• Sustainable agriculture;
  • Technology adoption;
  • Productivity;
  • Trivariate probit;
  • Stochastic dominance analysis;
  • Ethiopia


In the wake of the resource constraints for external farm inputs faced by farmers in developing countries, sustainable agriculture practices that rely on renewable local or farm resources present desirable options for enhancing agriculture productivity. In this study, plot-level data from the semi-arid region of Ethiopia, Tigray are used to investigate the factors influencing farmers' decisions to adopt agriculture practices, with a particular focus on conservation tillage, compost and chemical fertilizer. A trivariate probit model is used to analyze the determinants of adoption of these practices. In addition, stochastic dominance analysis is used to compare the productivity impacts of compost with that of chemical fertilizer based on a six-year cross-sectional farm-level dataset. Our results indicate heterogeneity with regard to the factors that influence adoption decisions of the three practices and the importance of both plot and household characteristics on influencing adoption decisions. In particular, we found that household endowments and access to information, among other factors, impact the choice of sustainable farming practices significantly. Furthermore, the use of stochastic dominance analysis supported the contention that sustainable farming practices enhance productivity. They even proved to be superior to the use of chemical fertilizers — justifying the need to investigate factors that influence adoption of these practices and to use this knowledge to formulate policies that encourage adoption.