Measuring Farm and Market Level Economic Impacts of Improved Maize Production Technologies in Ethiopia: Evidence from Panel Data

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 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.     

Resource saving and productivity enhancing impacts of crop management innovation packages in Ethiopia

Crop management innovations are often not discrete fixed stand‐alone options—and their adoption may imply various combinations and adaptations. This potentially confounds their impact assessment. This article assesses the resource saving and productivity enhancing impacts of a crop management package revolving around minimum tillage in maize‐based farming systems in northwest Ethiopia. An endogenous switching regression model was applied to plot‐ and household‐level survey data collected from 290 rural households operating 590 maize plots during the 2012 production year. Controlling for variations in plot and household characteristics, the average effect of minimum tillage package (minimum tillage package) on maize productivity is 0.44 t/ha. Compared to conventional practice (CP), adoption of the MTP decreased the average male and female labor use in maize production by 14.4 and 8.2 person‐days per ha, respectively. Similarly, MTP adoption decreased draft power use for land preparation by 13.2 pair of oxen‐days per ha. Compared to CP, in general, there is a considerable short‐run maize productivity gain and reduction in labor and draft power use under MTP.     

Production Risks and Food Security under Alternative Technology Choices in Malawi: Application of a Multinomial Endogenous Switching Regression

Employing nationally representative data, we investigate the impact of Sustainable Intensification Practices (SIPs) on farm households’ food security, downside risk and the cost of risk in Malawi. The analysis relies on a flexible moment‐based specification of a stochastic production function in a multinomial endogenous switching regression framework to correct for the selection bias stemming both from observed and unobserved heterogeneity. A quantile moment approach is used to estimate the cost of risk. After controlling for the effects of unobserved heterogeneity and several observable variables on maize production and downside risk functions, estimation results show that the adoption of SIPs increases food security and reduces downside risk exposure and the cost of risk. We estimate greater food security and larger reduction in downside risk from simultaneous adoption of both crop diversification (maize–legume intercropping and rotations) and minimum tillage, suggesting that there are complementary benefits from these practices. We find most of the cost of risk comes from exposure to downside risk. Our findings imply that in dealing with production risks development agents should encourage the adoption of agronomic and resource‐management practices along with other risk mitigation and food security improving strategies.     

Agricultural technology adoption and child nutrition enhancement: improved maize varieties in rural Ethiopia

Adoption of improved crop varieties can lead to multiple benefits to farm households, including increased productivity, incomes, and food consumption. However, possible impacts of adoption on child nutrition outcomes are rarely explored in the literature. This article helps bridge this gap through an impact assessment of the adoption of improved maize varieties (IMVs) on child nutrition outcomes using a recent household survey from rural Ethiopia. The conceptual linkage between IMV adoption and child nutrition is first established using an agricultural household model. Instrumental variable estimation suggests the overall impacts of adoption on child height‐for‐age and weight‐for‐age z‐scores to be positive and significant. Quantile instrumental variable regressions further reveal that such impacts are largest among children with poorest nutrition outcomes. Finally, by combining a decomposition procedure with system of equations estimation, it is found that the increase in own‐produced maize consumption is the major channel through which IMV adoption affects child nutrition.     

Regression Analysis with a Stochastic Design Variable

In regression models, the design variable has primarily been treated as a nonstochastic variable. In numerous situations, however, the design variable is stochastic. The estimation and hypothesis testing problems in such situations are considered. Real life examples are given.     

Does Intensive Tillage Enhance Productivity and Reduce Risk Exposure? Panel Data Evidence from Smallholders’ Agriculture in Ethiopia

We analyse the impact of intensity of tillage on wheat productivity and risk exposure using panel household‐plot level data from Ethiopia. In order to control for selection bias, we estimate a flexible moment‐based production function using an endogenous switching regression treatment effects model. We find that tillage has a complementary impact on productivity and risk exposure. As the intensity of tillage increases, productivity increases and farmers’ exposure to risk declines. Our results suggest that smallholder farmers use tillage as an ex‐ante risk management strategy. The main policy implication of this study is that the opportunity cost of switching to reduced tillage in wheat production seem rather high unless farmers are supported by appropriate incentive schemes.     

The relationship among systems engineers' capacity for engineering systems thinking,project types,and project success

In recent years, systems engineering and Project Management Bodies of Knowledge have been rapidly growing. However, despite the vast amount of literature available on systems engineering and project management, about two‐thirds of all projects still fail. A review of both project management and systems engineering publications reveals that most of these works focus on processes. We suggest focusing on people—project managers and systems engineers. One of our previous studies dealt with project managers; this article focuses on systems engineers. This article presents findings of a study aimed at exploring the relationship among systems engineers' capacity for engineering systems thinking (CEST), project types, and project success. The instrument used in this study was a self‐report questionnaire, composed of three parts. The first part assessed the participants' CEST, the second part assessed several measures of project success, and the third part assessed four dimensions of project type. The simple random sampling method was used, and the sample included 114 senior systems engineers who were randomly selected from the sampling frame. The study findings show that there is a statistically significant correlation between CEST and project success. The extent of the project's novelty, complexity, and technological uncertainty are moderator variables that affect this correlation.     

Agricultural mechanization and reduced tillage: antagonism or synergy?

This paper reviews agricultural mechanization and reduced tillage use in the context of sustainable intensification in developing country agriculture. The scoping review includes selected and contrasting cases – including Zimbabwe (manual systems), Bangladesh (2-wheel – single axle tractor systems), India (4-wheel – i.e. 2 axles tractor systems), Kazakhstan (mechanized systems) and Brazil (diverse systems). The expansion of reduced tillage appears strongly associated with the level of agricultural mechanization – facilitated by a number of common drivers and contextualized by the prevailing farm power and intensity of tillage. Soil conservation, timely planting and farm power savings in crop establishment are important drivers for the expansion of reduced tillage across the world, facilitated by conducive markets, institutional and policy environments and the integration of diverse actors to introduce, adapt and promote the necessary components.