Effects of tractor ownership on returns-to-scale in agriculture: Evidence from maize in Ghana

Takeshima, Hiroyuki; Houssou, Nazaire; Diao, Xinshen

doi:10.1016/j.foodpol.2018.04.001

Cited by 21 publications

(9 citation statements)

References 41 publications

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“…A possible reason is that better‐educated farmers are more likely to exit the farm but choose to participate in off‐farm work activities that are usually better paid (Takeshima et al . 2018). The estimated marginal effect of the household size variable is negative and statistically significant from zero, suggesting that large households are 2.3 per cent less likely to use farm machines.…”

Section: Resultsmentioning

confidence: 99%

“…The results show that the marginal effect of the education variable is negative and statistically significant, suggesting that an additional year of education decreases the probability of farm machinery use. A possible reason is that better-educated farmers are more likely to exit the farm but choose to participate in off-farm work activities that are usually better paid (Takeshima et al 2018). The estimated marginal effect of the household size variable is negative and statistically significant from zero, suggesting that large households are 2.3 per cent less likely to use farm machines.…”

Section: The Determinants Of Farm Machinery Usementioning

confidence: 99%

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Farm machinery use and maize yields in China: an analysis accounting for selection bias and heterogeneity

Zhou

et al. 2020

Aus J Agri & Res Econ

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Crop production in developing and emerging countries is increasingly dependent on the usage of farm machinery. However, it remains unclear whether low-productive and high-productive farmers benefit equally from farm machinery use. To address the research gap, this study examines the potential heterogeneous effects of farm machinery use on maize yields, using an unconditional quantile regression model and survey data from China. We employ a control function approach to address the selection bias issue associated with farm machinery use. The empirical results show that the use of farm machinery significant increases maize yields for all the selected quantiles (except for the 80th quantile); the low-productive farmers tend to benefit more from farm machinery use relative to their high-productive counterparts; and farm machinery use reduces the inequality and variability of maize yields.

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Section: Resultsmentioning

confidence: 99%

Section: The Determinants Of Farm Machinery Usementioning

confidence: 99%

Farm machinery use and maize yields in China: an analysis accounting for selection bias and heterogeneity

Zhou

et al. 2020

Aus J Agri & Res Econ

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“…According to a most recent study in Ghana as it relates to maize production, mechanization is not only associated with a greater return-to-scale but the ownership of machinery, specifically tractors, causes the rise in RTS. (Takeshima et al, 2018) Alongside the increase in production, the profitability of farms also appears to have a positive relationship with mechanization. Although equipment and machineries can be expensive, having the appropriate access to such technology at the right time can help to efficiently manage inputs in farms and overall productivity, thereby improving income (Ayodele, 2012).…”

Section: Effects Of Mechanizationmentioning

confidence: 99%

The Agricultural Mechanization in Africa: Micro-Level Analysis of State Drivers and Effects

Kirui

2019

SSRN Journal

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This paper examines the state, drivers and, consequently, the impacts of agricultural mechanization in eleven countries in Africa. Using representative multistage stratified household survey data and robust analytical approaches, findings show light hand-held tools and equipment remain the main type of machinery in most countries -about 48% of the sampled households have access to light machinery compared to 35% that have access to animal-powered machinery, and only about 18% that use tractor-powered machinery. Significant drivers of agricultural mechanization include the size of the household, gender of the household head, participation in off-farm economic activities, distance to the input and output markets, farm size, land tenure, type of farming system, and access to extension services. This study finds that after controlling for socioeconomic, demographic, and regional determinants, agricultural mechanization, significantly increases the amount of cropland cultivated and is also accompanied by input intensification especially in countries where land expansion is limited. We further find significant but mixed impact of agricultural mechanization on use of household and hired labor. The mixed evidence points to a need to carry out national rather than regional assessment to better inform policy. Finally, agricultural mechanization significantly raises the productivity of maize and rice. These findings point to the importance of developing favorable arrangements that would avail mechanization to small and medium scale farmers either through animal power or tractors. This would involve providing incentives for private sector to scale agricultural mechanization initiatives and targeting and engaging both male and female farmers by investing in supportive infrastructure and farmer training at scale.

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“…According to the literature, as an important technological and economic characteristic of the production structure, RTS have implications for the transformational patterns of agricultural and distributional effects of agricultural policies (Takeshima, Houssou, and Diao 2018). Previous studies have shown mixed results concerning household cocoa production RTS in Ghana.…”

Section: Returns To Scalementioning

confidence: 99%

Chronic sources of low cocoa production in Ghana: new insights from meta-analysis of old survey data

Tsiboe

2021

Agric. Resour. Econom. Rev.

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Several studies have tried to estimate the productivity and input use efficiency of cocoa farmers in Ghana, but they shed limited light on their chronic nature and other sources of low production. This study extends the literature by analyzing a unique nationally representative sample that constitutes 30 years of production. The results showed that pure farmer technical inefficiency is not only 8 percent points larger than the regional technology gap, but also consistently dominated the overall performance of farmers from 1987-2017. The policy implication of this finding at face value suggests that improving farmer managerial skills could increase output.

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Effects of tractor ownership on returns-to-scale in agriculture: Evidence from maize in Ghana

Cited by 21 publications

References 41 publications

Farm machinery use and maize yields in China: an analysis accounting for selection bias and heterogeneity

Farm machinery use and maize yields in China: an analysis accounting for selection bias and heterogeneity

The Agricultural Mechanization in Africa: Micro-Level Analysis of State Drivers and Effects

Chronic sources of low cocoa production in Ghana: new insights from meta-analysis of old survey data

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