RESUMEN

Positive Selection (PS) technique has been shown to reduce virus infection and increase yields, however there is insufficient empirical evidence on how this technology affects seed yam farm productivity. This study employed Propensity Score Matching (PSM) technique to evaluate the impact of PS on seed yam yields of 368 farmers randomly selected from Ghana and Nigeria. The findings showed that educational attainment, distance from the farm to the nearest market, cropping patterns, and other factors influenced farmers' adoption of PS. Furthermore, the adoption of PS technology resulted in a 16.98 % boost in farm productivity for PS seed yam farmers compared to their productivity without the technology. It is of the utmost importance that PS adoption be supported by developing tailored training materials for farmers to improve their use of the PS technology.

RESUMEN

Despite Rwanda's impressive economic success over the last decade, household food insecurity persists, particularly in rural areas. Empirical evidence is therefore deemed necessary to inform policies addressing food insecurity, hunger and poverty in general. This study examines household food security and its determinants in the rural areas of Southern and Northern provinces of Rwanda. Using cross-sectional data collected from 534 farming households, we estimated household food security status by Food Consumption Score (FCS) and Food Insecurity Experience Scale (FIES) and applied ordered Probit model to identify drivers of household food security. The results indicate that a significant proportion (74.4%) of households had an acceptable FCS, but 36.52% of the farming households experienced moderate and severe food insecurity when assessed with FIES. Ownership of livestock was identified as a key determinant of food security using both metrics, which affirms the importance of combating hunger and food insecurity in Rwanda through their 'one cow per household policy' and recommends that this policy be strengthened.

Asunto(s)

RESUMEN

Non-farm employment in agrarian communities in developing countries has received a lot of attention. However, its role in implementing climate change adaptation strategies is rarely discussed. This study employs a cross-sectional data to examine whether rural households in Southwest Nigeria are increasing the extent of climate change adaptation practices through their participation in non-farm employment. To account for selectivity bias, the study used endogenous treatment effect for count data model (precisely Poisson) augmented with the inverse probability-weighted-regression-adjustment (IPWRA) estimator. Both estimators found that rural non-farm jobs increase smallholder farmers' adaptive capacities and that participants would have used less adaptation techniques if they had not participated in non-farm work. Efforts to boost rural development must provide more employment opportunities for farmers, particularly during the off-cropping time. This will help farmers improve their ability to adopt more climate change adaptation strategies and, consequently increase farm productivity.

RESUMEN

This study explored the potential impact of rural non-farm income diversification on households' welfare and adoption of Zai-technology (a proxy for agricultural technology adoption) using primary data collected from agricultural households in the Upper East region of Ghana. We used Propensity Score Matching (PSM) and Inverse-Probability-weighted Regression Adjustment (IPWRA) techniques to estimate welfare and Zai-technology impacts of non-farm income diversification. After controlling for differences in covariates, the results show that non-farm income diversification increases the likelihood of Zai-technology adoption and contributes to significant household welfare gains. We therefore suggest that the activities of agricultural extension services and farmer-based organizations (FBOs) be enhanced as they facilitate the diversification of non-farm incomes, thereby increasing investment in productivity-enhancing technologies (Zai) and household welfare.

RESUMEN

This study considers the presence of a gender gap in technical efficiency in Ghana's cocoa production sector. The two-stage double bootstrap data envelopment analysis (DEA) procedure was applied to estimate the bias-corrected technical efficiency scores for male and female cocoa farm managers. The results indicate that there is a potential for male and female cocoa farm managers to increase output without altering the quantities of inputs employed. Applying the extended version of the Blinder-Oaxaca (B-O) decomposition approach, the findings suggest that female plot managers are, on average, less technically efficient compared to their male counterparts. This gap could be linked to differences in their resource endowments. Nevertheless, there are still significant unobservable factors that contribute to the gender efficiency gap. A comprehensive decomposition examination indicates that differences in educational attainment, engagement in non-farm activities, and farm size may contribute to the unexplained technical efficiency gap. The study recommends that female-sensitive programmes that seek to encourage the participation of non-farm activities and provide access to education and land utilization are essential in reducing the gender gap in technical efficiency.