While it is often recognised that agricultural technology adoption decisions are intertwined and best characterised by multivariate models, typical approaches to examining adoption and impacts of agricultural technology have focused on single technology adoption choice and ignored interdependence among technologies. We examine farm-and market-level impacts of multiple technology adoption choices using comprehensive household survey data collected in 2010/11 and 2012/13 in Ethiopia. Economic surplus analysis combined with panel data switching endogenous regression models are used to compute the supply shift parameter (K-shift parameter), while at the same time controlling for the endogeneity inherent in agricultural technology adoption among farmers. We find that our improved technology set choices have significant impacts on farm-level maize yield and maize production costs, where the greatest effect appears to be generated when various Journal of Agricultural Economics, Vol. 69, No. 1, 2018, 76-95 doi: 10.1111/1477 Ó 2017 The Agricultural Economics Society technologies are combined. The change in maize yield and production costs results in an average 26.4% cost reduction per kilogram of maize output (the K-shift parameter). This increases the producer and consumer surpluses by US$ 140 and US$ 105 million per annum, respectively. These changes in economic surplus help to reduce the number of poor people by an estimated 788 thousand per year. We conclude that deliberate extension efforts and other policies that encourage integration of technologies are important for maize technologies to yield their full potential at both farm and market levels.

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This study analyses the economics of conservation tillage (CT) with respect to its effect on maize yield and chemical fertiliser, herbicide, and female and male labour demand. We estimate production and input demand functions using seemingly unrelated regressions on plot‐level cross‐sectional farm household data collected in the north‐west of Ethiopia. A two‐step control function is applied to address potential endogeneity bias due to the inclusion of the CT adoption decision as an explanatory variable. Our results show that CT increases maize yield and chemical fertiliser demand. Additionally, the results show that the adoption of CT reduces female and male labour required for crop production. However, this is achieved through the increased use of herbicides, which might have an undesirable health and environmental effects.

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