Land ownership and technology adoption revisited: Improved maize varieties in Ethiopia

Does productive safety net program enhance livelihoods? Insights from vulnerable households in Wolaita zone, Ethiopia

BACKGROUND

The impact of Productive Safety Net Programs (PSNPs) on food security, poverty, and livelihoods has been examined in several studies. While some studies found positive impacts on food security and agricultural productivity, there are still gaps in understanding the long-term effects of these programs on poverty reduction and food security. This study aims to investigate the impact of PSNP on the livelihood of beneficiaries based on indicators including access to basic services, income, expenditure on food, adaptive capacity, and dietary diversity.

METHODOLOGY

This article used quasi-experimental design and treatment effects model taking into account access to basic services, income, food expenditure, assets, adaptive capacity, and household dietary diversity as outcome variables of interest. 300 respondents were randomly selected from the population of safety net beneficiaries and non-beneficiaries in the study area. Out of the 300 respondents, 150 were selected as the treatment group, who were beneficiaries of the safety net program. The algorithms used in analysis include regression adjustment, inverse probability weighing and propensity score matching.

RESULTS

The study's results reveal that the PSNP has no statistically significant impact on access to basic services and income based on all three algorithms, yet it does show a significant and negative effect on food expenditure and assets. The coefficients across all three models consistently demonstrate this negative impact, underscoring its statistical significance at the conventional significance level (p = 0.05). This suggests that the PSNP leads to a reduction in food expenditure. Furthermore, the analysis highlights substantial differences between PSNP members and non-members across all three variables, with non-members having higher mean values for assets. This difference is statistically significant at the 1% level, suggesting that membership in the PSNP has a tangible impact on asset ownership. The study's mixed findings emphasize the complexities of designing effective social protection programs that can adequately address the multifaceted nature of poverty.

Understanding the determinants and impact of the adoption of technologies for sustainable farming systems in water-scarce areas of Bangladesh

Introduction

Bangladesh's quest to achieve sustainable development goals has highlighted the need to enhance resilience against the challenges that interconnected food, energy, and water (FEW) nexus systems faces to support human well-being. The government has decided to promote the adoption of competent and cutting-edge technologies that can significantly contribute to balancing energy and water resource utilization in achieving a more sustainable and climate-smart food production system. Hence, scaled-up adoption of solar-powered irrigation systems and recommended fertilizer dose (SIRFD) applications were proposed. This study, to provide practical policy implications, attempts to identify the determinants and impact of SIRFD adoption in water-scarce areas of Bangladesh.

Methods

Determinants of adoption were analyzed using multinomial logistic regression, and the adoption impact was analyzed using treatment effect models.

Results

The results revealed that land typology, soil fertility perception, soil water retention, knowledge, environmental awareness, secondary income, close acquaintance adoption, and cash availability significantly influenced adoption decisions. The treatment effect model result indicated that farmers who adopted both technologies could reduce production costs by 1.36% and obtain an 8.92% higher ROI than non-adopters.

Conclusion

The study findings suggest that policy interventions on scaling up SIRFD adoption require focusing on knowledge development village-based demonstration activities, group farming models backed by micro-finance, and avoiding launching conflicting schemes.

Determinants and Impact of Solar Irrigation Facility (SIF) Adoption: A Case Study in Northern Bangladesh

Insufficient rainfall in the dry season and scarcity of surface water has resulted in firms’ reliance on groundwater for agriculture in the northern part of Bangladesh. Most irrigation systems in the country are diesel or electric, which raises the cost and demand for energy and pollutes the environment. Utilizing the abundant sunshine and disseminating solar-based irrigation systems is expected to be a fittingly rewarding experience for irrigation purposes. Therefore, this study identifies the factors influencing the adoption of solar irrigation facilities (SIFs) and the impacts of their adoption on irrigation cost, return on investment (ROI), and production costs, using survey data collected from 405 rice farmers of Dinajpur district. The study employed three treatment effect estimators, namely inverse probability weighting (IPW), regression adjustment (RA), and inverse probability weighted regression adjustment (IPWRA), to address the potential selection bias issue. The results revealed that farming experience, knowledge, environmental awareness, soil fertility, and irrigation machinery ownership significantly influenced adoption decisions. The treatment effect model result indicated that farmers who adopted this method could minimize irrigation costs by 1.88 to 2.22%, obtain 4.48 to 8.16% higher ROI, and reduce total production cost by 0.06 to 0.98% compared to non-adopters. Our findings suggested that policy interventions targeting scaling up SIFs should consider focusing on government and stakeholders’ greater attention on designing more appropriate schemes through experimentation and multiple iterations.

