Guo, Huanxiu and Marchand, Sébastien (2013) Is participatory social learning a performance driver for Chinese smallholder farmers? Working paper.
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Document available online at: https://halshs.archives-ouvertes.fr/halshs-00878886
Summary
This paper aims to test the effect of smallholder farmers' participatory social learning on their gain of performance in a village of southwest China. By exploring a panel structure survey data collected in the village, we identify the social learning effect using a Spatial Autoregressive (SAR) model. Particularly, we calculate the technical efficiency and environmental efficiency from a SFA model and use them as dependent variables of the model. Moreover, we investigate the social learning of different technologies, i.e., conventional and organic farming, by separating the estimations. Our identification results suggest that the effect of social learning is weak due to the technological heterogeneity in the general case, whilst it is significantly positive for organized organic farming. However, it appears that farmers learn to improve their economic performance (i.e., maximize yield) rather than environmental performance (i.e., minimize environmentally detrimental input). These results reveal a critical limitation of social learning, and demand more environmental orientation in the agricultural extension service, which is expected to guide smallholder farmers and foster their environmental performance for sustainable agricultural development.
EPrint Type: | Working paper |
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Keywords: | China (en), Smallholder farming (en), Social learning (en), Organic farming (en), Technical efficiency (en), Environmental efficiency (en), China. (en) |
Subjects: | "Organics" in general |
Research affiliation: | France > INRAe - Institut national de recherche pour l’agriculture, l’alimentation et l’environnement |
Related Links: | https://halshs.archives-ouvertes.fr/halshs-00878886/document |
Project ID: | HAL-INRAe |
Deposited By: | PENVERN, Servane |
ID Code: | 41740 |
Deposited On: | 12 Aug 2021 10:37 |
Last Modified: | 12 Aug 2021 10:37 |
Document Language: | English |
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