Farm-level and community aggregate economic impacts of adopting climate smart agricultural practices in three mega environments

Abstract

Recent studies highlight a growing concern over the limited adoption of climate smart agricultural (CSA) practices despite their potential benefits on adaptation, mitigation and productivity. Literature indicates several factors behind the lack of adoption including socio-demographic and economic conditions, agro-ecological scales and the nature of the practices. This paper examines to what extent and under which conditions such factors influence the adoption of CSA practices at farm, household and community level across three study sites in different continents: Vietnam, Nicaragua and Uganda. While cost benefit analysis (CBA) is employed to assess the farm-level profitability of CSA practices, the aggregate community impact disaggregated by different groups of farmer typologies with specific socio-economic features is derived from the adoption rate estimated by the relative advantage of practices and the income level of each group. Our main findings show great variation of farm-profitability of CSA practices across scales. Similar practices could generate different profitability depending on crop typologies, input access and prices, household types and local context. Regarding the aggregate profitability of CSA practices at regional scale, we found that under particular conditions, relevant factors of adoption matter to the adoption pattern and thereby affects the ranking. Such conditions include (i) high income inequality, (ii) large profitability gap of prioritized CSA practices, and (iii) large proportion of cost and benefit of the practices in the level of income. This study contributes to enhancing the prioritization process of CSA practices and provides practical guidance for research and policy to tailor the investment to appropriate end-users to assure the greatest impact for the community.

Financing Large-Scale Mitigation by Smallholder Farmers: What Roles for Public Climate Finance?

“…Our ex post assessment of investments supported by the IFAD SDCP indicates that while on-farm investments can be profitable, feasible loan repayment periods are longer than the tenor of most available loans, suggesting that farmers may be justified in not seeking to finance investments using loans. This finding has methodological implications, as many studies of the economics of mitigation or "climate smart" measures show negative abatement costs (i.e., $ per tCO 2 e) or financial profitability (e.g., positive benefit:cost ratios or net present values) based on discounted net revenue over a given investment period (e.g., Food and Agriculture Organization of the UN and New Zealand Agricultural Greenhouse Gas Research Centre, 2017; Henderson et al, 2017;Kashangaki and Ericksen, 2018;Lan et al, 2018), but without considering the time limit on loan repayments, which is critical for analysis of investment feasibility.…”

Reviewing Vietnam's Nationally Determined Contribution: A New Perspective Using the Marginal Cost of Abatement

“…Transformation of bamboo forest into crops (maize and cassava) prevented to avoid emission from deforestation. (Aalde et al, 2006;McNally et al, 2010;Lan et al, 2016Lan et al, , 2018,…”

“…Restore bamboo forest in current maize and cassava fields increase the amount of carbon sequestration per area, and decrease agriculture emissions (Aalde et al, 2006;De Jong et al, 2006;Lan et al, 2016Lan et al, , 2018 CFT model Prevent the change of mangroves into aquaculture prevent emissions of GHG. Putz and Chan, 1986;McNally et al, 2010;Lan et al, 2016Lan et al, , 2018 Mangrove restoration 1 20 50% of commitments of coastal forest restoration.…”

“…Recover mangrove in sandy in current aquaculture increase the amount of carbon sequestration per area. Putz and Chan, 1986;McNally et al, 2010;Lan et al, 2016Lan et al, , 2018 Mangrove restoration 2 20 50% of commitments of coastal forest restoration.…”

“…Replace rice by aquaculture reduce methane emission. Putz and Chan, 1986;Aalde et al, 2006;McNally et al, 2010;Lan et al, 2016Lan et al, , 2018Thuong Vo et al, 2017;McKinley et al, 2018 Rice transformed into maize 100 50% of the projections of rice area reduction.…”