Does Adoption of Multiple Climate-Smart Practices Improve Farmers’ Climate Resilience? Empirical Evidence From the Nile Basin of Ethiopia

Abstract

There is a paucity of information on conditioning factors that hinder or promote adoption of multiple climate-smart practices and on the synergies among such practices in increasing household resilience by improving agricultural income. This study analyzes how heat, rainfall, and rainfall variability affect farmers’ choices of a portfolio of potential climate smart practices — agricultural water management, improved crop seeds, and fertilizer — and the impact of these practices on farm income in the Nile Basin of Ethiopia. We apply a multinomial endogenous switching regression approach by modeling combinations of practices and net farm income for each combination as depending on household and farm characteristics and on a set of climatic variables based on geo-referenced historical precipitation and temperature data. A primary result of this study is that farmers are less likely to adopt fertilizer (either alone or in combination with improved varieties) in areas of greater rainfall variability. However, even when there is high variability in rainfall, farmers are more likely to adopt these two yield-increasing inputs when they choose to (and are able to) include the third part of the portfolio: agricultural water management. Net farm income responds positively to agricultural water management, improved crop variety or fertilizer when they are adopted in isolation as well as in combination. But this effect is greater when these practices are combined. Simulation results suggest that a warming temperature and decreased precipitation in future decades will make it less likely that farmers will adopt practices in isolation but more likely that they will adopt a combination of practices. Hence, a package approach rather than a piecemeal approach is needed to maximize the synergies implicit in various climate smart practices.

Determinants of adoption of climate-smart agriculture technologies in rice production in Vietnam

“…Farmers often build sustainable agricultural production systems that are resilient to different climate-related conditions and other shocks by using a combination of various CSATs (Maguza-Tembo et al, 2017). Unfortunately, of the few studies that have attempted to identify the determinants of farmer adoption of more than one CSAT (Di Falco and Veronesi, 2013;Parvathi and Waibel, 2015;Teklewold et al, 2013Teklewold et al, , 2017, none of them have been conducted in Vietnam. Thus, it is important to conduct such a study to identify the factors that determine the successful adoption of CSATs in the country.…”

“…In Step 1, a multinomial adoption selection model is used to identify the key determinants of adoption of CSATs singly and in combination. In Step 2, a counterfactual analysis is used to estimate the average adoption effect of alternative CSA packages on NRI (Teklewold et al, 2017).…”

“…expectation of yield gain from adoption, managerial skills, motivation, etc.) that may correlate with the outcome of interest (net farm income, crop yield and cost of material input) (Teklewold et al, 2013(Teklewold et al, , 2017. Farmers will adopt CSATs if the expected utility obtained from the technology is higher than the current technology.…”

“…The error terms in equation 5are likely to exhibit heteroscedasticity arising from the two-stage estimation procedure. To deal with the heteroscedastic problems, standard errors in equation 5are bootstrapped (Kassie et al, 2013;Teklewold et al, 2017). Self-selection models that are estimated in a two-stage procedure have been criticized for being sensitive to misspecification (Wu and Babcock, 1998).…”

“…Farmers have a vast array of alternative technologies that they can use either singly or in combination to deal with various environmental conditions (Dorfman, 1996;Teklewold et al, 2017). Due, however, to differences in cultures, awareness, resource endowments, objectives, preferences and socio-economic backgrounds, farmers differ in their willingness to adopt new technologies (Maguza-Tembo et al, 2017).…”