Agricultural technology assessment for smallholder farms: An analysis using a farm simulation model (FARMSIM)

Bizimana, Jean‐Claude; Richardson, James W.

doi:10.1016/j.compag.2018.11.038

Cited by 35 publications

(40 citation statements)

References 13 publications

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“…SERF uses certainty equivalents (CEs) and a range of absolute risk aversion coefficients (ARACs) to rank many risky alternatives simultaneously. Each option can be compared and ranked at each ARAC [42,44,45]. SERF s advantage over the conventional stochastic dominance analysis with respect to a function (SDFR) is that SERF involves comparing each alternative with all the other options simultaneously, not pairwise.…”

Section: Scenario Rankingmentioning

confidence: 99%

An Economic Comparison between Alternative Rice Farming Systems in Tanzania Using a Monte Carlo Simulation Approach

et al. 2020

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Tanzania is the second-largest producer of rice (Oryza sativa) in Eastern, Central, and Southern Africa after Madagascar. Unfortunately, the sector has been performing poorly due to many constraints, including poor agricultural practices and climate variability. In addressing the challenge, the government is making substantial investments to speed the agriculture transformation into a more modernized, commercial, and highly productive and profitable sector. Our objective was to apply a Monte Carlo simulation approach to assess the economic feasibility of alternative rice farming systems operating in Tanzania while considering risk analysis for decision-makers with different risk preferences to make better management decisions. The rice farming systems in this study comprise rice farms using traditional practices and those using some or all of the recommended system of rice intensification (SRI) practices. The overall results show 2% and zero probability of net cash income (NCI) being negative for partial and full SRI adopters, respectively. Meanwhile, farmers using local and improved seeds have 66% and 60% probability of NCI being negative, correspondingly. Rice farms which applied fertilizers in addition to improved seeds have a 21% probability of negative returns. Additionally, net income for rice farms using local seeds was slightly worthwhile when the transaction made during the harvesting period compared to farms applied improved varieties due to a relatively high price for local seeds. These results help to inform policymakers and agencies promoting food security and eradication of poverty on the benefits of encouraging improved rice farming practices in the country. Despite climate variability, in Tanzania, it is still possible for rice farmers to increase food production and income through the application of improved technologies, particularly SRI management practices, which have shown a promising future.

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Section: Scenario Rankingmentioning

confidence: 99%

An Economic Comparison between Alternative Rice Farming Systems in Tanzania Using a Monte Carlo Simulation Approach

et al. 2020

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“…Some researchers have reported that the low agricultural technology adoption (improved seeds, irrigation, fertilizers, tools) is one of the reasons for the yield gap [7]. Actually, in Côte d'Ivoire, the application of new agricultural technologies by rice farmers remains problematic.…”

Section: Introductionmentioning

confidence: 99%

Does Credit Influence Fertilizer Intensification in Rice Farming? Empirical Evidence from Côte D’Ivoire

et al. 2020

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In Côte d’Ivoire, the use of fertilizers in rice farming still remains low. Credit constraints have been frequently reported as the main reason hampering rice farmers from reversing this situation. However, there is no empirical evidence on the link between rice farmers’ access to credit (AC) and fertilizer intensification (FI). This article examines this issue by using a sample of 600 rice farmers randomly selected in seven rice areas. Data are analyzed by the IV-Probit and IV-Tobit models. The results reveal that FI and AC reciprocally influence each other, implying that they are endogenous. An increase of credit by XOF 100 could increase the quantity of fertilizer used by 2.70 kg, all other things being equal. Moreover, FI and AC are strongly influenced by some socio-economic, rice farm, and institutional factors. Policymakers should take actions to facilitate rice farmers’ access to credit and subsidized fertilizers. Other relevant explanatory variables should be considered in rice farming development policies. By providing empirical evidence of the link between rice farmers’ access to credit and fertilizer intensification in Côte d’Ivoire, this paper contributes to the agricultural finance literature.

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“…Not only do farm tools and implements enhance production efficiency and make farm work easier [50], they are crucial in semi-subsistence agriculture to access productive resources, especially land and water. Smallholders can quickly adopt farm technologies such as irrigation if tools for implementation are readily available and accessible [31].…”

Section: Discussionmentioning

confidence: 99%

“…Productive hand tools are essential to farming, from production to harvesting. Tools and implements critically determine farm activities and facilitate increased agricultural production that can restore food security [31,32].…”

Section: Access To Technologymentioning

confidence: 99%

Applying the Theory of Access to Food Security among Smallholder Family Farmers around North-West Mount Kenya

2020

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Access to productive resources such as land and water is fundamental for households that rely on crop and livestock production for their livelihoods. Research often assumes that agricultural production—and thus, food security—are favoured by tenure security of resources (as represented by a “bundle of property rights”). However, research has not yet elucidated how food security is influenced by additional factors, represented within a “bundle of powers”. Guided by the Theory of Access developed by Ribot and Peluso, we explore the main factors in the respective bundles of rights and powers that influence household food security around north-west Mount Kenya. We interviewed 76 households—38 food secure and 38 food insecure—who were subsampled from a previous food security survey of 380 households. Results show that household food insecurity was not exclusively the result of a lack of private property rights as many farmers had retained their property rights. Instead, a major factor preventing access to productive resources was the difficulty faced by food insecure households in accessing farm technology (i.e. hand tools and implements). Access to authority and via social relations were significantly correlated with access to technology, so improving the latter must take into account the former.

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Agricultural technology assessment for smallholder farms: An analysis using a farm simulation model (FARMSIM)

Cited by 35 publications

References 13 publications

An Economic Comparison between Alternative Rice Farming Systems in Tanzania Using a Monte Carlo Simulation Approach

An Economic Comparison between Alternative Rice Farming Systems in Tanzania Using a Monte Carlo Simulation Approach

Does Credit Influence Fertilizer Intensification in Rice Farming? Empirical Evidence from Côte D’Ivoire

Applying the Theory of Access to Food Security among Smallholder Family Farmers around North-West Mount Kenya

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