There has been growing interest in climate-smart agriculture among many national governments and the international donor community. An array of policies and programs could potentially be considered climate smart, but for the purposes of this paper, we define climate-smart agriculture as an approach that strives to meet the following criteria: (1) increase agricultural productivity in a sustainable manner, (2) improve the resilience of agricultural production and food systems to environmental change, or (3) reduce net greenhouse gas emissions associated with the agriculture and forestry sectors. This definition encompasses, but goes beyond, the traditional agricultural development policy concerns of increasing incomes and reducing rural poverty, thus increasing the complexity of the policy agenda and modeling that supports policy-making. The goal of the paper is to provide policymakers and program designers with an overview of the primary types of economic models that could be used to inform policy design and implementation. The most specific audience for the paper is international development practitioners who design projects, pilots, and other efforts to advance climate-smart agriculture, and who may wish to inject modeling sensibilities and approaches into such efforts. The readership of the paper is assumed to be subject matter specialists and generalists who are not economists but may need to consume the results of economic modeling. We describe alternative economic modeling approaches relevant for analyses of climate-smart agriculture approaches and provide general principles for selecting an approach for a specific application.
Developing climate-smart agriculture policies
By Luis Arturo Crouch, Daniel Lapidus, Robert Beach III, Dileep Birur, Massoud Moussavi, Eleanor Turner.
January 2017 Open Access Peer Reviewed
Crouch, L. A., Lapidus, D., Beach III, R., Birur, D., Moussavi, M., & Turner, E. (2017). Developing climate-smart agriculture policies: The role of economic modeling. RTI Press. RTI Press Publication No. OP-0034-1701 https://doi.org/10.3768/rtipress.2017.op.0034.1701
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