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.     

State-conditional Fertilizer Yield Response on Western Kenyan Farms

Fertilizer interventions have attained prominence in rural poverty reduction programs in Africa. Using data from maize plots operated by small farmers in western Kenya, we find a von Liebig-type relationship between soil organic matter (SOM) and maize yield response to nitrogen application. Low SOM commonly limits the yield response to mineral fertilizer application. Although fertilizer is, on average, profitable in our sample, on roughly one-third of the plots degraded soils limit the marginal productivity of fertilizer such that it becomes unprofitable at prevailing prices. Moreover, because poorer farmers most commonly cultivate soils deficient in SOM, fertilizer interventions might be less pro-poor than is widely assumed and may instead reinforce  ex ante  income inequality.     

Soil quality and fertilizer use rates among smallholder farmers in western Kenya

Studies of fertilizer use in sub-Saharan Africa have been dominated by analyses of economic and market factors having to do with infrastructure, institutions, and incentives that prevent or foster increased fertilizer demand, largely ignoring how soil fertility status conditions farmer demand for fertilizer. We apply a switching regression model to data from 260 farm households in western Kenya in order to allow for the possibility of discontinuities in fertilizer demand based on a soil carbon content (SCC) threshold. We find that the usual factors reflecting liquidity and quasi-fixed inputs are important on high-SCC plots but not on those with poorer soils. External inputs become less effective on soils with low SCC, hence the discernible shift in behaviors across soil quality regimes. For many farmers, improved fertilizer market conditions alone may be insufficient to stimulate increased fertilizer use without complementary improvements in the biophysical conditions that affect conditional factor demand.     

Household-level determinants of adoption of improved natural resources management practices among smallholder farmers in western Kenya

Integrated natural resources management (INRM), of which integrated soil fertility management (ISFM) is a component, offers considerable promise for increasing food production in Kenya. It nonetheless remains unclear whether ISFM/INRM techniques lend themselves easily to adoption by smallholder farmers. Using panel data collected in western Kenya in 1989 and 2002, this study finds that resource constraints limit many farmers’ adoption of ISFM/INRM techniques. The size of the farm owned by a household, the value of its livestock, off-farm income, family labor supply, and the educational attainment and gender of the household head all had a significant positive effect on the likelihood of adoption. Similar factors were found to be statistically significant in discouraging abandonment of the practices under study. There thus seem to exist reinforcing feedback between investments in soil fertility management and household wealth, as measured by asset endowments. Our findings raise important questions as to whether ISFM and related techniques are really affordable to poorer smallholder farmers.