Impacts of improved maize varieties in Nigeria: ex-post assessment of productivity and welfare outcomes

Abdoulaye, Tahirou; Wossen, Tesfamicheal; Awotide, Bola Amoke

doi:10.1007/s12571-018-0772-9

Cited by 80 publications

(72 citation statements)

References 28 publications

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“…The failure to account for the potential endogenous selection bias in the outcome equations may, therefore, result in biased and inconsistent estimators. Past studies have applied both semi-parametric and parametric approaches that take account of the potential self-selection problem (Abdoulaye, Wossen, & Awotide, ;Ainembabazi et al, 2018;Ali & Abdulai, 2010;Asfaw, Kassie, Simtowe, & Lipper, 2012;Becerril & Abdulai, 2010;Feleke, Manyong, Abdoulaye, & Alene, 2016;Khonje, Manda, Alene, & Kassie, 2015;Manda et al, 2019;Shiferaw et al, 2014;Tufa et al, 2019;Wossen et al, 2017). In this study, we use the parametric approach (endogenous switching regression model), and semi-parametric (propensity score matching) approaches, with the latter being used as a robustness check to the results of the former.…”

Section: Empirical Modelmentioning

confidence: 99%

Household welfare impacts of an agricultural innovation platform in Uganda

Ahimbisibwe

Morton

Feleke

et al. 2020

Food and Energy Security

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Technical approaches to food production are important to the food security of growing populations in developing countries. However, strategic investments in research and farm‐level adoption require greater coherence in agricultural, societal, and local policies. The Agricultural Innovation System (AIS) and formation of the Cassava Innovation Platform (CIP) in Uganda were designed to stimulate interactions between researchers and farmers, leading to the development of improved cassava varieties through participatory plant breeding (PPB) and participatory variety selection (PVS). Moreover, the establishment of a community‐based commercialized seed system called Cassava Seed Entrepreneurship (CSE) has made an important contribution to the rapid multiplication and dissemination of clean planting materials in Uganda. The impact of CIP participation on rural household welfare was measured by household consumption expenditure per capita. The Endogenous Switching Regression (ESR) model was applied to data from a formal household survey conducted in the eastern, northern, and mid‐western regions of Uganda. The education, farm size, livestock size, access to credit, cost of cassava planting materials, access to extension service, access to training, and social group membership are significantly associated with CIP participation. CIP participation resulted in a 47.4% increase in household consumption expenditure. This important evidence highlights the need to promote agricultural innovation platform for improving rural livelihoods. Moreover, CIP participation has impact heterogeneity within the participant group that is conditional on household characteristics such as the gender of the household head, pointing to the need to tailor specific interventions and target specific groups within farm households.

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Section: Empirical Modelmentioning

confidence: 99%

Household welfare impacts of an agricultural innovation platform in Uganda

Ahimbisibwe

Morton

Feleke

et al. 2020

Food and Energy Security

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“…This means that wealthier households could afford costlier technologies. As argued by (Abdoulaye et al 2018), wealth status of farmers play significant roles in the adoption of farm technology in most developing countries. As a result, it is expected that food-secure households with a high number of assets are likely to be more technically efficient.…”

Section: Descriptive Statistics Of Variablesmentioning

confidence: 99%

“…In recent times, major agricultural interventions and efforts have been geared towards increasing productivity in sub-Saharan Africa (SSA). For example, the development, dissemination, and adoption of the improved crop varieties and fertilizer technologies have been widely promoted across the region (Abdoulaye et al 2018;Ogunniyi et al 2015;Lunduka et al 2017). However, low productivity still characterizes the agricultural sector in the region (FAO 2004).…”

Section: Introductionmentioning

confidence: 99%

Determinants of Food Security and Technical Efficiency among Agricultural Households in Nigeria

Oyetunde-Usman

Olagunju

2019

Economies

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The challenge of food security in Nigeria hinges on several factors of which poor technical efficiency is key. Using a stochastic frontier framework, we estimated the technical efficiency of agricultural households in Nigeria and tested for the significance of mean technical efficiency of food-secure and food-insecure agricultural households. We further assessed the determinants of agricultural households’ inefficiencies within the stochastic frontier model and adopted a standard probit model to assess the determinants of households’ food security status. The results of our analyses revealed that; on the overall, the agricultural households had a mean technical efficiency of 52%, suggesting that agricultural households have the tendency of improving their technical efficiency by 48% using the available resource more efficiently. We found that households that are food-secure are more technically efficient than food in-secure households and this was significant at one-percent. Our results provide useful insights into the role of land size and number of assets as determinants of agricultural households’ food security and technical efficiency status.

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“…Technological change is critical for agricultural productivity growth and poverty reduction in developing countries especially in sub-Saharan Africa (SSA) (Gollin et al, 2002;Alene et al, 2009;Suri, 2011;Zeng et al, 2015). It is widely recognised that the development and dissemination of improved crop varieties and complementary agronomic practices are major drivers of smallholder agricultural productivity growth (Alene et al, 2009;Suri, 2011;Zeng et al, 2015;Kassie et al, 2017;Abdoulaye et al, 2018). However, empirical evidence on the relationship between agricultural research and poverty reduction suggests that improved agricultural technologies may not necessarily lead to poverty reduction as the poor are often constrained by structural barriers that make improved technologies inaccessible and less profitable for them (Suri, 2011;Zeng et al, 2015;Kassie et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Poverty Reduction Effects of Agricultural Technology Adoption: The Case of Improved Cassava Varieties in Nigeria

Wossen¹,

Alene²,

Abdoulaye³

et al. 2018

J Agricultural Economics

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We use DNA-fingerprinting to estimate the poverty reduction effect of adoption of improved cassava varieties in Nigeria. We estimate the counterfactual household income distribution of cassava producers by combining farm-level treatment effects with a market-level model. Our results suggest that adoption of improved cassava varieties has led to a 4.6 percentage point reduction in poverty, though this is sensitive to the measurement of adoption status. Therefore, accurate measurement of adoption is crucial for a more credible estimate of the poverty reduction effect of adoption. Our analysis also suggests that farmers who are more likely to be adopters are also likely to face higher structural costs. Addressing structural barriers that make improved technologies less profitable for the poor would therefore be important to increase the poverty reduction effect of improved cassava varieties.

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Impacts of improved maize varieties in Nigeria: ex-post assessment of productivity and welfare outcomes

Cited by 80 publications

References 28 publications

Household welfare impacts of an agricultural innovation platform in Uganda

Household welfare impacts of an agricultural innovation platform in Uganda

Determinants of Food Security and Technical Efficiency among Agricultural Households in Nigeria

Poverty Reduction Effects of Agricultural Technology Adoption: The Case of Improved Cassava Varieties in Nigeria

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