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To support countries implementing CSA solutions, the Economics and Policy Innovations for Climate Smart Agriculture (EPIC) group at FAO uses a methodology based on building a solid evidence base. The knowledge gained from datasets that combine household, geographical and climate data helps design policies that enhance food security and climate resilience while also taking advantage of mitigation opportunities to obtain financing. Appropriate application of CSA principles depends on specific conditions that vary between and within countries. Demographic, environmental, economic and institutional factors are all important determinants of the effectiveness of any particular policy. This chapter builds upon econometric results obtained from previous analyses by developing a conceptual model that introduces the temporal aspects of household vulnerability. The method is based on a factorial design with two vulnerability levels (high and low) and two production methods (conventional or business as usual, and improved agricultural management with high CSA potential). Farms are classified into groups based on cluster analysis of survey data from Zambia. Results provide a baseline consisting of probability distributions of yields, labor use, cash inputs and profit for each of the four combinations of vulnerability level and production system. This is useful for stochastic dominance analysis, but additional work is required to incorporate the temporal aspect of the problem. The chapter identifies data gaps and additional analyses required to capture the spatio-temporal aspects of household vulnerability and adaptive capacity.
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- Identifying Strategies to Enhance the Resilience of Smallholder Farming Systems: Evidence from Zambia
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