce
The dataset was produced via a literature search. The details are described in Ruzzante & Bilton (2021).