Gender discrimination and its impact on income, productivity, and technical efficiency: evidence from Benin

Kinkingninhoun-Medagbe, Florent M.; Diagne, Aliou; Simtowe, Franklin; Agboh-Noameshie, Afiavi R.; Adegbola, Patrice Ygué

doi:10.1007/s10460-008-9170-9

Cited by 80 publications

(47 citation statements)

References 23 publications

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“…This result implies that male farmers tend to be less efficient compared to their female counterparts. This is in line with the study of Kinkingninhoun-Meˆdagbe´ et al (2010) who estimated technical efficiency indices between men and women and the result of the study shows that women are on average more technically efficient than men.…”

Section: Household Characteristicssupporting

confidence: 91%

Estimating financing gaps in rice production in Southwestern Nigeria

Ojo

Ogundeji

Babu

et al. 2020

Economic Structures

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Rice is one of the most valuable cereal crops cultivated and consumed all over the world. It is a staple food in several African counties, Nigeria as an example and constitutes a large portion of the diet on a regular basis (Lu et al. 2018). Rice is cultivated in mostly all agro-ecological zones in Nigeria but on a relatively small scale. As asserted by FAO (2015), Nigeria is the continent's leading consumer of rice, one of the largest producers of rice in Africa and simultaneously one of the largest rice importers in the world. Rice is an important food security crop, it is an essential cash crop for it is AbstractThis study analysed the financing gaps relative to production frontier of rice farmers in Southwestern Nigeria. A multistage sampling technique was used to collect crosssectional data from 360 rice farmers selected from three states in the region. A Cobb-Douglas stochastic frontier and an adapted form of Harrod-Domar (HD) growth model was employed to determine the financing gap required the farmers to be at the frontier level. The empirical results of the frontier model show that quantity of labour, quantity of rice as planting material and herbicides were statistically significant in explaining the variations in the efficiency of rice production in Nigeria. However, age, gender, farming experience, household size, access to credit, access to information, adoption of improved variety and location of rice farmers as sources of technical inefficiencies. As revealed by the result of the HD growth model, the average amount of credit per season that farmers had access to was, 38,630.56 naira (₦) while the mean financing in the form of credit required to produce at the frontier level was ₦193,626.50, showing a financing shortfall of about 80%. As unravelled by the result of the study, it can thus be concluded that technical efficiency of rice farmers can be improved by ameliorating access to timely credit and agricultural information for improving rice productivity. These findings suggest that filling the financing gap of smallholder rice farmers will improve rice productivity in Nigeria. The study, therefore, recommends that strengthening the existing technology by building farmers' capacity on farm management practices would be the surest means of improving rice productivity growth in Nigeria. This would not only contribute to the intensification of rice production in Nigeria to meet its increasing rice demand, but also improve rice farmers' productivity and their households' incomes.

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Section: Household Characteristicssupporting

confidence: 91%

Estimating financing gaps in rice production in Southwestern Nigeria

Ojo

Ogundeji

Babu

et al. 2020

Economic Structures

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“…Using an SFP function, Kinkingninhoun‐Mêdagbé et al . () found an average TE score of 84%. Singbo and Oude Lansink () used a directional distance function to find an average TE score of 82% for lowland farming systems.…”

Section: Results and Analysismentioning

confidence: 95%

“…The MTE score estimates are lower than those obtained from previous studies on smallholder farmers in Benin. Using an SFP function, Kinkingninhoun-Mêdagb e et al (2008) found an average TE score of 84%. Singbo and Oude Lansink (2010) used a directional distance function to find an average TE score of 82% for lowland farming systems.…”

Section: Technical Efficiencymentioning

confidence: 99%

Tenure Security and Farm Efficiency Analysis Correcting for Biases from Observed and Unobserved Variables: Evidence from Benin

Lawin¹,

Tamini²

2018

J Agricultural Economics

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We analyse the impact of land tenure security on the technical efficiency of a sample of smallholder farmers in Benin, based on an output‐oriented stochastic distance function. We use propensity score matching to correct for selection bias from observed variables. The Greene () sample selection model is used to correct for selection bias due to unobserved variables. We estimate meta‐frontiers to analyse agricultural productivity and efficiency differences between landowners and non‐owners. Our results show that non‐owners have consistently higher levels of technical efficiency and productivity.

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“…This approach is widely used in the agricultural economics literature, but has only been used to a limited extent to consider whether inefficiency is correlated with the sex of the farmer. Two studies find that women and men have similar technical efficiency (Kinkingninhoun‐Mêdagbé, Diagne, Simtowe, Agboh‐Noameshie, & Adégbola, ; Overfield & Fleming, ) In Nigeria, among cassava farmers, Timothy and Adeoti () find that women have higher technical efficiency, but men have higher allocative efficiency.…”

Section: Empirical Estimates Of Gender Differences In Agricultural Prmentioning

confidence: 99%

Women and agricultural productivity: Reframing the Issues

Doss

2017

Development Policy Review

160

132

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Should agricultural development programmes target women in order to increase productivity? This article analyzes the challenges in distinguishing women's agricultural productivity from that of men. Most of the literature compares productivity on plots managed by women with those managed by men, ignoring the majority of agricultural households in which men and women are both involved in management and production. The empirical studies which have been carried out provide scant evidence for where the returns to projects may be highest, in terms of who to target. Yet, programmes that do not consider gendered responsibilities, resources and constraints, are unlikely to succeed, either in terms of increasing productivity or benefitting men and women smallholder farmers.

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Gender discrimination and its impact on income, productivity, and technical efficiency: evidence from Benin

Cited by 80 publications

References 23 publications

Estimating financing gaps in rice production in Southwestern Nigeria

Estimating financing gaps in rice production in Southwestern Nigeria

Tenure Security and Farm Efficiency Analysis Correcting for Biases from Observed and Unobserved Variables: Evidence from Benin

Women and agricultural productivity: Reframing the Issues

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