The productivity and income effects of adoption of improved soybean varieties and agronomic practices in Malawi

Tufa, Adane; Alene, Arega D.; Manda, Julius; Akinwale, M. G.; Chikoye, David; Feleke, Shiferaw; Wossen, Tesfamicheal; Manyong, Víctor M.

doi:10.1016/j.worlddev.2019.104631

Cited by 55 publications

(57 citation statements)

References 35 publications

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“…Households who had below‐average crop income tended to adopt the CSI technologies. These results are in line with several past studies (Lokshin & Sajaia, 2004; Manda et al, 2019; Tufa et al, 2019; Wossen et al, 2019).…”

Section: Resultssupporting

confidence: 93%

“…Table 6 presents the parameter estimates of the ESR model of consumption expenditure. While the ESR model is theoretically identifiable even when the same independent variables are in all the three equations, it is often suggested that instruments be used based on substantive arguments for better identification (Manda et al, 2019; Tufa et al, 2019). In this study, the number of neighboring farmers that were using the technology in the area was used as an instrument after performing a simple falsification test for its validity.…”

Section: Resultsmentioning

confidence: 99%

“…In particular, we applied the ESR model in this study to account for the potential self‐selection bias in adoption (Maddala & Nelson, 1975). Several have used this model in their studies in recent time (see Asfaw et al, 2012; Kassie et al, 2015; Khonje et al, 2015; Manda et al, 2019; Tufa et al, 2019; Shiferaw et al, 2014).…”

Section: Empirical Modelmentioning

confidence: 99%

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Are farmers using cropping system intensification technologies experiencing poverty reduction in the Great Lakes Region of Africa?

Nguezet

Ainembabazi

Alene

et al. 2020

Food and Energy Security

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This study evaluated the poverty reduction impact of the adoption of cropping system intensification (CSI) technologies using the endogenous switching regression (ESR) model in the Great Lakes region of Africa that comprises Burundi, eastern DR Congo, and Rwanda. The study data came from a household survey of 1,495 sample households interviewed between October and December 2014. Results indicated that the adoption of the CSI technologies had increased crop yield, crop income, and per capita consumption expenditure in the region, resulting in poverty reduction. Among the three countries, eastern DR Congo witnessed the highest poverty reduction (13% points) followed by Rwanda (6% points) and Burundi (2% points). Considering the adoption rate and size of the target population in each country at baseline, an estimated 180 thousand poor individuals had escaped poverty due to the adoption of the CSI technologies. This presents important evidence in favor of promoting CSI technologies as part of poverty reduction strategy. Given the large population size that remains poor even after adoption, we suggest that research‐based poverty reduction strategies such as the CSI technologies should be complemented with development interventions.

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Section: Resultssupporting

confidence: 93%

Section: Resultsmentioning

confidence: 99%

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Are farmers using cropping system intensification technologies experiencing poverty reduction in the Great Lakes Region of Africa?

Nguezet

Ainembabazi

Alene

et al. 2020

Food and Energy Security

Self Cite

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show abstract

“…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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“…Skevas and Grashuis [7] calculated the technical efficiency of grain marketing cooperatives in the Midwest of the United States, and hold that spatial spillover effects affect the technical efficiency of cooperatives. Tufa et al [8] found that soybean yields and net crop incomes for adopters are significantly higher than those of non-adopters over the entire probability distribution of ISVAPs adoption in Malawi. Gong et al [9] proposed that cooperative membership may encourage farmers to learn more advanced technology and take advantage of productivity-enhancing practices.…”

Section: Introductionmentioning

confidence: 99%

Analysis on Efficiency and Influencing Factors of New Soybean Producing Farms

Wang

Shi

2020

Agronomy

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The efficiency of new soybean producers is of great importance to the agricultural development of China. Based on the survey data of some counties (cities) in Heilongjiang, Jilin, Liaoning, and Inner Mongolia Autonomous Region, the efficiency of new soybean producers in these regions is calculated by means of the data envelopment analysis (DEA) model. Then, the Tobit model is used to select relevant explanatory variables to study the factors affecting the production efficiency, and relevant conclusions and suggestions are put forward. The results show that (1) in 2017, the new soybean producers’ average technical efficiency of soybean production in the research samples was 0.618, of which the average pure technical efficiency was 0.680 and the average scale efficiency was 0.872; (2) factors such as the degree of education, the soybean planting area, the degree of mechanization, and the soybean sales channel have positive impacts on the efficiency of new soybean producers, while the ones such as the stability of the soybean price, the difficulty in obtaining soybean market information, and the implementation of the soybean subsidy policy have negative impacts.

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The productivity and income effects of adoption of improved soybean varieties and agronomic practices in Malawi

Cited by 55 publications

References 35 publications

Are farmers using cropping system intensification technologies experiencing poverty reduction in the Great Lakes Region of Africa?

Are farmers using cropping system intensification technologies experiencing poverty reduction in the Great Lakes Region of Africa?

Household welfare impacts of an agricultural innovation platform in Uganda

Analysis on Efficiency and Influencing Factors of New Soybean Producing Farms

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