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Cited by 215

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Better Technology, Better Plots, or Better Farmers? Identifying Changes in Productivity and Risk among Malagasy Rice Farmers

Barrett, Christopher B., Moser, Christine M., McHugh, Oloro V., Barison, Joeli·2004·American Journal of Agricultural Economics

Abstract

We introduce a method for properly attributing observed productivity and risk changes among new production methods, farmers, and plots by controlling for farmer and plot heterogeneity. Results from Madagascar show that the new system of rice intensification (SRI) is indeed a superior technology. Although about half of the observed productivity gains appear due to farmer characteristics rather than SRI itself, the technology generates the estimated average output gains of more than 84%. The increased estimated yield risk associated with SRI would nonetheless make it unattractive to many farmers within the standard range of relative risk aversion.

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Crossref · 10.1111/j.0002-9092.2004.00640.x

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Metadata

Authors
Barrett, C. B., Moser, C. M., McHugh, O. V., & Barison, J.
Venue
American Journal of Agricultural Economics
Publisher
Wiley
Published
2004-11
Volume
86
Issue
4
Pages
869-888
ISSN
  • 0002-9092 (ISSN-L)
  • 1467-8276
OpenAlex
W2118821780
Cited by
215
References
2
FWCI
48.87
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Better Technology, Better Plots, or Better Farmers? Identifying Changes in Productivity and Risk among Malagasy Rice Farmers. https://app.cochat.ai/papers/10.1111/j.0002-9092.2004.00640.x
The paper
Barrett, C. B., Moser, C. M., McHugh, O. V., & Barison, J. (2004). Better Technology, Better Plots, or Better Farmers? Identifying Changes in Productivity and Risk among Malagasy Rice Farmers. American Journal of Agricultural Economics. https://doi.org/10.1111/j.0002-9092.2004.00640.x

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.