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Spatial patterns of organic agriculture adoption: evidence from Honduras

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

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    Bibliographic Info

    Paper provided by Georg-August-Universitaet Goettingen, GlobalFood, Department of Agricultural Economics and Rural Development in its series Discussion Papers with number 146715.

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    Date of creation: Mar 2013
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    Handle: RePEc:ags:gagfdp:146715

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    Related research

    Keywords: neighborhood effects; social conformity; spatial autoregressive probit model; organic agriculture; technology adoption; Central America; Agricultural and Food Policy; International Development; Land Economics/Use; Production Economics; Research and Development/Tech Change/Emerging Technologies; Research Methods/ Statistical Methods; O13; O33; Q12; Q16;

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