Heterogenous Factors of Adoption of Agricultural Technologies in West and East Africa Countries: A Review

This review brings to light, extensive body of research on the evolvement of agricultural technology in Sub-Saharan Africa with focus on adoption studies in West and East Africa countries. The review highlights historical green revolution events and the heterogeneity in the determinants of the adoption of agricultural technology. Three key popular indicators in adoption studies were reviewed for their heterogeneity; this includes land, extension & social institutions, and gender in light of comparison of studies in West and East Africa. The review shows that there is so much to be gained from enhancing the understanding of the heterogeneity that exists in key popular indicators in adoption studies considering the importance of adoption of agricultural technology in reducing poverty and food insecurity and the evolving impact of climate change and other human attributes that has defined the modification of various agricultural technology. Also, the review highlights the need to tailor extension and social learning toward existing heterogeneity to aid in promoting the adoption of agricultural technology. An important highlight includes the need to be wary of the downsides of the earlier green revolution while driving the efforts of new green revolution in West and East Africa and Sub-Saharan Africa in general.

Adoption of agricultural technologies in the developing world: A meta-analysis dataset of the empirical literature

The meta-analysis dataset presented is a convenience sample from 218 separate studies of agricultural technology adoption in Africa, Asia, and Latin America. Each study uses survey data to estimate a form of multiple regression of adoption of a technology (dependent variable) with a diverse array of predictor variables. Fifteen predictor variable categories are included in this dataset: Age, education, gender, household size, farming experience, land size, soil fertility, land slope, distance to inputs/outputs, access to credit, land tenure, livestock ownership, non-farm income, access to extension, and organization membership. Data have been cleaned and transformed to common units. A total of 384 statistical models are recorded, with a total of 2875 effect size estimates.

Gender differentiated small-scale farm mechanization in Nepal hills: An application of exogenous switching treatment regression

Farm mechanization among smallholder farming systems in developing countries is emerging as a viable option to off-set the effects of labor out-migration and shortages that undermine agricultural productivity. However, there is limited empirical literature on gender and farm mechanization. This study assesses the impacts of the gender of household heads on mini-tiller adoption in the hills of Nepal, using an exogenous switching treatment regression model. Our findings reveal that there is a significant gender gap in mini-tiller adoption between male-headed households (MH-HHs) and female-headed households (FH-HHs). Compared to MH-HHs, the mini-tiller adoption rate is significantly lower among the FH-HHs, and a large amount of unobserved heterogeneity is deriving this difference. Moreover, when MH-HHs and FH-HHs have similar observed attributes, the mini-tiller adoption rate among the food insecure FH-HHs is higher than in the food secure group. The gender-differentiated mini-tiller adoption rate can be minimized primarily by enhancing market access. Findings suggest that farm mechanization policies and programs targeted to the FH-HHs can reduce the gender-differentiated adoption gap in Nepal and similar hill production agro-ecologies in South Asia, which will enhance the farm yield and profitability.

Gender differences in the adoption of agricultural technology: The case of improved maize varieties in southern Ethiopia

This study explores the role of gender-based decision-making in the adoption of improved maize varieties. The primary data were collected in 2018 from 560 farm households in Dawuro Zone, Ethiopia, and were comparatively analyzed across gender categories of households: male decision-making, female decision-making and joint decision-making, using a double-hurdle model. The results show that the intensity of improved maize varieties adopted on plots managed by male, female, and joint decision-making households are significantly different. This effect diminishes in the model when we take other factors into account. Using the gender of the heads of households and agricultural decision-maker, the current study did not find significant evidence of gender difference in the rate and intensity of adoption of improved maize varieties. The intensity of adoption of improved maize varieties is lower for female-headed households where decisions are made jointly by men and women, compared to the male-headed households where decisions are made jointly. As the economic status is a key driver of adoption of improved maize varieties, it is recommended that the policies and programs that aim at developing and disseminating quality maize seeds in southern Ethiopia should emphatically support economically less endowed but more gender egalitarian joint decision-making households, especially female-headed ones.