In this thesis I inspect learning about adoption of technologies among cocoa farmers in Ghana, which are represented by non-labor inputs, particularly by fertilizer and hybrid seeds. Earlier research focused mainly on learning about returns associated with adoption of such innovative inputs. However, it is not clear whether the adopters learn about these returns or rather about what are the optimal amounts of these inputs. Therefore the focus of this thesis is to examine how do the farmers choose and learn about optimal amounts of inputs. Cocoa farming is very labor intensive, and thus this thesis concentrates on learning about both non-labor and labor inputs, which are closely connected. Similar research carried out in India suggests that heterogeneous returns among farmers might cause that the farmers rely rather on their own considerations than on observation of behavior of their village neighbors, i.e. social learning. The heterogeneous returns are also present among the Ghanaian cocoa farmers, which suggest that these farmers should similarly prefer individual learning over the social one. Using a model developed for estimation of the prevailing type of learning about the optimal amount of inputs, I show that the farmers do tend to prefer individual learning in case of the non-labor inputs but rather...
Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:327870 |
Date | January 2013 |
Creators | Švenka, David |
Contributors | Janský, Petr, Havránek, Tomáš |
Source Sets | Czech ETDs |
Language | English |
Detected Language | English |
Type | info:eu-repo/semantics/masterThesis |
Rights | info:eu-repo/semantics/restrictedAccess |
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