Master of Science / Department of Agricultural Economics / Timothy J. Dalton / Given the changing climate paradigm, food and poverty are likely to become more severe in Africa. Farmers can adapt to climate change, especially through conservation agriculture. This study relies on a minimum data approach developed by Antle and Valvidia (2006) to estimate the spatial distribution of opportunity cost for farmers in switching to conservation practices in Wa, Ghana. It assesses the economic feasibility of several scenarios that rely on production techniques currently studied by the CRSP SANREM project. We also explore the possibility that these practices can provide income from carbon sequestration payments implemented by the Kyoto protocol’s Clean Development Mechanisms. The methodology uses data from both a recent survey and information from secondary sources to assess simulated management practices. Results indicate that all the simulated management practices would theoretically benefit farmers. In fact, adoption rates for the four scenarios range from 52% to 65%, even without any carbon payment. Adding a proportional payment to the amount of carbon sequestered with these practices does not seem enough to influence farmers switch to switch to alternative scenarios. The analysis shows that these results hold even when additional fixed costs to adopt these practices are included. This case study demonstrates the usefulness of the minimum data approach in estimating the economic potential of conservation practices in Ghana. These production techniques may represent environmentally-friendly alternatives that are more profitable for farmers than current practices. The next step in assessing implementation of such practices would require studying farmers’ willingness to adopt these production systems, given their ex-ante economic returns.
Identifer | oai:union.ndltd.org:KSU/oai:krex.k-state.edu:2097/13248 |
Date | January 1900 |
Creators | Remaury, Hugo |
Publisher | Kansas State University |
Source Sets | K-State Research Exchange |
Language | en_US |
Detected Language | English |
Type | Thesis |
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