ArticleFood policy2019
Agricultural technology adoption and household welfare: Measurement and evidence.
Article in Food policy, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Empirical and methodological foundations on the impact of climate-smart agriculture on food security studies: Review.Heliyon · 2025Review
- Article
- Financial inclusion for sustainable agriculture: Pathways among smallholder women farmers in rural Zambia.PloS one · 2025Article
- What Influences Farmers' Adoption of Soil Testing and Formulated Fertilization Technology in Black Soil Areas? An Empirical Analysis Based on Logistic-ISM Model.International journal of environmental research and public health · 2022Article
- How accurate are yield estimates from crop cuts? Evidence from smallholder maize farms in Ethiopia.Food policy · 2021Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Previous studies on the adoption and impacts of improved crop varieties have relied on self-reported adoption status of the surveyed households. However, in the presence of weak variety maintenance and poorly functioning seed certification system, measurement errors in self-reported adoption status can be considerable. This paper investigates how such measurement errors can lead to biased welfare estimates. Using DNA-fingerprinting based varietal identification as a benchmark, we find that misclassification in self-reported adoption status is considerable, with significant false negative and positive response rates. We empirically show that such measurement errors lead to welfare estimates that are biased towards zero and substantially understate the poverty reduction effects of adoption. While the empirical evidence suggests attenuation bias, our theoretical exposition and simulations demonstrate that upward bias and sign reversal effects are also possible. The results point to the need for improved monitoring of the diffusion process of improved varieties through innovative adoption data collection approaches to generate robust evidence for prioritizing and justifying investments in agricultural research and extension.
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Registered trials
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