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Spatial effects in organic agriculture adoption in Honduras: the role of social conformity, positive externalities, and information

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  • Wollni, Meike
  • Andersson, Camilla I.M.

Abstract

In low potential agricultural areas like the Honduran hillsides characterized by soil degradation and erosion, organic agriculture can provide a means to break the downward spiral of resource degradation and poverty. We use original survey data to analyze the factors influencing the decision to convert to organic agriculture. Previous studies have emphasized the role of spatial patterns in the diffusion and adoption of agricultural technologies in general and organic agriculture in particular. These spatial patterns can result from a variety of underlying factors. In this article we test various potential explanations, including the availability of information in the farmer's neighborhood, social conformity concerns and perceived positive external effects of the adoption decision, in a spatially explicit adoption model. We find that farmers who believe to act in accordance with their neighbors' expectations and with greater availability of information in their neighborhood network are more likely to adopt organic agriculture. Furthermore, perceived positive productivity spillovers to neighboring plots decrease the probability of adoption. We discuss the implications of our findings for the dissemination of sustainable agricultural technologies in low-potential agricultural areas in developing countries.

Suggested Citation

  • Wollni, Meike & Andersson, Camilla I.M., 2013. "Spatial effects in organic agriculture adoption in Honduras: the role of social conformity, positive externalities, and information," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 149911, Agricultural and Applied Economics Association.
    • Handle: RePEc:ags:aaea13:149911
    DOI: 10.22004/ag.econ.149911
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    Community/Rural/Urban Development; Environmental Economics and Policy; International Development; Research and Development/Tech Change/Emerging Technologies; Research Methods/ Statistical Methods;
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