Production and market participation decisions of smallholder cowpea producers in the Northern Region of Ghana: A triple hurdle model approach

Kondo, Ebenezer; Sarpong, Daniel Bruce; Egyir, Irene S.

doi:10.22004/ag.econ.295654

Cited by 2 publications

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“…Factors affecting each of the three hurdles are specified as a function of household characteristics (hc) and institutional (i) factors. These are broadly specified as illustrated in equations 3-5 (Kondo et al, 2019).…”

Section: Sampling Frameworkmentioning

confidence: 99%

“…Conditional on awareness of and participation in GM maize production, rural farming households who own arable land are more likely to intensify GM maize production than those that depend on hired land because of the risk-averse behaviour associated with non-land owners. Kondo et al (2019) have noted that farmers who own their own land do not share the output with anyone and hence have the freedom to use their land as they see fit. They may be able to boost production because they have no obligation to compensate any landowners in cash or in kind.…”

Section: Drivers Of Intensity Of Gm Maize Production Among Rural Farm...mentioning

confidence: 99%

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Drivers of genetically modified maize production among rural farming households in Ngqushwa Local Municipality, South Africa: A triple hurdle approach

Zamisa

Taruvinga

2022

J. Agribus. Rural Dev.

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Enhancing rural agricultural productivity using proven technologies such as genetically modified (GM) maize production has many advantages as a pathway to economic development and poverty reduction. However, despite the global rise in GM maize and potential benefits of GM technology, the production rates and yields of smallholder farmers remain very low for reasons that are poorly understood. With this background, the aim of this study was to investigate the drivers of genetically modified (GM) maize awareness, participation, and intensity of production at the household level. Data were collected from 400 randomly selected respondents from Ngqushwa Local Municipality using a semi-structured questionnaire. Through a triple hurdle model, the study revealed that GM maize awareness is negatively influenced by age and female gender and positively influenced by married status, employment and number of years in school. Conditional on awareness of GM maize varieties, both participation and intensity of participation in GM maize production are positively influenced by land size, female gender, group membership, income and ownership of arable land and negatively influenced by employment. The study recommends that priority should be given to these socio-economic and institutional (group membership) factors by targeting GM maize awareness campaigns using platforms more suited to female-headed, older, less educated and unemployed rural farming households. The study also recommends addressing income, secure land ownership and access to large areas of land.

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Section: Sampling Frameworkmentioning

confidence: 99%

Section: Drivers Of Intensity Of Gm Maize Production Among Rural Farm...mentioning

confidence: 99%

Drivers of genetically modified maize production among rural farming households in Ngqushwa Local Municipality, South Africa: A triple hurdle approach

Zamisa

Taruvinga

2022

J. Agribus. Rural Dev.

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A triple hurdle model of organic vegetable awareness, adoption, and production among smallholder farmers in Ekiti and Oyo states of Nigeria

et al. 2023

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Production and market participation decisions of smallholder cowpea producers in the Northern Region of Ghana: A triple hurdle model approach

Cited by 2 publications

References 0 publications

Drivers of genetically modified maize production among rural farming households in Ngqushwa Local Municipality, South Africa: A triple hurdle approach

Drivers of genetically modified maize production among rural farming households in Ngqushwa Local Municipality, South Africa: A triple hurdle approach

A triple hurdle model of organic vegetable awareness, adoption, and production among smallholder farmers in Ekiti and Oyo states of Nigeria

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